INVESTIGATION INTO HEALTH & ENVIRONMENTAL HAZARDS OF PESTICIDES USE TO FARMING COMMUNITY IN KHYBER PAKHTUNKHWA, PAKISTAN
BY REHMAT ULLAH
A Dissertation submitted to The University of Agriculture, Peshawar in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY IN AGRICULTURE (AGRICULTURAL EXTENSION EDUCATION AND COMMUNICATION)
DEPARTMENT OF AGRICULTURAL EXTENSION EDUCATION AND COMMUNICATION FACULTY OF RURAL SOCIAL SCIENCES THE UNIVERSITY OF AGRICULTURE, PESHAWAR KHYBER PAKHTUNKHWA-PAKISTAN OCTOBER, 2018 INVESTIGATION INTO HEALTH & ENVIRONMENTAL HAZARDS OF PESTICIDES USE TO FARMING COMMUNITY IN KHYBER PAKHTUNKHWA, PAKISTAN
BY
REHMAT ULLAH
A Dissertationsubmitted to The University of Agriculture, Peshawar in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY IN AGRICULTURE (AGRICULTURAL EXTENSION EDUCATION AND COMMUNICATION)
Approved By:
______Chairman Supervisory Committee Prof. Dr. Khalid Nawab
______(Member Major Field of Study) Prof. Dr. Muhammad Zafarullah Khan
______(Member Minor Field of Study) Dr. Asad Ullah Assistant Professor Dept. of Rural Sociology
______Chairman and Convener Board of Studies Prof. Dr. Khalid Nawab
______Dean Faculty of Rural Social Sciences Prof. Dr. Noor P. Khan
______Director Advanced Studies and Research Dr. Shahid Sattar
DEPARTMENT OF AGRICULTURAL EXTENSION EDUCATION AND COMMUNICATION FACULTY OF RURAL SOCIAL SCIENCES THE UNIVERSITY OF AGRICULTURE, PESHAWAR KHYBER PAKHTUNKHWA-PAKISTAN OCTOBER, 2018
DEDICATION
I dedicate this humble effort to the Imam- ul-Anbia, the founder of Islamic Revolution Hazrat Muhammad (S.A.W)and to my adorable Parents, whom love and prayers, enables me to complete my degree, their sincere love and financial support brought me to be successful in my life. Rehmat Ullah
TABLE OF CONTENTS
CHAPTER NO. TITLE PAGE # LIST OF TABLES ...... i LIST OF FIGURES ...... iv ACRONYMS AND ABBREVIATIONS ...... vi ACKNOWLEDGMENTS ...... viii ABSTRACT ...... ix I INTRODUCTION...... 1 1.1 Agriculture in Pakistan ...... 1 1.2 Pesticides...... 1 1.3 Adverse Effects of Pesticides...... 2 1.4 Pesticides Use in Developing and Developed Countries ...... 3 1.5 Justification of Study ...... 5 1.6 Research Questions ...... 6 1.7 Objectives ...... 7 1.8 Research Hypothesis ...... 7 1.9 Limitations of the Study...... 7 II REVIEW OF LITERATURE ...... 9 2.1 Health Effects and Misuse of Pesticides ...... 9 2.2Environmental effect of Pesticides Use ...... 12 2.3 Role of Agriculture Extension in Safe Use of Pesticides ...... 13 2.4 Summary of Review of Literature ...... 14 III MATERIALS AND METHODS ...... 15 3.1 Universe of Study ...... 15 3.1.1 Khyber Pakhtunkhwa the Study Province ...... 15 3.2 Sampling Design ...... 15 3.2.1Multistage Sampling ...... 16 3.2.1.1Stage I. Selection of Districts...... 16 3.2.1.1.1 District Dera Ismail Khan ...... 16 3.2.1.1.2 District Charsadda ...... 16 3.2.1.1.3 District Mansehra ...... 17 3.2.1.1.4 District Swat...... 17 3.2.1.2Stage II. Selection of Tehsils ...... 17 3.2.1.3 Stage III. Selection of Union Councils ...... 17 3.2.1.4 Stage IV. Selection of Sample Size and Respondents ...... 18 3.3 Conceptual Framework the Study ...... 19 3.4 Research Design...... 21 3.5 Operationalization of Variables ...... 21 3.5.1 Knowledge of the Labels ...... 21 3.5.2 Most Commonly Used Pesticides and their Doses ...... 22 3.5.3 Knowledge of the Respondents Regarding Pesticides Practices, Judicious Use of Pesticides and Self-Reported Symptoms ...... 22 3.5.4 Harmful Environmental Effect of Pesticides ...... 22 3.5.5 Alternative Techniques to Pesticides Use ...... 23 3.5.6 Role of Agriculture Extension ...... 23 3.6 Research Instrument...... 23 3.7 Inclusion and Exclusion Criteria ...... 24 3.8 Validity of the Research Instrument ...... 24 3.9 Reliability of Research Instrument ...... 25 3.10 Data Collection ...... 25 3.11 Statistical Analysis of Data ...... 26 3.11.1 Chi-Square Test ...... 26 3.11.2 One Way Analysis of Variance (ANOVA) ...... 26 3.11.3 One Sample t-Test...... 27 3.11.4 Independent Sample t-Test ...... 27 3.11.5 Binary Logistic Regression Model ...... 28 3.11.6 Kruskal Gamma Test ...... 28 IV RESULTS AND DISCUSSION ...... 30 4.1 Demographic Characteristics ...... 30 4.1.1 Age of the Respondents ...... 30 4.1.2 Literacy Level of the Respondents ...... 31 4.1.3 Family System of the Respondents ...... 33 4.1.4 Tenancy Status of the Respondents ...... 34 4.1.5 Land holding of the Respondents ...... 35 4.1.6 Involvement of the Respondents in Farming ...... 36 4.1.7 Farming Experience of the Respondents ...... 37 4.1.8 Respondents‘ Major Source of Income ...... 38 4.2 Crop/Fruits/Vegetables Grown by Farmers ...... 40 4.3 Experiences in Spraying Pesticides ...... 42 4.4 Distribution of Respondents Regarding Type of Pesticides they Mostly Use ...... 43 4.5 Pesticides Acquisition ...... 45 4.6 Stage of Utilizing Pesticides in Crop/Fruits/Vegetables ...... 46 4.7 Most Commonly Used Pesticides and their Doses ...... 49 4.8 Decision about Spraying Pesticides ...... 61 4.9 Information about Dose of Pesticides ...... 62 4.10 Day Time Application of Pesticides ...... 63 4.11 Number of Sprays on Single Crop ...... 64 4.12 Picking of Produce after Application of Pesticides ...... 66 4.13 Knowledge Regarding Pictograms ...... 68 4.14 Checking the Labels ...... 76 4.15 Following the Instructions of Labels ...... 77 4.16 Precautionary Measures/Personal Protective Equipment (PPE) Farmers used during Pesticides Practices ...... 78 4.17 Knowledge about the Misuse of Pesticides ...... 93 4.18 Entrance into the Field after Spray ...... 96 4.19 Knowledge about the Pesticides Entrance to the Body ...... 97 4.20 Self-Reported Symptoms of Pesticides Use ...... 99 4.21 Heath and Environmental Hazards of Pesticides Use ...... 105 4.22 Disposal of Leftover Pesticides ...... 109 4.23 Judicious Use of Pesticides ...... 110 4.24 Knowledge about the Alternative Approaches ...... 113 4.25 Training Provided by Agriculture Extension Department ...... 122 4.26 How to Use Pesticides ...... 125 4.27 Health safety ...... 125 4.28 Integrated Pest Management ...... 128 4.29 Trained in Disposal of Pesticides and Empty Bottles ...... 128 4.30 Application Technology...... 131 4.31 Trained on Harmful Environment Effects ...... 131 4.32 Trained about the Symptoms and Treatment of Poison ...... 134 4.33 Environmental and Health Hazards of Pesticides Use ...... 134 4.34 Calibration of Pesticides ...... 137 4.35 Pesticides Application Techniques ...... 137 4.36 Safety Measures while Dealing with Pesticides ...... 140 4.37 Learning about the Understanding Pesticides Label ...... 140 4.38 Learning about the Biological Control of Pests ...... 143 4.39 Learning about the Augmentative Measures from Agriculture Extension Department ...... 143 4.40 Field days Arranged about the Pesticides ...... 146 4.41 Farmers Field School Approach used by Agriculture Extension Department ...... 146 4.42 Monitoring by Agriculture Extension Department ...... 149 4.43 Contacts by Farmers with Agriculture Extension Department ...... 149 4.44 Demonstrations arranged by Agriculture Extension Department on Pesticides ...... 152 4.45 Information Regarding Pest Resistant Varieties ...... 152 4.46 Information Shared by Agriculture Extension Department on Mechanical Control ...... 155 4.47 Information Shared by Agriculture Extension Department on Cultural Practices to Control Pests ...... 155 4.48 Information Shared about the Highly Toxic Pesticides by Agriculture Extension Dearptment ...... 158 4.49 Information shared by Agriculture Extension Department regarding Time of Pesticides Application ...... 158 4.50 Association among Pictograms and Demographic Attributes ...... 161 4.51 Association among Self-Reported Acute Poisoning and Following Labels Instructions ...... 169 4.52 Association among Checking Labels and Demographic Attributes...... 170 4.53 Association among Demographic Characteristics and Precautionary Measures Used By Farming Community ...... 170 4.54 Association among Demographic Characteristics and Knowledge about the Harmful Environmental Effects of Pesticides...... 174 4.55 Association among the Trainings Received by the Farming Community and Health and Knowledge about the Harmful Environmental Effects of Pesticides ...... 176 4.56 Analysis of Variance of Literacy Levels and Knowledge about the Hazardous Health and Environmental Effects of Pesticides...... 177 4.57 Independent Sample T-test of the Involvement in Farming and Environmental Hazards of Pesticides Use ...... 184 4.58 Binary Logistic Regression of Diseases Associated with Precautionary Measures ...... 185 V SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ...... 190 5.1 Summary ...... 190 5.2 Conclusions ...... 192 5.3 Recommendations ...... 194 LITERATURE CITED ...... 197 Annexure I Interview Schedule ...... 223 Annexure II Glossary ...... 243 Annexure III Map of Pakistan and KP Province Highlighted in Box...... 252 Annexure IV Map of KP Province showing the Sampled Districts ...... 253 Annexure V Map of District D.I.Khan showing the Sampled Tehsil ...... 254 Annexure VI Map of District Charsada showing the Sampled Tehsil ...... 255 Annexure VII Map of District Mansehra showing the Sampled Tehsil ...... 256 Annexure VIII Map of District Swat showing the Sampled Tehsil ...... 257 Annexure IX Pesticides Recommended for Various Pests ...... 258 Annexure X List of Registered Pesticides Companies in KP ...... 264 Annexure XI World‘s Ranking of Pesticide Use Per Acre ...... 268 Annexure XII Imports of Pesticides to Pakistan ...... 269 Annexure XIII General Description of Pesticides ...... 270 Annexure XIV Acute Toxicity of Pesticides ...... 270 Annexure XV Ban Pesticides In Pakistan ...... 271 Annexure XVI WHO Pesticides Hazards Classification ...... 272
LIST OF TABLES TABLE NO. TITLE PAGE #
3.1 Overall Sketch of the Sampling Procedure Using Multistage Sampling Technique ...... 18 4.1.1 Distribution of Respondents Regarding Age ...... 31 4.1.2 Distribution of Respondents Regarding Literacy Level ...... 32 4.1.3 Distribution of Respondents Regarding Family System ...... 34 4.1.4 Distribution of Respondents Regarding Tenural Status ...... 35 4.1.5 Distribution of the Respondents Regarding Landholding ...... 36 4.1.6 Distribution of Respondents Regarding Involvement in Farming ...... 37 4.1.7 Distribution of Respondents Regarding Farming Experience ...... 38 4.1.8 Distribution of Respondents Regarding Major Source of Income ...... 39 4.2 Distribution of Respondents Regarding Crops/Fruits/Vegetables they Grow ...... 41 4.3 Distribution of Respondents Regarding since How Long they are Using Pesticides ...... 43 4. 4 Distribution of the Respondents Regarding the Type of Pesticides they Use Most Frequently ...... 44 4.5 Distribution of the Respondents Regarding the Source from where they Bought Pesticides ...... 45 4.6 Distribution of Respondents Regarding the Stages they Use Pesticides at ...... 47 4.7.1 Status of the Most Commonly Used Pesticides ...... 53 4.7.2 Distribution of Respondents Regarding the Use of Most Common Pesticides and there Doses ...... 58 4.8 Distribution of Respondents Regarding Decision about when to Spray ...... 61 4.9 Distribution of Respondents Regarding Information about the Dose of Pesticides ...... 63 4.10 Distribution of Respondents Regarding the Time they Follow to apply pesticides ...... 63 4.11 Distribution of Respondents Regarding the Average No. of Spray on Single Crop ...... 65 4.12 Distribution of Respondents Regarding the Picking of Fruits/Produce after Spray ...... 67 4.13.1 Distribution of Respondents Regarding Knowledge about Activity Pictogram ...... 68 4.13.2 Distribution of Respondents Regarding Advisory Pictogram ...... 69 4.13.3 Distribution of Respondents Regarding Enviromental & other Hazards Pictogram ...... 72 4.13.4 Distribution of Respondents Regarding Toxicity Levels Pictorgram ..... 75 4.13.5 Distribution of Respondents Regarding Toxicity Level Pictograms (Colour) ...... 76 4.14 Distribution of Respondents Regarding they Check the Labels or not before applying Pesticides ...... 77 4.15 Distribution of Respondents Regarding they Follow Instructions on Labels ...... 78
i 4.16.1 Distribution of Respondents Regarding Using Mask during Spraying ...... 81 4.16.2 Distribution of Respondents Regarding Wearing Separate Clothes for Spray Purpose ...... 81 4.16.3 Distribution of Respondents Regarding Action when Pesticides Came in Contact with Body ...... 81 4.16.4 Distribution of Respondents Regarding Hand Covering Material When Mixing of Pesticides ...... 83 4.16.5 Distribution of Respondents Regarding Taking a Bath After Pesticides Use ...... 83 4.16.6 Distribution of Respondents Regarding Smoking While Spraying ...... 83 4.16.7 Distribution of Respondents regarding what they do With Empty Bottles of Pesticides ...... 86 4.16.8 Distribution of Respondents Regarding Changing Clothes after Application of Pesticides ...... 86 4. 16.9 Distribution of Respondents Regarding Wearing Boots While Spraying ...... 86 4.16.10 Distribution of Respondents Regarding Using Mixture Equipment While Mixing ...... 88 4.16.11 Distribution of Respondents Regarding Covering Nose and Mouth with any other Thing (Cloth) ...... 88 4.16.12 Distribution of Respondents Regarding Knowledge about the Direction of Wind to Spray ...... 88 4.16.13 Distribution of Respondents Regarding Mixing of Pesticides in Open Place or Close Room ...... 90 4.16.14 Distribution of Respondents Regarding Eat or Drink while Spraying ...... 90 4.16.15 Distribution of Respondents Regarding Using Goggles ...... 90 4.16.16 Distribution of Respondents Regarding Using Glasses ...... 92 4.16.17 Distribution of Respondents Regarding Using Face Shield ...... 92 4.16.18 Distribution of Respondents Regarding Using Respirators ...... 92 4.17 Distribution of the Respondents Regarding the Knowledge about the Misuse of Pesticides ...... 95 4.18 Entrance into the Field after Spray ...... 97 4.19 Knowledge about the Pesticides Entrances into the Body ...... 98 4.20 Self-Reported Symptoms of Pesticides Use ...... 101 4.21 Distribution of the Respondents Regarding Knowledge about the Health an Environmental Hazards of Pesticides ...... 107 4.22 Disposal of Left Over Pesticides ...... 109 4.23 Distribution of Responds Regarding Judicious Use of Pesticides ...... 111 4.24.1 Distribution of Respondents Regarding Using Bio-Pesticides ...... 114 4.24.2 Distribution of Respondents Regarding doing Organic Farming ...... 114 4. 24.3 Distribution of Respondents Regarding doing Crop Rotation ...... 114 4.24.4 Distribution of Respondents Regarding Using Crop Mixtures ...... 115 4.24.5 Distribution of Respondents Regarding Using Trap Crops ...... 1 15 4.24.6 Distribution of Respondents Regarding Using Pheromone Traps ...... 116 4.24.7 Distribution of Respondents Regarding Using Light Traps ...... 166 4.24.8 Distribution of Respondents Regarding Hot and Cold Treatment ...... 117
ii 4.24.9 Distribution of Respondents Regarding Using Insect Resistant Varieties ...... 117 4.24.10 Distribution of Respondents Regarding Using Weeds Free Seeds ...... 118 4.24.11 Distribution of Respondents Regarding Crop Residual Removal ...... 118 4.24.12 Distribution of Respondents Regarding Using Parasites ...... 119 4.24.13 Distribution of Respondents Regarding Avoiding Imbalance Doses ...... 119 4.24.14 Distribution of Respondents Regarding Spraying Registered Pesticides ...... 120 4.24.15 Distribution of Respondents Regarding Timely Shallow Tillage ...... 120 4.24.16 Distribution of Respondents Regarding Timely Sowing Reduce Pest Pressure ...... 121 4.24.17 Distribution of Respondents Regarding Parasitoids ...... 121 4.24.18 Distribution of Respondents Regarding Using Soap ...... 122 4.25.1 Association among Activity Pictogram and Demographic Attributes ...... 164 4. 25.2 Advisory Pictogram and Demographic Attributes ...... 165 4. 25.3 Environmental & other Hazards ...... 166 4.25.4 Toxicity Levels Pictogram and Demographic Attributes ...... 167 4.25.5 Toxicity Levels (Colour) Pictogram and Demographic Attributes ...... 168 4.26 Association among Self-Reported Symptoms and Following Instructions on Labels ...... 169 4.27 Association among Checking Labels and Demographic Attributes ...... 170 4.28 Association among Demographic Characteristics and Precautionary Measures Used by Farming Community...... 172 4.29 Association among Demographic Characteristics and Knowledge about the Harmful Environmental Effects of Pesticides ...... 175 4.30 Association among the Training Received by the Farming Community and Health and Knowledge about the Harmful Environmental Effects of Pesticides ...... 176 4.31 Analysis of Variance of Literacy Levels and Knowledge about the Hazardous Health and Environmental Effects of Pesticides ...... 178 4.32 Independent Sample T-Test of Involvement in Farming and their Knowledge about the Health and Environmental Hazard of Pesticides ...... 185 4.33 Binary Logistic Regression of Diseases associated with Precautionary Measures ...... 188
iii LIST OF FIGURES FIGURE NO. TITLE PAGE #
3.1 Conceptual Framework of the Study ...... 20 4.1 Distribution of Respondents Regarding Training Provided by Agriculture Extension Department ...... 124 4.2 Distribution of Respondents Regarding How to Use Pesticides ...... 126 4.3 Distribution of Respondents Regarding Learning Safety Measures from Agriculture Extension Department ...... 127 4.4 Distribution of Respondents Regarding Learning about Integrated Pest Management from Agriulture Extension Department ...... 129 4.5 Distribution of Respondents Regarding Trained in Disposal of Pesticides and Empty Bottles ...... 130 4.6 Distribution of Respondents Regarding Trained in Application technology by Agriculture Extension Department ...... 132 4.7 Distribution of Respondents Regarding Trained in Harful Enviromental Effects ...... 133 4.8 Distribution of Respondents Regarding Trained about the Symptoms and Treatment of Poison by Agriculture Extension Department...... 135 4.9 Distribution of Respondents Regarding Environmental and Health Hazards of Pesticides Use ...... 136 4.10 Distribution of Respondents Regarding Learning about the Calibration of Pesticides...... 138 4.11 Distribution of Respondents Regarding Learning Pesticides Application Techniques ...... 139 4.12 Distribution of Respondernts Regarding learning the Safety Measures while Dealing with Pesticides ...... 141 4.13 Distribution of Respondents Regarding Learning about the Understanding Pesticides Labels from Agriculture Extension Department .....142 4.14 Distribution of Respondents Regarding Learning about the Biological Control of Pests ...... 144 4.15 Disribution of Respondents Regarding Learning about the Augmentative Measures from Agriculture Extension Department ...... 145 4.16 Distribution of Respondents Regarding Field Days Arranged about the Pesticides by Agriculture Extension Department ...... 147 4.17 Distribution of Respondents Regarding Farmers Field School Approach used by Agriculture Extension Department ...... 148 4.18 Distribution of Respondents Regarding Monitoring by Agriculture Extension Department ...... 150 4.19 Distribution of Respondents Regarding Contacts by Farmers with Agriculture Extension Department ...... 151 4.20 Distribution of Respondents Regarding Demonstrations arranged by Agriculture Extension Department on Pesticides ...... 153 4.21 Distribution of Respondents Regarding Information Shared by Extension Department Regarding Pest Resistant Varieties ...... 154 4.22 Distribution of Respondents Regarding Information Shared by Agriculture Extension Department on Mechanical Control ...... 156 4.23 Distribution of Respondents Regarding Information Shared by Agriculture Extension Department on Cultural Practices to Control Pests ...... 157
iv 4.24 Distribution of Respondents Regarding Information Shared about the Highly Toxic Pesticides by Agriculture Extension Dearptment ...... 159 4.25 Distribution of Respondents Regarding Information shared by Agriculture Extension Department Regarding Time of Pesticides Application ...... 160 4.26 Means of Literacy Level and Causes Damage to Human Health ...... 179 4.27 Means of Literacy Level and Causes Damage to Animal Health ...... 179 4.28 Means of Literacy Level and Pesticides Causes Damage to Wild Life ...... 180 4.29 Means of Literacy Level and Pesticides Harmful to Water Life ...... 180 4.30 Means of Literacy Level and Pesticides Kills Pollinators ...... 181 4.31 Means of Literacy Level and Pesticides Causes Damage to Soil Fertility ...... 181 4.32 Means of Literacy Level and Pesticides Causes Damage to Soil Organisms ...... 182 4.33 Means of Literacy Level and Pesticides Accumulation in Food Chain ...... 182 4.34 Means of Literacy Level and Resurgence of Pest due to Killing of Natural Enemies through Pesticides ...... 183 4.35 Means of Literacy Levels and Pesticides Contaminates Air ...... 183
v ACRONYMS & ABBREVIATIONS
ADHD Attention Deficit/Hyperactive Disorder AED Agriculture Extension Department As Arsenic BC Before Christ BHC Benzene Hexa Chloride CCA Chromium-Copper-Arsenate CS Capsule Suspension D.I.Khan Dera Ismail Khan DDD Dichlorodiphenyldichloroethane DDT Dichlorodiphenyltrichloroethane DET Diethyltoluamide DNA Deoxyribonuclic Acid DVN Diarrhea Vomiting Nausea EC Emulsifiable Concentrates EPA Environment Protection Agency ETL Economic Threshold Level FAO Food and Agriculture Organization FFS Farmers Field School FSCs Farm Services Centers G Granules Gm Gram GoP Government of Pakistan Ha Hectare Hg Mercury IFAD International Fund for Agriculture Development IPM Integrated Pest Management IUPAC International Union of Pure and Applied Chemistry KAP Knowledge, Attitude and Practice Kg kilogram Km Kilometer KP Khyber Pakhtunkhwa LD Lethal Dose LSGH Large-Scale Closed Greenhouses Mg Milligram MDGs Millennium Development Goals Ml Milliliter MRL Maximum Residue Limit MS Mean Square NGOs Non-Governmental Organizations NWFP North West Frontier Province OLD Oral Lethal Dose Pb Lead PPAF Pakistan Poverty Alleviation Fund PPE Personal Protective Equipment SC Suspension Concentrates SD Standard Deviation SG Soluble Granules SL Soluble Liquid
vi SMEDA Small Medium Enterprise Development Authority SPSS Statistical Package for Social Sciences SS Sum of Square U.S. United States UC Union Council ULV Ultra Low Volume UNEP United Nation Environment Program UN United Nation UNU United Nation University USAID United State Agency for International Development WG Water-dispersible Granules WHO World Health Organization WP Wettable Powder
vii ACKNOWLEDGEMENTS
I am highly obliged to my Allah Almighty whose bounteous blessings are countless and WHO bestowed the courage upon me to accomplish the gigantic task of Ph.D. research. I am highly indebted to the personality of the Holy Prophet Muhammad (Peace be upon him) whose messages always enlightened our minds to find the real destination of learning. Writing a Dissertation, is a challenging intellectual exercise that requires the efforts of many people. I have been lucky to have the guidance of Prof. Dr. Khalid Nawab, Department of Agricultural Extension Education and Communication, The University of Agriculture, Peshawar. This whole research work was carried out under his kind supervision. I express my heartiest and sincere thanks to him for building up my scientific temperament of the study. Who always inspired me to work hard with devotion and his positive and constructive criticism paved the way to get the dissertation in a refined form. I express my deep appreciation to my indigenous Co-advisor, Prof. Dr. Muhammad Zafarullah Khan for providing the basic idea about the research plan of the present study. I will remember his repeatedly saying words ―work hard with zeal and zest and don‘t take it light or burden on you so that it may become the basis of honor for you‖. I am grateful to Dr. Asad Ullah, Assistant Professor, Department of Rural Sociology for help in collecting relevant literature for this research project and valuable suggestions, technical guidance and moral support throughout the span of my study. Indeed, I am indebted to the all other teachers of Agricultural Extension Education and Communication Department i.e. Dr. Idress Khattak, Dr. Ikram Ul Haq, Dr. Ayesha khan, Dr. Urooba Dawood and Dr. Raheel for their kind suggestions and support. Moreover, I also extend my thanks to Mr. Saeed Ur Rahman Superintendent of the Department of Agricultural Extension Education and Communication for his timely processing of the formalities. I am also thankful to Mr. Nazif, Mr. Shakeel, Mr. Himayatullah and all other members of the department for their on and off help and support. It will remain incomplete if I don‘t admire the greatness with respect to guidance, solving my problems and technical as well as moral support of Dr. Kalim Ullah, Scientific Officer Pakistan Central Cotton Committee, Dera Ismail Khan. Due to his technical support and sincere help during research work, the present study was made to an end. I am in loss of literary power to express my gratitude to Mr. Inam Ullah, Asif Nawaz Shahzad Malik, Ronaq Zaman, Adnan Danishwar Khan and the list goes on who were always by my side and I am extending special thanks for their moral support throughout the Ph.D. time period. Finally, I am thankful to my parents, my brothers; Captain Sami Ullah Khan and Advocate Naeem Ullah Khan, all my family members and my friends who were enthusiastic of me getting the Ph.D. degree and to instill into me the value of hard work. Rehmat Ullah
viii INVESTIGATION INTO HEALTH & ENVIRONMENTAL HAZARDS OF PESTICIDES USE TO FARMING COMMUNITY IN KHYBER PAKHTUNKHWA, PAKISTAN
Rehmat Ullah and Khalid Nawab
Department of Agricultural Extension Education and Communication Faculty of Rural Social Sciences The University of Agriculture, Peshawar-Pakistan October, 2018
ABSTRACT
Pesticide is any agent used to kill or control pest thus helps in preventing crops from being harmed by insects, weeds or pathogens etc. Besides their advantages, the pesticides may cause unfriendly effect both on health and environment if not dealt with care. Human health and environmental risks associated with pesticide exposure are a global concern. The present study was thus an endeavor to investigate the health and environmental hazards of pesticides use to farming community in Khyber Pakthunkhwa, Pakistan. The prominent objectives of the study was investigate the toxic pesticides used by farming community in reference to the WHO toxicity classes, health and environmental risk to farmers due to improper use, possible ways to reduce the use of pesticides and part of Agriculture Extension Department in judicious use of pesticides. Cross sectional survey design was utilized as a part of the current investigation. Four union councils through multistage sampling technique was selected i.e. UC Band Kurai, Khanmai, Baffa and Baidara from districts D.I.Khan, Charsadda, Mansehra and Swat respectively. Sample size of 384 respondents was selected for the present study. SPSS ver. 20 were used for analysis of data collected. Simple frequencies, percentages were calculated whereas chi-square test, t-test and binary logistic regression model was utilized.
Statistical analysis of the data revealed that majority of the respondents were using pesticides from the last 10 years. The respondents were not using proper personal protection measures while using pesticides and re-enter their fields the following day thus increases the odds of health issues to the farming community and were suffered from various acute poisoning cases i.e. headache, sneezing, cough, nausea, dizziness, feeling weak, difficulty in seeing, eye irritation, shortness of breath, burning sensation etc. Moreover, the knowledge of the farming community regarding the health and environmental hazards was also low. Overall 49 different sorts of pesticides were reported by the farming community as the most commonly used by them and majority were insecticides. Mostly the insecticides were from Class-II (moderately hazard) of the pesticides toxicity level followed by the Class III (slightly hazard) and Class U (unlikely to present acute hazard). Only two insecticides i.e. Carbofuron and Cartap from Cartap Hydrochloride chemical group were from Class-Ib which are highly hazardous. Moreover, number of sprays in field crops were low as compared to vegetables and fruits and mostly they pick their produce in 3-5 days of pesticides application in vegetables and fruits. Similarly the other unhealthy practices of pesticides observed were the re-spray of the leftover pesticides in the same season or in the upcoming season which results in increase in number
ix of sprays per season. Disposing the left over pesticides in field or solid waste and overdosing & low dosing against the prescribed/recommended was also an un healthy practice recorded during the study which was due to the fact that majority of the respondents had less knowledge about the prudent use of pesticides and not checking and following the guidelines on labels. In this connection the role of the Agriculture Extension Department (AED) was also not palatable. Almost half of the respondents got training regarding the pesticides application, and other health and environmental issues related to pesticides but still the respondents were not fully aware of the healthy practices which showed that the office didn‘t not completely conferred or imparted the knowledge about the highly toxic pesticides, calibration of pesticides, pesticides application techniques, safety measures, understanding the labels/instructions on pesticides containers and so forth to the respondents.
It is concluded that farmers on account of less extension services regarding pesticides, uses the pesticides improperly, having no idea of proper selection of pesticides and their application time. This improper use causes various health hazards like nausea, vomiting, headache etc. it was also concluded that farmers were not been trained properly. Therefore it is suggested that farmers should be properly trained for the safe and efficient use of pesticides. Furthermore, it is also suggested that the Agriculture Extension Department ought to strictly check the sub-standard and highly toxic pesticides in the market.
x I. INTRODUCTION
1.1 Agriculture in Pakistan
Well along from its birth, agriculture played dominant part to became the back bone of Pakistan‘s economy (Haque, 2002). Pakistan holds rich natural resources, topography and water, thus has a huge potential to decent agriculture production (Rehman et al., 2011 and Rehman et al., 2013). Due to diversity in climatic zones, it has a great capability to produce all sort of foods but unluckily only ¾th out of total area is arid (Chaudhry and Rasul, 2004). Moreover, agriculture has 21% share in gross domestic product (GDP), holds 45% of work force and 60% rural inhabitants rely over it. Similarly, Khyber Pakhtunkhwa province agriculture shares 22% in provincial GDP whereas provides 44% of employment to inhabitants and about 80% population relies on agriculture on way or the other. Agriculture also contributes major part to the agro-based industries (Govt. of Pakistan, 2013) that‘s why agriculture occupies linchpin position in Pakistan‘s economy but unfortunatlly the current production of agriculture sector is much low comparatively to advance countries. The low production has many factors i.e. rain showers, lodging, climatic issues, inputs, seed, fertilizers, pesticides etc.
1.2 Pesticides
―Pesticide‖ is any agent used to kill or control any pest. a substance used for destroying insects or other organisms harmful to cultivated plants or to animals. There is a large variety of pesticides intended to kill particular pests. The most generally used are insecticides, herbicides, fungicides, rodenticides, fumigants and other pesticides include algaecides etc.
Human made pesticides are developed from natural chemicals and plants extracts for crop protection against pest. The prudent use of pesticides are thought necessary for control of weeds, insects, and diseases in order to minimize the losses and increase productivity for ever increasing world population. The statistics of UN FAO indicated that world‘s food losses are 55% and the ratio of pre-harvest are 35% and post-harvest 20%. This clearly envisaged that the due to poor handling and no crop protection strategies adopted the losses at pre-harvest stages increased. It is also alarming that
1 the pre-harvest losses in developing countries are 75% whereas in developed countries its only 10-30%. This huge gap compels the residents of developing countries to protect their crops from various sort of pest and ultimately increased the use of pesticides (Khan et al., 2011a).
The agriculture sector is under immense pressure to fulfill the food requirements in order to uphold the food security of overwhelming and ever growing population. It is evident from the statistics of FAO that 868 million inhabitants of the world undergoes from under nourishment and continues to touch the mark of 2 billion. Thus to control the losses at pre-harvest stages which is most specifically due to pest attacks is point of concern in many developing countries. Approximately, 9000species of insects, 50,000 species of plant pathogen and 8000 species of weeds damages the crops worldwide. The split of damage/losses is as; insect (14%), Pathogens (13%), weeds (13%) but these loses were declined to 35-40% due to pesticides use. Even though that the pesticides plays a crucial role in plant protection it has significant negative or adverse effect both to the human health and the environment which is the result of poor handling and misuse.
1.3 Adverse Effects of Pesticides
As farmers are not properly educated regarding pesticide use, and due to poor literacy rate, farmer can‘t read and understand the awareness brochures of pesticides which are written and printed in English and Urdu languages. They made to believe by the company representative that pesticides are the only medication to their crops; farmer used them without knowing the insect population and crop condition. They consider and believed pesticides as cure rather than a basis of poison (Anwar, 2008b). Its leakage during transportation, field application, storage and 50% of the farmers do not use protective clothing and masks during spray. Sometimes farmers retains edible oil, drinking water and milk in pesticides empty containers and their indiscriminate use due to Government‘s stress-free policies on pesticide application that may cause disturbance in the ecosystem (Khan et al., 2011b). Similarly, due to non-appearance of food laws in Pakistan resulted in the concentration of pesticides residues in food items. Similar studies (Mekonnen and Agonafir, 2002; Obopile et al., 2008; Macharia et al., 2013; Abang et al., 2014; Damte and Tabor, 2015) also concluded that the risky use of pesticides, lower dosing and over dosing of synthetic chemicals in order to
2 protect the crops from pest is more tending towards the developing countries rather than developed ones.
Choice of pesticides application greatly affects the society at large because pesticides affect the general public in multiple ways. Despite of the negative effect to the users of pesticides the pesticides affect the vernal public or consumers exposed to it directly or through food (Menzler- Hokkanen, 2006). Regardless of the serious issues/risks concern to pesticides the farming community is busy using it in order to achieve high yield by protecting the crop from pest. Due to these facts the Public Health sector has serious concern about it as epidemiological studies had reported significant association of various sorts of cancers, neurologic pathologies, respiratory symptoms and hormonal and reproductive abnormalities because of pesticides. Past studies revealed that the families who reside beside the agricultural fields have high level of pesticides contents in their bodies (McCauley et al., 2001; Quandt et al., 2004). Similarly, during the application of pesticides farmers usually suffer from the damage (Tariq et al., 2007). Even in the previous studies it is revealed that the pesticides adverse effect causes point mutation and chromosomal mutation in farming community resulting in cell transformation (Larrea et al., 2010).
Pesticides are poisonous by nature and constitute one of the most hazardous groups of toxin to the ecosystem and human health (UNU, 2003; Belmonte et al., 2005; Pimentel, 2005; Hoi et al., 2009; Panuwet et al., 2012; Ahouangninou et al., 2012). The use of pesticides in developing countries and its hazard is increasing day by day (Karlsson 2004; Hoi et al., 2013; Rı´os-Gonza´lez et al., 2013; Jansen and Dubois 2014). Due to its diversity in nature the pesticides is widely used for to fight against pest in agriculture, gardening, homes, and soil (Cooper and Dobson, 2007). But inspite of these returns, pesticide poisoning is definitely a public health problem globally and its use is still increasing, particularly in developing countries (Wesseling et al., 2001).
1.4 Pesticides Use in Developing and Developed Countries
Risk associated with human being due to exposure to pesticides is of global concern. It is being reported that this risk is high enough in the developing countries in comparison to the developed ones. Due to this fact it is of increasing concern to
3 curtail the use of widespread pesticides throughout globe because on one side pesticides protects our crops but due to misuse it has a high adverse effect in comparison to its benefit. This is not only treacherous for public health but also for the other non-targeted organism, air, water and the environment itself (Travisi et al., 2006; Cooper & Dobson, 2007; Devine and Furlong, 2007).
In the field of environmental chemistry pesticides are classified as micro-pollutants, being present in very small quantities. They are referred to as xenobiotic because they are exogenous Man-made chemicals, foreign to the natural environment and show biological, mainly biocidal, activity. When applying pesticides, most of the chemicals will directly or indirectly reach the soil. Some will drift or evaporate into the air during or after application, circulate in to the atmosphere, and after more or less changes in distribution, be returned to the soil or the water, which covers two-third of the earth surface. Run off from treated land is another major source of pesticides in surface water, and in addition large stretches of water may be treated purposively with pesticides for control of aquatic weeds, diseases vectors and undesirable fish (Haskell, 1985).
Agricultural extension is a major channel of communication between farmers and researchers to improve crop production. Extension services are one of most important cause about chemical pesticides using by farmers because extension services have focused on chemical pesticide diffusion in developing countries for long time (Orr, 2003). Agricultural extension and education missions newly focus on to improve farmer's production with environmental preservation approach. Many researchers believe that participatory methods can be more effective in IPM technology adoption by farmers as success of farmer's field school (FFS) method is evident (Asiabaka, 2002).The most prominent ones includes the FFS approach specifically in Asia and Africa which gave very fruitful results to promote IPM (Quizon et al., 2001).
In Pakistan, an agricultural extension service operates in each province under the supervision of provincial governments and is taking several initiatives to optimize agriculture productivity and production. Agriculture Extension Department is playing a crucial role in the check and balance of pesticides use, i.e. pesticides dealers‘ registration, sample testing for safe use etc. Agriculture Extension Department is the
4 communication channel through which farming community can be well trained in best and safe use of pesticides.
1.5 Justification of Study
Exposure to pesticides is major occupational risk in developing countries (Kofod et al., 2016). Organophosphates; which are most widely used pesticides causes‘ acute poisoning by inhibiting cholinesterase enzymes and results in headache, dizziness, vomiting, paralysis and worst case death (Kapka-Skrzypczak et al., 2011). About 220,000 people die worldwide because of the pesticides poisoning. The majority is from developing countries which might be due to the weak safety standards and lack of using protective measures. It is also evident from the previous studies that pesticides used in the developing countries are mostly unscientific and unregulated which is the serious threat to the human and environment (Ibrahim, 2016). The pesticides misuse is also prevalent mostly in developing countries due to their policies which is still at infancy. Several instances of chronic toxicity or deaths have been reported among the exposed farm population due to occupational, accidental or intentional poisoning (Devi, 2009).
It is not easy to develop a technology without pesticides that would produce the amount of food and fiber and sustain the level of public health that we have now-a- days. But their use is a dilemma. In Pakistan, pesticides still have a high status in their application for securing adequate agricultural production and boosting yields. The magnitude of benefit derived from using pesticides in Pakistan is suggested by the value of a gradually increase in pesticide use. This leads to the statement that only the benefits of pesticide use have been taken into consideration but the hazards produced by their use have not yet been adequately taken into description. Pest control is a main apprehension for vegetable growers. Consumers do not buy insect damaged produce. Moreover, consumers are also worried about pesticide residues, so that the health benefits produced by eating vegetables are not counteracted by any possible perils caused by pesticides that stay on fresh produce.
In order to promote safe storage, handling and use of pesticides among handlers in Khyber Pakhtunkhwa Province; it is critical to assess their degree of knowledge and safety practices with regard to pesticides practices i.e. handling, exposure routes,
5 personal protective equipment and self-reported toxicity symptoms of pesticides of the farming community. Moreover, the role of Agriculture Extension department in educating farming community regarding logical use of pesticides was also examined so that logical conclusions and suggestions could be deduced. Therefore, documentation of pesticides handlers' knowledge, practices and toxicity symptoms in Khyber Pakhtunkhwa province is very urgent. This will eventually minimize the risk of exposure to pesticides and reduce absenteeism, mortality rate and labour turnovers in pesticides and agricultural industry. Moreover, this will add to academic knowledge and foster a good basis of policies for bodies that control matters pertaining to pesticides in Khyber Pakhtunkhwa. Furthermore, the present study will also be significant in the following areas and beyond:
1.6 Research Question
Pesticides act like a double edge sword i.e. on one side it fights against the agricultural pests but on the other hand it also has an adverse effect both on human health and environment as well. Agricultural pests can cause considerable reductions in farm yields and income. As a result, pesticides are profoundly used in attempts to alleviate this problem. According to WHO estimates in 1973 the human poisoning cases reported annually were 500000 whereas in 1986 the figure crossed the one million mark plus 20,000 deaths. Similarly a joint study by United Nation Environmental Program and WHO in 1990 reported three million cases whereas 220,000 results in fatalities (WHO, 1990). The situation is more alarming in developing countries where the people death rate is high instead of infections (Eddleston et al., 2002). As farmers use increasing quantity of pesticides, poisonings will continue to increase (WHO, 1990). Unsafe use of pesticides is damaging the health of the farmers and the community in Pakistan as well and thus resulting in annual deaths of 10,000 whereas 500000 suffered from poisoning (DAWN, 2004). Therefore, it was considered imperative to conduct a study in order to find out the health and environmental hazards of pesticides use to farming community in Khyber Pakhtunkhwa with the following objectives.
6 1.7 Objectives
1. To find out the commonly used pesticides in the region and its comparison with WHO toxicity classes. 2. To find out the health and environmental risks due to improper/unbalanced/excessive use of pesticides (including symptomatic acute poisoning cases). 3. To investigate the recommended versus actually used doze of the various pesticides by the farming community. 4. To pin point the possible ways to reduce the use of pesticides. 5. Role of Agriculture Extension Department in rational use of pesticides. 6. To put forward recommendations for policy implications.
1.8 Research Hypothesis
H0 There is no significant association among demographic characteristics and Precautionary measures used by farming community.
H0 There is no significant difference among literacy levels and knowledge about the hazardous health and environmental effect of pesticides.
H0 There is no significant association among demographic characteristics and knowledge about the harmful environmental effect of pesticides.
H0 There is no significant association among the training received by the farming community and health and knowledge about the harmful environmental effects of pesticides.
1.9 Limitations of the Study
Due to time and financial constraints, one year data were gathered from representative samples of the target groups. It was difficult to probe the various sort of pesticides use by them because most of respondents didn‘t remember their names. To tackle that problem, pictures of various pesticides used in the locality were shown to them so that they may identify the exact pesticide used by them. This was done because it was one of the main purposes of the present study.
7 Sales Executive and Pesticide Dealers were also contacted in order to know what sort of pesticides they sale in the locality most frequently so as to ask about the exact use of pesticides from the farming community by showing them pictures. Due to time and financial constraints four districts were taken for the present study. It will give much better results with increased number of sampled districts.
8 II. REVIEW OF LITERATURE
The review of literature helps form a foundation upon which the entire research work must be built. The review, thus, helps researchers gain an understanding of and insight to the area of their research interests. It also guides them about the avenues that have been disregarded in the past and research methodologies used by different scientists for their studies. The purpose of this chapter is to present and synthesize what is currently known about agricultural extension and pesticide use in agricultural settings. In order to have a comprehensive view of the related literature, the researcher conducted an extensive search of the relevant literature. For this purpose, books, research journals, thesis, reports, workshop proceedings and websites related to the study were visited. Few past researches are discussed below:
2.1 Health Effects and Misuse of Pesticides
Mancini (2006) conducted a study to examine the impact of IPM in cotton farming. This study was carried out where FFS approach was implemented on IPM in cotton area. Two groups were included in the study i.e. those who did participation in FFS whereas those who didn‘t participated. He reported that 84% of the respondents were suffered from acute poising and among that majority were of women and poor farmers. WHO category Ib and II were the commonly used pesticides used in the area. The spray rate per season was found to be 8 sprays per season. The IPM minimized the use of spray up to 78% without any harm to productivity. He further reported that IPM has minimized the pesticides use but there is still a scope to reduce the impacts such global warming etc. He put forward the conclusions that activities based on education seems to be efficient approach resulting in direct access to the quality trainings.
Devi (2009) studied the level of awareness regarding pesticide use/ handling in the farms of Kerala. The understating of pesticides use from various aspects revealed better understanding from one side and poor understanding on the other. The workers were unaware of the colour code on the packets regarding the toxicity due to lack of proper training. Due to this fact they were using even toxic pesticides as considering it the safe one. Majority of the respondents were literate in the area but no one bothered to read the labels. Acute health risks were reported by very few however it frequency
9 was increasing day by day. This might be due to the fact that the workers had inadequate understating of the toxicity levels, poor handling practices etc. The present study highlighted that there is dire need of trainings to farming community regarding scientific management of pesticides and its use.
Khan et al. (2011a) conducted a study extracted pesticides residues through anhydrous sodium sulfate and ethyl acetate from leaf and edible portion whereas chromatography technique for cleanup process. All the extracts were exposed to HPLC for separation purpose. On the edible portion significant pesticides residue were found whereas highly significant difference was found for the leafy portion. In the edible portion of bitter gourd traces of cypermethrin was found whereas Lambda cyhalothrin and Mancozeb traces were detected in edible portion of bitter gourd and cucumber respectively. The Cypermethrin traces were also found in high amount (1.86 mgkg-1) in Okra leaves.
Latif et al. (2011) conducted a market based survey to examine the levels of the 26 pesticides in some common fruits of Hyderabad region of Pakistan. Gas Chromatography along with micro electron capture detector was used to extract the level of pesticides residue. Results showed that out of the 131 samples about 53 were contaminated whereas 3 samples exceeded the MRLs of some pesticides. The two pesticides viz. Chlorpyrifos (1256 µg/kg) and dieldrin (1236 µg/kg) were detected in almost all samples and this was in higher concentration in orange and apple samples. These results showed that there was contamination of fruits in the Hyderabad region of Pakistan and they further suggested that monitoring studies should be launched on other fruits in other locality of the Pakistan which may serve for the future policy implication regrind the use of pesticide.
Sefa et al. (2015) found that in Ghana for the management of pest farmers mostly used chemical pesticides. However the adverse effect on environment and health also increases. Therefore they conducted a study to know the safe use of the pesticides by farming community. Results of their study showed that majority (92.4%) of the respondents used Knapsack sprayers for pesticide application purpose. Hand held applicator was used by 4.5 % of the respondents whereas 3.1% of the respondents used mortised sprayers. Only 15.6% of the respondents use protective stuff while
10 spraying whereas over 80% of the respondents reenter the field within 3 days. The study also revealed that the farmers suffered from acute poising
Faheem et al. (2015) reported that most of the pesticides are synthetic chemical compounds most intensively used in agriculture. These pesticides are not problem- free, despite the gigantic benefits resulting from them. The extensive use of pesticides poses a risk to plants, animals and human as some of them are persistent and their toxic residues may enter food chain. Pesticides are continuously being used in developing countries, which are increasing gradually and majority (60-70%) of the pesticide-poisoning cases occurs there. Farmer‘s illiteracy, pathetic law enforcement, unfavorable hygienic conditions makes the situation worse in these countries. The data on pesticides residues in fruits shows that the most of samples are contaminated with one or more pesticides including organochlorine, however, this contamination remains within the maximum residues level (MRLs) with few exceptions. The fruit samples from cities like Karachi, Hydrabad and Nawabshah shows 36%, 12.5% & 8% of samples were contaminated with one or more pesticide with concentrations higher than MRLs. The data on pesticides residues in cattle meat/fish/poultry is very scarce; few studies report the presence of one or more pesticides from cities like Karachi and Faisalabad with 100% contamination of samples. Cattle meat (muscles) samples from Faisalabad show the pesticide contamination as high as 47 times the MRLs.
Sainju (2015) conducted reported in his study that knowledge regarding the personal protective equipment was known to 85% used mask, 8% used gloves. Thus, no farmers were found using boots and goggles. Practices of washing hand among farmers were found to be93%. Majority (92%) of the farmers neither smoked nor drank or ate anything during spray of pesticides. There is a low education level, lack of information about pesticide residue, and inadequate personal protection during pesticide use among farmers in Thimi Bhaktapur.
Imoro et al. (2019) conducted a survey and identified 39 agrochemical shops in the Tamale Metropolis. Thirty-six different pesticides were identified on the market, mainly comprised of insecticides and herbicides. The predominant active ingredients were cypermethrin and glyphosate in insecticides and herbicides, respectively. The survey revealed 18 kinds of pesticides commonly used by the farmers on their fields, with atrazine being the most commonly used herbicide (42%) and Lambda Super 2.5
11 EC the most commonly used insecticide (50%). The study also revealed that 64% of the respondents disposed of their empty pesticide containers indiscriminately and 44% stored used and unused pesticides in their bedrooms.
2.2 Environmental effect of Pesticides Use
Tariq et al. (2007) reported that inspite of the use of heavy pesticides had controlled the pests but on the other hand like other countries Pakistan is also facing numerous problems from heavy use of pesticides. The water table is also found contaminated due to the use of pesticides in some area of Punjab and Sindh. In cotton growing areas there is considerable evidence that pesticides used has been over used due to which farmer‘s health is at higher risk for acute and chronic health effects. Similarly it is also important aspect that the farmers used higher doze than the recommended due to which the cotton pickers, workers etc. are at higher risks due to heavy concentration of pesticides.
Fianko et al. (2011a) put forward his findings that using pesticides had significantly improved the agriculture productivity in Ghana however its heavy use led to environmental problems. They further reported that in Ghana water bodies, soil, and sediments had been found in Ghana to be contaminated with pesticides which is the clear cut evidence that farming community had significantly increased the use pesticides. From biological point of view many studies showed that human health is at risk due to the heavy pesticide use. Many studies reported the chronic as well as acute poisoning of the human beings due to pesticides. In this connection the major threat is to the field workers and consumers. This also stagnant the trade to the foreign because of high level of pesticides residue in the food products.
Adeola (2012) examined the pest management, awareness and perception about the environmental risks due to the use of pesticides. Data was collected from vegetables growers which were selected through purposive sampling technique. The results showed that wide variety of pesticides were in use by the farming community. Similarly majority of the respondents were aware of the environmental risks but though majority (85%) of the respondents never bothered to use protective clothes etc. while applying pesticides. Farmers showed a positive attitude towards the negative
12 effect of pesticides on environment. It was recommended that extension department should promote the safe use of pesticides and trainings should be arranged.
Kabir and Rainis (2012) determined the level of farmers‘ perception about harmful effects of pesticides on environment. They sampled 180 farmers were and personally interviewed them. The results showed that majority (86.1%) of the respondents had low to medium level of perception; while only 13.9% farmers had high perception regarding adverse effects of pesticides on environment. Results of linear regression analysis indicated that extension contact, experience in vegetable farming, education and training on integrated pest management (IPM) are the four factors that significantly influence the farmers‘ perception.
Shahid et al. (2016) highlighted that pesticides are widely used worldwide to control a range of pests infesting the agricultural crops. Increased use of pesticides has threatened human and environmental health. They further reported that of the total pesticides used in Pakistan, insecticides shared major portion, followed by herbicides, acaricides, and fumigants. High percentage of pesticides is being applied in the Punjab province, followed by Sindh, Khyber Pakthunkhwa and Baluchistan. In Pakistan, the pesticide uses are mostly focused on cotton crop (almost 70–85 % of total pesticides use) and other crops such as wheat, sugarcane, maize, rice and tobacco as well as for vegetables and fruits. Different groups of pesticides, especially the residues of organochlorine, have been reported in soils and waters in different areas of Pakistan.
2.3 Role of Agriculture Extension in Safe Use of Pesticides
Al-Zaidi et al. (2011) conducted a study to find out the farmers knowledge level about the effect of pesticides on environment. It was conducted in six different locations with lump sum of 204 farmers which were selected through stratified random sample. It was found that only 5% of the respondents didn‘t rely on Agriculture extension as they preferred other sources for seeking information. It was also found that they majority of the farming community had positive attitude towards the negative effects on the environment due to use of pesticides. Axi-sprayers or portable sprayers were found to be the most common method of spraying. They reported a need was felt to launch the training programs by agriculture extension department. They also further
13 suggested that the existing agriculture extension services also need to be improved in order to make positive contribution in increasing production alongside ensuring the health factor and environmental factor due to use of pesticides. Similarly the communication gap between the research and extension need to be filled because it was found that mostly farmer rely on agriculture extension as a source of information therefore the research findings of updated technology must be promoted to the farming community.
2.4 Summary of Review of Literature
From the present review of literature it is concluded that the use of the pesticides had an immense effect on health and environment of the farming community. The major reason found were the heavy use of pesticides and over dozing which results in acute and chronic health risks. In most of the studies the traces of pesticides in the food was also found. This was due to the fact that the farmers were unaware of the labels its proper use, which protective measures to be followed and from which class it belongs. It is also concluded from the past review that the major threat is that farmers are unaware of the WHO classes due to this fact they never knew the toxicity of the pesticides which results in their acute and chronic health risks. Similarly it is also observed that the use of pesticides not only effect the instant user i.e. farmer but due to its residual effect it also effect the consumers. It is also concluded from the past review that the agriculture extension department played its part in minimizing the use of pesticides without the loss to the productivity. While in one another study it is concluded that the extension can do much better in this regard because most of the farmers rely on agriculture extension as a source of information.
14 III. MATERIAL AND METHODS
This chapter provides the detailed sketch of the methodology i.e. how the research was conducted and which procedures were followed to inspect the problem under study. Therefore, the details of factors considered in this study viz. universe of study, research and sampling design, till the analysis of data are given in this chapter. The details are as under:
3.1 Universe of Study
The universe of study was Khyber Pakhtunkhwa (KP) province of Pakistan which is divided into 4 Agro-Ecological Zones Viz. Northern Mountainous, Eastern Mountainous, Central Plain Valley and Southern Piedmont Plain. The KP province is shown on Pakistan Map as Annexure III.
3.1.1 Khyber Pakhtunkhwa the Study Province
Khyber Pakhtunkhwa is located in the northwest region of Pakistan. It is aligned with the border of Afghanistan. The Khyber Pakthunkhwa was known as NWFP (North West Frontier Province) till 2010; afterwards its name was changed to Khyber Pakthunkhwa. It is the 3rd largest province both by population and economy; however, it is smaller geographically. The residents of this province are mostly Pashtuns, Hazarewal, Chitrali and Kohistanis.
Khyber Pakhtunkhwa has a diversified climate. In the extreme north the temperature is quite low however, in the extreme south the temperature is quite high i.e., District Dera Ismail Khan is one of the hottest places in south Asia. The air of this area is quite dry and daily and annual range of temperature is quite large. Rainfall also varies widely. Although large parts of Khyber Pakhtunkhwa are typically dry, the province also contains the wettest parts of Pakistan in its eastern fringe especially in monsoon season from mid of June to mid of September.
3.2 Sampling Design
A definite plant of obtaining sample from a population is referred as sampling design. Multistage sampling design was utilized in the present study.
15 3.2.1 Multistage Sampling
Multistage sampling technique was used in the present study. The multistage or cluster sampling is imperative because it is economically apt and secondly it is suitable when the sampling frame of the individual elements is not available. It is the selection of sample from the subset at each stage (Cochran, 1977). The multistage sampling of the respondents is as under:
3.2.1.1 Stage 1. Selection of Districts
One district was selected randomly from each Agro-ecological zone. In this connection, District Dera Ismail Khan (D.I.Khan) was selected from Southern Piedmont Plain, District Charsadda from Central Plain Valley, and District Mansehra from Eastern Mountainous Zone whereas District Swat was selected from Northern Mountainous Zone. The locations of the sampled districts are shown in Annexure IV.
3.2.1.1.1 District D.I.Khan
District D.I.Khan has the hottest climate in South Asia and thus Dates are grown here in abundance and are one of the major exports. One of the most famous products of this district is "Dhakki date" and Langra mango. Major crops grown in the district are cotton, maize, rice, sugar cane, gram, wheat, barley, rape seed and mustard. Agriculture is major source of earning and this district is very well known for its horticultural crops. Vegetables grown in the district are garlic, ladyfinger, onion, potato, bringel, turnip, carrot, tomato and chilies among others (SMEDA, 2009).
3.2.1.1.2 District Charsadda
Charsadda is 17 miles from Peshawar located in the west of the KP Total cultivated area is 210255 acres (61%), irrigated area is 180339 acres, i.e. 86% of the total cultivated area. (http://www.smeda.org/index.php?option=com_content&view= article&id=105&catid47 & Itemid=258). The land of Charsadda is known to be the most fertile land of Khyber Pakhtunkhwa and the most common growing crops are wheat, maize, rice, potato, tomato and sugarcane. Major fruits in Charsadda are water melon, musk melon, apricots, dates, guava, mango, pear, peaches, plums, persimmons and strawberry (SMEDA, 2009).
16 3.2.1.1.3 District Mansehra
The name of District ‗Mansehra‘ is derived from its headquarters town Mansehra. Mansehra district comprised of two important cropping seasons i.e. kharif and rabi. The kharif, ranges from April to August whereas rabi ranges from October to March. The major crops grown in this district includes maize, rice, wheat, peas and other seasonal vegetables. Due to favorable climatic conditions, the district is rich in vegetables and fruits. Cabbage, carrot and radish in vegetables and peaches, plums and pears in fruit are grown in the area (SMEDA, 2009).
3.2.1.1.4 District Swat
The valley of Swat is situated in the north of Khyber Pakhtunkhwa province. The district is enclosed by the sky-high mountains. Chitral and Gilgit are situated in the North, Dir in the West, and Mardan in the South, while Indus separates it from Hazara in the east. Swat lies in the temperate zone. The summer in lower Swat valley is short and moderate while it is cool and refreshing in the upper northern part. The winter season is long and extends from November to March; rain and snowfall occurs during this season. The average annual precipitation in district Swat ranges from 1000mm to 1200mm. The major crops grown here are maize, rice, canola, onion, tomato, fruits etc. (PPAF, 2015).
3.2.1.2 Stage II Selection of Tehsils
Single Tehsil was selected from each district keeping in mind the time and financial resources. The tehsils selected were as; Tehsil Paharpur, selected from district D.I.Khan, Tehsil Charsada in district Charsada, Tehsil Mansehra in Mansehra whereas Tehsil Matta was selected in Swat district. All these tehsils were selected in collaboration of Agriculture Extension Department, Govt. of KP and these were the agriculture rich tehsils.
3.2.1.3 Stage III Selection of Union Councils
From each selected Tehsils one Union Council was selected i.e. Union Council Band Kurai, Baidara, Khanmai and Baffa was selected from Tehsil Paharpur, Matta, Charsadda and Mansehra respectively. These UCs were selected purposively with the
17 collaboration of Agriculture Extension Department that these UCs are agriculturally rich.
3.2.1.4 Stage IV Selection of Sample Size and Respondents
The sample size was determined on the basis of guesses variability i.e. 50% for maximum sample size as suggested by Kasely and Kumar (1989). Therefore, the number of farmers (respondents) included in the present study were determined using formula for unknown population which is defined in Equation (i).
n = Z2 V2/ d2------(Equation i) Where, Z2 = Reliability coefficient (Constant) = 1.96 n = Sample size V = 50% this is because similar studies were difficult to find and taking the assumption that 50% of the farmers will be using pesticides in their fields d = assumed marginal error (5%) n = (1.96)2 (50)2 = 384 2 (5) Therefore, through equal allocation formulae, 96 respondents were selected each from the selected Tehsils.
Table 3.1 Overall Sketch of the Sampling Procedure Using Multistage Sampling Technique Union Sr. # Zones Districts Tehsils Sample Council
1 Northern Mountainous Zone Swat Matta Baidara 96
2 Eastern Mountainous zone Mansehra Mansehra Baffa 96
3 Central Plain valley Charsadda Charsadda Khanmai 96
4 Southern piedmont Plain D.I.Khan Paharpur Bandkurai 96
Total 384
18 3.3 Conceptual Framework
For the purpose of this study two types of variable were used. The dependent variables included respondents‘ health effects (acute poisoning cases) due to pesticides use whereas the independent variables consists of the demographic attributes, checking labels, knowledge about the labels, training revived from the Agriculture Extension Department, knowledge about the health and environmental hazards of pesticides use and using personal protective equipment. Through this proposed framework the association of demographic attributes was checked with following instructions, checking labels, knowledge about the harmful health and environmental effects and personal protective equipment used by farming community. Furthermore, the proposed framework also provides an opportunity to examine whether the training given by the Agriculture Extension Department has any influence on the knowledge about the harmful health and environmental effects. Finally, the influence of the personal protective equipment utilization and its effect in reduction of acute poisoning was also examined (Figure 3.1).
19
Demographic Attributes Following Instructions
Age Checking Labels Literacy
Landholding Training Received by farming Involvement in Farming community from Agriculture Extension Department Farming Experience
Knowledge about the harmful health and environmental effects
Personal Protective Equipment used by farming community
Independent Variables
Health and Environmental hazards
Dependent Variable
Fig. 3.1 Conceptual Frame work of the study
20
3.4 Research Design
The decision of using the appropriate research design is the real crux of the study in order to find the solution to the issue under examination (Farooq et al., 2007). The research design authenticates that the procedure used in the study is good and adequate. It also surges the value and worth of the study through cognizance of different dimensions of data and focusing the correct results. Therefore, the goal of precise, solid and legitimate results achievement, the smooth and appropriate way is the suitable research design selection.
Cross sectional survey design was utilized as a part of the current investigation. Data collected at one point is the fundamental concept of cross sectional survey (Borg and Gall, 1989). It is best suited in determining the perceptions, expectations and respondents interests. The cross sectional survey is also most appropriate in a view to establish correlation between two and more variables and could be examined by a range of methods. It is also useful due to the fact that it can be utilized both for small as well as large population by selecting studying samples, to discover the incidence distribution and relationships of various social and psychological aspects (Kerlinger, 1964).
3.5 Operationalization of Variables
The operational definition refers to how the specific variables was measured in the current study. In different studies different variables may be measured with different way however in the present study how the variables were measured is discussed below:
3.5.1 Knowledge about the Labels
Knowledge about the labels over the pesticides containers specifically the pictograms was assessed by asking respondents and showing them the actual pictogram and their response was consider as yes if they successfully identify the pictogram whereas otherwise if the respondents were unable to identify the concern pictogram.
21 3.5.2 Most Commonly Used Pesticides and their Doses
The most commonly used pesticides by the respondents were assessed by asking respondents about the regularly and most commonly used pesticides by them other than that which is used often by them. For those commonly used pesticides the actual dose used by them was also investigated in terms of ml and gm per liter of water and this was then converted to per ha dose. The farmers' dose was then compared with the recommended dose through paired sample t-test to find out the difference among the actual dose and the recommended dose.
3.5.3 Knowledge of the Respondents Regarding Pesticides Practices, Judicious Use of Pesticides and Self-Reported Symptoms
This refers to the existing practices being performed by the respondents regarding pesticides use. Precautionary measures farmers used during pesticides practices was mostly assessed through true false type of response i.e.‖ Yes‖ for performing and No for not performing the specific precautionary practice. Similarly, knowledge about the misuse of pesticides was also assessed through true false type of response i.e. ‖ Yes‖ for having knowledge about it and ―No‖ for no concept of it. The judicious use of pesticides was assessed using the same ―Yes‖ and ―No‖ scale. Those who had concept about and was agree about the particular practice of judicious use was considered as ―Yes‖ whereas those who had no concept or was not agree with the particular technique of judicious use was considered as ―No‖. Similarly, for the acute poisoning cases the response was also assessed in ―Yes‖ and ―No‖. Those who experienced any acute poisoning was considered as ―Yes‖ whereas those who never experience any particular acute poisoning was considered as ―No‖.
3.5.4 Harmful Environmental Effect of Pesticides
Knowledge about the harmful environmental effects of the pesticides were assessed from the respondents by using 4 point scale i.e. don‘t know, low, medium and high. The scale was measured as Don‘t know = having no concept or only heard about it Low = low level of knowledge about it (less than 40% accuracy) Medium = Medium Level of knowledge about it (41- 60% accuracy)
22 High = High level of knowledge about it (above 60%)
3.5.5 Alternative Techniques to Pesticides Use
The extent of knowledge about the alternative technique to pesticides use was assessed using 5 point liker scale. The respondents were enquired about the lump sum of 20 alternative techniques and they were asked to rate their knowledge on a self- reported Likert scale of 5 points which is as follows: 1 = very low 2 = low 3 = medium 4 = high 5 = very high
Whereas very low refers to the no concept at all about it, low refers to the only concept about it and no thorough knowledge, medium for having knowledge about it but not applied it practically, whereas the high refers to knowledge and applied often whereas the very high refers to having knowledge and they are practicing it frequently.
3.5.6 Role of Agriculture Extension
Role of Agriculture Extension Department was assessed from the respondents in respect of various activities which agriculture extension perform under their mandate i.e. advisory service, trainings etc. in the form of ―Yes‖ and ―No‖. Those respondents who got services from agriculture extension department about particular variable was considered as ―Yes‖ and those who didn‘t get services about particular variable was considered as ―No‖
3.6 Research Instrument
Various methods i.e. questionnaire, interview schedule etc. can be used for collection of data but the data collection through personal interview (Interview Schedule) technique gives opportunity to the interviewer/researcher to dig out the factual data upon which research can rely (Denscombe, 2003 ; Khan, 2007). This is because of the fact that personal interview technique is much flexible, adaptable and more
23 importantly, the reaction rate is high. Thus keeping in view the importance of interview schedule and objectives of the present study, well-structured interview schedule was developed which was based on open, close and partially open ended questions. The farmers were inquired regarding these questions/information. The questions were based on health and environmental hazards to the farming community. Moreover, 5 point Likert Scale (Ali, 2011; Haq et al. 2009; Ajayi and Gunn, 2009) was also utilized i.e. 1 for very low, 2 for low, 3 for medium, 4 for high and 5 for very high.
3.7 Inclusion and Exclusion Criteria
Only those respondents were included in the study that had three or above acre agricultural land in case of district Charsadda and District D.I.Khan whereas in case of District swat and District Mansehra those farmers were included in the study that holds at least more than 1 acre agricultural land.
3.8 Validity of the Research Instrument
Validity of research instrument is judged by the experts keeping in view the purpose and objectives of the study. Validity ensures the accuracy of the research instrument that either the particular research instrument will be valid for doing any particular study for which it has been developed. Face validity and content validity of the research instrument ensures to greater extent that precise data are been collected. In validity of the research instrument both face and content validity are important. Face validity refers to the response from the audience to the specific research instrument whereas content validity refers to the questions covered the area of interest (Wimmer and Dominick, 2003). Therefore, face and content validity of the interview schedule was measured. Specialists from the Department of Agricultural Extension Education and Communication, The University of Agriculture, Peshawar checked the face and content validity of the data collection tool and suggestions was incorporated as brought forwarded by them.
24 3.9 Reliability of Research Instrument
Getting quality data requires validity and reliability of the research instrument and is considered as one of important steps because reliability is the counterpart of the validity (Wingenbach et al., 2003; Khan et al., 2012). Reliability refers to the internal consistency of the research instrument and thus the internal consistency has its own distinctive place in the research instrument. The internal consistency is actually the homogeneity or the continuity of an instrument in terms of reliability (Cronbach, 1951). Reliability can also be explained as a two separate concepts i.e. size of instrument error which reflects the observed results and second is the degree to which measurements are repeatable over time. There are many different ways to determine reliability (Nunnally and Bernstein, 1994). Cronbach‘s alpha coefficient is one method of assessing the internal consistency (reliability of an instrument). For reliability of the research instrument, data from 30 farmers were collected which were not included in actual study. After collection of the data, the data were subjected to SPSS ver. 20 for scale test i.e. Cronbach‘s alpha test (Cronbach, 1951). Cronbach alpha value obtained was 0.831 representing good internal consistency.
3.10 Data Collection
Data collected for the present study were based on both primary and secondary sources. Various published and unpublished sources were used for the purpose of secondary data whereas primary data were collected using well developed interview schedule. Face to face interviews were conducted in order to record firsthand information and to remove any ambiguity of the respondents as and when prevails regarding any question. Face to face interview technique was selected because all the respondents were not expected to be in the condition to answer the questions because there is possibility of illiterate farmers among the respondents, even though the literate will not be in the position to respond properly to all the questions. Therefore, the personal interview was used to be suitable gain the firsthand information from the respondents.
25 3.11 Statistical Analysis of Data
Statistical Package for Social Sciences (SPSS) ver. 20 was used for analysis of the data. Simple frequencies and percentages were calculated whereas data were also presented in graphs where felt necessary. Moreover, the following inferential statistics were applied.
3.11.1 Chi-Square Test
The association test i.e. chi-square was used to find out the association among various variables of the study at 95% confidence level. Chi-Square test can be expressed as (equation (3.1)…
rc 2 2 ()Oeij ij ……………………….. (3.1) ij11 eij
This represents that it follows 2 -distribution with (rc 1)( 1) degrees of freedom under null hypothesis (Hₒ). However, Oij is the observed frequency and eij is the expected frequency.
3.11.2 One Way Analysis of Variance (ANOVA)
In order to find out the significant difference among three or more than three independent groups one way Anova is used. It measures the means of the groups and tell us that either they are significantly different among them or not. The assumptions of Anova are…
Population is normally distributed The groups under consideration are independent
Moreover, ANOVA is robust in nature and it can give accurate results even with slight violation of the assumptions (Chaudry and Kamal, 2009).
Specifically, it tests the null hypothesis:
H0 = µ1= µ2= µ3=….. µk
26 3.11.3 One Sample t-Test
The hypothesis for one sample t-test are as follows:
H0 = No difference exist between the true mean and compare value
Hi = Difference exist between the true mean and compare value
This clarifies that the null hypothesis should be rejected if difference exists between the true mean and compare mean. The alternative hypothesis can be assumed in one of the three forms i.e. measuring difference irrespective of the direction, two tailed hypothesis is used. Secondly if the directions matters among the sample mean either an upper tailed or lower tailed hypothesis is used. However, the null hypothesis remains the same for each type of one sample t-test (Chaudry and Kamal, 2009).
The one sample t-test is defined in equation 3.2 as…
̅ ------(Equation 3.2) ̂ √ ̅ = The sample mean ̂ = The sample standard deviation n = The sample size
m0 = The hypothesized value
3.11.4 Independent Sample t-Test
Independent sample t-test is parametric test and measures the means of the two independent groups and tell us that either any statistical difference exists between them (Chaudry and Kamal, 2009).
The independent sample t-test is defined in equation 3.3 as…
̅̅̅̅ ̅ ̅̅̅ ----(Equation-3.3)
√
Where;
̅̅ ̅ = Mean of first sample
̅̅ ̅ = Mean of second sample
27 n1= Standard deviation of first Sample n2= Standard deviation of second Sample
S= Pooled standard deviation
3.11.5 Binary Logistic Regression Model
Formally, a logistic model is one where the log-odds of the probability of an event is a linear combination of independent or predictor variables. A logistic regression will model the chance of an outcome based on individual characteristics. Because chance is a ratio, what will be actually modeled is the logarithm of the chance given by:
Log (π/1−π) = β0+β1x1+β2x2+…βmxm
Where π indicates the probability of an event, and βi are the regression coefficients associated with the reference group and the xi explanatory variables.
D= Dummy (0=Otherwise 1= Yes)
Y = Self-Reported Symptoms (D)
β1= TBAPU (D) (Taking Bath after Pesticide Use)
β2= SWS (D) (Smoking While Spraying)
β3= CCAPP (D) (Change clothes after application of pesticides)
β4= CNM (D) (Covering Nose and mouth)
β5= EDWS (D) (Eat or drink while spraying)
β6= UFS (D) (Using face shield)
β7= UR (D) (Using respirator)
3.11.6 Kruskal Gamma Test
The gamma coefficient (also called gamma statistic, or Goodman and Kruskal gamma) tells us how closely two pair of data points match. Gamma tests and association among points and also tells us the strength of association. Gamma can be calculated for ordinal variables that are continuous variables or discrete variables. It is also particularly useful when data has outliers, as it doesn‘t effects the results much. The gamma coefficient ranges between -1 to 1. The closer to 1 or -1 the stronger the relationship will be.
28 1 = perfect positive association
-1 = perfect negative association
0 = there is no association
29 IV. RESULTS AND DISCUSSION
The worth of results and discussion chapter is to explicate the findings of the study in a systematic manner. The findings regarding current problem are presented with respect to the previously known facts about the problem and also to clarify innovative understanding about the problem. The purpose of research is not only the collection of data but it also includes the presentation of the analyzed data in a logical form so that it can be easily understood. Keeping in view the above importance, findings of the present study are organized along with interpretation and discussion in this chapter in order to make coherent inferences.
4.1 Demographic Profile
Demographic characteristics refers to the background characteristics of the respondents i.e. age, education, literacy status etc. which has the possible effect on the other variables of the study. Therefore data regarding set of these demographic characteristics of the respondents were collected and presented in this section.
4.1.1 Age of the Respondents
Age is an important variable in the decision process (De-Acedo Liza´rraga et al., 2007) on the ground that younger farmers tend to be more adaptable in their choices to embrace new ideas and adopt proper and safe handling methods. Moreover, old age farmers did not trust new agricultural technology and adhre to their old patterns of agricultural activities (Duah, 2002). Due to the utmost importance of the age factor the sampled respondents were probed regarding their ages and were categorized into three categories i.e. 28-34 years, 35-45 years and 46-62 years as shown in Table 4.1.1.
30 Table 4.1.1 Distribution of Respondents Regarding Age Age of the Respondents UCs Total 28-34 Years 35-45 Years 46-62 Years
Bandkurai 9(2.4) 30(7.8) 57(14.8) 96(25)
Khanmai 13(3.4) 33(8.6) 50(13.1) 96(25)
Baffa 17(4.5) 42(10.8) 37(9.6) 96(25)
Baidara 19(4.9) 30(7.8) 47(12.2) 96(25)
Total 58(15.2) 135(35.1) 191(49.7) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
Results in Table 4.1.1 showed that majority (49.7%) of the respondents were from the age category of 46-62 years, followed by the respondents which were from the age category of 35-45 years. Only 15.2% of the respondents were from the age category of 28-34 years. Among the age category of 46-62 years majority (14.8%) of the respondents were from Bandkurai Union Council, followed by the 13% who were from the Khanmai Union Council. Only 9.6% of the respondents from the age category of 46-62 years were observed in Baffa Union Council. These results exhibit that middle aged and above middle age farmers were typically hooked in agricultural sector and the young people have been engaged in activities other than agriculture. These findings are in accordance with the previous findings of Rajashekar et al. (2017) who also reported that most of the respondents (46.70%) who belong to middle age were involved in agricultural activities. Khurshid et al. (2017) also testified that majority of the respondents that were involved in agricultural activities belong to old age group. The results are also in consonance with that of Chuks (2014), Sharma (2014), Jamali et al. (2014) and Giri et al. (2009) who narrated that majority of respondents were either from middle or older age.
4.1.2 Literacy Level of the Respondents
Education is the main and very important weapon which can bring about the desirable transition in the behavior. Education reflects in the form of mental maturity, expands and enhance knowledge, improves the quality of mind and general competency
31 especially by the mean of formal schooling education. The educated and well qualified person seems analytical, logical and wise towards various state of affairs occur to him and due to this fact it is also confirmed from various other past researches (Ekanem et al., 2006; Okunade, 2007; Ata, 2011) that it plays a foremost role in the adoption practices by farming community. Furthermore, educated farmer can easily cognize the matter of food security to the country and thus plays its role best in it by making sage agricultural decisions (Ata, 2011). Similarly, there is a general insight that farmers who had high education acquire more income from agricultural sector. This is because of employing the technological advancement of agriculture on their fields and swiftly amending themselves to these technologies instead of refraining. Moreover, capability of farmers who had high education is greater as compared to the illiterate ones because of the fact that education clearly strengthen learning ability (Okunade, 2007) and has strong association with getting good agricultural information (Ekanem et al., 2006). Therefore, data regarding literacy status was recorded and based upon the responses of the respondents four categories were developed as shown in Table 4.1.2.
Table 4.1.2 Distribution of Respondents Regarding Literacy Level Literacy Level of the Respondents UCs Total Middle Matric Intermediate Above Intermediate Bandkurai 34(8.9) 45(11.7) 5(1.3) 12(3.1) 96(25)
Khanmai 24(6.2) 41(10.7) 15(3.9) 16(4.2) 96(25)
Baffa 22(5.7) 22(5.7) 27(7.0) 25(6.5) 96(25)
Baidara 24(6.2) 25(6.5) 21(5.5) 26(6.8) 96(25)
Total 104(27.1) 133(34.6) 68(17.7) 79(20.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Results in Table 4.1.2 showed that majority (34.6%) of the respondents were literate up to matric followed by the literacy category of middle (27.1%). Similarly 20.6% of the respondents were literate above intermediate level whereas intermediate level respondents were only 17.7% of the total respondents. Among the matric level respondents‘ majority (11.7%) were from Bandkurai Union Council followed by the respondents from Khanmai Union Council i.e. 10.7% (Table 4.1.2). Moreover, only
32 5.7% of the literate respondents up to matric were from Baffa union council. These results showed that in agriculture sector somehow farmers are literate which represent a good sign that they can do the best decisions regarding agriculture farming. Our results are in divergence with that of Okwu (2007); Rayit (2010) and Ata, (2011) who espied 37%, 49.2% and 59% illiterate respondents in his research findings respectively. These findings are in agreement with that of Giri et al. (2009) who reported that majority of the respondents were literate whereas Mengistie et al. (2017) reported majority as illiterate. The instant contradiction of results might be due to the fact of change of behavior of respondents or nature due to change in locality of the study. Similarly, present findings are in consonance with that of Jamali et al. (2014) who pinpoints majority of the respondents as literate up to primary.
4.1.3 Family System of the Respondents
In the joint family system each individual shares what s/he had; the members of joint families hold large landholdings thus fulfilling the necessities of daily basis through joint venture and most specifically the man power for the agricultural activities. This helps in optimized productivity in contrast to the nuclear family system probability because of the small landholding and less labour. The procurement of labour by the nuclear families thus increases the cost of production and results in low net income. Moreover, in comparison to nuclear family system, the purchase power of joint family system will be high enough and thus various farm implements may easily be available to the farmers having joint family system (Ullah, 2015). The respondents were investigated about their family system and their responses were classified into two categories i.e. nuclear and joint family system and are presented in Table 4.1.3
33 Table 4.1.3 Distribution of Respondents Regarding Family System Family System of the Respondents UCs Total Nuclear Joint Bandkurai 62(16.1) 34(8.9) 96(25)
Khanmai 60(15.6) 36(9.4) 96(25)
Baffa 78(20.3) 18(4.7) 96(25)
Baidara 77(20.1) 19(4.9) 96(25)
Total 277(72.1) 107(27.9) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Results in Table 4.1.3 portray that majority (72.1%) of the respondents were associated with nuclear whereas 27.9% of the sampled respondents belonged to joint family system. Among nuclear family system majority (20.3%) and (20.1%) of respondents were from Baffa and Baidara Union Council respectively. Similarly only 16.1% and 15.6% of the respondents were from Bandkurai and Khanmai Union Councils respectively. Our results are in contrast with that of Ullah et al. (2016) who reported that majority (50.98%) of the respondents were from joint families.
4.1.4 Tenancy Status of the Respondents
Tenancy refers to the rules and conditions set for holding any agricultural land. This plays a significant contribution in favor of agriculture management and adoption of sustainable agricultural techniques and practices. The owner will be much devoted to get high income from the land and thus will be interested to adopt the improved practices. On the other hand the tenant has not that much capacity to invest high input/cost in order to get high production thus will affect the overall production and profit (Idrees, 2003). The tenancy is basically the property right of the individual to the land and among which the prominent ones are tenants, owner-cum tenants and owners (Ata, 2011). Furthermore, it is the general perception that owner cultivators are always far better than those who hold lands as a tenant and owner-cum tenant due to the fact that farmers‘ tenancy have an impact on the attitude of the farmers regarding the exposure to the latest technologies or desire to have it. Thus in the light of the above importance it was deemed necessary to probe into the real image of the farming community regarding tenancy status. Upon their responses three categories
34 were developed i.e. owners, owner cum tenant and tenants. The data pertaining to the tenancy status are presented in the Table 4.1.4.
Table 4.1.4 Distribution of Respondents Regarding Tenural Status Tenancy status of the respondents UCs Total Owners Owner cum Tenant Tenant Bandkurai 55(14.3) 17(4.4) 24(6.2) 96(25)
Khanmai 62(16.1) 15(3.9) 19(4.9) 96(25)
Baffa 62(16.1) 14(3.6) 20(5.2) 96(25)
Baidara 59(15.4) 22(5.7) 15(3.9) 96(25)
Total 238(62.1) 68(17.6) 78(20.3) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data pertaining to tenancy status in Table 4.1.4 represent that majority (62.1%) of the respondents were owner cultivators followed by 20.3% of the respondents who were tenant. Only 17.6% of the total respondents were observed as owner-cum tenants in the present study (Table 4.1.4). Among the owner cultivators 16.1% each owner cultivators were from Baffa and Khanmai Union Council whereas 15.4% and 14.3% of the owner cultivators were from Baidara and Bandkurai Union Council respectively. The instant results reflect that the landholders were much conscious regarding their farming activities thus instead of relying on the tenants they were busy cultivating their lands by themselves. Our results are in conformity with that of Ashraf (2008) and Ullah (2015) who also reported in their studies that majority of the respondents were owner cultivators and actively participating in agricultural activities.
4.1.5 Land Holding of the Respondents
―Landholding‖ is the term which refers to the land held by any individual. Large land holder usually take risks whereas small landholders don‘t put their self in risk thus they are reluctant to adopt improved practices on their lands on trial basis in order to check the output (Ata, 2011).. The collected data were sorted out into three categories i.e. <6 hectare (ha), 6-10 ha and >10 ha. The information regarding this important characteristic was imperative which was collected and presented in Table 4.1.5. The
35 tenants were also investigated regarding the landholding which they hold on tenancy basis.
Table 4.1.5 Distribution of the Respondents Regarding Landholding
Land Holding of the Respondents UCs Total <6 ha 6-10 ha >10 ha Bandkurai 40(10.4) 27(7.0) 29(7.6) 96(25)
Khanmai 37(9.6) 41(10.7) 18(4.7) 96(25)
Baffa 53(13.8) 28(7.3) 15(3.9) 96(25)
Baidara 49(12.8) 39(10.2) 8(2.1) 96(25)
Total 179(46.6) 135(35.2) 70(18.2) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
The data laid out in Table 4.1.5 showed a clear picture that majority (46.6%) of respondents had a landholdings <6 ha. About 35.2% of the respondents had reported their landholding in category of 6-10 ha whereas only 18.2% respondents fell under the category of landholding >10 ha of land. Among the respondents who had landholding <6 ha; majority i.e. 13.8% and 12.8% were from Baffa and Baidara union council respectively. Similarly 10.4% of the respondents were from Bandkurai and only 9.6% of the respondents were from Khanmai Union Council. It can be presumed that with large landholding one has many options to try new technology or crops on trial basis or one can take risk to try on large scale but the results obtained here might be the results of fragmentation of land holdings from generation to generation led to most of the large famers turning to small, semi-medium and medium farmers. Our results are in line with that of Khooharo (2008b) who reported that majority of the respondents had landholding up to 10 ha.
4.1.6 Involvement of the Respondents in Farming
It is general perception that the residents of rural areas are more inclined towards agriculture due to abundant farm lands and less other income opportunities or employment sources. However, rural urban fringe inhabitants are partially involved in agricultural activities. In both cases the involvement indicates the zeal and interest of the individual which ultimately affect the adoption of improved agricultural
36 techniques (Ullah, 2015). The data were collected from respondents about their involvement in agriculture as a full time or part time basis and are presented in Table 4.1.6.
Table 4.1.6 Distribution of Respondents Regarding Involvement in Farming Involvement in farming UCs Total Part Time Full time Bandkurai 17(4.4) 79(20.6) 96(25)
Khanmai 29(7.6) 67(17.4) 96(25)
Baffa 47(12.2) 49(12.8) 96(25)
Baidara 40(10.4) 56(14.6) 96(25)
Total 133(34.6) 251(65.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data illustrated in Table 4.1.6 pinpoint that overwhelming majority (65.4%) of the respondents were involved in agriculture on fulltime basis, whereas 34.6% were involved on part time basis. Among the full time basis involvement in farming; majority of the respondents were from UC Bandkurai which show more involvement of respondents in agricultural activities in comparison to other UCs. The instant results showed that agriculture is the dominant sector in the locality upon which the inhabitants of the area rely upon. Due to this fact they were indulge in agricultural activities on full time basis. About 17.4% of the respondents were from Khanmai UC. Similarly 14.6% of the respondents were from Baidara whereas only 12.8% of the respondents were from Baffa UC. Our results affirm the results of Ullah (2015) who also portrayed that majority (52.94%) of the respondents were actively involved in agriculture sector on full time basis.
4.1.7 Farming Experience of the Respondents
The years of involvement in agriculture can be termed as the farming experience. An individual or farmer is an institution inside oneself which continuously provokes knowledge flourished by him during his life and through understanding and experiences. Experience is the typical element in farmers‘ learning and has due prominence in acceptance or rejection of agriculture innovation (Agwu et al., 2008). The other situation may be the inverse to this in which the farmer may turn out to be
37 more rational in tolerating most recent information as he became erudite through experiences that most recent information may be valuable for boosting farm‘s output. Therefore, to find out the real picture in respect of farming experience of the sampled respondents they were investigated in this regard and the information collected were presented in Table 4.1.7.
Table 4.1.7 Distribution of Respondents Regarding Farming Experience Farming Experience of the Respondents UCs Total <11 Years 11-20 Years >20 Years Bandkurai 23(6) 47(12.2) 26(6.8) 96(25)
Khanmai 37(9.6) 27(7) 32(8.3) 96(25)
Baffa 22(5.7) 60(15.6) 14(3.6) 96(25)
Baidara 34(8.9) 42(10.9) 20(5.2) 96(25)
Total 116(30.2) 176(45.8) 92(24.0) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Results given in Table 4.1.7 depicted that majority (45.8%) of the respondents were indulged in agriculture from last 11-20 years followed by the respondents who had farming experience <11 years. Similarly 24% of the respondents had a farming experience >20 years (Table 4.1.7). The instant results showed that though 36.4% of the respondents (Table 4.1.6) were involved in agriculture on part time basis but still all the respondents had good farming experience. Among the category of the respondents who had 11-20 years farming experience; majority of the respondents were from Baffa UC i.e. 15.6% followed by the respondents from Bandkurai i.e. 12.2%. Similarly 10.9% of the respondents were from Baidara whereas only 7% of the respondents were from Khanmai UC. Our results are more or less in line with that of Giri et al. (2009); Chuks, (2014), and Ullah, (2015) who also reported that 52% of the respondents had a farming experience above 10 years.
4.1.8 Respondents’ Major Source of Income
Other than farm income, subsequently pays off farmers to fulfill their ordinary necessities/desires (IFAD, 2002). Past studies showed a worthy correlation of the income from other sources with best choices of selection of innovations (Adeniji and
38 Ega, 2006). The individuals with diverse sources of the income and high income will be definitely the risk taker and will shoot for picking the better opportunities in order to get high agricultural yield. In contrast those individuals who had less or poor income might feel difficulty or lack the interest of selection of better technology. Similarly the same will also have meager enthusiasm for searching and adoption of improved agricultural technology. Thus considering it as an important attribute and realizing the potential outcomes complexity it was thought necessary to accumulate information regarding the sources of income and their responses are presented in Table 4.1.8.
Table 4.1.8 Distribution of Respondents Regarding Major Source of Income Major Source of Income UCs Total Agriculture Govt. Employee Business Bandkurai 63(16.4) 14(3.6) 19(4.9) 96(25)
Khanmai 68(17.7) 13(3.4) 15(3.9) 96(25)
Baffa 52(13.5) 16(4.2) 28(7.3) 96(25)
Baidara 37(9.6) 25(6.5) 34(8.9) 96(25)
Total 220(57.3) 68(17.7) 96(25.0) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
The data illustrated in Table 4.1.8 indicated that agriculture was the chief source of income (57.3%) subsequent to the category of business comprising 25 % of respondents who were busy in doing farming along with business for earning income. About 17.7% of respondents besides government servants were involved in agricultural practices (Table 4.1.8). Among the agriculture as income source majority (17.7%) of the respondents were from Khanmai UC followed by the respondents from Bandkurai UC i.e. 16.4%. Similarly 13.5% of the respondents were from Baffa UC whereas 9.6% of the respondents were from Baidara. The instant result depicts the enthusiasm of the respondents that they fully rely on agriculture sector and fulfilling their daily needs. Verma et al. (2013) upholds our results; who also reported that overwhelming majority of the respondents rely on agriculture sector for their livelihood.
39 4.2 Crops/Fruits/Vegetables Grown by Farmers
Crops/fruits/vegetables grown by farmers show their commitment and dependency on the agriculture sector. This also shows the struggle for getting maximum return from agricultural land through multiple crops cultivation. Knowing the crops in which the farmers were busy in growing will give better pictures about what sort of major crops are been in the trend regarding the selected areas. Moreover, it will also help to sort out which crops are under the heavy pesticides use. In order to probe into the diversity of crops/fruits/vegetables grown by the farming community they were asked about the various crops/fruits/vegetables they grow and their responses were presented in Table 4.2.
40 Table 4.2 Distribution of Respondents Regarding Crops/Fruits/Vegetables they Grow Frequency (%) Sr.# Crops/Vegetabl- Total %age -es/Fruits Bandkurai Khanmai Baffa Baidra Crops 1 Wheat 96(25) 96(25) 96(25) 96(25) 384 100
2 Rice 52(13.54) 19(4.94) 11(2.86) 7(1.82) 89 23.17
3 Sugarcane 93(24.21) 40(10.41) - - 133 34.63 4 Gram 13(3.38) - - - 13 3.38 5 Maize 44(11.45) 19(4.94) 31(8.07) 35(9.11) 129 33.59 6 Lentil 7(1.82) - - - 7 1.82 Vegetables 7 Tomato 115(29.94) 40(10.41) 51(13.28) 29(7.55) 235 61.19 8 Onion 24(6.25) 31(8.07) 21(5.46) 15(3.9) 91 23.69 9 Okra 19 (4.94) - - - 19 4.94 10 Cucumber 24(6.25) 36(9.37) 28(7.29) 25(6.51) 113 29.42 11 Sponge gourd 9(2.34) 14(3.64) 5(1.3) 4(1.04) 32 8.33 12 Bitter gourd 16(4.1) 12(3.12) 8(2.08) 2(0.52) 38 9.89 13 Turnip 31(8.07) 41(10.67) 24(6.25) 17(4.42) 113 29.42 14 Radish 56(14.58) 36(9.37) 24(6.25) 5(1.3) 121 31.51 15 Potato - - 16(4.16) - 16 4.16 16 Pepper 2(0.52) 5(1.302) 11(2.86) - 18 4.68 Fruits 17 Mango 18(4.68) - - - 18 4.68 18 Date Palm 41(10.67) - - - 41 10.67 19 Plam - - 13(3.38) 21(5.46) 34 8.85 20 Peach - - 19(4.94) 32(8.33) 51 13.28 21 Pear - - 6(1.56) 17(4.42) 23 5.98 22 Apricot - - 8(2.08) 21(5.46) 29 7.55 23 Persimmon - - - 19(4.94) 19 4.94 24 Citrus 3(0.78) 10(2.6) 8(2.08) - 21 5.46 25 Apple - - 2(0.52) 45(11.71) 47 12.23 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
41 The Data presented in Table 4.2 depicted that diverse kind of crops/fruits/vegetables were grown by different respondents. It was found that all of the study respondents i.e. 384 were growing wheat. Rice was grown by 23.17% of the total respondents whereas sugarcane was grown by 34.63% of the respondents. Majority of the sugarcane grower were from UC Bandkurai which might be due to the fact that in D.I.Khan district there are five sugar mills and is easy to shift the sugarcane at short distance. Similarly tomato was grown by 61.19% of the respondents. Onion was reported by 23.69% respondents, whereas gram (3.38%), maize (33.59%), okra (4.94%), lentil (1.82%), cucumber (29.42%), sponge gourd (8.3%) and bitter gourd was reported by 9.89% of the total respondents. Moreover, mango, date palm, plum, peach, pear, apricot, persimmon was reported by 4.68, 10.67, 8.85, 13.28, 5.98, 7.55 and 4.94% respectively. Similarly, turnip, radish, potato, pepper, citrus and apple were reported by the 29.42, 31.51, 4.16, 4.68, 5.46 and 12.23% respectively.
The instant results depict that over 25 type of different agricultural crop/fruits/vegetables were under the practice of farmers of the study locality. This is a good sign that farming community instead of relying on single or two crops they grow various sorts of crops. This apart from the income to them also plays a better role in the food security of the country. Moreover, there was a diversity of cropping pattern in the various sampled districts i.e. crops were mostly grown in the plain areas i.e. UC Bandkurai and UC Khanmai followed by the vegetables whereas fruits were found under practice of majority of the mountainous areas i.e. UC Baffa and UC Baidara.
4.3 Experiences in Spraying Pesticides
―Using pesticides from many years‖ results in better understanding of the pros and cons of the pesticides. A person with greater experience in pesticides use has the possibility to has a better know how about the various sort of practices concern to the use of pesticides i.e. its application, using of various sort pesticides, health effects and which pesticides are used for which particular pests etc. Due to this importance it was also thought necessary to know the level of respondents i.e. their experience in using pesticides. Therefore, the respondents were asked about the number of years since they were busy in using various sorts of pesticides in their crops/vegetables/fruits and their responses were presented in Table 4.3.
42 Table 4.3 Distribution of Respondents regarding Since How Long they are Using Pesticides Year of Experience in Pesticides use UCs Total <6 Years 6-10 Years >10 Years Bandkurai 13(3.4) 25(6.5) 58(15.1) 96(25)
Khanmai 24(6.2) 7(1.8) 65(16.9) 96(25)
Baffa 17(4.4) 37(9.6) 42(10.9) 96(25)
Baidara 19(4.9) 55(14.3) 22(5.7) 96(25)
Total 73(19) 124(32.3) 187(48.7) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data presented in Table 4.3 showed that majority (48.7%) of the respondents were using pesticides from >10 years. About 32.3% of the respondents were using pesticides from 6-10 years whereas only 19% of the total respondents were using pesticides from <6 years. Among the respondents who were using pesticides for >10 years, majority were in the Khanmai UC i.e. 16.9% whereas 15.1% were from the Bandkurai UC (Table 4.3). Similarly, about 11% of the respondents were from Baffa UC and only 5.7% of the respondents were using pesticides for more than 10 years. The instant results depict that the farming community mostly rely on pesticides regarding control of pests which prevails; therefore, they were using pesticides for so many years regularly. Our results are in similarity with that of Devi (2009) who reported that majority of the respondents had experience in pesticides usage from more than 10 years.
4.4 Distribution of Respondents regarding Type of Pesticides they Mostly Use
Using different sort of pesticides show the prevalence of the pests in the area i.e. using weedicides in majority represent the weed prevalence in the area, insect pest in case of insecticides use and diseases in case of fungicides. Therefore, to know what sorts of pesticides they mostly rely upon, the respondents were investigated regarding the type of pesticides they use and their responses are presented in Table 4.4.
43 Table 4. 4 Distribution of the Respondents Regarding the Type of Pesticides they Use Most Frequently Type of Pesticides UCs Total Insecticides Weedicides Fungicides All of the Above Bandkurai 29(7.6) 37(9.6) 9(2.3) 21(5.5) 96(25)
Khanmai 32(8.3) 22(5.7) 15(3.9) 27(7) 96(25)
Baffa 27(7) 9(2.3) 45(11.7) 15(3.9) 96(25)
Baidara 37(9.6) 4(1) 51(13.3) 4(1) 96(25)
Total 125(32.6) 72(18.8) 120(31.2) 67(17.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.4 depicted that majority (32.6%) of the respondents were using insecticides followed by the respondents who were most commonly using fungicides i.e. 31.2%. About 19% of the respondents were using weedicides whereas only 17.4% of the respondents were using all of the mentioned i.e. insecticides, weedicides and fungicides (Table 4.4). Among the respondents who were most commonly using insecticides for killing of pests, the majority (9.6%) were from Baidara UC followed by the respondents from Khanmai UC i.e. 8.3%. Similarly about 8% of the respondents were from Bandkurai UC where farmers were using insecticides as most commonly used pesticides whereas only 7% of the respondents were from UC Baffa (Table 4.4). Moreover, it was observed that the use of weedicides were mostly recorded in UC Bandkurai and Khanmai which might be attributed to the reason that these areas are densely occupied by the field crops like wheat, rice and sugarcane. These crops have major weeds problem and hence comparatively more usage of weedicides. Similarly the use of fungicides was mostly recorded in Baidara and Bafa. More use of fungicides in these UCs might be due to the more cultivation of fruits and vegetables which are more succulent in comparison to field crops along with humid conditions of the area. As the humid conditions also provide favorable climate to fungus, thus reflects the more use of fungicides in these UCs. Our results are in conformity with that of Sheikh et al. (2011) who also reported in their study about pesticides and associated impact on human health in Sindh province of Pakistan that majority of the respondents reported insecticides as the major pesticides under their use.
44 4.5 Pesticides Acquisition
It is generally believed that the consumption conduct of the consumers is based on social, cultural, economic characteristics upon which consumers have little influence. This contention is also as same worthy and valid with respect to farmer‘s pesticides selection. They can be conceptualized as passive or ‗captive‘ users to a great extent because of the fact that they mostly depends on local markets which usually have uncertified and un-licesenced pesticides retailers. The sources of the pesticides acquisition of the respondents were diverse i.e. local market and Farm Services Center (FSC). The respondents were probed regarding the purchase of pesticides from various sources and their responses are presented in Table 4.5.
Table 4.5 Distribution of the Respondents Regarding the Source from where they Bought Pesticides Sources from where Respondents bought Pesticides UCs Total Local Market Farm Services Center (FSC) Bandkurai 55(14.32) 41(10.7) 96(25)
Khanmai 66(17.18) 25(6.5) 96(25)
Baffa 71(18.48) 30(7.8) 96(25)
Baidara 81(21.09) 15(3.9) 96(25)
Total 273 (71.1) 111(28.9) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.5 showed that majority (71.1%) of the respondents obtained the pesticides from local agro-chemical input dealers. Moreover, about 30% of the respondents were inclined to buy pesticides from Farm Service Center (Table 4.5). Among the respondents who bought pesticides from market the majority (17.2%) were from the Baidara UC whereas 12.2% were from the Khanmai UC. About 10% were from Bandkurai UC and 9.6% were from Baffa UC. This is not surprising because during field observation it was found that majority of the respondents use to seek pesticides dealers for apt selection of pesticides because they were not fully able to identify and assure the disease or pest (Table 4.8). During informal discussion they also reported that some pesticides work effectively on some vegetables whereas not on others. The consequent farmers perception reflects the advices provided by agro- input dealers and so the excessive use and misuse. This might be due to the fact that
45 the pesticides dealers are more inclined towards profit instead of toxicity or effectiveness of the pesticides.
The instant results are in line with Sefa et al. (2015) who also reported in their study that pesticides were usually bought from local market by the respondents. During informal discussion with the respondents it was found that toxicity, residual effect, environmental impacts etc. were never their points of concern in selection and purchase of pesticide. They were more interested in less expensive and broad spectrum pesticides i.e. they were of the view that we need such type of pesticides which works for all sort of weeds or insect pest or diseases and along with its availability the price must be cheaper. This clearly indicates that farmers were not interested in the safe farming both for themselves and for the consumers.
4.6 Stage of Utilizing Pesticides in Crops/Fruits/Vegetables
Application of pesticides at various stages also had impact both on the consumers and the applicators i.e. every pesticide had its own duration after which the fruit or crop may be harvested in order to avoid the residual contents in the produce. Furthermore, some pesticides had its own timing of application i.e. pre-emergence stage of application just after sowing or after first irrigation in wheat specifically to control weeds. Therefore, if the pesticides are not applied on proper stage results in misuse of the pesticides. Therefore, it was an important factor to know which stages the farmers usually prefer to spray the pesticides and their responses are presented in Table 4.6.
46 Table 4.6 Distribution of Respondents Regarding the Stages they use Pesticides Sr. # Crop/vegetable/fruit Frequency Seed treatment Just after Sowing Any other stage Crops 1 Wheat 384 321(83.59) 203(52.86) 210 (54.68) 2 Rice 89 31(8.07) 48(53.93) 61(68.53) 3 Sugarcane 133 103(26.8) 58(43.60) 122(91.72) 4 Gram 13 - 3(23.07) 4(30.76) 5 Maize 129 22(5.7) 34(26.35) 79(61.24) 6 Lentil 7 - - - Vegetables 7 Tomato 235 222(57.8) 24(10.21) 178(75.74) 8 Onion 91 72(18.75) 12(13.18) 71(78.02) 9 Okra 19 12(3.12) 8(42.10) 12(63.15) 10 Cucumber 113 93(24.2) 55(48.67) 96(84.95) 11 Sponge gourd 32 11(2.86) 4(12.5) 19(59.37) 12 Bitter gourd 38 13(3.38) 5(13.15) 27(71.05) 13 Turnip 113 52(13.54) 67(59.29) 79(69.91) 14 Radish 121 104(27.08) 35(28.92) 92(76.03) 15 Potato 16 7(1.82) 5(31.25) 11(68.75) 16 Pepper 18 11(2.86) 8(44.44) 16(88.89)
47 Fruit 17 Mango 18 - - 18(100) 18 Date Palm 41 - - 41(100) 19 Plum 34 - - 34(100) 20 Peach 51 - - 51(100) 21 Pear 23 - - 23(100) 22 Apricot 29 - - 29(100) 23 Persimmon 19 - - 19(100) 24 Citrus 21 - - 21(100) 25 Apple 47 - - 47(100) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
48 Data in Table 4.6 show the pesticides use by the respondents at various stages of the crops/vegetables/fruits. It was found that in wheat crop majority (83.59%) of the respondents use pesticides for seed treatment followed by the respondents who use pesticides in any other stages i.e. tillering, anthesis stages etc. (54.68%). Only 52.86% of the respondents use pesticides at just after sowing stage which was mostly for weed control by applying the pre-emergence weedicides. Similarly, in rice majority (68.53%), gram (30.76%) and in maize 61.24% of the respondents use pesticides in latter stages.
In vegetables the pattern of pesticides application apart from seed treatment were more inclined towards the later stages i.e. in tomato 75.74% of the respondents use pesticides in later stages, onion (78.02%), okra (63.15%), cucumber (84.95%), sponge gourd (59.37%), bitter gourd (71.05%), turnip (69.91%), radish (76.03%), potato (68.75%) and pepper (88.89%). This is a serious sign of health issues because in vegetables mostly the pesticides were applied at the latter stages preferable at the time of fruiting and thus causes possible health issues to the consumers. In fruits all of the respondents who cultivated the fruit orchards were using pesticides in later stages i.e. just after flowering or fruiting stage. This again put the health of the consumers at risk.
4.7 Most Commonly Used Pesticides and their Doses
Toxicity of formulated chemical product are classified by WHO into the following categories i.e. class Ia is extremely hazardous, class Ib is highly hazardous, Class-II is moderately hazardous, Class-III is slightly hazardous, Class-U is unlikely to present acute serious hazards in normal use whereas Class-O are obsolete chemicals to be considered as pesticide (WHO, 2009). Nearly 90 percent of the banned pesticides fall into category of Class-Ia, Class-Ib and Class-II of the WHO hazard grades.
Results in Table 4.7.1 showed the various types of pesticides in use by the farming community. The instant survey depicts that there were 49 different sorts of pesticides most commonly in use by the farming community as per the present study. Among the 49 No.s of various pesticides 14 No.s were weedicides, 25 No.s were insecticides whereas 10 No.s were fungicides. Instant results showed that majority of the pesticides in use were insecticides which showed the prevalence of insect pest in the area is high
49 enough in contrast to the diseases and weeds. Similarly, majority (5 No.s) of the weedicides were from Class III of hazardous followed by 3No.s weedicides which were from Class II whereas 5 No.s were from Class U. only one weedicides from Class-O was observed in the present study. These weedicides were from different chemical groups i.e. Triazine, Amide, Dinitroanilin, Organic, Phenylpyrazolin, Aryloxyphenoxypropionate, Organophosphorus, Chloroacetamide, Nitrile, Phenoxy, Pyridinecarboxylic acid, Sulfonylurea, Diphenylether and Sulfonylurea. The weedicides used for various purposes are showed in the Table 4.7.1. This showed that the farming community was using pesticides from moderately hazardous and slightly hazardous classes (WHO Recommended Classification of Pesticides by Hazard, 2009). The instant results are in contrast with that of Chitra et al. (2013) who reported in their study that majority of the respondents were using pesticides from highly hazardous Class of WHO.
Similarly, 25 No.s different sorts of insecticides were reported by the respondents. Among them the majority (14 No.s) of the insecticides were from Class-II of the pesticides toxicity level followed by the Class III and Class U i.e. 4 No.s each respectively. Only two insecticides i.e. Carbofuron and Cartap from Cartap Hydrochloride chemical group were from Class-Ib which represents highly hazardous (WHO, 2009). The insecticides were from the chemical group of Anthranilic Diamide, Nicotinoid, Pyrethroid, Organophosphates, Neonicotinoids, Organochlorines, Avermectins and Urea. The insecticides used for various pests as reported by the respondents were presented in Table 4.7.1. Our results are in conformity with that of Jamali et al. (2014) who also reported that majority of the pesticides were from Class-II of WHO toxicity classification. Similarly, Mengistie et al. (2017) reported that most commonly used pesticides were Mancozeb, Karate, Malathion and Ridomil Gold which are in conformity with our results. Moreover, they also reported that majority of the pesticides were from Class-II of WHO toxicity classes.
These results conclude that majority of the respondents‘ utilized Organophosphorus group of chemical to meet their needs (Table 4.7.1) which are esters and derived from the phosphoric acid. In human being, it acts on impeding acetyl cholinesterase of the central nervous system which is an essential enzyme responsible for controlling the level of neurotransmitter acetylcholine, disrupting the nerve impulse by serine
50 phosphorylation of the hydroxyl group in the active site of the acetyl cholinesterase (Sorgob and Vilanova, 2002). The indicators include damage to reflexes, nausea, dizziness, headache, convulsions, comma, and sometimes lead to death (Perry et al., 1974). Organophosphorus has alkylating properties that is paramount from mutagenesis point of view because they directly act on deoxyribonucleic acid (DNA) adding ethyl, methyl of the alkyl group mostly to the nitrogenous bases with nucleophilic groups which is capable to react with electrophiles. Compounds comprised of Organophosphorus are frequently used in agriculture mostly as insecticides and miticides and their mode of action is through contact or ingestion. The compounds are commonly used in grains, vegetables, fruits, sugarcane and cotton crops and many more. Greater exposure to organochlorines which is a type of pesticide causes clorance, kind of acne cause by chlorine holding chemicals and also skin rashes. Organophosphate insecticide has also adverse effect on the immune system and causes numerous psychiatric diseases like depression, anxiety, disorientation and paranoid behavior. The other pesticides could cause cramps, too much perspiration, weakness, inability to breath, muscle twitching, unconsciousness, tremors, vomiting, blurring of vision and ultimately death in case of greater exposure (Garcia et al. 2012).
Among the ten fungicides as reported by the farming community majority (08 No.s) were from the Class-II whereas only two were from Class-U (Table 4.7.1). The fungicides reported by the farming community were from Dithio-carbamates, Triazoles, Oximino-acetates, Methoxy-acrylates and Organophosphorus chemical group. The results of the present study indicated a wide variety of chemicals were utilized as pesticides in the area. Although 49 No.s different pesticides were reported by the respondents which were being used in the locality yet but it could be lower than actual number of pesticides in use because of the fact that different farmers have different interest of applying pesticides and due to the sample of 384 respondents only 49 were reported. The vegetable and fruits farmers depended heavily on use of pesticides for control of different pests and diseases and over 49 No.s different formulations were used. This might be because of the reason that their attitude has been developed that solely the pesticides use is the solution of the controlling pests thus they were busy in spraying various sort of pesticides. The same was also reported by Jamali et al. (2014) who said that farmers were much interested to control the pests by using pesticides and thus were using diverse pesticides in the study area.
51 This study authenticated that pesticide sellers whom aim is only of business profit deteriorate the health and environmental risks associated with too much use of pesticides. In African countries, similar pattern of pesticide application was reported (Abate et al., 2000). The situation is also worse in many of the developed countries because the choice of the pesticide used by farmers is totally dependent on the suppliers (Epstein and Bassein, 2003). It is due to pest and disease which drastically reduce the yield of vegetables; therefore, the farmers are constrained to excessive use of pesticide in order to achieve high yield. The public extension wing in Pakistan sustains the facilities to offer subsidized pesticides to the farmers but the farmers still relay on pesticides dealers and due to illiteracy among the farmers they are not capable to select accurate pesticide along with amount of dose to avoid its adverse effect on health and environment.
Numerous studies found that Maximum Residual Limit (MRL) in most of vegetables was crossed by residues of pesticides (Taneja, 2005) which may cause chronic health damage to end users (Mukherjee and Gopal, 2003). Around the world, monitoring of pesticides is carried out in order to evaluate effects of their residues on environment. At present, pesticides are widely used for controlling pest and the most frequently used pesticides include organochlorines (Toan et al., 2007). The existence of residues of pesticides was found in numerous environmental components and commodities due to wide usage of pesticides (Kumari et al., 2006; Kumari and Kathpal, 2009; Wang et al., 2008). These residues of the pesticides can enter the human body by water, food and the environment.
52 Table 4.7.1 Status of the Most Commonly Used Pesticides WHO Sr.# Active ingredient Brand Name Chemical Group Pest Class WEEDICIDES Atrazine+S Primextra gold Controls certain annual grasses and broadleaf weeds in Maize, 1 Triazine and amide III metolachlor 720 SC Sugarcane and Sweet Corn 2 Pendimethalin Stomp 455 g/l CS Dinitroaniline A pre-emergent herbicide for the control of grass weeds III 3 S metolachlor Dual gold 960 EC Organic Annual grasses and some annual broad-leaved weeds III Controls wild oats and ryegrasses in winter and spring wheat 4 Penoxaden Axial 050 EC Phenylpyrazolin and winter and spring barley. Controls blackgrass in winter and - spring barley as part of an integrated control strategy Puma super 69 Aryloxyphenoxypro 5 Fenoxaprop O EW pionate Annul and perennial grass weed Round up PM 540 6 Glyphosate Organophosphorus Annual and perennial weeds III g/l SL Atrazine+S Triazine+chloroacet 7 Several Controls weeds in maize, sugar cane and sweet corn III metolachlor amide Buctril super 60 8 Bromoxynil+MCPA Nitrile+ Phenoxy Broad leaf weeds II EC 60 Aminopyralid+flora Pyridinecarboxylic Crow pea, Common 9 Lancelot 45 WG U sulam acid Goosefoot, Field bindweed
10 Fluroxypyr+MCPA Harvester 50 EC Pyridinecarboxylic Crow pea, Jungle onion, Common vetch, Corn spurry, U+II acid+ Phenoxy Common Goosefoot, Field bindweed, Broadleaf dock, Blue pimpernel, Metsulfuron+ 11 Allymax 66.7 WG Fathen, nettle U tribenuron Sulfonylurea leaved goosefoot, Bur clover, Yellow sweetclover Fumitory,
12 Oxyfluorfen Axifin 24 EC Field bindweed U Diphenylether Broadleaf dock, Blue pimpernel, Fathen, nettle 13 Triasulfuron Logran 75 WG U Sulfonylurea leaved goosefoot, Jungle onion, Aryloxyphenoxypro 14 Haloxyfop Percept 10.8 EC Bermuda grass, Water couch, Johnson grass, Crab grass, II pionate
53 INSECTICIDES Chlorantraniliprole+ Voliam Flexi 300 Heliothus, Brinjal stem borer, key sucking, chewing and 15 Anthranilic diamide U Thiamethoxam SC lepidopteran pests in citrus and tree fruit Spinola bug, pod bug, Mango hopper, Citrus psylla, WB Plant
16 Imidacloprid Confidor 200 SL Nicotinoid hopper, Aphids, White fly, Mango mealy bug, Cotton II mealybug, S. cane Leaf hopper, Red pumpkin beetle, Mirid bug Spinola bug, pod bug, Black bug, Cutworm, Shoot fly, Citrus 17 Bifenthrin Talstar10 EC Pyrethroid II leaf miner, Vegetable leaf miner, Plant hopper, Green leaf, hopper, Thrips, sucking insects/wide range of insects, Hairy caterpillar, Rice leaf folder, Capsule 18 Lemda cyhalothrin Karate 5 CS Pyrethroid II borer, Mango hopper, Rice grass hopper, Cutworm, Citrus leaf miner, Gamacyhalothrin+ch Pyrethroid+ Black bug, Brinjal stem borer, Pink bollworm, Cabbage butter 19 Bolten 31EC II lorpyrifos Organophosphates fly, Protects a variety of vegetable crops, corn and canola from 20 Chlorantraniliprole Coragen 20 SC Anthranilic diamide U insects such as, cutworms and armyworms. 21 Trichlorfon Dipterex 30 T 60 Organophosphates Fruit fly II 22 Gama cyhalothrin Proaxis 60 SC Pyrethroids Spinola bug, pod bug, Rice leaf folder, Pink bollworm II Cypermethrin 10 Defoliators, Green leaf 23 Cypermethrin Pyrethroid II EC Hopper, Capsule borer, Chlorantraniliprole+ White stem borer, Yellow stem borer, Top borer, Stem borer, 24 Virtako 0.6 Gr Anthranilic diamide U Thiamethoxam Sugarcane root borer, Maize borer 25 Chlorantraniliprole Ferterra 0.4 G Diamides White stem borer, Yellow stem borer, Stem borer, U A broad spectrum of sucking soil and leaf-feeding pests like 26 Thiamethoxam Actara 25 WG Neonicotinoids III Aphids, Jassids, Thrips & Whitefly Larsbin 40 EC 40 27 Chlorpyrifos Organophosphates Stalk borer, termites, soil born insects II EC Green leaf hoppers, 28 Malathion Malathion 57 EC Organophosphates III Thrips, Rice bug 29 Endosulfan Thionex 35EC Organochlorines Ball worm, thrips, II
30 Emamectin Several Avermectins Lepeidopterous fruit worm III Nicotiamide 31 Acetamiprid Several Sucking pests and mites II Profesofos+Cyper 32 Polytrin C Pyrethroids Caterpillars, aphids, mites and other sucking pests II methrin
54 armyworms, pinworms, diamondback moths, fruitworms and 33 Emamectin benzoate Proclaim Avermectins - leafrollers Key insect pests in a variety of crops including citrus, soybeans, 34 Dimethoate Dimethoate 4C Organophosphate II corn, cotton, pears, pecans and potatoes. Cartap Meloidogyne species, Root, stem, top, 35 Carbofuron Furadan 3 G Ib hydrochloride Gurdaspur borer Cartap Plant hopper, Green leaf 36 Cartap Padan 4 G Ib hydrochloride Hopper
37 Profenophos curacran 500 EC II Organophosphorus Against lepidopterous larvae
38 Match 50 EC II Lufenuron Urea Against lepidopterous larvae Diafenthiruron 39 Diafenthiuron Urea III 50% SC Sucking pests & mites FUNGICIDES 40 Propineb Antracol 70 WP Dithio-carbamates Early blight U Powdery mildew, early blight, Decline, 41 Difenoconazole Score 250 SC Triazoles II
Trifloxystrobin+Teb Oximino-acetates+ 42 Nativo 75 WG Leaf spot, Rice blast, Powdery mildew, Leaf rust, Citrus scab II uconazol triazoles Azoxystrobin+flutri 43 Nanok 25 SC Methoxy-acrylates Leaf spot, Rice blast, Downy mildew, Leaf rust II afol Mencozeb+metalaxa Ridomil gold 68 Dithiocarbamate + 44 Late blight, powdery mildew, Collar rot, II l WG Anilide 45 Copper hydroxide Champion 77 WP - Bacterial leaf blight II 46 Propeconazol Tilt Organophosphorus Blast, Rust II 47 Copper Oxychloride Several Inorganic Early blight II 48 Delamethrin Pyrethroid Inorganic Chewing and sucking pest II 49 Thiophanate methyl Several Benzimidazole Powdery Mildew U Note: Ia = Extremely hazardous, Ib = Highly Hazardous, II = moderately hazardous; Source: Field Survey, 2018 III = Slightly hazardous; U = Unlikely to present acute hazard in normal use; O = Obsolete as pesticide, not classified.
55 Similarly the respondents were also investigated that what dose you applied in controlling the pest and then was checked with the recommended dose in order to find out the difference. The results of one sample t-test were presented in Table 4.7.2. It was found that majority of the respondents were using high dose then the recommended dose. Lamda cyhalothrin insecticide were the most frequently applied by the respondents i.e. 172 respondents and highly significantly (P≤0.01) above the recommended dose with the mean difference of +19.25 ml ha-1 and t-value of 9.831. Similarly highly significant (P≤0.01) difference was also observed in Primextra gold 720 SC with mean difference of +12.71ml ha-1, Dual gold 960 EC (+11.95 ml ha-1), Lancelot 45 WG(+1.2gm ha-1), Logran 75 WG (+2.35 gm ha-1), Proaxis 60 SC (+10.5 ml ha-1), Cypermethrin 10 EC (+9 ml ha-1), Actara 25 WG (+5.3 gm ha-1) and Score 250 SC (+11.5 ml ha-1) (Table 4.7.2). Moreover, significantly (P≤0.05) high dose was observed in Buctril super 60 EC 60 (+2.43 ml ha-1), Match 050 EC (+11.24 ml ha-1), Diafenthiuron 50% SC (+18.19 ml ha-) and Furadan 3 G (+1.9 kg ha-1) then the recommended. It was a matter of serious concern that Furadan 3 G were from the Class-Ib (Table 4.7.1) and still farmers were busy to use high dose then the recommended; thus affecting the environment and their health as well. Furadan is a systemic insecticide; it is been absorbed through roots and carried out to the other parts of the plants where insecticidal concentrations are attained. Moreover, carbofuran also serve as contact activity against pests.
Furthermore, highly significantly (P≤0.01) low dose was observed in Axial 050 EC (-23.21 ml ha-1), Confidor 200 SL (-18 ml ha-1), Ridomil gold 68 WG (-16.5 g ha-1) and Champion 77 WP (-13.5 g ha-1). Significantly (P≤0.05) low dose then the recommended was recorded in Round up PM 540 g/l SL (-6.17 ml ha-1), Proclaim (-6.81 gm ha-1) and Padan 4 G (-0.78 kg ha-1). Using below the recommended dose of pesticides results in creating resistance against the pest which ultimately results in increasing number of pesticide spray. Therefore it can be concluded that the farming community were not following the exact recommended dose and thus misusing the pesticides. Among the sample respondents majority (47.39%) of the respondents reported Cypermethrin 10 EC followed by the Ridomil gold 68 WG (47.14%), Nativo 75 WG (46.35%), Actara 25 WG (44.79%), Karate 5 CS (44.79%), Coragen 20 SC(44.53%) and Score 250 SC (44.53%). The increased use of
56 pesticides i.e. cypermethrin, can also be associated with failure of breeding in honey bees (Nafees et al. 2008). The instant results showed that the problem is not the pesticide but how it is been handled. The indiscrimation in violation of recommendations effects the agriculture sustainability, health of growers/consumers and environment itself. This situation calls for a transformation of these practices. Moreover, farmers were using inappropriate doses of pesticide. Overdosing ha-1 introduces surplus pesticides to the environment and may result in crop damage. Furthermore, inaccurate dilution can reduce pesticide efficiency or can increase residues and speed up the development of pesticide resistance.
57 Table 4.7.2 Distribution of Respondents Regarding the Use of Most Commonly Pesticides and its Dose WEEDICIDES Recommended Mean Farmers Sr. # Brand Name Active Ingredient Difference t-value Freq. (%) Use/Ha dose/Ha±SD 1 Primextra gold 720 SC Atrazine+S metolachlor 1600 ml 1612.71±30 +12.71 4.89** 103 (26.82) 2 Stomp 455 g/l CS Pendimethalin 2000 ml 1997.9±80 +2.09 0.29NS 129 (33.59)
3 Dual gold 960 EC S metolachlor 1600 ml 1611.95±18.67 +11.95 7.09** 123 (32.03)
4 Axial 050 EC Penoxaden 660 ml 636.78±20.88 -23.21 11.92** 115 (29.95)
5 Puma super 69 EW Fenoxaprop 1000 ml 1001.54±8.33 +1.54 1.82NS 97 (25.26)
6 Round up PM 540 g/l SL Glyphosate 4000 ml 3993.82±27.03 -6.17 -2.15* 89 (23.18)
7 Buctril super 60 EC 60 Bromoxynil+MCPA 800 ml 802.43±5.91 +2.43 2.53* 123 (32.03)
8 Lancelot 45 WG Aminopyralid+florasulam 25 gm 26.27±3.1 +1.27 3.14** 59 (15.36)
9 Harvester 50 EC Fluroxypyr+MCPA 800 ml 799.71±8.21 -0.285 -0.20NS 68 (17.71)
10 Allymax 66.7 WG Metsulfuron+ tribenuron 16 gm 16.45±1.05 +0.45 1.97NS 128 (33.33)
11 Axifin 24 EC Oxyfluorfen 600 ml 603±13.01 +3 1.01NS 86 (22.40)
12 Logran 75 WG Triasulfuron 32 gm 34.35±0.81 +2.35 12.93** 113 (29.43)
13 Percept 10.8 EC Haloxyfop 700 ml 696±13.13 -4 -1.36NS 39 (10.16)
INSECTICIDES
58 14 Voliam Flexi 300 SC Chlorantraniliprole+Thiamethoxam 160 ml 162.5±9.24 +2.5 1.20NS 143 (37.23)
15 Confidor 200 SL Imidacloprid 400 ml 418±15.07 -18 -5.33** 137 (35.67)
16 Talstar10 EC Bifenthrin 500 ml 492.25±14.82 -7.5 -2.26* 82 (21.35)
17 Karate 5 CS Lemda cyhalothrin 500 ml 519.25±8.87 +19.25 9.83** 172 (44.79)
18 Bolten 31EC Gamacyhalothrin+chlorpyrifos 1000 ml 1014.5±42.48 +14.5 1.52NS 88 (22.91)
19 Coragen 20 SC Chlorantraniliprole 100 ml 98.32±1.31 -1.68 -0.96NS 171 (44.53)
20 Dipterex 30 T 60 Trichlorfon 200 gm 206.5±14.24 +6.5 2.041NS 42 (10.93)
21 Proaxis 60 SC Gama cyhalothrin 200 ml 210.5±12.76 +10.5 3.67** 21 (5.46)
22 Cypermethrin 10 EC Cypermethrin 500 ml 509±12.09 +9 3.32** 182 (47.39)
Chlorantraniliprole+Thiamethox 23 Virtako 0.6 Gr 8 kg 7.9±0.30 -0.1 -1.45NS 31 (8.07) am
24 Ferterra 0.4 G Chlorantraniliprole 8 kg 7.8±0.42 -0.2 -1.49NS 17 (4.42)
25 Actara 25 WG Thiamethoxam 50 gm 55.3±6.07 +5.3 3.49** 172 (44.79)
26 Larsbin 40 EC 40 EC Chlorpyrifos 4 liter 4.21±3.72 +0.21 1.031NS 71 (18.48)
27 Match 050 EC Lufenuron 400 ml 411.24±16.17 +11.24 2.45* 46 (11.97)
28 Malathion Malathion 57 EC 8 liter 8.03±0.23 -0.03 -0.92NS 21 (5.46)
29 Polytrin C Profesofos + Cypermethrin 1 liter 0.98±0.32 -0.02 -0.23NS 73 (19.01)
59 30 Diafenthiuron 50% SC Diafenthiuron 1600ml 1618.19±23.12 +18.19 2.98* 41 (10.67)
31 Proclaim Emamectin benzoate 260gm 252.19±12.34 -6.81 -1.29* 27 (7.03)
32 Furadan 3 G Carbofuron 18 kg 19.9±1.57 +1.9 2.93* 61 (15.88)
33 Diafenthiruron 50% SC Diafenthiuron 400ml 391.2±6.91 -8.8 -1.02NS 38 (9.89)
34 Padan 4 G Cartap 9 kg 9.78±1.38 -0.78 -2.01* 74 (19.27) FUNGICIDES
35 Antracol 70 WP Propineb 1000 gm 986.23±66.35 -13.77 -0.91NS 134 (34.9)
36 Score 250 SC Difenoconazole 200 ml 211.5±13.48 +11.5 3.81** 171 (44.53)
37 Nativo 75 WG Trifloxystrobin+Tebuconazol 130 gm 128.92±0.76 -1.08 -0.79NS 178 (46.35)
38 Nanok 25 SC Azoxystrobin+flutriafol 400 ml 403.29±5.21 +3.29 1.76NS 128 (33.33)
39 Ridomil gold 68 WG Mencozeb+metalaxal 500 gm 483.5±20.07 -16.5 -3.67** 181 (47.14)
40 Champion 77 WP Copper hydroxide 500 gm 486.5±19.54 -13.5 -3.09** 51 (13.28)
41 Tilt 250 EC Propiconazole 500 gm/L 492±17.94 -8 -1.99NS 121 (31.51)
(Figures in Parenthesis are precentages) Source: Field Survey, 2018
60 4.8 Decision about Spraying Pesticides
Decision about the spraying pesticides depends on various factors i.e. farmers‘ income, return price of the produce which farmer is being busy in growing, advices of the fellow farmers, pesticides dealers etc. For application of pesticides usually farmers either made self-decision or seek help from the pesticides dealers, fellow farmers, Agriculture Extension Agent or Agriculture Research. The effects of pesticides are greatly influenced by the timing of application. It is very important to apply pesticide at a proper time of the day for safe pesticide application and to minimize exposure threat. Therefore, timely decision about the application of pesticides is of immense importance. Due to this important reason the farmers were investigated regarding the decision about when to spray on the crop and their responses are presented in Table 4.8.
Table 4.8 Distribution of Respondents Regarding Decision about when to Spray Decision about when to Spray
UCs Self- Agriculture Total Fellow Farmer Pesticide Dealer Decision Extension Agent Bandkurai 33(8.6) 14(3.6) 29(7.6) 20(5.2) 96(25)
Khanmai 17(4.4) 11(2.9) 24(6.2) 44(11.5) 96(25)
Baffa 23(6) 0(0) 30(7.8) 43(11.2) 96(25)
Baidara 22(5.7) 0(0) 15(3.9) 59(15.4) 96(25)
Total 95(24.7) 25(6.5) 98(25.5) 166(43.2) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data illustrated in Table 4.8 envisaged that majority (43.4%) of the respondents reported that the decision is made by the pesticide dealer about when to spray on crops/fruits/vegetables. Similarly 25.5% of the respondents reported that Agriculture Extension Agent decided for us that when to spray pesticides on the crops/fruits/vegetables. Similarly 24.7% of the respondents made self-decision regarding the time to spray pesticides whereas 6.5% of the respondents takes help from fellow farmers. Among the 43.4% of the respondents who reported pesticides dealer for decision making the majority (15.4%) were from Baidara UC followed by Khanmai (11.5%), Baffa
61 UC (11.2%), and Bandkurai UC (5.2%) respectively. This indicates that the widespread misuse of pesticides is because of the fact that pesticide dealers do not have the expertise to guide farmers on effectively controlling pests. Even if they have the necessary expertise, they are obviously motivated by profits from their own business of pesticide sale, as are the pesticide company representatives. Our results are in contrast with that of Jamali et al. (2014) who reported that majority (75%) of the respondents made self-decision regarding pesticides application however Sheikh et al. (2011) reported that majority of the respondents take information regarding spray from pesticides dealers.
4.9Informatoin about Dose of Pesticides
Pesticides used in sprays are mostly available in soluble or wettable powders and also in liquid concentrates which needs to be diluted with water before their use. The other diluents include deodorized kerosene would be for particular applications. The accurate quantity of water applied to an area is of no importance unless it falls in recommended range, provides the suggested quantity of pesticides, offers accurate coverage and has moderate drift or runoff. Therefore, to find out how the respondents came to know about the dosage/rate of pesticides and their responses are presented in Table 4.9. Data presented in Table 4.9 depict that majority (48.8%) of the respondents asked from pesticides sales man regarding the dose of pesticides whereas 22.1% of the respondents took help from Agriculture Extension Agent. Similarly 14.8% of the respondents ask from fellow farmers while 14.3% of the respondents directly consult the label on the pesticides packing. Among the 48% of the respondents the majority were from Khanmai UC i.e. 14.1% who consult Pesticides Sales man for dose of pesticides followed by respondents from Baffa i.e. 13% whereas 11.2% were from the Bandkurai UC (Table 4.9).
62 Table 4.9 Distribution of Respondents Regarding Information about the Dose of Pesticides Source of Information about the Dose of Pesticides
UCs Agriculture Fellow Pesticides Pesticide Label Extension Agent Farmer Sales man Total Bandkurai 29(7.6) 11(2.9) 13(3.4) 43(11.2) 96(25)
Khanmai 20(5.2) 8(2.1) 14(3.6) 54(14.1) 96(25)
Baffa 27(7) 14(3.6) 5(1.3) 50(13.1) 96(25)
Baidara 9(2.3) 22(5.7) 25(6.5) 40(10.4) 96(25)
Total 85(22.1) 55(14.3) 57(14.8) 187(48.8) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
4.10 Day Time Application of Pesticides
Good timing is essential for successful plant‘s pest and disease control. For control of any pest there is specific time table and appropriate stage. Similarly, application of pesticides at the right time of the day is also mandatory for maximum effect. Therefore, the time of the application of pesticides was asked from respondents and their responses are presented in Table 4.10. Table 4.10 Distribution of Respondents Regarding the Time they follow to Apply Pesticides Time of Spray UCs Morning Afternoon Evening Total
Bandkurai 31(8.1) 41(10.7%) 24(6.2) 96(25)
Khanmai 14(3.6) 64(16.7) 18(4.7) 96(25)
Baffa 11(2.9) 56(14.6) 29(7.6) 96(25)
Baidara 19(4.9) 62(16.1) 15(3.9) 96(25)
Total 75(19.5) 223(58.1) 86(22.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
63 Data in Table 4.10 showed that majority (58.1%) of the respondents were applying pesticides at afternoon followed by the 22.4% of the respondents who were applying pesticides in the evening. This might be due to the fact that some of the respondents were government servant and after attending the office they use the free time at evening for pesticides application. Almost 20% of the respondents were applying the pesticides at morning time. It was not a given sign that less respondents were utilizing the pesticides at morning time because plants absorb water best early in the morning, they will absorb chemicals most effectively early in the morning and again around dusk. Our results are in contrast with that of Jamali et al. (2014) who reported that majority (63%) of the use to spray at evening time.
4.11 Number of Sprays on Single Crop
Data presented in Table 4.11 show the average number of sprays on single crop. It was found that majority of the respondents on average applied 1-2 sprays on wheat and rice i.e. 48.69% and 70.78% respectively. On sugarcane majority (54.88%) of the respondents reported 3-5 sprays which might be due to the fact that growth season of sugarcane is long therefore, the respondents use to apply pesticides off and on. Similarly, for tomato and onion majority of the respondents performed 3-5 sprays i.e. 77.87% and 73.62% respectively. This might be due to the fact the tomato and onion are mostly under the attack of pests. On gram all of the respondents reported that they performed 1-2 sprays. Moreover, on maize, okra, and lentil majority of the respondents performed 1-2 sprays i.e. 72.86, 78.94 and 42.85% respectively. About 78.76% of the respondents reported that they performed 3-5 sprays in cucumber whereas, 59.37% of the respondents reported that they used 3-5 sprays in case of sponge gourd.
Majority (57.89%) of the respondents reported that they performed 1-2 sprays in bitter gourd whereas, 72.22% of the respondents performed the same in mango. On pear, apricot and persimmon 3-5 sprays were reported by the majority of the respondents i.e. 78.26, 75.86 and 42.1% respectively. Above 5 sprays were reported by the majority of the respondents on plum and peach i.e. 47.05% and 84.31%. On turnip, radish, potato, pepper, citrus and apple the number of the sprays reported by majority of the respondents were 1-2 sprays i.e. 90.26, 84.29, 56.25, 94.44, 85.71 and 68.08% respectively (Table 4.11).
64 Table 4.11 Distribution of Respondents regarding the average No. of Spray on Single Crop No. of Sprays Sr. # Crop/vegetable/fruit F 1- 2 3-5 Above 5 Crops 1 Wheat 384 187(48.69) 171(44.53) 26(6.77) 2 Rice 89 63(70.78) 14(15.73) 12(13.48) 3 Sugarcane 133 41(30.82) 73(54.88) 19(14.28) 4 Gram 13 7(53.84) - - 5 Maize 129 94(72.86) 35(27.13) - 6 Lentil 7 3(42.85) - - Vegetables 7 Tomato 235 29(12.34) 183(77.87) 23(9.78) 8 Onion 91 13(14.28) 67(73.62) 11(12.08) 9 Okra 19 15(78.94) 4(21.05) - 10 Cucumber 113 16(14.15) 89(78.76) 8(7.07) 11 Sponge gourd 32 11(34.37) 19(59.37) 2(6.25) 12 Bitter gourd 38 22(57.89) 13(34.21) 3(7.89) 13 Turnip 113 102(90.26) 11(9.73) - 14 Radish 121 102(84.29) 19(15.70) - 15 Potato 16 9(56.25) 7(43.75) - 16 Pepper 18 17(94.44) 1(5.55) - Fruits 17 Mango 18 13(72.22) 5(27.77) - 18 Date Palm 41 6(14.63) - - 19 Plum 34 5(14.70) 13(38.23) 16(47.05) 20 Peach 51 2(3.92) 6(11.76) 43(84.31) 21 Pear 23 3(13.04) 18(78.26) 2(8.69) 22 Apricot 29 4(13.79) 22(75.86) 3(10.34) 23 Persimmon 19 7(36.84) 8(42.10) 4(21.05) 24 Citrus 21 18(85.71) 3(14.28) - 25 Apple 47 32(68.08) 11(23.40) 4(8.51) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
65 4.12 Picking of Produce after Application of Pesticides
Each and every pesticides has specific harvest interval and according to which pesticides application is necessary to avoid or minimize the residual effect and lawful application. It is necessary to follow the label accurately to avoid pesticide residues in the crop. Table 4.12 shows the data regarding the days after pesticides application; the respondents used to pick the fruits/produce. It was found that all the respondents in wheat, rice, and sugarcane harvest the produce after more than ten days of pesticides application. In case of tomato majority (59.57%) of the respondents reported that they pick the produce in above 10 days of pesticides application whereas 24.25% of the respondents used to pick the produce 6-10 days after application of pesticides. Only 16.17% of the respondents reported that they pick their produce after 1-5 days of the pesticides application. Similarly in onion majority of the respondents reported that they pick their produce in above 10 days of the application of pesticides. The same response was also recorded in gram and maize i.e. majority of the respondents reported that they harvest the produce after more than ten days of the application of pesticides (Table 4.12).
In okra majority of the respondents reported that they harvest their produce after 6-10 days of pesticides application. The same pattern was also reported by the majority (72.57%) of the respondents on cucumber whereas in sponge gourd and bitter gourd majority of the respondents reported that they harvest the produce after more than ten days of pesticides application. In mango, date palm, plum, apricot, persimmon, turnip, potato, pepper, citrus and apple majority of the respondents reported that they harvest their produce after more than ten days of the application of pesticides (Table 4.12). The instant results clearly depicts that the harvest of produce within 7 days of the pesticides application is putting the lives of the consumers in danger. The only recommended practice is to follow the label exactly, which was not the regular practice of the respondents. However, the harvest interval of the following week seems a somewhat better practice because most of the commonly available pesticides are considered not to have their maximum residue limits in the produce.
66 Table 4.12 Distribution of Respondents Regarding the Picking of Fruits/Produce after Spray
No of Days Sr. # Crop/vegetable/fruit Frequency 1 to 5 6 to 10 Above 10 Crops 1 Wheat 384 - - 384(100) 2 Rice 89 - - 89(100) 3 Sugarcane 133 - - 133(100) 4 Gram 13 - - 7(53.84) 5 Maize 129 - - 129(100) 6 Lentil 7 - - - Vegetables 7 Tomato 235 38(16.17) 57(24.25) 140(59.57) 8 Onion 91 2(2.19) 9(9.89) 80(87.9) 9 Okra 19 6(31.588) 9(47.37) 4(21.05) 10 Cucumber 113 17(15.04) 82(72.57) 14(12.38) 11 Sponge gourd 32 6(18.75) 7(21.98) 19(59.37) 12 Bitter gourd 38 2(5.26) 9(23.68) 27(71.05) 13 Turnip 113 7(6.19) 32(28.31) 74(65.48) 14 Radish 121 9(7.43) 17(14.04) 95(78.51) 15 Potato 16 - - 16(100) 16 Pepper 18 2(11.11) - 16(88.89) Fruits 17 Mango 18 - 3(16.67) 15(83.33) 18 Date Palm 41 - - 9(21.95) 19 Plam 34 3(8.82) 13(38.23) 18(52.94) 20 Peach 51 23(45.09) 22(43.13) 6(11.76) 21 Pear 23 3(13.04) 12(52.17) 8(34.78) 22 Apricot 29 2(6.89) 12(41.37) 15(51.72) 23 Persimmon 19 - 6(31.57) 13(68.42) 24 Citrus 21 1(4.76) 3(14.28) 17(80.95) 25 Apple 47 4(8.51) 16(34.04) 27(57.44) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
67 4.13 Knowledge Regarding Pictograms
Pesticide labels also contain self-explanatory pictures (for users with limited reading abilities) on safe use, safe handling and potential hazards. Improper use of pesticides can cause sever damage to health and environment. In the same connection the pictograms on the packing of the pesticides clearly indicates the toxicity and instructions for its use. Therefore the respondents were investigated regarding their knowledge about the pictograms and data was presented in Tables 4.13. Table 4.13.1 Distribution of Respondents Regarding Knowledge about Activity Pictogram Activity Pictogram Sr. Pictogram Meaning UCs Yes No # Bandkurai 55(14.3) 41(10.7) Khanmai 50(13.0) 46(12.0) Handle Carefully- 1 Baffa 45(11.7) 51(13.3) Liquid Product Baidara 53(13.8) 43(11.2) Total 203(52.9) 181(47.1) Bandkurai 58(15.1) 38(9.9) Handle Carefully- Khanmai 55(14.3) 41(10.7) 2 Powder or Granules Baffa 57(14.8) 39(10.2)
Product Baidara 54(14.1) 42(10.9) Total 224(58.3) 160(41.7) Bandkurai 65(16.9) 31(8.1) Khanmai 51(13.3) 45(11.7) 3 Use a Sprayer Baffa 67(17.4) 29(7.6)
Baidara 62(16.1) 34(8.9) Total 245(63.8) 139(36.2) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.13.1 show the responses of the respondents regarding their knowledge about the activity pictogram of Pesticides. It was found that only 52.9% of the respondents indicated the ―Handle Carefully-Liquid Product” pictogram whereas ―Handle Carefully-
68 Powder or Granules Product” was reported by 58.3% of the respondents. Similarly overwhelming majority (63.8%) of the respondents had the knowledge about the ―Use a Sprayer” Pictogram (Table 4.13.1). Our results are in contrast with that of Giri et al. (2009) who reported that majority of the respondents were not able to understand the activity pictograms.
Table 4.13.2 Distribution of Respondents Regarding Advisory Pictogram
Advisory Pictogram Sr. # Pictogram Meaning UCs Yes No Bandkurai 56(14.6) 40(10.4) Use Khanmai 48(12.5) 48(12.5) 4 Protective Baffa 52(13.5) 44(11.5) Gloves Baidara 55(14.3) 41(10.7) Total 211(54.9) 173(45.1) Bandkurai 73(19.0) 23(6.0) Khanmai 65(16.9) 31(8.1) Wash after 5 Baffa 66(17.2) 30(7.8) Use Baidara 76(19.8) 20(5.2) Total 280(72.9) 104(27.1) Bandkurai 71(18.5) 25(6.5) Khanmai 62(16.1) 34(8.9)
6 Wear a Mask Baffa 70(18.2) 26(6.8) Baidara 69(18.0) 27(7.0) Total 272(70.8) 112(29.2) Bandkurai 45(11.7) 51(13.3) Wear a Khanmai 32(8.3) 64(16.7) 7 Protective Baffa 45(11.7) 51(13.3) Overall Baidara 55(14.3) 41(10.7) Total 177(46.1) 207(53.9)
69 Bandkurai 49(12.8) 47(12.2) Khanmai 50(13.0) 46(12.0) 8 Use a Shield Baffa 58(15.1) 38(9.9) Baidara 42(10.9) 54(14.1) Total 199(51.8) 185(48.2) Bandkurai 58(15.1) 38(9.9) Khanmai 46(12.0) 50(13.0) 9 Wear Glasses Baffa 50(13.0) 46(12.0) Baidara 61(15.9) 35(9.1) Total 215(56.0) 169(44.0) Bandkurai 61(15.9) 35(9.1) Khanmai 47(12.2) 49(12.8) 10 Wear Boots Baffa 53(13.8) 43(11.2) Baidara 56(14.6) 40(10.4) Total 217(56.5) 167(43.5) Bandkurai 46(12.0) 50(13.0) Khanmai 42(10.9) 54(14.1) Wear 11 Baffa 49(12.8) 47(12.2) Respirator Baidara 58(15.1) 38(9.9) Total 195(50.8) 189(49.2) Bandkurai 45(11.7) 51(13.3) Wear Khanmai 47(12.2) 49(12.8) 12 Protective Baffa 54(14.1) 42(10.9) Clothing Baidara 36(9.4) 60(15.6) Total 182(47.4) 202(52.6) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.13.2 show the responses of the respondents regarding advisory pictogram. It was found that majority (54.9%) of the respondents were aware about the pictogram of ―Using Protective Gloves”. Similarly 72.2% of the respondents were aware of the ―Wash after Use” pictogram whereas almost 71% of the respondents were aware of the ―Wear
70 Mask” pictogram. Awareness of ―Wear a Protective Overall” pictogram was reported by 46.1% while awareness about ―Use a Shield” pictogram was reported by 51.8% of the respondents. Almost 56% each of the respondents had the knowledge about the ―Wear Glasses” and ―Wear a Boot” pictogram respectively. Half of the total respondents had the knowledge about the ―Wear Respirator” pictogram whereas ―Wear Protective Clothing” pictogram was reported by 47.4% of the respondents (Table 4.13.2).
Our results are in contradiction with that of Mengistie et al. (2017) who reported that majority of the respondents had no knowledge about the pictogram like wear boots, wear protective clothing, use a face shield and wash hand after use however our results are in line with them regarding wear a boot pictogram. Our results are also in conformity with that of Giri et al. (2009) who reported that majority of the respondents were aware of the advisory pictograms i.e. protective gloves, washing after use, wear mask ,wear boots, wear glasses, protective clothes, wearing a respirator whereas wear face shield pictogram was not known to majority of the respondents.
71 Table 4.13.3 Distribution of Respondents Regarding Enviromental & other Hazards Pictogram Enviromental & Other hazards Sr. # Pictogram Meaning UCs Yes No Bandkurai 71(18.5) 25(6.5) Dangerous for Khanmai 59(15.4) 37(9.6) 13 Livestock and Baffa 65(16.9) 31(8.1) Poultry Baidara 73(19) 23(6) Total 268(69.8) 116(30.2) Bandkurai 64(16.7) 32(8.3) Khanmai 45(11.7) 51(13.3) Dangerous for 14 Baffa 53(13.8) 43(11.2) Wildlife Baidara 65(16.9) 31(8.1) Total 227(59.1) 157(40.9) Bandkurai 60(15.6) 36(9.4) Dangerous for Khanmai 55(14.3) 41(10.7) fish/do not 15 Baffa 72(18.8) 24(6.2) Contaminate Baidara 90(23.4) 6(1.6) Water Total 277(72.1) 107(27.9) Bandkurai 40(10.4) 56(14.6) Keep Locked Khanmai 33(8.6) 63(16.4) Away or Out 16 Baffa 45(11.7) 51(13.3) of Reach from Baidara 54(14.1) 42(10.9) Children Total 172(44.8) 212(55.2) Bandkurai 65(16.9) 31(8.1) Khanmai 51(13.3) 45(11.7) 17 Poison Baffa 58(15.1) 38(9.9) Baidara 67(17.4) 29(7.6)
Total 241(62.8) 143(37.2)
72 Bandkurai 29(7.6) 67(17.4) Khanmai 32(8.3) 64(16.7) 18 Corrosive Baffa 40(10.4) 56(14.6) Baidara 37(9.6) 59(15.4) Total 138(35.9) 246(64.1) Bandkurai 67(17.4) 29(7.6) Khanmai 54(14.1) 42(10.9) 19 Flammable Baffa 62(16.1) 34(8.9) Baidara 68(17.7) 28(7.3) Total 251(65.4) 133(34.6) Bandkurai 60(15.6) 36(9.4) Khanmai 37(9.6) 59(15.4) 20 Explosive Baffa 49(12.8) 47(12.2) Baidara 62(16.1) 34(8.9) Total 208(54.2) 176(45.8) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data illustrated in Table 4.13.3 depict that majority (69.8%) of the respondents were aware of ―Dangerous for Livestock and Poultry” Pictogram. ―Dangerous for Wildlife” Pictogram was known to about 59.1% of the respondents whereas knowledge about ―Dangerous for Fish/Do No Contaminate Water” Pictogram was indicated by 72.1% of the respondents; among them majority were from Baidara UC. This might be due to the fact that Baidara UC is mountainous and full of water springs therefore, they reported that they cause harm to the water life if utilized against them. ―Keep Locked Away or Out of Reach from Children” pictogram was reported by 44.8% of the respondents whereas, almost 63% of the respondents were aware of the ―Poison” pictogram. The most unknown pictogram to majority of the respondents was the ―Corrosive” pictogram as reported by the only 35.9% of the total respondents (Table 4.13.3). They were of the view that they are unable to identify what this sign denotes. This might be also due to the fact that due to non- availability of such type of pesticides which are corrosive or they haven‘t use such type of
73 pesticides which is corrosive therefore, they haven‘t the experience to understand this pictogram while personal interview with them.
Those respondents who were aware of the “Corrosive” pictogram reported that they have only knowledge about that pictogram though they haven‘t seen such type of pictogram on any pesticides container. About 65.4% of the respondents were aware of the ―Flammable” Pictogram. The instant results are not in conformity with that of Mengistie et al. (2017) who reported that majority of the respondents had no knowledge about the ―Dangerous For Fish/Do No Contaminate Water” and “Keep Locked Away or out of reach from Children” which might be due to the fact that majority of the respondents in their study were illiterate i.e. 55%. Our results are in contrast with that of Giri et al. (2009) who reported that enviromental & other hazards pictogram were poorly understood by majority of the respondents.
Data regarding Toxicity level pictogram is presented in Table 4.13.4. It was found that majority (71.6%) of the respondents were not aware of the ―Slightly Hazardous” Pictogram followed by the respondents i.e. 59.4% who were aware of the ―Moderate Hazard” Pictogram. ―Highly Hazard” Pictogram which has the octagon shape was reported by only 35.9% of the respondents that they have awareness about that pictogram. From the instant results it can be concluded that though all the respondents were little bit literate while some of them were highly literate still unable to identify; this represents that there is always chance of misuse of such pesticides which is ―highly hazard”.
74 Table 4.13.4 Distribution of Respondents Regarding Toxicity Levels Pictorgram Toxicity Levels Pictorgram Sr. # Pictogram Meaning UCs Yes No Bandkurai 25(6.5) 71(18.5) Slightly Khanmai 36(9.4) 60(15.6) 21 Hazardous Baffa 30(7.8) 66(17.2) (Caution) Baidara 18(4.7) 78(20.3) Total 109(28.4) 275(71.6) Bandkurai 58(15.1) 38(9.9) Moderate Khanmai 65(16.9) 31(8.1) 22 Hazard Baffa 66(17.2) 30(7.8) (Warning) Baidara 39(10.2) 57(14.8)
Total 228(59.4) 156(40.6) Bandkurai 13(3.4) 83(21.6) Highly Khanmai 24(6.2) 72(18.8) 23 Hazard Baffa 40(10.4) 56(14.6) (Danger) Baidara 61(15.9) 35(9.1) Total 138(35.9) 246(64.1) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Similarly data in Table 4.13.5 show that ―Extremely Toxic” color pictogram was reported by 54.9% of the respondents which might be due to the fact that red color is always a sign of danger and thus they were aware that this pictogram is extremely toxic. About 42% of the respondents had knowledge about the “Highly Toxic” Color Pictogram whereas ―Moderately Toxic” Pictogram was known to only 20.1% of the respondents. Similarly 33.9% of the respondents were familiar with the ―Slightly Toxic” color pictogram. Our results are in similarity with that of Giri et al. (2009) who also reported in their study, that majority of the farmers were not aware of the color coding scheme of pesticides toxicity.
75 Table 4.13.5 Distribution of Respondents regarding Toxicity Level Pictograms (Colour) Toxicity Levels Pictorgram
Sr. # Pictogram Meaning UCs Yes No Bandkurai 52(13.5) 44(11.5)
Extremely Toxic Khanmai 43(11.2) 53(13.8) 24 (Oral Lethal Dose Baffa 52(13.5) 44(11.5) 1-50mg/kg) Baidara 64(16.7) 32(8.3) Total 211(54.9) 173(45.1) Bandkurai 42(10.9) 54(14.1)
Highly Toxic Khanmai 37(9.6) 59(15.4) 25 (Oral Lethal Dose Baffa 43(11.2) 53(13.8) 50-500 mg/kg) Baidara 39(10.2) 57(14.8) Total 161(41.9) 223(58.1) Bandkurai 19(4.9) 77(20.1) Moderately Khanmai 16(4.2) 80(20.8) Toxic (Oral 26 Baffa 21(5.5) 75(19.5) Lethal Dose 501- Baidara 21(5.5) 75(19.5) 5000 mg/kg) Total 77(20.1) 307(79.9) Bandkurai 27(7.0) 69(18.0) Slightly Toxic Khanmai 30(7.8) 66(17.2) (Oral Lethal 27 Baffa 27(7.0) 69(18.0) Dose >5000 Baidara 46(12.0) 50(13.0) mg/kg) Total 130(33.9) 254(66.1) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
4.14 Checking the Labels
A label is the written, printed or graphic material firmly attached to a product container which provides clear instructions about the proper and safe usage of respective pesticide. Labels are legal documents and convey essential safety information and use recommendations. Therefore, in order to know about the respondents whether they check
76 the labels of the pesticides container or not they were asked about it and their responses are presented in Table 4.14.
Table 4.14 Distribution of Respondents Regarding they Check the Labels or not Before Applying Pesticides Checking the Labels before Applying UCs Total Yes No Bandkurai 65(16.9) 31(8.1) 96(25)
Khanmai 51(13.3) 45(11.7) 96(25)
Baffa 49(12.8) 47(12.2) 96(25)
Baidara 61(15.9) 35(9.1) 96(25)
Total 226(58.9) 158(41.1) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.14 show that majority (58.9%) of the respondents reported that they use to check the labels of pesticides prior its application whereas 41.1% of the respondents never use to check the pesticides labels. This might be due to the fact that they were regularly using pesticides since so many years and thus had the knowledge how to apply or they are unable to understand the labels thus never use to check the labels. Moreover, it might also be due to the fact that pesticides utilization was a routine work for them and thus were never cautious about the health and environmental hazards.
Our results are in contrast with that of Mengistie et al. (2017) who reported in their study that majority of the respondents never use to check the labels of the pesticides which might be due to the change in study area and behavior of the inhabitants. Our results are also somewhat in contradiction with that of Giri et al. (2009) who reported that half of the respondents use to read labels of the pesticides. Sainju (2015) also put forward his findings that majority (94%) of the respondents never use to check the labels.
4.15 Following the Instructions of Labels
Only checking label is of no use if it is not followed while pesticides utilization. The instructions are very important to be followed because every pesticide belongs to different
77 Class of toxicity and required dealing accordingly. Some may be too dangerous while other may require different sort of handling i.e. Granules, Emulsifiable concentrate, wetable powders etc. Similarly on each pesticides container there is always mentioned what protective measures you should take prior to its utilization for safe use. Therefore, the respondents were investigated whether they follow the instruction of labels or not and their responses are presented in Table 4.15.
Table 4.15 Distribution of Respondents Regarding they Follow Instruction on Labels Do you Follow Instruction UCs Total Yes No Bandkurai 65(16.9) 31(8.1) 96(25)
Khanmai 51(13.3) 45(11.7) 96(25)
Baffa 48(12.5) 48(12.5) 96(25)
Baidara 60(15.6) 36(9.4) 96(25)
Total 224(58.3) 160(41.7) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data illustrated in Table 4.15 show that majority (58.3%) of the respondents reported that they follow the instructions of labels whereas 41.7% of the respondents never use to follow the instructions. This might be due to the fact that either respondents were unable to purchase the safety equipment which is mentioned on the labels or they took the labels as light instead of strictly following. Our results are in contrast with that of Devi (2009) who reported that overwhelming majority (97%) of the respondents didn‘t follow the instructions of labels. It is worth mentioning that among those who use to check the labels, 224 respondents followed somehow the instructions on labels if not all.
4.16 Precautionary Measures/Personal Protective Equipment (PPE) Farmers used during Pesticides Practices
Manmade pesticides are widely utilized for the control of detrimental pests in agriculture and to inhibit the yield losses or damage of the product. Due to their high biological activity along with their extended persistence in environment, these pesticides can cause detrimental losses to environment and human. The farming community has normally
78 greater exposure to pesticides as compared to the consumers. Farmers are exposed to the pesticides during preparation and application of pesticide solution and also during cleaning of the pesticide equipment. Specifically, the farmers who are involved in mixing, loading and spraying of pesticides are more unprotected from these chemicals because of splashes and spills, direct contact with spray due to missing or faulty protective equipment and also to their drift. Moreover, the farmers are also exposed to pesticides while carrying out activities not directly associated with pesticide use. For instance, the farmers involved in manual labor in fields treated with pesticides may face losses from direct spray, drift from adjacent fields, or through contact of pesticide residue on crop and soil and this form of exposure is commonly underrated. The dermal and inhalation contact with pesticides are normally most common exposure of farmers to pesticides. Dermal contact with pesticide usually takes place during handling of pesticides on the body areas which are not covered with protective clothing like face and hands. The exposure to pesticide among farmers would be minimized through reduce use of pesticide and appropriate use of personal protective equipment during entire process of pesticides handling.
Personal Protective Equipment (PPE) refers to all kinds of clothing and equipment used to minimize and inhibit self-exposure from harmful materials. It is of significance importance when dealing with intensively harmful pesticides which cause chronic health diseases. The equipment enumerated on the label should be used during the application of pesticide. In order to inhibit dermal exposure during the application of pesticides, numerous kinds of Personal Protective Equipment are used which includes chemical-resistant coveralls, hats, boots, gloves and long sleeve shirts. The type of PPE used among farming community depends on the toxicity of the pesticide, exposure condition and the preference of the workers. The least possible PPE used for majority of the pesticides includes the use of boots and gloves. But, highly poisonousness pesticides required the use of several types of PPE for decreasing the exposure. Numerous kinds of PPE assure corresponding levels of personal protection against skin exposure.
Data in Table 4.16.1 depict that majority (76.8%) of the respondents were using masks during spraying, whereas 23.2% of the respondents didn‘t use mask while spraying. This might be due to the fact that farmers usually try to make alternate solution of, in order to
79 save time and money thus they used to use cloth etc. instead of proper masks available in market. Similarly, about 54.4% of the respondents reported that they use separate clothes for spraying purpose whereas, 45.6% of the respondents were not in the favor to wear apropos clothes for spraying purpose (Table 4.16.2). When the respondents were inquired regarding the action which they took as the pesticides came in contact with the body they reported that they simply wash it with water immediately i.e. 56%. Similarly, 27.6% of the respondents reported that they do nothing whereas only 16.4% of the respondents use to visit doctor as the pesticides came in contact with their body (Table 4.16.3). Giri et al. (2009) also reported that majority of the respondents use to cover their nose and wear protective clothing. This was due to the fact that it was easy to wear clothes and mask as reported by the Giri et al. (2009). Mengistie et al. (2017) also reported that majority of the respondents didn‘t wear proper clothes during spraying.
80 Table 4.16.1 Distribution of Respondents Regarding Using Mask during Spraying Using Mask during Spraying UCs Total Yes No Bandkurai 56(14.6) 40(10.4) 96(25)
Khanmai 85(22.1) 11(2.9) 96(25)
Baffa 79(20.6) 17(4.4) 96(25)
Baidara 75(19.5) 21(5.5) 96(25)
Total 295(76.8) 89(23.2) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.2 Distribution of Respondents Regarding Wearing Separate Clothes for Spray Purpose Wearing Separate Clothes for Spray Purpose UCs Total Yes No Bandkurai 49(12.8) 47(12.2) 96(25)
Khanmai 51(13.3) 45(11.7) 96(25)
Baffa 49(12.8) 47(12.2) 96(25)
Baidara 60(15.6) 36(9.4) 96(25)
Total 209(54.4) 175(45.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.3 Distribution of Respondents Regarding Action when Pesticides Came in Contact with Body Action when Pesticides Came in Contact with Body UCs Total Do Nothing Washing Consult Doctor Bandkurai 28(7.3) 64(16.7) 4(1.0) 96(25)
Khanmai 53(13.8) 40(10.4) 3(.8) 96(25)
Baffa 25(6.5) 55(14.3) 16(4.2) 96(25)
Baidara 0(0) 56(14.6) 40(10.4) 96(25)
Total 106(27.6) 215(56.0) 63(16.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
81 Data regarding covering hands while mixing pesticides is presented in Table 4.16.4. It was found that majority (33%) of the respondents used to wear gloves while mixing pesticides followed by the respondents who cover hands with plastic bags i.e. 29.4%. About 20% of the respondents responded that they cover hands with clothes while, 17.4% of the respondents mix the pesticides bare handed. Similarly, the respondents were asked that whether they take a bath after pesticides application or not and their responses are presented in Table 4.16.5. It was found that 58.9% of the respondents use to take a bath after pesticides application whereas, 41.14% of the respondents didn‘t take bath. Smoking while spraying was reported by only 34.4% of the respondents whereas overwhelming majority (65.6%) never used to smoke while spraying pesticides (Table 4.16.6). Sainju (2015) also reported that majority of the respondents didn‘t smoke cigarette while spraying pesticides.
Both smoking and chewing gum may increase the pesticide exposure because of more frequent hand to mouth contact. Previous studies (Manyilizu et al., 2017) also indicated that with smoking during pesticide application significantly increased the risk of chest pain. Our results are in conformity with that of Giri et al. (2009) who reported that less than 41 % of the respondents take a bath after spraying pesticides. Similarly they also reported that very few wear gloves while mixing pesticides. The large majority of the sprayers (farmers) did not shower after pesticide spraying and carried on working in the field (Mengestie et al., 2017). In the instant study during close observation of spraying practices at the site revealed some unsafe practices and most of the farmers were of the view that we feel uncomfortable with the wearing of the separate clothes, boots, goggles etc. for spraying and thus they were reluctant for safe spray.
82 Table 4. 16.4 Distribution of Respondents Regarding Hand Covering Material when Mixing of Pesticides Hand Covering Material While Mixing Pesticides Hand Cover UCs Hand Cover Hand Cover Total with Plastic Bear hand with Clothes with Gloves Bags Bandkurai 24(6.2) 32(8.3) 34(8.9) 6(1.6) 96(25) Khanmai 33(8.6) 40(10.4) 20(5.2) 3(.8) 96(25) Baffa 12(3.1) 22(5.7) 39(10.2) 23(6.0) 96(25) Baidara 7(1.8) 19(4.9) 35(9.1) 35(9.1) 96(25) Total 76(19.8) 113(29.4) 128(33.3) 67(17.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.5 Distribution of Respondents Regarding Taking a Bath after Pesticides Use Taking a Bath after Pesticides Use UCs Total Yes No Bandkurai 61(15.9) 35(9.1) 96(25) Khanmai 60(15.6) 36(9.4) 96(25) Baffa 48(12.5) 48(12.5) 96(25) Baidara 57(14.8) 39(10.2) 96(25) Total 226(58.9) 158(41.1) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.6 Distribution of Respondents Regarding Smoking While Spraying Smoking while Spraying UCs Total Yes No Bandkurai 27(7.0) 69(18.0) 96(25) Khanmai 39(10.2) 57(14.8) 96(25) Baffa 37(9.6% 59(15.4) 96(25) Baidara 29(7.6% 67(17.4) 96(25) Total 132(34.4% 252(65.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
83 An empty pesticide container can be hazardous because of residues left inside. Improperly discarded pesticide container can be very hazardous. It can injure sanitation workers and also lead to environmental pollution. An empty container can attract curious children and animals and are serious threat to them thus it should be properly disposed off. Data regarding disposal of empty bottle was collected and is presented in Table 4.16.7. It was found that majority (34.1%) of the respondents disposed the empty bottles of pesticides with usual trash whereas, 25.8% of the respondents reported that they burn the bottles. Similarly 24.2% of the respondents reported that they use the bottle in home for various purposes after cleaning with water thoroughly. Almost 16% of the respondents reported that they throwaway the empty bottles alongside the field. The common practices of throwing the empty pesticide container in the field or garbage were dangerous because they lead to environmental pollution. Some findings were supported by Saleh et al. (1995) who reported that most of the farmers disposed of empty containers around or inside the farm after damaging them so that they cannot be reused. Similar findings regarding the disposal of empty pesticide bottles have also been reported by Huang et al. (2000); they further concluded that some of the farmers also kept the empty bottles for other uses i.e. domestic use. Our results are in contrast with that of Mengesties et al. (2017) who reported that majority of the respondents throw away the empty bottles alongside the field.
Clothes become saturated with pesticides through repeated use, if not washed properly after pesticide use. Rubber gloves and boots that are contaminated on the inside can greatly increase pesticide absorption through the skin. About 62.8% of the respondents reported that they change the clothes after pesticides application (Table 4.16.8). From the instant results it can be concluded that only 54% of the farmers were using separate clothes for spraying purpose (Table 4.24.2) but here the majority were of the view that they use to change clothes after spraying. This showed that in spite of wearing separate clothes they change the clothes after spraying. Moreover, overwhelming majority (69.5%) reported that they wear boots while spraying (Table 4.16.9). This might be due to the fact that most commonly during field visit it was observed that farmers were wearing high boots because of the reason that they feel easy with boots while working in the field. During informal
84 discussion with respondents who reported that we never use to wear boot while spraying. It was also observed that during winter season they also wear boots while spraying but often.
Our results are in line with that of Azmi et al. (2006) and Jamali et al. (2014). Giri et al. (2009) also reported that very few of the respondents wear boots while spraying pesticides. Our results in contrast with that of Giri et al. (2009) who reported that majority of the respondents dispose the empty bottle by burring in the pit followed by the respondents who throwaway the empty bottles alongside the field.
85 Table 4.16.7 Distribution of Respondents Regarding “What do you do With Empty Bottles of Pesticides” Disposal of Empty Bottles of Pesticides
UCs Disposed with Throwing away Burned Use in House Usual trash Alongside Field Total Bandkurai 15(3.9) 32(8.3) 34(8.9) 15(3.9) 96(25)
Khanmai 27(7) 30(7.8) 23(6) 16(4.2) 96(25)
Baffa 35(9.1) 25(6.5) 21(5.5) 15(3.9) 96(25)
Baidara 22(5.7) 44(11.5) 15(3.9) 15(3.9) 96(25)
Total 99(25.8) 131(34.1) 93(24.2) 61(15.9) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.8 Distribution of Respondents Regarding Changing Clothes after Application of Pesticides Change Clothes after Application of Pesticides UCs Total Yes No Bandkurai 54(14.1) 42(10.9) 96(25)
Khanmai 65(16.9) 31(8.1) 96(25)
Baffa 60(15.6) 36(9.4) 96(25)
Baidara 62(16.1) 34(8.9) 96(25)
Total 241(62.8) 143(37.2) 384 (Figures in Parenthesis are percentages) Table 4. 16.9 Distribution of Respondents Regarding Wearing boots while spraying Wearing Boots while Spraying UCs Total Yes No Bandkurai 66(17.2) 30(7.8) 96(25)
Khanmai 74(19.3) 22(5.7) 96(25)
Baffa 67(17.4) 29(7.6) 96(25)
Baidara 60(15.6) 36(9.4) 96(25)
Total 267(69.5) 117(30.5) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
86 Data regarding using mixing equipment is presented in Table 4.16.10. It was found that majority (63%) of the respondents were using various mixing equipment whereas, 37% of the respondents were not using mixing equipment for pesticides mixing. Overwhelming majority (83.3%) of the respondents was covering their noses prior to apply pesticides as a precautionary measure whereas, 16.7% of the respondents were not covering their nose (Table 4.16.11). Similarly majority (61.7%) of the respondents were aware about the direction of wind in which to spray whereas, 38.3% of the respondents were unaware about the direction of wind in which to spray (Table 4.16.12). Our results are in contrast with that of Giri et al. (2009) who reported that majority of the respondents didn‘t know about the direction of wind to spray in order to avoid direct contact of pesticides with the body. However, our results are in conformity with that of Sefa et al. (2015) who reported that majority of the respondents know about the direction in which to spray. It is obvious from the results that pesticide applicators appeared to identify the consequences of spraying against the wind. They observed the direction of the wind before they start spraying. Sprayer vapor/smoke as guide to determine the wind direction was somewhat an appropriate practice.
87 Table 4. 16.10 Distribution of Respondents Regarding Using Mixture Equipment While Mixing Using Mixture Equipment while mixing UCs Total Yes No Bandkurai 52(13.5) 44(11.5) 96(25)
Khanmai 56(14.6) 40(10.4) 96(25)
Baffa 62(16.1) 34(8.9) 96(25)
Baidara 72(18.8) 24(6.2) 96(25)
Total 242(63.0) 142(37.0) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.11 Distribution of Respondents Regarding Covering Nose and Mouth with any Other Thing (Cloth) Covering Nose and Mouth with any other thing (Cloth) UCs Total Yes No Bandkurai 78(20.3) 18(4.7) 96(25)
Khanmai 82(21.4) 14(3.6) 96(25)
Baffa 85(22.1) 11(2.9) 96(25)
Baidara 75(19.5) 21(5.5) 96(25)
Total 320(83.3) 64(16.7) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.12 Distribution of Respondents Regarding Knowledge about the Direction of Wind to Spray Knowledge about the Direction of Wind to Spray UCs Total Yes No Bandkurai 47(12.2) 49(12.8) 96(25)
Khanmai 70(18.2) 26(6.8) 96(25)
Baffa 59(15.4) 37(9.6) 96(25)
Baidara 61(15.9) 35(9.1) 96(25)
Total 237(61.7) 147(38.3) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
88 Mixing pesticides in open air and close air also has effect on the human being i.e. in close room there is no fresh air and inhaling the fumigation of pesticides may result in acute diseases. It was therefore, thought necessary that the respondents must be investigated about the mixing place of pesticides that whether they mix pesticides in open air or close room and their responses are presented in Table 4.16.13. It was found that majority (75.5%) of the respondents were mixing pesticides in open air whereas, 24.5% were mixing pesticides in close room. This might be due to the fact that majority of the farmers use to take pesticides to the field and took with them all the spraying equipment and there they prepare the solution and apply as well.
Similarly data in Table 4.16.14 depict that majority (52.6%) of the respondents didn‘t eat or drink while spraying whereas, 47.4% of the respondents reported that they usually eat or drink while spraying. Moreover, usually farmers chew a gum or eat anything during applying pesticides may increase the risk factors i.e. diarrhea. This was also reported by the Manyilizu et al. (2017) that eating while spraying increases risk of diarrhea. Previous studies show that lack of using PPE is associated with increased risk of exposure, consequently leading to potential adverse health effects (Prado-Lu, 2007). Our results are in contrast with that of Sainju (2015) who reported that majority (93%) of the respondents never used to eat or drink while spraying. Moreover, about 64% of the respondents were using goggle while spraying whereas 36.2% of the respondents were not using goggles while spraying (Table 4.15.15). Giri et al. (2009) reported that majority of respondents mix the pesticides in the field which is in conformity with that of our results.
89 Table 4. 16.13 Distribution of Respondents Regarding Mixing of Pesticides in Open Place or Close Room Mixing of Pesticides UCs Total Open Air Close room Bandkurai 73(19.0) 23(6.0) 96(25)
Khanmai 69(18.0) 27(7.0) 96(25)
Baffa 67(17.4) 29(7.6) 96(25)
Baidara 81(21.1) 15(3.9) 96(25)
Total 290(75.5) 94(24.5) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.14 Distribution of Respondents Regarding Eat or Drink while Spraying Eat or Drink while Spraying UCs Total Yes No Bandkurai 31(8.1) 65(16.9) 96(25)
Khanmai 56(14.6) 40(10.4) 96(25)
Baffa 58(15.1) 38(9.9) 96(25)
Baidara 37(9.6) 59(15.4) 96(25)
Total 182(47.4) 202(52.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 16.15 Distribution of Respondents Regarding Using Goggles Using Goggles UCs Total Yes No Bandkurai 67(17.4) 29(7.6) 96(25)
Khanmai 68(17.7) 28(7.3) 96(25)
Baffa 51(13.3) 45(11.7) 96(25)
Baidara 59(15.4) 37(9.6) 96(25)
Total 245(63.8) 139(36.2) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
90 Majority (52.1%) of the respondents were not wearing glasses while applying pesticides whereas, 47.9% of the respondents were wearing glasses (Table 4.16.16). Similarly overwhelming majority (81.5%) of the respondents never used to wear face shield while pesticides application whereas, 18.5% of the respondents were using face shield (4.16.17). Overwhelming majority (66.9%) of the respondents were not using respirator while spraying whereas, only 33.1% of the respondents reported that they wear respirator while spraying (Table 4.16.18).
During informal discussion with the respondents when it was asked that why not you are properly following the precautionary measures for safe pesticides spray so they responded that on one side we feel uncomfortable and we didn‘t work properly.
Empirically, specific studies have shown the high human and environmental risks of unsafe use of pesticides in many African countries such as Benin (Ahouangninou et al. 2012), Uganda (Kateregga, 2012) and Kenya (Macharia et al. 2013). Maria et al. (2015) also reported that majority of the respondents never used to wear glasses and boots while spraying pesticides. Past studies showed that the exposure to pesticides can be greatly reduced by the use of appropriate PPE. Batel and Hinz (1987) have proved that a large decrease in dermal exposure occurred by using gloves for hands and hoods for the head area. Popendorf (1987) has also concluded that dermal exposure was reduced by coveralls and the use of gloves can decrease exposure by a factor of ten.
91
Table 4. 16.16 Distribution of Respondents Regarding Using Glasses Using Glasses UCs Total Yes No Bandkurai 38(9.9) 58(15.1) 96(25) Khanmai 35(9.1) 61(15.9) 96(25) Baffa 49(12.8) 47(12.2) 96(25) Baidara 62(16.1) 34(8.9) 96(25) Total 184(47.9) 200(52.1) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Table 4. 16.17 Distribution of Respondents Regarding Using Face Shield Using Face shield UCs Total Yes No Bandkurai 8(2.1) 88(22.9) 96(25) Khanmai 24(6.2) 72(18.8) 96(25) Baffa 20(5.2) 76(19.8) 96(25) Baidara 19(4.9) 77(20.1) 96(25) Total 71(18.5) 313(81.5) 384(100) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Table 4. 16.18 Distribution of Respondents Regarding Using Respirator Do You Use respirator UCs Total Yes No Bandkurai 19(4.9) 77(20.1) 96(25) Khanmai 29(7.6) 67(17.4) 96(25) Baffa 32(8.3) 64(16.7) 96(25) Baidara 47(12.2) 49(12.8) 96(25) Total 127(33.1) 257(66.9) 384(100) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
92 4.17 Knowledge about the Misuse of Pesticides
Data in Table 4.17 depict that majority (76.8%) of the respondents had no knowledge about the banned pesticides whereas, only 23.2% of the respondents had somewhat knowledge about the banned pesticides. Similarly, 70.3% of the respondents had proper knowledge about the nozzles of pesticides sprayer whereas, 29.7% of the respondents reported that they have no proper knowledge about the nozzles. Through improper nozzles there are always high chances of misuse of pesticides i.e. for applying pesticides against insects and one use the nozzles with big droplet size may results in stress to crop. Similarly, using small droplet nozzles for controlling weeds will not control the weeds effectively and ultimately will increase the number of sprays. This is due to the fact that insect body is of small size and small droplet size is efficient to kill the insect, giving no or less stress to plants whereas in case of the weeds the surface area of the weeds is large enough thus requires big droplet size of spray for effective control.
Knowledge about the Economic Threshold Level (ETL) level of particular pest was investigated and it was found that only 31% of the respondents had the knowledge of ETL level of pest which prevails in their locality whereas, 69% were unaware of it. ETL is very important factor in applying pesticides because above ETL level the crop is almost damaged by pest and applying pesticides at that is misuse too and increase cost of production as well. Therefore, in the instant study it was found that farmers were unaware from the ETL and thus were busy in misuse of pesticides (Table 4.17).
Every pesticide has its separate mode of action some of them are for preventive purposes, some are for curative purpose i.e. some are systematic and some are contact pesticides. Thus applying contact pesticides as a preventive measure is the misuse of pesticides whereas, applying contact pesticides as preventive measures is totally wastage of pesticides and money. Therefore, the farmers were investigated regarding their knowledge about the mode of action of pesticides and it was found that majority (63.5%) of the respondents were unaware of the mode of action of pesticides whereas, only 36.5% of the respondents were aware of the mode of action of pesticides (Table 4.17).
93 Expiry of pesticides is very important factor which on one side harms the human beings and environment and on other hand wastes money of farmers because of no proper function. The farmers were asked about the knowledge about the pesticides expiry and their responses are presented in Table 4.17. It was found that majority (51.3%) of the respondents were unaware of the expiry of pesticides because of the negligence and some of them were of the view that on most of the pesticide packing‘s the expiry is not mentioned thus they don‘t care about checking the expiry of pesticides. Similarly, they were also not checking the expiry of the pesticides because of the reason that the chemical is not used for eating purpose thus they were not taking care about the pesticides expiry. Overwhelming majority (64.1%) of the respondents had the knowledge about the pesticides proper solution preparation whereas 35.9% of the respondents were not aware of the proper solution preparation thus involved in the misuse of pesticides (Table 4.17).
Using high doze than recommended is also one of the factor of misuse of pesticides. It was found that majority (66.9%) of the respondents were using high dose than recommended which was because of the fact that they were of the view that with the recommended or low dose we are unable to control pests. Knowledge about the toxicity level of the pesticides is also an important factor because those who know about the toxicity level of pesticides will not use the extremely hazardous and highly hazardous pesticides in order to not contaminate the environment and so the human health. It was found that majority (51.8%) of the respondents were aware of the toxicity level of the pesticides whereas, 48.2% of the respondents reported that they had no proper knowledge about the toxicity levels (Table 4.17).
94 Table 4.17 Distribution of the Respondents Regarding the Knowledge about the Misuse of the Pesticides Particulars UCs Yes No Bandkurai 23(6.0) 73(19.0) Khanmai 19(4.9) 77(20.1) Using banned agricultural pesticides Baffa 25(6.5) 71(18.5) Baidara 22(5.7) 74(19.3) Total 89(23.2) 295(76.8) Bandkurai 57(14.8) 39(10.2) Khanmai 75(19.5) 21(5.5) Knowledge of proper nozzles Baffa 86(22.4) 10(2.6) Baidara 52(13.5) 44(11.5) Total 270(70.3) 114(29.7) Bandkurai 40(10.4) 56(14.6) Khanmai 25(6.5) 71(18.5) Knowledge of ET level of particular pest Baffa 32(8.3) 64(16.7) Baidara 22(5.7) 74(19.3) Total 119(31.0) 265(69.0) Bandkurai 40(10.4) 56(14.6) Khanmai 25(6.5) 71(18.5) Knowledge about mode of action Baffa 38(9.9) 58(15.1) Baidara 37(9.6) 59(15.4) Total 140(36.5) 244(63.5) Bandkurai 49(12.8) 47(12.2) Khanmai 36(9.4) 60(15.6) Knowledge about the expiry of pesticides Baffa 43(11.2) 53(13.8) Baidara 59(15.4) 37(9.6) Total 187(48.7) 197(51.3) Bandkurai 65(16.9) 31(8.1) Knowledge about proper solution Khanmai 51(13.3) 45(11.7%) preparation Baffa 60(15.6%) 36(9.4)
95 Baidara 70(18.2) 26(6.8) Total 246(64.1) 138(35.9) Bandkurai 58(15.1) 38(9.9) Khanmai 64(16.7) 32(8.3) Using high doze than recommended Baffa 60(15.6) 36(9.4) Baidara 75(19.5) 21(5.5) Total 257(66.9) 127(33.1) Bandkurai 49(12.8) 47(12.2) Khanmai 40(10.4) 56(14.6) Knowledge about the toxicity levels of Baffa 51(13.3) 45(11.7) pesticides Baidara 45(11.7) 51(13.3) Total 185(48.2) 199(51.8) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
4.18 Entrance into the Field after Spray
The minimum time between applying a chemical and workers entering the treated area without protective clothing is known as the re-entry or restricted entry interval. It is dangerous to the farmer to enter before re-entry interval. Data illustrated in Table 4.18 depict that majority (37.5%) of the respondents enter the field on the following day after spray whereas, 33.6% of the respondents reported that they enter their field after more than 2 days for field activities. Only 11.7% of the respondents reported that they enter their field after two days of pesticides application. Our results are in conformity with that of Sefa et al. (2015) who also reported that majority of the respondents enter their fields within 1-3 days.
96 Table 4.18 Entrance into the Field after Spray
Entrance into the field after spray
UCs On the Following More than two Total After Two days day days Bandkurai 47(12.2) 15(3.9) 34(8.9) 96(25)
Khanmai 56(14.6) 20(5.2) 20(5.2) 96(25)
Baffa 27(7) 31(8.1) 38(9.9) 96(25)
Baidara 14(3.6) 45(11.7) 37(9.6) 96(25)
Total 144(37.5) 111(28.9) 129(33.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
4.19 Knowledge about the Pesticides Entrance to the Body
Pesticides can move into the human body by three means that includes, through skin (contact), mouth (ingestion) and through the lungs (inhalation). Pesticides in liquid and gas form can enter the body through all the three routes of entry while solids have lower chance of entry by lungs. If solid particles of pesticides are too small or if they remain on the skin for a long time then their penetration in to body takes place in the same ways like liquids and gases. However, the utmost pathway for pesticide poisoning among the pesticide users is through skin (Baldi et al., 2006). Absorption of pesticides through skin might occur as a result of splashes and spills when using pesticides. To a low extent, dermal absorption might also occur through exposure to residues. The degree of harmfulness by dermal absorption are influenced by toxicity of pesticide to skin, exposure duration, formulation of pesticide, and the parts of body adulterated (MacFarlane et al., 2013). Granular, dusts and powder form of pesticides are not absorbed certainly by skin and body tissues as the other liquids forms whereas liquid form of pesticide containing organic solvents and oil based pesticides commonly are absorbed more rapidly compared to dry form of pesticides.
Exposure to pesticides takes place when hands are not washed by touching pesticide containers or handling of pesticides, splashing of pesticides on skin, wearing pesticide
97 adulterated clothing and pesticide application during wind. Contact with treated plants and soil leads to dermal exposure. Exposure to pesticide occurs by rubbing forehead and eyes with pesticide adulterated hands or gloves, mixing of dry formulations without wearing goggles, application in windy weather, exposure to drift and splashing pesticides in eyes. Exposure to pesticides also occurs when hands are not washed before smoking, eating and chewing, pesticides enters the mouth. Unintentional application of pesticides to food, storage of pesticides in containers used for drinking and drift on lip and mouth leads to oral exposure. Likewise, drift exposure during and after mixing, powders, dusts and any other dry formulations (Shiekh et al., 2011). The respondents were asked about the knowledge about how pesticide enters the body and their responses are presented in Table 4. 19.
Table 4. 19 Knowledge about the Pesticides Entrances into the Body Knowledge about the pesticides entrance into the body UCs Total Skin Breath Eye All of Above Bandkurai 9(2.3) 41(10.7) 11(2.9) 35(9.1) 96(25)
Khanmai 29(7.6) 10(2.6) 16(4.2) 41(10.7) 96(25)
Baffa 20(5.2) 26(6.8) 9(2.3) 41(10.6) 96(25)
Baidara 16(4.2) 39(10.2) 13(3.4) 28(7.3) 96(25)
Total 74(19.3) 116(30.2) 49(12.8) 145(37.7) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data regarding pesticides entrance to the body is presented in Table 4.19. It was found that majority (37.7%) of the respondents reported that pesticides enter to the body through all means which were indicated i.e. skin, breath and eye. About 30.2% of the respondents reported that pesticides mostly enter the body through breath. They were of the view that pesticides enter the body through breath because while spraying the pesticides—it contaminates the air in the form of mist and while breathing it enters the body and creates health problems i.e. headache, dizziness etc. with the same mechanism as that of cigarette smoking. About 19.3% of the respondents reported that pesticides enter the body or create problem it comes in contact with skin whereas, only 12.8% reported that the fumes of the pesticides enter the body through eyes and create health problems (Table 4.19).
98 4.20 Self-Reported Symptoms of Pesticides Use
Although lack of personal protection and risky behaviors were common among most of the respondents, there were some differences reported between respondents. Data illustrated in Table 4.20 show that majority (78.1%) of the respondents had been through headache after application of pesticides whereas, 21.9% of the respondents never been through headache. Similarly excessive sweating was reported by 39.3% of the respondents whereas itching was reported by 74.7% of the respondents. Itching is one of the important acute disease which occurs when pesticides came in contact with the body—which ultimately causes blisters as well. About 48.7% of the respondents reported that they had been through severe sneezing after application of the pesticides. This might be due to the fact that while spraying the pesticides contaminates air which in return when inhaled inside create sneezing problems.
Cough was reported by 34.1% of the respondents whereas stomach ache was reported by 23.2%. Majority of them were those who used to eat and drink while spraying or didn‘t wash their hands properly after the application of pesticides. Nausea was reported by 43.2% of the respondents. This is most common that almost every second drug and chemical create the problem of DVN i.e. Diarrhea Vomiting and Nausea. Though vomiting was not reported by any of the respondents during the study but diarrhea (35.9%) and nausea (43.2%) was reported by them. Similarly, dizziness was reported by the 24.7% of the respondents whereas feeling weak was reported by 38.5%. About 26.8% of the respondents reported that they had been through the problem of difficulty in seeing whereas eye irritation was reported by majority (63.5%) of the respondents. This might be due to the fact that though some of the respondents didn‘t cover their eyes while spraying and those who cover their eyes while spraying didn‘t cover their eye while mixing of pesticides. Thus due to fumes of the pesticides they also had been through the problem of eye irritation (Table 4.20).
Fever was reported by half (50.3%) of the respondents whereas insomnia was reported by 24.7% of the respondents. Similarly, chest pain was reported by the 25.5% of the respondents whereas blisters were reported by the overwhelming majority (60.9%). Catarrh
99 was reported by 23.4%, body pain was reported by the 34.4% of the respondents. Furthermore, burning sensation was reported by 77.3% of the respondents (Table 4.20). From the instant results it can be concluded that majority of the respondents had been through such type of diseases which were directly related with inhalation of pesticides fumes or mist or when these came in contact with the body.
Our results are in similarity with that of Manyilizu et al. (2017) who also reported that majority of the respondents had been through diarrhea, burning sensation, itching, eye irritation, dizziness, and chest pain whereas, our results are in contrast with that of the diseases reported by them i.e. forgetfulness and vomiting which was not reported by any respondent in our study. The reason might be due to some of the precautionary measures which they adopted. Our results are also in conformity with that of Mengestie et al. (2017) who also reported eye irritation and shortness of breath as the most frequent self-reported poisoning cases.
100 Table 4.20 Self-Reported Symptoms of Pesticides Use Symptom UCs Yes No Bandkurai 66(17.2) 30(7.8) Khanmai 77(20.1) 19(4.9) Headache Baffa 76(19.8) 20(5.2) Baidara 81(21.1) 15(3.9) Total 300(78.1) 84(21.9) Bandkurai 38(9.9) 58(15.1) Khanmai 56(14.6) 40(10.4) Excessive sweating Baffa 38(9.9) 58(15.1) Baidara 19(4.9) 77(20.1) Total 151(39.3) 233(60.7) Bandkurai 61(15.9) 35(9.1) Khanmai 77(20.1) 19(4.9) Itching Baffa 68(17.7) 28(7.3) Baidara 81(21.1) 15(3.9) Total 287(74.7) 97(25.3) Bandkurai 38(9.9) 58(15.1) Khanmai 44(11.5) 52(13.5) Sneezing Baffa 56(14.6) 40(10.4) Baidara 49(12.8) 47(12.2) Total 187(48.7) 197(51.3) Bandkurai 39(10.2) 57(14.8) Khanmai 28(7.3) 68(17.7) Cough Baffa 30(7.8) 66(17.2) Baidara 34(8.9) 62(16.1) Total 131(34.1) 253(65.9) Bandkurai 22(5.7) 74(19.3) Stomach ach Khanmai 27(7.0) 69(18.0) Baffa 25(6.5) 71(18.5)
101 Baidara 15(3.9) 81(21.1) Total 89(23.2) 295(76.8) Bandkurai 41(10.7) 55(14.3) Khanmai 50(13.0) 46(12.0) Nausea Baffa 41(10.7) 55(14.3) Baidara 34(8.9) 62(16.1) Total 166(43.2) 218(56.8) Bandkurai 28(7.3) 68(17.7) Khanmai 27(7.0) 69(18.0) Dizziness Baffa 21(5.5) 75(19.5) Baidara 19(4.9) 77(20.1) Total 95(24.7) 289(75.3) Bandkurai 32(8.3) 64(16.7) Khanmai 54(14.1) 42(10.9) Feeling weak Baffa 44(11.5) 52(13.5) Baidara 18(4.7) 78(20.3) Total 148(38.5) 236(61.5) Bandkurai 38(9.9) 58(15.1) Khanmai 35(9.1) 61(15.9) Diarrhea Baffa 46(12.0) 50(13.0) Baidara 19(4.9) 77(20.1) Total 138(35.9) 246(64.1) Bandkurai 28(7.3) 68(17.7) Khanmai 27(7.0) 69(18.0) Difficulty in Seeing Baffa 29(7.6) 67(17.4) Baidara 19(4.9) 77(20.1) Total 103(26.8) 281(73.2) Bandkurai 53(13.8) 43(11.2) Eye irritation Khanmai 48(12.5) 48(12.5) Baffa 63(16.4) 33(8.6)
102 Baidara 80(20.8) 16(4.2) Total 244(63.5) 140(36.5) Bandkurai 33(8.6) 63(16.4) Khanmai 28(7.3) 68(17.7) Fatigue Baffa 29(7.6) 67(17.4) Baidara 20(5.2) 76(19.8) Total 110(28.6) 274(71.4) Bandkurai 69(18.0) 27(7.0) Khanmai 64(16.7) 32(8.3) Shortness of breath Baffa 74(19.3) 22(5.7) Baidara 55(14.3) 41(10.7) Total 262(68.2) 122(31.8) Bandkurai 38(9.9) 58(15.1) Khanmai 42(10.9) 54(14.1) Fever Baffa 58(15.1) 38(9.9) Baidara 55(14.3) 41(10.7) Total 193(50.3) 191(49.7) Bandkurai 17(4.4) 79(20.6) Khanmai 34(8.9) 62(16.1) Sleeplessness/insomnia Baffa 31(8.1) 65(16.9) Baidara 13(3.4) 83(21.6) Total 95(24.7) 289(75.3) Bandkurai 27(7.0) 69(18.0) Khanmai 25(6.5) 71(18.5) Chest pain Baffa 32(8.3) 64(16.7) Baidara 14(3.6) 82(21.4) Total 98(25.5) 286(74.5) Bandkurai 53(13.8) 43(11.2) Blisters Khanmai 60(15.6) 36(9.4) Baffa 65(16.9) 31(8.1)
103 Baidara 56(14.6) 40(10.4) Total 234(60.9) 150(39.1) Bandkurai 23(6.0) 73(19.0) Khanmai 27(7.0) 69(18.0) Catarrh Baffa 22(5.7) 74(19.3) Baidara 18(4.7) 78(20.3) Total 90(23.4) 294(76.6) Bandkurai 37(9.6) 59(15.4) Khanmai 31(8.1) 65(16.9) Body pain Baffa 30(7.8) 66(17.2) Baidara 34(8.9) 62(16.1) Total 132(34.4) 252(65.6) Bandkurai 77(20.1) 19(4.9) Khanmai 59(15.4) 37(9.6) Burning sensation Baffa 80(20.8) 16(4.2) Baidara 81(21.1) 15(3.9) Total 297(77.3) 87(22.7)
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
104 4.21 Heath and Environmental Hazards of Pesticides Use
Data presented in Table 4.21 show that majority (50.3%) of the respondents were of the view that pesticides use causes high damage to human health followed by the respondents who reported that pesticides cause low level damage to human health i.e. 15.6%. Similarly 31.8% of the respondents reported that pesticides also cause damage to animals‘ health with high level whereas, 41.9% reported it as low. They were of the view that whenever pesticides are applied in the field and any animal grazed on it, it causes severe damage to that particular animal health. About, 34.9% of the respondents reported that pesticides cause low damage to wildlife whereas, 34.1% of the respondents reported medium level damage to wildlife through pesticides.
Damage to water life was reported by majority (35.7%) of the respondents as low. This was due to the fact that the respondents never use these pesticides against water life whereas, 31.5% of the respondents reported that it cause medium level damage to water life bodies because whenever pesticides is applied through flooding technique it creates problem for water life in canalization or water channels. With the use of pesticides pollinators are been killed, was reported by 29.9% of the respondents as high whereas 26.6% reported it as low (Table 4.21). This was due to the fact that whenever the pesticides is applied in the field and when the pollinator came in that field got killed as the pesticides came in contact with them or they feed on that crop or insect which is being killed by pesticides.
Overwhelming majority (50.5%) and 48.2% of the respondents reported that they don‘t know whether the pesticides affect the soil fertility and damage useful organisms in soil or not. This might be due to the fact that they haven‘t the in depth knowledge about the chemical reactions in soil whenever pesticides are applied and it enters the soil or kill the useful organisms i.e. microbes etc. Accumulation of pesticides in food chain was reported by the majority (31.8%) as medium whereas, 29.9% of the respondents reported it as low. Similarly, pesticides usage causes resurgence of pest population after removing natural enemies was reported by majority (31.8%) of the respondents as low. Air contamination with use of pesticides was reported by majority (37.8%) of the respondents as low (Table
105 4.21). This might be due to the fact that they were of the view that pesticides loose its effect from 4 to 10 days therefore they reported it as low level of damage to the environment.
Our results are in contrast with that of Mengistie et al. (2017) who reported that majority of the respondents narrated that pesticides cause damage to human health, animal health and water bodies. Our results are in conformity with that of Jansen and Harmsen (2011) and Teklu et al. (2015) who reported that the environmental impacts of pesticides are not well understood by farmers. Al-Zaidi et al. (2011) also reported that majority of the respondents had low level of knowledge regarding the pesticides hazard effect on health and environment i.e. affect soil fertility, affect soil organism and air contamination.
106 Table 4. 21 Distribution of the Respondents Regarding Knowledge about the Health and Environmental Hazards of Pesticides Hazards UCs Don’t Know Low Medium High Bandkurai 7(1.8) 14(3.6) 23(6) 52(13.5) Khanmai 23(6) 32(8.3) 6(1.6) 35(9.1) Cause damage to Baffa 11(2.9) 12(3.1) 29(7.6) 44(11.5) human health Baidara 4(1) 2(0.5) 28(7.3) 62(16.1) Total 45(11.7) 60(15.6) 86(22.4) 193(50.3) Bandkurai 9(2.3) 49(12.8) 21(5.5) 17(4.4) Khanmai 13(3.4) 55(14.3) 4(1) 24(6.2) Cause damage to Baffa 6(1.6) 33(8.6) 14(3.6) 43(11.2) animal health Baidara 17(4.4) 24(6.2) 17(4.4) 38(9.9) Total 45(11.7) 161(41.9) 56(14.6) 122(31.8) Bandkurai 4(1) 46(12) 29(7.6) 17(4.4) Khanmai 3(0.8) 39(10.2) 27(7) 27(7) Cause damage to Baffa 6(1.6) 22(5.7) 43(11.2) 25(6.5) wildlife Baidara 20(5.2) 27(7) 32(8.3) 17(4.4) Total 33(8.6) 134(34.9) 131(34.1) 86(22.4) Bandkurai 9(2.3) 51(13.3) 19(4.9) 17(4.4) Khanmai 6(1.6) 39(10.2) 24(6.2) 27(7) Cause damage to Baffa 6(1.6) 22(5.7) 43(11.2) 25(6.5) water life Baidara 14(3.6) 25(6.5) 35(9.1) 22(5.7) Total 35(9.1) 137(35.7) 121(31.5) 91(23.7) Bandkurai 15(3.9) 39(10.2) 19(4.9) 23(6) Khanmai 22(5.7) 24(6.2) 26(6.8) 24(6.2) Kills pollinators Baffa 17(4.4) 11(2.9) 30(7.8) 38(9.9) Baidara 16(4.2) 28(7.3) 22(5.7) 30(7.8) Total 70(18.2) 102(26.6) 97(25.3) 115(29.9) Bandkurai 73(19) 10(2.6) 5(1.3) 8(2.1) Effects soil Khanmai 52(13.5) 18(4.7) 10(2.6) 16(4.2) fertility Baffa 40(10.4) 18(4.7) 16(4.2) 22(5.7)
107 Baidara 29(7.6) 43(11.2) 11(2.9%) 13(3.4) Total 194(50.5) 89(23.2) 42(10.9%) 59(15.4) Bandkurai 59(15.4) 23(6.0) 9(2.3%) 5(1.3) Damage the Khanmai 50(13) 19(4.9) 11(2.9%) 16(4.2) useful organisms Baffa 44(11.5) 17(4.4) 10(2.6%) 25(6.5) in soil Baidara 32(8.3) 26(6.8) 23(6.0%) 15(3.9) Total 185(48.2) 85(22.1) 53(13.8%) 61(15.9) Bandkurai 23(6) 25(6.5) 40(10.4%) 8(2.1) Khanmai 27(7) 37(9.6) 16(4.2%) 16(4.2) Accumulate in Baffa 17(4.4) 35(9.1) 19(4.9%) 25(6.5) food chain Baidara 16(4.2) 18(4.7) 47(12.2%) 15(3.9) Total 83(21.6) 115(29.9) 122(31.8%) 64(16.7) Cause Bandkurai 18(4.7) 50(13) 20(5.2%) 8(2.1) resurgence of Khanmai 40(10.4) 28(7.3) 12(3.1%) 16(4.2) pest population Baffa 26(6.8) 26(6.8) 19(4.9%) 25(6.5) after removing Baidara 16(4.2) 18(4.7) 47(12.2%) 15(3.9) natural enemies. Total 100(26.0) 122(31.8) 98(25.5%) 64(16.7) Bandkurai 22(5.7) 51(13.3) 15(3.9%) 8(2.1) Khanmai 43(11.2) 25(6.5) 12(3.1%) 16(4.2) Cause air Baffa 26(6.8) 31(8.1) 14(3.6%) 25(6.5) contamination Baidara 16(4.2) 38(9.9) 22(5.7%) 20(5.2) Total 107(27.9) 145(37.8) 63(16.4%) 69(18.0) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
108 4.22 Disposal of Leftover Pesticides
There are only a few environmentally safe ways of disposing the leftover or unwanted pesticides. Leftover solutions of pesticides must be disposed off with minimal damage to the environment. In order to know the exact situation of the respondents i.e. what they did with the left over pesticides they were asked about the disposal of leftover pesticides and their responses are presented in Table 4.22.
Table 4.22 Disposal of Left over Pesticides Disposal of Left over pesticides Total
In In solid UCs In the canalization/water Waste Re-Spray Field channels Disposal Bandkurai 18(4.7) 21(5.5) 14(3.6) 43(11.2) 96(25)
Khanmai 28(7.3) 4(1.0) 27(7.0) 37(9.6) 96(25)
Baffa 26(6.8) 8(2.1) 31(8.1) 31(8.1) 96(25)
Baidara 17(4.4) 11(2.9) 15(3.9) 53(13.8) 96(25)
Total 89(23.2) 44(11.5) 87(22.7) 164(42.7) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data reported in Table 4.22 depict that majority (42.7%) of the respondents re-spray the leftover pesticides either in the same crop or in the upcoming season. Among them majority was from Baidara UC i.e. 13.8% followed by the respondents from Bandkurai UC i.e. 11.2%. Similarly, 23.2% of the respondents were disposing the leftover pesticides in the field followed by the respondents who reported that they dispose the left over pesticides in solid waste. About, 11.5% of the respondents reported that they dispose the pesticides in canalization/water channels.
It can be concluded that this can potentially pollute the water bodies which are sources of livelihood for human communities and support varied animals and plants life as also reported by Ntow et al. (2006). The health risks associated with pesticide contamination of
109 fish from the Densu River Basin in Ghana have also been reported by Fianko et al. (2011). Moreover, the practice of holding unused pesticides in storage for another pest control cycle presents unnecessary risks of damage to containers and represents an unproductive investment of operating funds. The best solution for storage of leftover pesticide materials is to buy only what is needed. This will help greatly to reduce environmental and personal injury risks.
4.23 Judicious Use of Pesticides
Judicious use of pesticides can play a best role in minimizing and avoiding the misuse of pesticides. This can create an attitude of not totally dependent on the pesticides solely which is harmful both to the health and environmental factors. The judicious use of pesticides can be applying pesticides at ETL level which will result in optimum use of pesticides. Similarly application of registered pesticides, right dose and application time etc. can also serve in judicious use of pesticides. The respondents were probed into the matter and their responses are presented in Table 4. 23.
110 Table 4.23 Distribution of Respondents Regarding Knowledge about Judicious Use of Pesticides Particulars UCs Yes No Bandkurai 39(10.2) 57(14.8) Khanmai 21(5.5) 75(19.5) Applying chemical at Baffa 49(12.8) 47(12.2) Economic Threshold Level Baidara 41(10.7) 55(14.3) Total 150(39.1) 234(60.9) Bandkurai 42(10.9) 54(14.1) Knowledge about the Khanmai 23(6) 73(19.0) compatibility of chemicals Baffa 51(13.3) 45(11.7) with natural enemies Baidara 56(14.6) 40(10.4) Total 172(44.8) 212(55.2) Bandkurai 39(10.2) 57(14.8) Khanmai 21(5.5) 75(19.5) Recommended doze Baffa 49(12.8) 47(12.2) Baidara 49(12.8) 47(12.2) Total 158(41.1) 226(58.9) Bandkurai 67(17.4) 29(7.6) Khanmai 80(20.8) 16(4.2) Right time of application Baffa 82(21.4) 14(3.6) Baidara 58(15.1) 38(9.9) Total 287(74.7) 97(25.3) Bandkurai 91(23.7) 5(1.3) Khanmai 93(24.2) 3(0.8) Proper application Baffa 90(23.4) 6(1.6) technology Baidara 83(21.6) 13(3.4) Total 357(93) 27(7) Bandkurai 45(11.7) 51(13.3) Use of soft insecticide Khanmai 68(17.7) 28(7.3) Baffa 45(11.7) 51(13.3)
111 Baidara 21(5.5) 75(19.5) Total 179(46.6) 205(53.4) Bandkurai 76(19.8) 20(5.2) Khanmai 77(20.1) 19(4.9) Integration of pesticides Baffa 70(18.2) 26(6.8) with IPM techniques Baidara 56(14.6) 40(10.4) Total 279(72.7) 105(27.3) (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data regarding judicious use of pesticides is presented in Table 4.23. It was found that majority (60.9%) of the respondents had no information about the judicious use of pesticides by applying chemicals at ETL. Similarly knowledge about the compatibility of chemicals with natural enemies was reported by 44.8% of the respondents as yes whereas, 55.2% of the respondents had no knowledge about the compatibility of chemicals with natural enemies. Knowledge about the recommended dose was not known to majority (58.9%) of the respondents. In this connection they also reported that they take help from pesticides dealer and agriculture extension worker or fellow farmers. Whereas, they also reported that they are using high dose than the recommended because with the recommended dose we were unable to control the pest. Applying the pesticides at right time was reported by majority (74.7%) of the respondents. This might be due to the fact that they also reported that they took help from pesticides dealer and agriculture extension worker regarding when to spray. Therefore, they were practicing the right time of application of pesticides on their crops/fruits/vegetables.
Proper technology in application of pesticides also matters in judicious use of pesticides because without proper technology there are high chances of misuse of pesticides. Therefore, majority (93%) of the respondents reported that they are using proper technology for applying pesticides. This might be due to the fact that majority of the respondents had a greater experience in applying pesticides therefore, in order to save time, money and labor costs they use proper application technologies. Using soft insecticides was reported by the 46.6% of the respondents whereas, 53.4% of the respondents were not on the view to use soft pesticides use practices. This was because of the fact that they were
112 not satisfied with using soft pesticides thus not utilizing soft pesticides. Integration of pesticides with integrated pest management was reported by majority (72.7%) of the respondents (Table 4.23).
4.24 Knowledge about the Alternative Approaches
Shifting from high use of pesticides to minimum it is important to switch to alternate cropping systems. One of the most known cropping system is organic farming which the production of food without the use of pesticides and fertilizers principles. It is generally said that without the use of fertilizers and pesticides the production might be less but the production will have good qualitative attributes for human beings. The same way respondents were probed about the alternative approaches which they know to the synthetic pesticides i.e. bio-pesticides, using crop mixtures, crop rotation, using trap crops, light traps etc. Therefore, the respondents were investigated regarding the alternative techniques and their responses are presented in Tables 4.24.1-18.
Data regarding use of bio-pesticides as an alternative technique to synthetic pesticides were collected and presented in Table 4.24.1. It was found that majority (37.5%) of the respondents reported knowledge about the use of bio-pesticides as very low followed by the respondents i.e. 31.2% who reported low whereas, only 11.2% and 8.9% of the respondents reported it as high and very high. Similarly knowledge about the organic farming was reported by majority (33.3%) as medium whereas, 27% of the respondents reported low (Table 4.24.2). Knowledge about the crop rotation as alternative technique to cope with the pests problems was reported by majority (34.1%) as medium followed by the respondents i.e. 21.6% who reported it as high (Table 4.24.3).
113 Table 4.24.1Distribution of Respondents Regarding Using Bio-Pesticides Scale UCs Total Very Low Low Medium High Very High Bandkurai 34(8.9) 26(6.8) 21(5.5) 8(2.1) 7(1.8) 96(25)
Khanmai 48(12.5) 17(4.4) 4(1.0) 16(4.2) 11(2.9) 96(25)
Baffa 41(10.7) 25(6.5) 11(2.9) 15(3.9) 4(1) 96(25)
Baidara 21(5.5) 52(13.5) 7(1.8) 4(1.0) 12(3.1) 96(25)
Total 144(37.5) 120(31.2) 43(11.2) 43(11.2) 34(8.9) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.2 Distribution of Respondents Regarding Doing Organic Farming UCs Scale
Very Low Low Medium High Very high Total Bandkurai 28(7.3) 29(7.6) 20(5.2) 15(3.9) 4(1) 96(25)
Khanmai 22(5.7) 29(7.6) 26(6.8) 6(1.6) 13(3.4) 96(25)
Baffa 14(3.6) 26(6.8) 41(10.7) 4(1) 11(2.9) 96(25)
Baidara 28(7.3) 21(5.5) 41(10.7) 2(.5) 4(1) 96(25)
Total 92(24.0) 105(27.3) 128(33.3) 27(7.0) 32(8.3) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.3 Distribution of Respondents Regarding Doing Crop Rotation Scale UCs Total Very Low Low Medium High Very high Bandkurai 10(2.6) 5(1.3) 34(8.9) 27(7.0) 20(5.2) 96(25)
Khanmai 9(2.3) 3(.8) 32(8.3) 24(6.2) 28(7.3) 96(25)
Baffa 5(1.3) 18(4.7) 36(9.4) 17(4.4) 20(5.2) 96(25)
Baidara 30(7.8) 16(4.2) 29(7.6) 15(3.9) 6(1.6) 96(25)
Total 54(14.1) 42(10.9) 131(34.1) 83(21.6) 74(19.3) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
114 Crop mixtures were reported by majority (32.3%) as medium whereas, 28.6% of the respondents reported it as low (Table 4.24.4). Knowledge about the trap crops was reported by the majority (58.1%) as very low followed by the respondents i.e. 19.8% who reported it as low (Table 4.24.5). Knowledge about using traps e.g. pheromone traps were reported by the majority (34.4%) of the respondents as very low and majority of them were those who had orchards. In case of the fruit fly attack they usually use pheromone traps (Table 4.24.6) in which Methayl Euginol and Deptrix is used with the formulae of 10:5:85 i.e. 10% Methayl Euginol, 5% Deptrix, 85% water.
Table 4. 24.4 Distribution of Respondents Regarding Using Crop mixtures Scale UCs Total Very Low Low Medium High Very High Bandkurai 10 (2.6) 27(7) 27(7) 15(3.9) 17(4.4) 96(25)
Khanmai 6(1.6) 23(6) 38(9.9) 5(1.3) 24(6.2) 96(25)
Baffa 11(2.9) 32(8.3) 38(9.9) 4(1) 11(2.9) 96(25)
Baidara 18(4.7) 28(7.3) 21(5.5) 13(3.4) 16(4.2) 96(25)
Total 45(11.7) 110(28.6) 124(32.3) 37(9.6) 68(17.7) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.5 Distribution of Respondents Regarding Using Trap Crops Scale UCs Total Very Low Low Medium High Bandkurai 57(14.8) 17(4.4) 18(4.7) 4(1) 96(25)
Khanmai 51(13.3) 15(3.9) 27(7) 3(.8) 96(25)
Baffa 54(14.1) 27(7) 11(2.9) 4(1) 96(25)
Baidara 61(15.9) 17(4.4) 9(2.3) 9(2.3) 96(25)
Total 223(58.1) 76(19.8) 65(16.9) 20(5.2) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
115 Table 4. 24.6 Distribution of Respondents Regarding Using Pheromone Traps Scale UCs Total Very Low Low Medium High Very High Bandkurai 40(10.4) 17(4.4) 9(2.3) 22(5.7) 8(2.1) 96(25)
Khanmai 23(6) 31(8.1) 25(6.5) 10(2.6) 7(1.8) 96(25)
Baffa 27(7) 22(5.7) 26(6.8) 9(2.3) 12(3.1) 96(25)
Baidara 42(10.9) 11(2.9) 13(3.4) 15(3.9) 15(3.9) 96(25)
Total 132(34.4) 81(21.1) 73(19) 56(14.6) 42(10.9) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Similarly knowledge about the light traps was reported by majority (63.3%) of the respondents as very low followed by the 23% of the respondents who reported knowledge about the light traps as very low (Table 4.24.7). Knowledge about the hot and cold treatment was reported by the overwhelming majority (68.5%) of the respondents as very low whereas 21.4% of the respondents reported it as low (Table 4.24.8). Knowledge about the insect resistant variety as alternative technique to the synthetic pesticides use was reported by majority (26.6%) of the respondents as medium followed by the respondents i.e. 22.7% of the respondents who reported it as low. Only 23.4% and 13.5% of the respondents reported knowledge about the insect resistant variety as high and very high respectively (Table 4.24.9).
Table 4. 24.7 Distribution of Respondents Regarding Using Light Traps Scale UCs Total Very Low Low Medium High Very High Bandkurai 62(16.1) 19(4.9) 11(2.9) 4(1) -- 96(25) Khanmai 63(16.4) 25(6.5) 5(1.3) 3(0.8) -- 96(25) Baffa 52(13.5) 29(7.6) 5(1.3) 10(2.6) -- 96(25) Baidara 66(17.2) 17(4.4) 0(0) 13(3.4) -- 96(25) Total 243(63.3) 90(23.4) 21(5.5) 30(7.8) -- 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
116 Table 4. 24.8 Distribution of Respondents Regarding Hot and Cold Treatment Scale UCs Total Very Low Low Medium High Very High Bandkurai 56(14.6) 32(8.3) -- 8(2.1) -- 96(25)
Khanmai 42(10.9) 38(9.9) -- 16(4.2) -- 96(25)
Baffa 70(18.2) 11(2.9) -- 15(3.9) -- 96(25)
Baidara 95(24.7) 1(0.3) -- 0(0) -- 96(25)
Total 263(68.5) 82(21.4) -- 39(10.2) -- 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.9 Distribution of Respondents Regarding Using Insect Resistant variety Scale UCs Total Very Low Low Medium High Very High Bandkurai 14(3.6) 4(1) 32(8.3) 28(7.3) 18(4.7) 96(25)
Khanmai 22(5.7) 15(3.9) 25(6.5) 20(5.2) 14(3.6) 96(25)
Baffa 13(3.4) 26(6.8) 17(4.4) 29(7.6) 11(2.9) 96(25)
Baidara 4(1) 42(10.9) 28(7.3) 13(3.4) 9(2.3) 96(25)
Total 53(13.8) 87(22.7) 102(26.6) 90(23.4) 52(13.5) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.24.10 depict that majority (34.4%) of the respondents reported knowledge about weeds free seed as medium followed by 27.3% of the respondents who reported as high. Only 20.1% of the respondents had reported high on Likert Scale regarding knowledge about the weeds free seed (Table 4.24.10). This might be due to the fact that sampled respondents had a good farming experience and thus were able to identify the weeds free seed. This also showed that in the instant study the use of weedicides were reported very less by majority of them. Similarly, knowledge about the removal of crop residues after its harvest as alternative technique to minimize the pest population was reported by the majority (31%) of the respondents as it as high followed by the 26.8% of the respondents as medium. Only 19.8% of the respondents reported it as very high (Table
117 4.24.11). Parasites are organisms that live at the expense of another organism i.e. Habrobracon hebetor is a minute wasp of the family ―Braconidae‖ that is an ectoparasitoid of several species of moth caterpillars. Knowledge about using parasite for controlling pest population was reported by the majority (59.9%) of the respondents as very low whereas only 4.4% of the respondents reported it as high (4.24.12). Moreover, none of the respondents practically used parasite. Table 4. 24.10 Distribution of Respondents Regarding Using Weed Free Seed Scale UCs Total Very Low Low Medium High Very High Bandkurai 6(1.6) 5(1.3) 23(6) 43(11.2) 19(4.9) 96(25)
Khanmai 9(2.3) 3(.8) 44(11.5) 26(6.8) 14(3.6) 96(25)
Baffa 11(2.9) 5(1.3) 28(7.3) 23(6) 29(7.6) 96(25)
Baidara 4(1) 27(7) 37(9.6) 13(3.4) 15(3.9) 96(25)
Total 30(7.8) 40(10.4) 132(34.4) 105(27.3) 77(20.1) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.11 Distribution of Respondents Regarding Crop Residual Removal Scale UCs Very Low Low Medium High Very High Total Bandkurai 13(3.4) 9(2.3) 20(5.2) 29(7.6) 25(6.5) 96(25)
Khanmai 12(3.1) 6(1.6) 26(6.8) 37(9.6) 15(3.9) 96(25)
Baffa 10(2.6) 5(1.3) 22(5.7) 38(9.9) 21(5.5) 96(25)
Baidara 5(1.3) 26(6.8) 35(9.1) 15(3.9) 15(3.9) 96(25)
Total 40(10.4) 46(12) 103(26.8) 119(31) 76(19.8) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
118 Table 4. 24.12 Distribution of Respondents Regarding Using Parasites Scale UCs Very Low Low Medium High Very High Total Bandkurai 47(12.2) 30(7.8) 15(3.9) 4(1.0) -- 96(25)
Khanmai 57(14.8) 24(6.2) 12(3.1) 3(0.8) -- 96(25)
Baffa 62(16.1) 26(6.8) 5(1.3) 3(0.8) -- 96(25)
Baidara 64(16.7) 15(3.9) 10(2.6) 7(1.8) -- 96(25)
Total 230(59.9) 95(24.7) 42(10.9) 17(4.4) -- 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
Data in Table 4.24.13 depict that majority (30.7%) of the respondents reported knowledge about avoiding imbalance dose of pesticides can minimize the use of synthetic pesticides. About 31% of the respondents report it as high and 13% as very high (Table 4.24.13). Similarly, spraying registered pesticides as alternative technique to minimize the hazardous effect was reported by majority (39.8%) of the respondents as high. Only 15.4% of the respondents reported it as very high (Table 4.24.14). Timely shallow tillage in order to minimize the pest population and so the use of synthetic pesticides was reported by majority (28.9%) of the respondents as high whereas only 19.3% of the respondents reported it as very high (4.32.15).
Table 4. 24.13 Distribution of Respondents Regarding Avoiding Imbalance Dose Scale UCs Very Low Low Medium High Very High Total Bandkurai 10(2.6) 16(4.2) 35(9.1) 28(7.3) 7(1.8) 96(25)
Khanmai 14(3.6) 4(1.0) 31(8.1) 24(6.2) 23(6) 96(25)
Baffa 12(3.1) 5(1.3) 30(7.8) 38(9.9) 11(2.9) 96(25)
Baidara 20(5.2) 26(6.8) 14(3.6) 28(7.3) 8(2.1) 96(25)
Total 56(14.6) 51(13.3) 110(28.6) 118(30.7) 49(12.8) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
119 Table 4. 24.14 Distribution of Respondents Regarding Spraying Registered Pesticides Scale UCs Total Very Low Low Medium High Very High Bandkurai 10(2.6) 5(1.3) 25(6.5) 46(12.0) 10(2.6) 96(25)
Khanmai 29(7.6) 3(.8) 27(7) 23(6) 14(3.6) 96(25)
Baffa 13(3.4) 6(1.6) 21(5.5) 36(9.4) 20(5.2) 96(25)
Baidara 5(1.3) 13(3.4) 15(3.9) 48(12.5) 15(3.9) 96(25)
Total 57(14.8) 27(7) 88(22.9) 153(39.8) 59(15.4) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018 Table 4. 24.15 Distribution of Respondents Regarding Timely Tillage Scale UCs Total Very Low Low Medium High Very High Bandkurai 10(2.6) 9(2.3) 26(6.8) 27(7) 24(6.2) 96(25)
Khanmai 9(2.3) 18(4.7) 30(7.8) 25(6.5) 14(3.6) 96(25)
Baffa 6(1.6) 25(6.5) 17(4.4) 27(7) 21(5.5) 96(25)
Baidara 5(1.3) 16(4.2) 38(9.9) 22(5.7) 15(3.9) 96(25)
Total 30(7.8) 68(17.7) 111(28.9) 101(26.3) 74(19.3) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
Timely sowing of crop can reduces the pest pressure and can help to minimize the pesticides application. Data regarding this important variable were collected from the respondents and presented in Table 4.24.16. It was found that majority (29.7%) of the respondents were of the view that timely sowing can minimize the pest population whereas, only 24.5% and 21.6% of the respondents reported it as high and very high respectively (Table 4.24.16). Similarly, using parasitoids instead of pesticides is also an important step to minimize the use of pesticides. It was found that majority of the respondents i.e. 61.7% were not in the favor and were not aware of the use of parasitoids in order to control pest. This was because of the reason that farmers demanded the quick control of pest whereas, using parasitoids the speed of controlling is comparatively low as by the pesticides (Table 4.24.17).
120 Insecticidal soaps provide a relatively safe and cost-effective pest-control option. In general, insecticidal soaps are most effective against small, soft-bodied insects and other arthropods. Due to the importance of using soap as pesticides, the important variable was included in the study and asked from the respondents. The data regarding this important factor are presented in Table 4.24.18. It was found that majority (62.5%) of the respondents reported it as very low whereas, only 14.6% and 2.6% reported it as high and very high (Table 4.24.18). They were of the view that pest population is so resistant that soap is not efficient enough to control pests.
Table 4. 24.16 Distribution of Respondents Regarding Sowing Time to Reduce Pest Pressure Scale UCs Total Very Low Low Medium High Very High Bandkurai 13(3.4) 5(1.3) 24(6.2) 35(9.1) 19(4.9) 96(25)
Khanmai 15(3.9) 3(.8) 33(8.6) 20(5.2) 25(6.5) 96(25)
Baffa 11(2.9) 11(2.9) 32(8.3) 24(6.2) 18(4.7) 96(25)
Baidara 17(4.4) 18(4.7) 25(6.5) 15(3.9) 21(5.5) 96(25)
Total 56(14.6) 37(9.6) 114(29.7) 94(24.5) 83(21.6) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
Table 4. 24.17 Distribution of Respondents Regarding Parasitoids Scale UCs Total Very Low Low Medium High Bandkurai 44(11.5) 33(8.6) 15(3.9) 4(1) 96(25)
Khanmai 52(13.5) 27(7.0) 14(3.6) 3(0.8) 96(25)
Baffa 61(15.9) 21(5.5) 11(2.9) 3(0.8) 96(25)
Baidara 80(20.8) 16(4.2) 0(0) 0(0) 96(25)
Total 237(61.7) 97(25.3) 40(10.4) 10(2.6) 384 (Figures in Parenthesis are percentages) Source: Field Survey, 2018
121 Table 4. 24.18 Distribution of Respondents Regarding Using Soap Scale UCs Very Low Low Medium High Total Bandkurai 56(14.6) 18(4.7) 18(4.7) 4(1) 96(25)
Khanmai 42(10.9) 24(6.2) 27(7) 3(0.8) 96(25)
Baffa 61(15.9) 21(5.5) 11(2.9) 3(0.8) 96(25)
Baidara 81(21.1) 15(3.9) 0(0) 0(0) 96(25)
Total 240(62.5) 78(20.3) 56(14.6) 10(2.6) 384
(Figures in Parenthesis are percentages) Source: Field Survey, 2018
4.25 Training Provided by Agriculture Extension Department
Pesticides are a complex, toxic and hazardous technology and require many information and techniques to use. Specifically, smallholder farmers need adequate technical support from state and/or non-state actors to apply pesticides correctly. Pesticides can be dangerous if improperly applied, especially to those people who work with pesticides. Therefore, the respondents were asked about the trainings provided by Agriculture Extension Department. Data regarding trainings given to farmers by Agriculture Extension Department were collected from the farming community and presented in Fig. 4.1. It was found that majority (53%) respondents reported that they obtained training from Agriculture Extension Department. Whereas, about 46.6% of the respondents reported that they haven‘t got any training from the Agriculture Extension Department. Moreover, they also reported that Agriculture Extension Department usually focuses on the progressive growers.
It can be concluded from the instant results that highly dependence on the pesticides by the untrained farmers can significantly increase the health and environmental hazards. This might be due to the fact that if they are not properly trained in handling the pesticides there will always be high chances of miss-use. Our results are in conformity with that of Sefa et al. (2015) and Mengestie et al. (2017) who also reported that majority of the respondents didn‘t get any training from the state side. Similar situation was also reported by the
122 (Aslam et al., 2007) in Pakistan, that the level of knowledge of farmers on applying pesticides was shown to be less good; demonstrating the need for training the farmers. Moreover, Damalas and Koutroubas (2017) also argued that previous trainings has the association with increased levels of farmers‘ knowledge of pesticides and beliefs about pesticide hazard control.
123
70
63 60 57 51 52
50
40 45 39 44 No 33
30 Yes No ofRespondents No 20
10
0 Bandkurai Khanmai Baffa Baidara
179(46.6%) 205 (53.4%)
No Yes
Fig 4.1 Distribution of Respondents Regarding Training Provided by Agriculture
Extension Department Source: Field Survey, 2018
124 4.26 How to Use Pesticides
As already discussed in the previous portion of this study that pesticides itself is not dangerous but depends on our selection, handling and usage. Therefore, in this regard data regarding how to use pesticides techniques learned from the Agriculture Extension Department were collected and presented in Fig. 4.2. Majority, (54.4%) of the respondents reported that they haven‘t learn from the Agriculture Extension Department that how to use pesticides whereas 45.6% of the respondents reported that they have learned how to use pesticides from Agriculture Extension Department. During informal discussion they reported that whenever they go to the Agriculture Extension Department office of their locality they usually learn some new techniques. Our results are slightly in contradiction with that of Gwivaha (2015) who reported in their study that only 35% of the respondents were trained in the skill of how to use pesticides which might be due to the change in the study area and behavior of the sample respondents.
4.27 Health Safety
Health safety is of supreme importance while doing spraying practices. The pesticides if not handled properly may create huge health issues both the instant user and the end consumer. Therefore, to find out whether the Agriculture Extension Department have provided any information to the farming community regarding the health safety while using pesticides or not and their responses are presented in Fig. 4.3. Data illustrated in Fig. 4.3 show that majority (54.9%) of the respondents reported that they didn‘t learn health safety from Agriculture Extension Department regarding pesticides use. Similarly, only 45.1% of the respondents reported that they have learnt health safety while using pesticides from Agriculture Extension Department. During informal discussion some of the respondents reported that health safety equipment i.e. goggles, glasses etc. was being arranged by Agriculture Extension Department when demanded. Similarly, Sharifzadeh et al. (2018) reported that those farmers who experienced health risks related to working with pesticides (mean 2.0 vs. 1.77), farmers who used protection when spraying (mean 2.58 vs. 1.87), and farmers who knew about natural enemies of pests (mean 2.11 vs. 1.85) tended to consider environmental criteria when selecting and using pesticides. Thus it can be concluded that for the safe and appropriate use of pesticides by the farming community
125 they may be trained in the health safety and harmful environmental effects of improper pesticides use.
70
63 60 57 52
50 51
45 44 40 39 No 33
30 Yes No ofRespondents No 20
10
0 Bandkurai Khanmai Baffa Baidara
175(45.6) 209(54.4)
No Yes
Fig. 4.2. Distribution of respondents regarding how to use pesticides
Source: Field Survey, 2018
126
70
60 60 49 47 55
50
40 47 49 41 N0
30 36 Yes No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
211(54.9) 173(45.1)
N0 Yes
Fig 4.3 Distribution of respondents regarding learning safety measures from agriculture extension department Source: Field Survey, 2018
127 4.28 Integrated Pest Management
Global environmental policy recently emphasized on reduced chemical application agricultural production process because excessive usage of chemical fertilizers and pesticides are documented one of the major environmental pollution resources. There are many researches in agriculture which have showed green revolution input for example chemical fertilizers and chemical pesticides can threat animal and humans‘ health. Therefore, research institutes working on new agricultural technology deeply pay attention on sustainability of technology (Chizari et al., 2000). IPM, biological fertilizers are selected as sustainable technologies instead of chemical pesticides in agriculture (Bartlett, 2005). Due to this fact the respondents were investigated regarding IPM techniques been shared with you by Agriculture Extension Department or not and their responses are presented in Fig. 4.4 It was found that majority (52.3%) of the respondents reported that they have not learned IPM techniques from Agriculture Extension Department whereas, 47.7% of the respondents reported that they have learned IPM techniques from Agriculture Extension Department. Our results are in contrast with that of Mohammadrezaei and Hayati (2015) who reported that Agriculture Extension had the main role in transferring the IPM techniques among the growers of the locality.
4.29 Trained in Disposal of Pesticides and Empty Bottles
Disposing the leftover pesticides and the empty canes or packing also has its important due place same as the precautions to be taken during the application of pesticides. This is because of the fact that leftover pesticides re-spray increases the number of sprays per seasons of the crops and its unscientific disposal may have environmental issues. Therefore, data regarding disposing techniques learned from the Agriculture Extension Department was collected and was presented in Fig. 4.5. It was found that overwhelming majority (65.6%) of the respondents reported that they have not learned disposal techniques of pesticides. Similarly, only 35.4% of the respondents reported that they have learned the disposal techniques of the pesticides. This depicts that the Agriculture Extension Department is not fully cautious about the health and environmental effects of pesticides. Therefore, they didn‘t communicate properly how to dispose the pesticides and
128 empty bottles. Moreover, it might also be due to the fact that the respondents had never strong communication with the extension department and thus they reported that they never taught us how to dispose the empty bottles and pesticides.
60 57 52 55
50 51
40 45 41 39 44
30 No Yes
20 No.of Respondents
10
0 Bandkurai Khanmai Baffa Baidara
183(47.7) 201(52.3)
No Yes
Fig 4.4 Distribution of respondents regarding learning about integrated pest management from agriulture extension department Source: Field Survey, 2018
129 80 75
70 66
60 56
55 50
40 41 No 40 Yes
30 No.of Respondents 30 20 21 10
0 Bandkurai Khanmai Baffa Baidara
132(35.4) 252(65.6)
No Yes
Fig 4.5 Distribution of respondents regarding trained in disposal of pesticides and empty bottles
Source: Field Survey, 2018
130 4.30 Application Technology
While using pesticides the right choice of application is also necessary because of the fact that if no proper application technology is used, there will always be chances of the misuse. e.g. if one wants to spray on tree so using PIR pumps etc. will not be suitable, here power sprayer will suit very much because the PIR pumps had not that much pressure so that the pesticides can be reached at the top of tree and is specifically developed for the said purpose. On the other hand power sprayer has the capacity to build enough pressure so that the pesticides can reach easily at the top of tree. Therefore, the farmers were investigated regarding the application technology of pesticides taught to them by Agriculture Extension Department and their responses are presented in Fig. 4.6. It was found that majority (55.7%) of the respondents didn‘t learn application technology of the pesticides from the Agriculture Extension Department. Only 44.3% of the respondents reported that they have learned application technology from the Agriculture Extension Department.
4.31 Trained on Harmful Environment Effect
Data regarding learning about the environmental effect of the pesticides were gathered and presented in Fig. 4.7. It was found that majority (71.1%) of the respondents didn‘t learned anything regarding harmful environmental effect of pesticides. About 28.9% of the respondents reported that they have learned about harmful environmental effect of pesticides use from Agriculture Extension Department. The present results are in agreement with that of Sharifzadeh et al. (2018) who reported that those farmers who has a concept of pesticides hazards over those who thought pesticides has no hazardous effects. Therefore it is a good sign that the judicious use of the pesticide can be inculcated among farming community through awareness. By bringing awareness among the farming community about the harmful environmental effect of the pesticides use they will be in better position to select the pesticides before its purchase as criteria which can cause least damage to the environment.
131
70
60 58 57 52 55
50
40 44 41 No 38 39
30 Yes No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
170(44.3) 214(55.7)
No Yes
Fig. 4.6 Distribution of respondents regarding trained in application technology by agriculture extension department
Source: Field Survey, 2018
132
90 79 80
70 66 61 67
60
50 No 40 Yes
No.of Respondents 30 35 29 30 20
10 17
0 Bandkurai Khanmai Baffa Baidara
111(28.9) 273(71.1)
No Yes
Fig. 4.7 Distribution of respondents regarding trained in harmful enviromental effects
Source: Field Survey, 2018
133 4.32 Trained about the Symptoms and Treatment of Poison
As the pesticides are hazardous for health and there is always chance of any mishap regarding health issue of the applicator. Therefore, the applicator must have the basic knowledge about the instant effects/symptoms of pesticides on human health (acute poisoning) and its remedy. It is also worth mentioning that on most of the pesticide containers the symptoms and antidotes are mentioned for safety of the applicator in advance if anything bad happens while applying pesticides. Therefore, to know about the actual situation that whether any information shared by the Agriculture Extension Department or not regarding this important aspect and their responses are presented in Fig. 4.8. It was found that majority (72.7%) of the respondents didn‘t learn about the symptoms and treatment of the poisonous effects of the pesticides use from Agriculture Extension Department. Only 27.3% of the respondents reported that they have learnt about the symptoms and treatment of the poisonous effects of the pesticides use from Agriculture Extension Department.
4.33 Environmental and Health Hazards of Pesticides Use
Data regarding learning about the environmental hazards of the pesticides use are presented in Fig.4.9. It was found that majority (62.2%) of the respondents didn‘t learn about the environmental hazards of pesticides use whereas 31.8% of the respondents reported that they have learnt about the harmful environmental effects of heavy pesticides use from Agriculture Extension Department. Majority (38 respondents) were from Baffa UC who reported that they have learned about the health and environmental hazards of pesticides use from Agriculture Extension Department.
134
90 82 80 70 67
70
60 60
50 No 40 Yes 36
No.of Respondents 30 29 20 26
10 14
0 Bandkurai Khanmai Baffa Baidara
105(27.3)
279(72.7)
No Yes
Fig. 4.8 Distribution of respondents regarding trained about the symptoms and treatment of poison by agriculture extension department
Source: Field Survey, 2018
135
80 76
70 62 58 66
60
50
40 No 38 Yes 30
34 30 No.of Respondents 20 20 10
0 Bandkurai Khanmai Baffa Baidara
122(31.8) 262(62.2)
No Yes
Fig. 4.9 Distribution of respondents regarding environmental and health hazards of pesticides use
Source: Field Survey, 2018
136 4.34 Calibration of Pesticides
Misuse of pesticides always occurs at the time of calliberation of pesticides. The reason behind this is not proper weighing in respect of Soluble granules (SG) or Wetable powder (WP) or mls in case of Soluble liquids (SL), Suspension Concentrates (SC) etc. the farmers usually take a rough guess and make the solution for spray which beside giving stress to crop in case of high dose and chances of creating resistance by pest incase of low dose or no proper control of pest. Therefore, to know whether information was shared by Agriculture Extension Department that how to calliberate pesticides and their responces are presented in Fig. 4.10. It was found that majority (52.6%) of the respondents reported that they learned about the calliberation of pesticides from Agriculture Extension Department whereas, 47.4% of the respondents negate learning about the callibaration of pesticides from Agriculture Extension Department. Majority (52) respondents were from Baffa UC who reported that they learned calliberation from Agriculture Extension Department.
4.35 Pesticides Application Techniques
Learning pesticides techniques prior to application of pesticides is the core of safe pesticides application. If an individual does not know basics about how to apply pesticides then there are high chances of misuse, damage to crop, health and environment. Data regarding learning the application techniques of pesticides are illustrated in Fig. 4.11. It was found that majority (53.6%) of the respondents didn‘t learn the application techniques from the Agriculture Extension Department and mostly were from Khanmai UC. Similarly, 46.4% of the respondents reported that they had learned the pesticides application techniques from the Agriculture Extension Department and mostly were from Baffa UC.
137
60 57 52 56 51
50
40 45 44 40 39 30 No Yes
20 No.of Respondents
10
0 Bandkurai Khanmai Baffa Baidara
182(47.4) 202(52.6)
No Yes
Fig. 4.10 Distribution of respondents regarding learning about the calibration of pesticides
Source: Field Survey, 2018
138 60 57 52 55 50 50
44
40 46 41 39 30 No Yes
No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
178(46.4) 206(53.6)
No Yes
Fig. 4.11 Distribution of respondents regarding learning pesticides application techniques
Source: Field Survey, 2018
139 4.36 Safety Measures while Dealing with Pesticides
Data regarding learning about the safety measures while dealing with pesticides from Agriculture Extension Department are figured in Fig. 4.12. It was found that majority (55.5%) of the respondents didn‘t learn about the safety measures while using pesticides, from the Agriculture Extension Department whereas, 44.5% of the respondents were of the view that they have learned safety measures from the Agriculture Extension Department. Macfarlane et al. (2008) reported that training is likely to be an important intervention for reducing farmers‘ exposure to pesticides. Thus in light of the above definition it can be concluded that the safety training can play a significant role in minimizing the exposure to pesticides and improves farmers‘ safety.
4.37 Learning about Understanding Pesticides Label
Pesticide labels contain detailed instructions about the usage of product legally which must be followed in order to avoid mishaps. Data regarding learning about the understanding of the labels from the Agriculture Extension Department are presented in Fig. 4.13. It was found that majority (60.2%) of the respondents never learned about the understanding of labels from the Agriculture Extension Department. Only 39.8% of the respondents learned about the understanding of the labels of pesticides from Agriculture Extension Department.
140 70 62 60 57 51 49
50
47 40 45 39 No
30 34 Yes No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
171(44.5) 213(55.5)
No Yes
Fig. 4.12 Distribution of respondernts regarding learning the safety measures while dealing with pesticides
Source: Field Survey, 2018
141
80 71 70
60 53
51 56 50
40 No 45 43 40 Yes
30 No.Respondents of 20 25
10
0 Bandkurai Khanmai Baffa Baidara
231(60.2) 153(39.8)
No Yes
Fig. 4.13 Distribution of respondents regarding learning about the understanding pesticides labels from agriculture extension department
Source: Field Survey, 2018
142 4.38 Learning about the Biological Control of Pests
Data regarding learning about the biological control of pest from Agriculture Extension Department are presented in Fig. 4.14. It was found that majority (73.2%) of the respondents didn‘t learn about the biological control of the pests from Agriculture Extension Department whereas, only 26.8% of the respondents reported that they learned about biological control from Agriculture Extension Department. Those respondents who reported that they learn about biological control of pests from Agriculture Extension Department were of the view that we learn about the traps and the cards as recommended by the Department in some cases.
4.39 Learning about the Augmentative Measures from Agriculture Extension Department
The release of natural enemies (predators, parasites and pathogens) to control pests is a type of biological control called augmentation. This approach uses commercially available species that are applied in a timely manner to prevent population increases, or to suppress a pest population (Horne, 2007). Data regarding learning about the Augmentative Measures from Agriculture Extension Department are presented in Fig. 4.15. It was observed that majority (73.2%) of the respondents never learned about the Augmentative Measures from Agriculture Extension Department. Almost 27% of the respondents reported that they did learned Augmentative Measures from Agriculture Extension Department
143 90 80 80 76 67 70 58
60
50 No 40 Yes
No.of Respondents 30 38
29 20 20 10 16
0 Bandkurai Khanmai Baffa Baidara
103(26.8) 281(73.2)
No Yes
Fig. 4.14 Distribution of respondents regarding learning about the biological control of pests
Source: Field Survey, 2018
144 90 81 80 76
70 65
60 59
50 No 40 Yes 37
No.of Respondents 30 31 20 20
10 15
0 Bandkurai Khanmai Baffa Baidara
103(26.8) 281(73.2)
No Yes
Fig. 4.15 Disribution of respondents regarding learning about the augmentative
measures from agriculture extension department
Source: Field Survey, 2018
145 4.40 Field days Arranged about the Pesticides
In the field day the farmers from the same locality gathered and also shared their own experiences besides the teachings or promotion of new techniques by the Agriculture Extension Department. Data regarding field days arranged by Agriculture Extension Department on pesticides are presented in Fig. 4.16. Majority (68%) of the respondents negatively reported that extension department didn‘t arrange any field day regarding pesticides whereas, only 32% of the respondents reported that Agriculture Extension Department did arranged field days on pesticides.
4.41 Farmers Field School Approach used by Agriculture Extension Department
Farmer Field School (FFS) is a season-long training activity that occurs in the field. It is season-long so that it covers all the different developing stages of the plants/crops and their relevant management/control techniques. The training procedure is always learner- centered, participatory and relying on an experiential studying technique (FAO, 2000). Farmers Field School approach is a good approach which can be used to communicate the knowledge and practical techniques to the farming community regarding pesticides. Thus question was asked from the respondents where there were any FFS activities arranged by Agriculture Extension Department and their responses are presented in Fig. 4.17. It was found that majority (85.4%) of the respondents were of the view that Agriculture Extension Department never arranged any such activity whereas, 14.6% of the respondents reported that they have arranged such activities.
146
80 70 75 70 60 56
60
50
40 No 40 Yes
30 36 No.of Respondents 20 26 21
10
0 Bandkurai Khanmai Baffa Baidara
123(32)
261(68)
No
Yes
Fig. 4.16 Distribution of respondents regarding field days arranged about the pesticides by agriculture extension department
Source: Field Survey, 2018
147
100 90 90 84 87 80 67 70
60
50 No
40 Yes
No.of Respondents 30
20 29
10 6 9 12 0 Bandkurai Khanmai Baffa Baidara
56(14.6)
328(85.4)
No Yes
Fig. 4.17 Distribution of respondents regarding farmers field school approach used by agriculture extension department
Source: Field Survey, 2018
148 4.42 Monitoring by Agriculture Extension Department
It is also one of the main activity of Agriculture Extension Department to visit farmers‘ field in order to check their field regarding diseases, pests etc. and to provide on spot recommendations to them. This is because of the fact that to educate the farmers to learn about their everyday problems and learning how to solve the problems. In this regard they agriculture extension workers visit the farmers‘ field in order to bring change in their attitude and behavior and thus they are called change agents. Data regarding monitoring by the Agriculture Extension Department regarding pest prevalence and monitoring of the farmers field are presented in Fig. 4.18. It was found that majority (53.1%) of the respondents reported that Agriculture Extension Department never monitored our fields whereas 46.9% of the respondents reported that they monitor their fields regarding the pest prevalence and give recommendations.
4.43 Contacts by Farmers with Agriculture Extension Department
Farmers‘ visit to extension personnel for gaining new knowledge and information is inevitable because farmers faces multidimensional and ever changing problems for which farmers contacts extension personals to get proper solution (Abbas et al., 2008). Data regarding contact by the respondents with Agriculture Extension Department are presented in Fig. 4.19. It was found that majority (60.9%) of the respondents did contacted Agriculture Extension Department whereas, 39.1% of the respondents reported that they never contacted the Agriculture Extension Department regarding their issues.
149
60 57
51 55 49 50
47 45 40 41
39 30 No Yes
No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
180(46.9) 204(53.1)
No Yes
Fig. 4.18 Distribution of respondents regarding monitoring by agriculture extension department
Source: Field Survey, 2018
150
70 62 59 60 55 58
50
40 38 41 No 37
30 34 Yes No.of Responents 20
10
0 Bandkurai Khanmai Baffa Baidara
234(60.9) 150(39.1)
No Yes
Fig. 4.19 Distribution of respondents regarding contacts by farmers with agriculture
extension department
Source: Field Survey, 2018
151 4.44 Demonstrations arranged by Agriculture Extension Department on Pesticides
Demonstration plots are very effective and important for quick learning by doing activities practically. It means to show some activity practically and clearly and audience is expected to pick it properly. Due to its practical natures, it is very effective method to practically teach farmers certain technique/s. Data regarding demonstration arranged by Agriculture Extension Department are presented in Fig. 4.20. It was found that majority (64.6%) of the respondents were of the view that no demonstration is being arranged by Agriculture Extension Department in the past whereas, 35.4% of the respondents reported that demonstrations were arranged by the Agriculture Extension Department.
4.45 Information Regarding Pest Resistant Variety
Pest resistant variety is the basic component in the IPM approach. It is one of the safest and less laborious techniques to use the pest resistant variety in order to minimize the pest attack. Therefore, the respondents were investigated regarding the information shared by the Agriculture Extension Department regarding the pest resistant variety or not and their responses are presented in Fig. 4.21. It was found that majority (60.9%) of the respondents reported that they never share such information with them whereas, 39.1% of the respondents reported that they got information from Agriculture Extension Department regarding pest resistant varieties.
152
80 72 70 62 65 60
49 50
47 40 No Yes 30 31
34 No.of Respondents
20 24
10
0 Bandkurai Khanmai Baffa Baidara
136(35.4) 248(64.6)
No Yes
Fig. 4.20 Distribution of respondents regarding demonstrations arranged by agriculture extension department on pesticides
Source: Field Survey, 2018
153
80
70 63 68
60 55
48 50
40 48 No 41 Yes 30 28
No.of Respondents 33 20
10
0 Bandkurai Khanmai Baffa Baidara
150(39.1)
234(60.9)
No Yes
Fig. 4.21 Distribution of respondents regarding information shared by extension department regarding pest resistant variety
Source: Field Survey, 2018
154 4.46 Information Shared By Agriculture Extension Department on Mechanical Control
Controlling pests by mean of physical mean is called mechanical control. Data regarding knowledge about the mechanical control of pest been imparted by the Agriculture Extension Department are presented in Fig.4.22. It was found that majority (59.6%) of the respondents reported that Agriculture Extension Department didn‘t provided information regarding mechanical control of the pest whereas, the rest of the respondents reported that agriculture extension department did share information on mechanical control of pest.
4.47 Information Shared by Agriculture Extension Department on Cultural Practices to Control Pests
Cultural practices to control pests is one of the safest technique to control pests. Cultural practices refers to the control of pests through crop rotation, soil quality management, trap crops, tillage practices, change in plantation and harvest dates, intercropping etc. In this regard the respondents were probed and data regarding knowledge shared by Agriculture Extension Department with the farmers about cultural practices are presented in Fig. 4.23. Majority (60.9%) of the respondents reported that Agriculture Extension Department didn‘t share information regarding cultural practices to control pests whereas, 39.1% of them reported that Agriculture Extension Department do shared such type of information. The reason of not sharing this very much important information with the farming community might be attributed to the less contact by the farming community or less queries by the farmers in this regard.
155
80 71 70
60 52 51 55 50
41 No 40 45 44 Yes
30 No.of Respondents
20 25
10
0 Bandkurai Khanmai Baffa Baidara
155(40.4)
229(59.6)
No Yes
Fig. 4.22 Distribution of respondents regarding information shared by agriculture
extension department on mechanical control
Source: Field Survey, 2018
156
70 64 62 60 56 52
50
40 44 No 40 34 30 Yes
32 No.of Respondets 20
10
0 Bandkurai Khanmai Baffa Baidara
150(39.1) 234(60.9)
No Yes
Fig. 4.23 Distribution of respondents regarding information shared by agriculture
extension department on cultural practices to control pest
Source: Field Survey, 2018
157 4.48 Information Shared about the Highly Toxic Pesticides by Agriculture Extension Department
Data regarding information provided to the farming community about the highly toxic pesticides were presented in Fig. 4.24. It was found that majority (69.3%) of the repsondents reproted that Agriculture Extension Department didn‘t share such type of infromation whereas 30.7% of the respondents reported that Agriculture Extension Department provided information regarding highly toxic pesticides.
4.49 Information shared by Agriculture Extension Department Regarding time of Pesticides Application
Time of application of pesticides is of immense importance in the sense that if the pesticide is applied right at the time of economic threshold level will have cost effective control over pest rather than at economic injury level. Moreover, each pest has effective state of development at which the control of pest is easy in comparison to the developed stage. Therefore, the farmers were investigated regarding the information provided by the Agriculture Extension Department regarding time of pesticides application and were presented in Fig. 4.25. It was found that majority (54.4%) of the respondents were of the view that they didn‘t shared such information whereas, 45.6% of the respondents reported that Agriculture Extension Department shared such type of information.
158
80 76
70 72 61 57
60
50
40 No 39 Yes 30 35
No.of Respondents 24 20 20 10
0 Bandkurai Khanmai Baffa Baidara
118(30.7) 266(69.3)
No Yes
Fig. 4.24 Distribution of respondents regarding information shared about the highly toxic pesticides by agriculture extension dearptment
Source: Field Survey, 2018
159
70
57 60 59 53 50
50
46 40 43 37 No 39
30 Yes No.of Respondents 20
10
0 Bandkurai Khanmai Baffa Baidara
175(45.6) 209(54.4)
No Yes
Fig. 4.25 Distribution of respondents regarding information shared by agriculture extension department regarding time of pesticides application
Source: Field Survey, 2018
160 4.50 Association among Pictograms and Demographic Attributes
Results in Table 4.25.1 show that there was highly significant (P≤0.01) association of all the three activity pictograms i.e. handle careful liquid product, handle carefully- powder or granules product and use a sprayer pictogram with all the demographic attributes i.e. age, literacy, land holding, involvement in farming and farming experience. Results of gamma test show that all the demographic attributes had positive association with activity pictograms whereas, age, involvement in farming and farming experience the association was negative. This show that with increase of age the respondents were not aware of the activity pictogram which was due to the fact that respondents with high age never used to check the labels (Table 4.27). Similarly, with increase in farming experience and involvement in farming as full time, the respondents became aware of this pictogram.
Results in Table 4.25.2 show that there was highly significant (P≤0.01) association among use protective gloves pictogram with literacy and farming experience. It was also found that the association was positive with literacy and negative with farming experience which might be due to the fact that those respondents who had more farming experience less often used to check the labels (Table 4.27). Similarly, wash after use had also significant association with age whereas, highly significant (P≤0.01) association was observed with literacy and farming experience. Wear a mask pictogram also had highly significant (P≤0.01) association with literacy whereas significant (P≤0.05) association with land holding was observed. Highly significant (P≤0.01) association was observed among wear a protective overall pictogram with literacy and farming experience. Significant association (P≤0.05) was observed with age and involvement in farming.
Use a shield pictogram had also highly significant (P≤0.01) association with age, literacy, and farming experience whereas, significant (P≤0.05) association with landholding. Highly significant (P≤0.01) association was also observed among wear a boots pictogram and literacy whereas significant association (P≤0.05) was observed with age and landholding. Wear a respirator pictogram had also a highly significant (P≤0.01) association with literacy and farming experience whereas significant association (P≤0.05) was observed with age. Highly significant (P≤0.05) association was observed among wear protective
161 clothing with age and farming experience whereas, significant (P≤0.05) association was observed with literacy (Table 4.25.2).
Chi-square results in Table 4.25.3 depeict that there was highly significant (P≤0.01) association of dangerous for livestock & poultry with literacy and farming experience. Significant association (P≤0.05) was observed with landholding. Similarly, dangerous for wildlife pictogram had highly significant (P≤0.01) association with literacy and farming experience whereas, significant association (P≤0.05) with involvement in farming was found. Dangerous for fish do not contaminates water had highly significant (P≤0.01) association with literacy and farming experience whereas significant association (P≤0.01) was observed with age and land holding. Moreover, keep locked away or out of reach from children pictogram had highly significant (P≤0.01) association with literacy and farming experience whereas, significant association (P≤0.05) was observed with landholding. Poison pictogram had highly significant (P≤0.01) association with farming experience whereas, significant association with age, literacy and landholding. Corrosive pictogram had also highly significant (P≤0.01) association with the farming experience whereas significant (P≤0.05) association was observed with age, literacy and landholding. Flammable pictogram had highly significant (P≤0.01) association with literacy and farming experience whereas, age and landholding had significant association (P≤0.05). Explosive pictogram had highly significant (P≤0.01) association with the literacy and farming experience whereas, significant (P≤0.05) association was observed with involvement in farming.
Results in Table 4.25.4 show that all the toxicity levels pictorgram had highly significant (P≤0.01) association with literacy. Similarly, only non-significant association of age was observed with moderate hazard pictogram. Landholding had non-significant association with all the toxicity levels pictograms whereas only highly hazard pictogram had significant (P≤0.05) association with involvement in farming.
Chi-square results in Table 4.25.5 depicted that highly significant (P≤0.01) association of age with moderately toxic and slightly toxic Pictogram whereas, significant (P≤0.05) association was observed with highly toxic pictogram. It was also found that there was
162 highly significant (P≤0.01) association with literacy and extremely toxic pictogram whereas significant (P≤0.05) association was observed with all other pictograms. Similarly, highly significant (P≤0.01) association was observed among extremely toxic & slightly toxic with landholding whereas significant (P≤0.05) association was observed with moderately toxic pictogram. Significant association (P≤0.05) was observed among involvement in farming and extremely toxic pictogram whereas, highly significant (P≤0.01) association was observed with slightly toxic pictogram.
163 Table 4.25.1 Association among Activity Pictogram and Demographic Attributes
Activity Pictogram Involvement in Age Literacy Land Holding Farming experience farming Sr. # Pictogram Meaning 2 ᵞ ᵞ ᵞ ᵞ ᵞ
Handle Carefully- 1 16.92** -0.28 104.54** 0.60 35.25** 0.22 9.96** -0.33 69.06** -0.49 Liquid Product
Handle Carefully- 2 powder or granules 14.42** -0.21 97.50** 0.63 30.25** 0.33 8.51** -0.31 35.90** 0.37
product
3 Use a sprayer 16.24** -0.22 135.20** 0.76 39.10** 0.14 11.42** -0.37 95.21** -0.32
*=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
164 Table 4. 25.2 Advisory Pictogram and Demographic Attributes
Involvement in Farming Age Literacy Land Holding farming experience Sr. # Pictogram Meaning 2 ᵞ ᵞ ᵞ ᵞ ᵞ
Use protective gloves 6.63ns -- 122.19** 0.71 9.25ns -- 7.75ns -- 97.66** -0.51 4
61.93** 5 Wash after use 12.34* -0.27 88.62** 0.70 4.07ns -- 2.84ns -- -0.49
6 Wear a mask 7.75ns -- 98.13** 0.71 34.19* -0.10 7.74ns -- 2.32ns --
Wear a protective 7 12.30* -0.27 88.73** 0.56 2.66ns -- 16.18* -- 71.15** -0.65 overall
8 Use a shield 37.77** -0.34 148.96** 0.51 50.02* -0.20 9.12ns -- 86.33** -0.53
9 Wear glasses 14.59* -0.10 134.04** 0.70 43.10* -0.17 7.33ns -- 8.47ns --
10 Wear boots 20.78* -0.25 117.34** 0.68 31.62* -0.11 10.30ns -- 4.09ns --
165 11 Wear respirator 20.09* -0.25 157.33** 0.69 8.27ns -- 7.14ns -- 65.64** -0.47
Wear Protective 12 59.42** -0.45 39.25* 0.05 6.25ns -- 2.92ns -- 81.32** -0.58 Clothing
*=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
Table 4. 25.3 Enviromental & Other hazards
Age Literacy Land Holding Involvement in farming Farming experience Sr. # Pictogram Meaning 2 ᵞ ᵞ ᵞ ᵞ ᵞ
Dangerous for 13 7.51ns -.027 104.33** 0.67 32.04* 0.02 8.09ns -- 82.24** 0.40 livestock and poultry
Dangerous for 14 0.68ns -- 83.03** 0.62 6.67ns 16.07* -0.423 58.77** 0.52 wildlife
Dangerous for fish/do 15 40.57* -0.55 83.72** 0.63 25.23* -0.11 10.31ns -- 99.73** 0.61 no contaminate water
Keep locked away or 16 out of reach from 9.47ns -0.22 88.53** 0.56 33.20* -0.04 9.55ns -- 66.03** 0.61
children
17 Poison 21.72* -0.33 131.18** 0.73 38.71* 0.08 9.00ns -- 112.59** 0.59
166 18 Corrosive 48.96* -0.52 59.88* 0.49 31.01* -0.33 0.24ns -- 74.01** 0.69
19 Flammable 17.68* -0.28 126.40** 0.75 37.70* 0.10 8.67ns -- 113.41** 0.50
20 Explosive 0.32ns -- 93.86** 0.61 8.49ns -- 24.42* -0.50 70.94** 0.57
*=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
Table 4.25.4 Toxicity Levels Pictorgram and Demographic Attributes Age Literacy Land Holding Involvement in farming Farming experience Sr. # Pictogram Meaning 2 ᵞ ᵞ ᵞ ᵞ ᵞ
Slightly 21 Hazardous 12.16* -0.24 41.17** 0.32 2.65ns -- 2.0ns -- 22.25* 0.32
(Caution)
Moderate 22 Hazard 7.52ns -- 86.89** 0.55 9.08ns -- 10.85ns -- 42.54** 0.51
(Warning)
Highly 23 Hazard 13.37* -0.18 98.07** 0.67 4.74ns -- 29.26* -0.536 44.37** 0.55
(Danger) *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
167 Table 4.25.5 Toxicity Levels (Colour) Pictorgram and Demographic Attributes Involvement in Sr. # Pictogram Meaning Age Literacy Land Holding Farming experience farming
Extremely Toxic (Oral Lethal 24 2.66ns -- 133.75** 0.75 55.95** 0.24 18.43* 0.44 65.89** ᵞ = 0.56 Dose 1 -50mg/kg)
Highly Toxic (Oral Lethal 25 9.86* -0.26 49.70* 0.43 1.53ns 0.14ns 0.04 37.38* ᵞ = 0.49 Dose 50-500 mg/kg)
Moderately Toxic 26 (Oral Lethal 50.41** -0.34 54.55* 0.45 20.11* -0.03 6.24ns -- 23.87* ᵞ = 0.49
Dose 501-5000 mg/kg)
Slightly Toxic (Oral Lethal 27 21.25** -0.006 49.66* 0.50 68.29** -0.34 90.50** -0.80 23.84* ᵞ =0.42 Dose >5000 mg/kg)
*=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
168 4.51 Association among Self-Reported Acute Poisoning and Following Labels Instructions
Results in Table 4.26 show that there was highly significant (P≤0.01) association among sneezing, cough, nausea, eye irritation, shortness of breath and body pain with the following instruction on label variable. The association was negative because the gamma value was negative as showed in Table 4. This showed that following up instructions had minimized the acute poisoning cases. Similarly, significant (P≤0.05) association was observed among excessive sweating, stomach ache, dizziness, blisters, catarrh and burning sensation with the following instructions as mentioned on labels. All the other self-reported poisoning cases had non-significant association with the following instructions.
Table 4.26 Association among Self-Reported Symptoms and Following Instructions on Labels
2 Symptom Value ᵞ Value Headache 2.63ns 0.53 Excessive sweating 8.90* -0.30 Itching 3.26ns 0.11 Sneezing 26.98** -0.50 Cough 126.02** -0.88 Stomach ach 18.56* -0.34 Nausea 189.21** -0.57 Dizziness 22.38* -0.52 Feeling weak 5.14ns 0.24 Diarrhea 67.18** -0.76 Difficulty in Seeing 5.79ns -0.63 Eye irritation 142.64** -0.23 Fatigue 3.56ns -0.02 Shortness of Breath 70.58** -0.57 Fever 6.25ns -0.13 Sleeplessness/insomnia 7.47ns -0.04 Chest pain 4.27ns 0.13 Blisters 8.97* -0.17 Catarrh 7.93* -0.88 Body pain 143.67** -0.90 Burning sensation 30.27* -0.66 *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non- significant
169 4.52 Association among Checking Labels and Demographic Attributes
Results in Table 4.27 show that there was highly significant (P≤0.01) association among literacy and checking of the labels. Similarly, significant (P≤0.05) association was observed with age whereas, all other attributes had non-significant association. The age had the negative association, whereas the literacy had the positive association. This show that with increase of literacy respondents used to check the labels as they were much conscious about their health.
Table 4.27 Association among Checking Labels and Demographic Attributes
2 Demographic Attributes Value ᵞ Value Age 20.16* -0.22 Literacy 116.38** 0.68 Landholding 12.35 ns 0.13 Involvement In farming 7.69ns -0.30 Farming Experience 98.21ns -0.51 *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non- significant
4.53 Association among Demographic Characteristics and Precautionary Measures Used By Farming Community
Chi-square results show in Table 4.28 depicted that there was highly significant (P≤0.01) association of age with Using Mask during Spraying whereas significant (P≤0.05) association was observed with that of Smoking during pesticides application, Change clothes after application of pesticides, Cover nose and mouth with any other thing (cloth), knowledge about direction of wind to apply spray, Do you use to eat or drink and using goggles, glasses and respirator. Similarly literacy had highly significant (P≤0.01) association with that of Using Mask during Spraying, Smoking during pesticides application, Change clothes after application of pesticides, Do you know in which direction of wind to apply spray, Do you use to eat or drink while spraying? and Using glasses. Significant (P≤0.05) association was observed among literacy and Taking a bath after pesticide application, Wearing Boots while spraying, Change clothes after
170 application of pesticides, wearing boots while spraying, using mixture equipment, cover nose and mouth with any other thing (cloth) and do you use respirator (Table 4.28).
Land holding had significant (P≤0.05) association with that of wearing separate clothes for spray purpose, smoking during pesticides application, change clothes after application of pesticides, cover nose and mouth with any other thing (cloth) and do you use Respirator. Highly significant (P≤0.01) association was observed among land holding and taking a bath after pesticide application, wearing Boots while spraying and do you know in which direction of wind to apply spray. Similarly, highly significant (P≤0.01) association was observed among landholding and cover nose and mouth with any other thing (cloth), using goggles and Using glasses. However, highly significant (P≤0.01) association was observed with that of using mask during spraying, wearing separate clothes for spray purpose, using mixture equipment, do you use to eat or drink while spraying? and do you use respirator. Farming experience had highly significant (P≤0.01) association with that of Do you use to eat or drink while spraying? whereas, significant (P≤0.05) association was observed with using mask during Spraying, wearing separate clothes for spray purpose, smoking during pesticides application, change clothes after application of pesticides, using mixture equipment, do you know in which direction of wind to apply spray, using goggles, face shield and do you use respirator (Table 4.28).
171 Table 4.28 Association among Demographic Characteristics and Precautionary Measures Used by Farming Community
Involvement in Precautionary Measures Age Literacy Land Holding Farming experience farming 2 Using Mask during Spraying =25.14** =46.01** =4.27ns =16.18* =18.97* ᵞ =0.16 ᵞ =0.08 ᵞ =0.20 ᵞ =-0.53 ᵞ =0.30
Wearing Separate clothes for spray =2.93ns =4.58ns =10.67* =12.79* =19.69* purpose ᵞ =0.13 ᵞ =-0.02 ᵞ =-0.33 ᵞ =-0.35
Taking a bath after pesticide application =12.84ns =61.10* =63.40** =3.61ns =4.44ns ᵞ =0.50 ᵞ =0.65
Smoking during pesticides application =21.17* =61.17** =53.24* =1.13ns =38.79* ᵞ =0.21 ᵞ =-0.51 ᵞ =-0.22 ᵞ =0.31
Change clothes after application of =17.27* =133.89** =42.11* =2.79ns =34.56* pesticides ᵞ =-0.09 ᵞ =0.51 ᵞ =0.07 ᵞ =-0.37
Wearing Boots while spraying =8.87ns =43.21* =103.56** =1.08ns =4.45ns ᵞ =0.27 ᵞ =0.45 ᵞ =0.85
Using mixture equipment =1.75ns =45.34* =3.87ns =4.01* =25.43* ᵞ =-0.09 ᵞ =0.47 ᵞ =0.17 ᵞ =-0.22 ᵞ =-0.36
Cover nose and mouth with any other =44.41* =40.64* =30.02* =27.33** =4.31ns thing (cloth) ᵞ =0.10 ᵞ =0.31 ᵞ =0.51 ᵞ =-0.82
172 2 Do you know in which direction of wind =6.70* =98.31** =67.30** =1.05ns =13.60* to apply spray ᵞ =0.142 ᵞ =0.68 ᵞ =0.58 ᵞ =0.07
Do you mix pesticides in open air or =2.54ns =7.89ns =5.77ns =1.73ns =2.33ns close room? ᵞ =0.10 ᵞ =-0.03
Do you use to eat or drink while =26.66* =121.48** =3.24ns =24.48* =107.75** spraying? ᵞ =0.61 ᵞ =0.26 ᵞ =0.21 ᵞ =0.50 ᵞ =-0.78
Using Goggles =20.90* =5.68ns =7.67ns =47.42** =27.02* ᵞ =-0.39 ᵞ =0.009 ᵞ =-0.05 ᵞ =-0.64 ᵞ =-0.41
Using glasses =11.54* =94.42** =6.54ns =42.23** =1.31ns ᵞ =-0.21 ᵞ =0.51 ᵞ =-0.71 ᵞ =-0.64
Face shield =7.38ns =13.15ns =7.68ns =3.75ns =19.22* ᵞ =0.03 ᵞ =0.02 ᵞ =0.02 ᵞ =-0.21
Do you use Respirator =7.28* =49.60* =41.22* =29.96* =18.09* ᵞ =-0.12 ᵞ =0.45 ᵞ =0.01 ᵞ =-0.54 ᵞ =-0.19 *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
173 4.54 Association among Demographic Characteristics and Knowledge about the Harmful Environmental Effect of Pesticides
Results in Table 4.29 show the association among the knowledge about the environmental hazards of pesticides and demographic attributes. It was found that there was highly significant (P≤0.01) association among age and all other environmental hazards variable except Cause damage to wildlife, kill pollinators, effect soil fertility, damage soil organism, resurgence of pest population and contaminate the air. Similarly, significant (P≤0.05) positive association of literacy was observed with cause damage to human health, animal, wildlife, water life and accumulation in food chain. Land holding also had significant (P≤0.05) positive association with that of cause damage to human health, and animal health. Furthermore, farming experience had also significant (P≤0.05) positive association with that of cause damage to human health, animal health, kill pollinators and accumulation in food chain.
174 Table 4.29 Association among Demographic Characteristics and Knowledge about the Harmful Environmental Effect of Pesticides
Farming Hazards Age Literacy Land Holding experience 2 Cause damage to human =87.43** =42.27* =44.05* =45.31* health ᵞ =0.10 ᵞ =0.42 ᵞ =-0.10 ᵞ =-0.45
Cause damage to animal =182.66** =55.79* =41.62* =38.49* health ᵞ =0.31 ᵞ =0.12 ᵞ =-0.14 ᵞ =-0.34
=33.85* Cause damage to wildlife =9.62ns =17.14ns =14.70ns ᵞ =0.23
Cause damage to water =166.34** =47.22* =18.07ns =12.10ns life ᵞ =0.21 ᵞ =0.26
=51.38* Kill pollinators =15.15ns =14.52ns =15.24ns ᵞ =-0.23
Effects soil fertility =13.79ns =12.06ns =6.81ns =8.71ns Damage to the useful organisms in soil =19.34ns =19.29ns =7.68ns =12.52ns
Accumulates in food =190.15** =37.11* =29.72* =18.29ns chain ᵞ =0.17 ᵞ =0.44 ᵞ =-0.43 Pesticides usage causes resurgence of pest =16.03ns population after =25.33ns =11.01ns =8.59ns removing natural ᵞ =0.75 enemies.
Cause air contamination =5.01ns =25.07ns =14.49ns =12.09ns *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non-significant
175 4.55 Association among the Training Received by the Farming Community and Knowledge about the Health and Harmful Environmental Effects of Pesticides
Results in Table 4.30 Show that there was highly significant (P≤0.01) association of knowledge of environmental hazards i.e. cause damage to human health, animal health, accumulation in food chain and causes air contamination with training received from the Agriculture Extension Department. Similarly, significant (P≤0.05) association was observed with that of cause damage to wildlife, water life and kills pollinators. The instant results show that trainings had significant impact on the knowledge of the farming community. Numerous previous studies (Macfarlane et al., 2008; Levesque et al., 2012 and Jørs et al., 2014) had also shown significant association of the training and with farmers‘ attitude to pesticide use.
Table 4.30 Association among the Training Received by the Farming Community and Health and Knowledge about the Harmful Environmental Effects of Pesticides
Hazards Training received
2 ᵞ
Cause damage to human health 70.84** 0.57
Cause damage to animal health 90.09** -0.49
Cause damage to wildlife 38.27* 0.42
Cause damage to water life 48.82* 0.39
Kills pollinators 27.55* -0.35 Effects soil fertility 9.67ns -- Damage to the useful organisms in soil 4.09ns --
Accumulates in food chain 127.23** 0.39 Pesticides usage causes resurgence of pest 3.86ns -- population after removing natural enemies.
Cause air contamination 102.08** 0.57 *=significance at 5% level of probability, **=significance at 1% level of probability, ns= non- significant
176 4.56 Analysis of Variance of Literacy Levels and Knowledge about the Hazardous Health and Environmental Effect of Pesticides
Results of mean square (Table 4.31) show that there was highly significant (P≤0.01) difference among the various groups of literacy regarding all variable about the knowledge of the hazardous environmental effect of pesticides. Maximum (3.937) mean value was observed in the group of above intermediate followed by the intermediate (3.147) and middle (2.962) (Fig. 4.26) regarding causing damage to human health. Maximum (3.203) mean value was observed in above intermediate group followed by middle (2.933) whereas, mean value of 2.588 was observed in the group of matric in the case of causing damage to animal health (Fig. 4.27). Pesticide being harmful to wild life was reported by the above intermediate with mean value of 3.278 followed by the middle (2.606) and matric (2.544) (Fig. 4.28). Moreover, above intermediate also reported with maximum mean of 3.266 that pesticide is harmful to water life (Fig. 4.29). Similarly, 3.028 mean was observed in above intermediate group of respondents who reported that pesticides kill pollinators (Fig. 4.30). Pesticides damages the soil fertility was also reported by the above intermediate with the mean value of 2.848 whereas, lowest mean was recorded in the matric group of respondents (Fig. 4.31). The same pattern was also observed in the damage to soil organisms with the mean value of 2.848 in above intermediate group (Fig. 4.32). Maximum mean value among all the attributes was recorded for knowledge of pesticides accumulation in food chain was 3.443 and was observed in above intermediate group of respondents followed by the matric group respondents with mean value of 2.603 (Fig. 4.33). Pesticides application kills the natural enemies of pest and thus create the resurgence of pest; the same questions was asked from the respondents of various groups and the maximum mean value was observed i.e. 3.38 in above intermediate group (Fig.4.34) whereas, 3.114 mean value was also observed in above intermediate group regarding knowledge about pesticides contaminates air (Fig.4.35). Maximum mean value of 3.114 was observed in above Intermediate category regarding air contamination by pesticides followed by Matric (2.221) and intermediate (2.191) (Fig. 4.36).
177 Table 4.31 Analysis of Variance of Literacy Levels and Knowledge about the Hazardous Health and Environmental Effect of Pesticides SS df MS F Sig. Between Groups 76.419 3 25.473 27.518 .000 Cause damage to Human Within Groups 351.766 380 0.926 health Total 428.185 383 Between Groups 62.883 3 20.961 22.325 .000 Animal Within Groups 356.781 380 0.939 Total 419.664 383 Between Groups 33.376 3 11.125 14.845 .000 Harmful to wild life Within Groups 284.781 380 0.749 Total 318.156 383 Between Groups 32.660 3 10.887 13.776 .000 Causes damage to Water Within Groups 300.298 380 0.790 Life Total 332.958 383 Between Groups 33.660 3 11.220 10.119 .000 Kill pollinators Within Groups 421.338 380 1.109 Total 454.997 383 Between Groups 84.396 3 28.132 27.670 .000 Soil fertility Within Groups 386.343 380 1.017 Total 470.740 383 Between Groups 76.895 3 25.632 24.059 .000 Damage useful soil Within Groups 404.845 380 1.065 organism Total 481.740 383 Between Groups 124.573 3 41.524 59.815 .000 Accumulation in food Within Groups 263.799 380 0.694 chain Total 388.372 383 Resurgence of pest after Between Groups 117.947 3 39.316 50.694 .000 removal of natural Within Groups 294.709 380 0.776 enemies of pest Total 412.656 383 Between Groups 89.354 3 29.785 33.924 .000 Air contamination Within Groups 333.636 380 0.878 Total 422.990 383
178
Fig. 4.26 Means of literacy level and causes damage to human health
Fig. 4.27 Means of literacy level and causes damage to animal health
179
Fig. 4.28 Means of literacy level and pesticides causes damage to wild life
Fig. 4.29 Means of literacy level and pesticides harmful to water life
180
Fig. 4.30 Means of literacy level and pesticides kills pollinators
Fig. 4.31 Means of literacy level and pesticides causes damage to soil fertility
181
Fig. 4.32 Means of literacy level and pesticides causes damage to soil organism
Fig. 4.33 Means of literacy level and pesticides accumulation in food chain
182
Fig. 4.34 Means of literacy level and resurgence of pest due to killing of natural enemies through pesticides
Fig. 4.35 Means of literacy levels and pesticides contaminates air
183 4.57 Independent Sample T-test of the Involvement in Farming and Environmental Hazards of Pesticides Use
Results in Table 4.32 show that there was highly significant (P≤0.01) difference among the two groups i.e. those who were involved on full time basis and those who were involved on part time basis in agriculture sector. The highly significant (P≤0.01) difference was observed in causing damage to human health (t=7.62), animal health (t=9.80), accumulates in food chain (t=7.67) and pesticides usage causes resurgence of pest population after removing natural enemies (t=7.82). Similarly, significant (P≤0.05) difference in knowledge among the two groups were observed in the knowledge regarding cause damage to wildlife (t=4.63), water life (t=4.29), kill pollinators (t=4.73) and causes air contamination (t=3.90). However, there was no significant difference among the knowledge among the two groups regarding effect of the soil fertility and cause damage to the useful organisms in soil. This indicates that no matter whether the farmers has good experience of farming by fully indulge in agriculture sector or that who were involved in agriculture on part time basis both have equal knowledge about these particular attributes.
184 Table 4.32 Independent Sample t-Test of Involvement in Farming and Their Knowledge about the Health and Environmental Hazard of Pesticides Variables df t-Value SE
Cause damage to human health 382 7.62** 0.10
Cause damage to animal health 382 9.80** 0.10
Cause damage to wildlife 382 4.63* 0.09
Cause damage to water life 382 4.29* 0.09
Kills pollinators 382 4.73* 0.11
Effects soil fertility 382 2.21NS 0.11
Damage to the useful organisms in soil 382 1.07NS 0.11
Accumulates in food chain 382 7.67** 0.10
Pesticides usage causes resurgence of pest population 382 7.82** 0.10 after removing natural enemies
Cause air contamination 382 3.90* 0.10
4.58 Binary Logistic Regression of Diseases Associated with Precautionary Measures
The results of binary logistic regression analysis of diseases associated with precautionary measures are presented in Table 1. The regression analysis reveal that taking bath after pesticide use can highly significantly (P≤0.01) reduces the headache (-2.28), dizziness (-- 5.64), feeling weak (-1.81), difficulty in seeing (-3.05), chest pain (-1.21), burning sensation (-0.96), and fever (-1.05). This might be due to the fact that the pesticides content which might absorbed by the clothes came in contact with the body. Therefore, taking bath after the pesticides practices can significantly minimize the poisoning cases.
185 Similarly, the precautionary measures were also associated with the factor of smoking while spraying (Table 4.33). It was found that those who are smoking while spraying, highly significantly (P≤0.01) influenced and found victim of headache, nausea, dizziness, shortness of breath, chest pain and fever whereas, others were significantly found victims of sneezing. During the application of pesticides, more specifically with the power sprayer the pesticides take the form of mist when sprayed. This mist easily enters the body of the pesticides applicator personnel/farmer. During the smoking, the applicator regularly inhales the chemical mist due to the fact that he is not covering his mouth or nose. Our results are in in conformity with that of Manyilizu et al. (2017) who also reported that smoking was associated with an increased incidence of chest pain, while eating and chewing gum during pesticide use was associated with increased levels of diarrhea.
CCAPP also highly significant reduces the adverse effects like headache (-0.22), excessive sweating (-1.21), feeling weak (-0.93), blisters (-3.61), body pain (-5.17) and fever (-3.902) whereas, significantly reduces the nausea (-2.21), diarrhea (-1.54), shortness of breath (- 5.76) and chest pain (-3.60) as shown in Table 1. Changing clothes was also found to be important factor in order to minimize the acute poising cases which might be due to the fact that the clothes after application of pesticides might accumulate the pesticides contents and thus results in blisters etc.
Covering nose and mouth is also considered as one of the most important precautionary measures and this covering response in relation to health concerns are given in Table 1. It was observed that covering nose and mouth had highly significantly (P≤0.01) reduces the dizziness (-2.90), feeling weak (-1.11), diarrhea (-1.89), shortness of breath (-0.84), chest pain (-1.58), burning sensation (-2.94), fever (-2.69) and difficulty in seeing (-0.62) in comparison to those who not covers the nose and mouth.
Eating and drinking in the field is common phenomena in the field by the farming community. Since they use pesticides and eat and drink as well in the field. Thus they were investigated regarding the eating and drinking habit while, they use pesticides and it was found that EDWS had negative highly significant (P≤0.01) contribution towards chest pain
186 1.83) and fever (3.31) however, significant (P≤0.01) negative contribution towards nausea (-0.05), difficulty in seeing (3.53) and diarrhea (1.55) was found (Table 1). This showed that after the application of pesticides those respondents who used to eat or drink were significantly affected from the chest pain, fever, nausea, diarrhea etc.
Using Face Shield had also highly significant (P≤0.01) negative contribution towards nausea (-20.69), shortness of breath (-0.93), burning sensation (-4.94) whereas, significant negative contribution towards fever (-1.79) was found. Moreover, UR had highly significant (P≤0.01) negative contribution towards sneezing (-4.23), cough (-2.72), nausea (-1.44), dizziness (-20.70), difficulty in seeing (-19.90) and fever (-3.09) was also found in the present study (Table 1). Using face shield and respirator is important PPE while doing pesticides practices. The instant results show that the chances of nausea, shortness of breath, burning sensation and fever can be significantly minimized with the use of the face shield.
187 Table 4.33 Binary Logistic Regression of Diseases associated with Precautionary Measures Headache Excessive sweating Sneezing Cough Nausea Nagelkerke R2=0.34 Nagelkerke R2=0.06 Nagelkerke R2=0.57 Nagelkerke R2=0.66 Nagelkerke R2=0.55 Independent X2(9)=150.11** X2(9)=18.21** X2(9)=218.37* X2(9)=249.5** X2(9)=204.61** Variable Likelihood=253.33 Likelihood=496.47 Likelihood=313.69 Likelihood=243.39 Likelihood=321.11
β Wald β Wald Β Wald β Wald β Wald Constant 19.77 31.26 -1.26 8.81 -21.26 0.002 -20.81 0.001 -19.31 0.003 TBAPU -2.28** 18.16 -0.20 ns 0.52 -0.41 ns 1.36 -0.75 ns 3.30 0.68 ns 3.35 SWS 1.66** 0.35 0.51 ns 2.30 0.49* 2.09 -0.29 ns 0.49 1.91** 27.25 CCAPP -1.20 ns 0.26 -1.21** 13.41 0.29 ns 0.82 1.29 ns 5.66 -2.21* 33.28 CNM -0.03 ns 0.96 -0.34 ns 0.71 -0.24 ns 0.30 -0.17 ns 0.11 -0.72 ns 2.52 EDWS 0.37 ns 0.31 0.28 ns 1.22 -0.82 ns 5.89 -0.08 ns 0.04 0.05* 0.02 UFS -0.10 ns 0.10 0.12 ns 0.11 18.25 ns 0.001 16.92 ns 0.02 -20.69** 4.81 UR -1.42 ns 0.26 -0.13 ns 0.13 -4.23** 29.73 -2.72** 6.08 -1.44** 9.89 Dizziness Feeling Weak Difficulty in Seeing Diarrhea Shortness of Breath Nagelkerke R2=0.80 Nagelkerke R2=0.28 Nagelkerke R2=0.69 Nagelkerke R2=0.43 Nagelkerke R2=0.63 X2(9)=299.16** X2(9)=91.28** X2(9)= 251.71** X2(9)=144.76** X2(9)=231.16** Likelihood=130.49 Likelihood=420.71 Likelihood=196.86 Likelihood=356.78 Likelihood=248.93 Β Wald β Wald β Wald β Wald Β Wald Constant -18.10 0.03 -0.13 0.41 -20.21 0.002 -20.97 0.02 0.78 0.80 TBAPU (D) -5.64** 53.50 -1.81** 31.37 -3.05** 19.06 -0.77 ns 5.01 -1.50 ns 5.02 SWS(D) 4.30** 26.36 -0.93ns 0.08 0.135 ns 0.09 0.50 ns 2.00 4.33** 37.48 CCAPP(D) 0.87 ns 2.21 -0.93** 8.65 2.65 ns 39.29 -1.54* 18.18 -5.76* 53.83 CNM (D) -2.90** 15.17 -1.11** 6.95 -0.62* 1.07 -1.89** 16.49 -0.84** 0.96 EDWS (D) 1.54 ns 4.94 -0.92 ns 10.74 3.53* 31.50 1.55* 20.01 -4.48 ns 30.69 UFS (D) -0.24 ns 1.30 -2.39 ns 9.46 1.52ns 1.32 21.46 ns 2.48 -0.93** 4.61 UR (D) -20.70** 14.31 4.03 ns 26.86 -19.90** 19.21 -0.23 ns 0.348 -0.05 ns 0.01
188
Chest Pain Blisters Burning Sensation Body Pain Fever Nagelkerke R2=0.72 Nagelkerke R2=0.42 Nagelkerke R2=0.63 Nagelkerke R2=0.22 Nagelkerke R2=064 X2(9)=258.28** X2(9)=145.64** X2(9)=205.53** X2(9)=228.61* X2(9)=252.6** Likelihood=177.32 Likelihood=368.16 Likelihood=205.40 Likelihood=165.88 Likelihood=279.72 Β Wald β Wald β Wald β Wald β Wald Constant -19.58 0.001 -2.29 21.33 -3.02 17.62 -2.07 2.96 -1.18 4.07 TBAPU (D) -1.21** 6.63 0.29 ns 0.77 -0.96** 4.02 -1.22 ns 3.07 -1.05** 5.97 SWS(D) 0.80** 2.42 1.63 ns 15.30 0.74 ns 1.23 -1.37 ns 4.40 2.78** 29.49 CCAPP(D) -3.60* 55.11 -3.61** 54.65 -0.69 ns 1.28 -5.17** 73.58 -3.90** 49.72 CNM (D) -1.58** 6.81 -3.41 ns 34.10 -2.94** 21.79 0.61 ns 0.87 -2.69** 16.84 EDWS (D) 1.83** 16.46 0.08 ns 0.08 0.98 ns 5.71 -2.39 ns 18.93 3.31** 65.42 UFS (D) 17.77 ns 2.38 3.63 ns 28.20 -4.94** 33.60 3.03 ns 6.35 -1.79* 5.84 UR (D) 1.24 ns 1.10 -2.94 ns 18.34 0.68 ns 0.35 -1.66 ns 2.95 -3.09** 18.31
TBAPU= Taking Bath after Pesticide Use, SWS= Smoking While Spraying, CCAPP= Change clothes after application of pesticides, CNM= Covering Nose and mouth, EDWS= Eat or drink while spraying, UFS= Using face shield, UR= Using respirator, D= Dummy (0=otherwise 1= Yes)
189
V. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary
To feed the world‘s ever growing population, the crop protection is of immense importance. Presently the crop safety is mostly achieved through various chemicals applied in various fashions in various crops and vegetables. Among these some of the chemicals are very injurious while others also have harmful aspects regarding their unsafe and unprotected application methods. To elaborate these harmful aspects, the present study was carried out to find out the health and environmental hazards of pesticides use in the farming community.
To find out these harmful aspects, a cross sectional survey was designed and respondents were selected through multistage sampling technique. In the first stage four districts were selected from the four agro-ecological zone of KP i.e. District Dera Ismail Khan (Southern Piedmont Plain), District Charsadda (Central Plain Valley), District Mansehra (Eastern Mountainous Zone) whereas District Swat was selected from Northern Mountainous Zone. In the second stage tehsils were selected from each selected district i.e. Tehsil Paharpur (D. I. Khan), Tehsil Charsada (Charsada), Tehsil Mansehra (Mansehra) whereas, Tehsil Matta was selected in Swat district. In the third stage from each selected Tehsil single Unions council was selected i.e. UC Band Kurai, Baidara, Khanmai and Baffa were selected from tehsil Paharpur, Matta, Charsadda and Mansehra respectively. Sample size of 384 respondents (96 from each UC) was selected for the present study. These respondents were evaluated for demographic, socio-economic, application method and knowledge of pesticides, health and environmental concerns of pesticides. Data were collected through well-structured interview schedule whereas, the analysis was made through SPSS ver. 20.
Demographic attributes revealed that almost all the respondents were educated and most of them (49.7%) were elder (>45 year) belonging to nuclear families (72.1%). It was also recorded that although most of the respondents (47%) had land holding <6 ha, 65.4% of the respondents were involved in full time farming having their own land (62%). Moreover, they had a good farming experience of 11-20 years and agriculture
190 was the main source of income of these respondents. They were mostly growing wheat, tomato, sugarcane, maize, radish, cucumber, turnip, onion and rice.
The respondents were also investigated regarding type of pesticides commonly used, their toxicity, dose and acquisition. It was observed that 81% farmers are dealing with almost all types of pesticides (insecticides, weedicides, fungicides) from more than 6 years and they mostly receive the pesticides from the local market (71.1%). 49 different pesticides were reported to be used having 25 insecticides, 14 weedicides and 10 fungicides. Among these, 25 pesticides were moderately hazardous (class II), 9 were slightly hazardous (class III) whereas only two insecticides (Carbofuron & Cartap) were from class Ib which has been declared as highly toxic by WHO standards. As the commonly used pesticides were toxic, the respondents were further investigated regarding the dosage of these pesticides. It was alarmingly observed that most of the respondents used high dose of pesticides than the recommended because they either consult the fellow farmers or salesmen having no idea of its side effects like health and environmental concerns. This scenario might cause serious health and environmental concerns because they are toxic and also used with more dose than the recommended. Moreover, the spraying decision might also be considered as serious concern on account of the reason that some of the farmers even not consult the extension worker or pesticide dealer, rather he sprays according to their own observations. Another health concern particularly in fruits and vegetables were that the produce was harvested only after few days (1-5 days) of pesticides application and brought to the market for consumer use. One of the possible reasons of this negligence might be that some of the farmers (41%) don‘t read or follow the labeled instructions.
The instant study envisaged that most of the farmers were unaware about the pictograms labels on the pesticides containers. Furthermore, it was found that the farmers were busy in unhealthy practices of pesticides application i.e. the precautionary measures were not followed by majority of the respondents and they re-enter the fields the following day of pesticides application; which results in many of the acute poisonous cases. The most common self-reported acute poisonous cases were headache, sneezing, cough, nausea, dizziness, feeling weak, difficulty in seeing, eye irritation, shortness of breath, burning sensation etc. Moreover, the knowledge of the farming community regarding the health and environmental hazards was also low.
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Similarly, the other unhealthy practices of pesticides observed were the re-spray of the leftover pesticides in the same season or in the upcoming season, disposing the left over pesticides in field or solid waste which was due to the fact that majority of the respondents had less knowledge about the judicious use of pesticides. In this connection the role of the Agriculture Extension Department (AED) was also not satisfactory. Almost half of the respondents got training regarding the pesticides application, and other health and environmental issues related to pesticides. The department not fully extended or imparted the knowledge about the highly toxic pesticides, calibration of pesticides, pesticides application techniques, safety measures, understanding the labels/instructions on pesticides containers etc.
5.2 Conclusions
From the present study the following conclusions were drawn…
Despite good literacy level, most of them do not care to read the instructions on the containers of pesticides and follow them. Due to which most farmers in the present study were not aware of the health hazards caused by the inappropriate handling of pesticides inspite of the fact that farmers were using pesticides for so many years. The farmers lacked knowledge on safe handling and use of pesticides which leads to improper usage of pesticides and ultimately may be ineffective, useless, wastage of time and money. Knowledge of pesticide selection, timing of application and harvesting period is very important to avoid health risks. However, the situation on ground may be attributed to the weak agriculture extension services and trainings. Farmers were taking risk of health because they have in-sufficient protection gears freely, cheaply or even not available to them on high cost. From the present study it can also be concluded that trainings had the sufficient role in the proper use of the pesticides by the farming community. Without training, farmers were unable to make good decisions of pesticides usage. Additionally, farmers would not be able to identify the active ingredients in pesticides to avoid their use. On the other hand the literacy status may also be taken from the angle that most of the literate farmers were busy in using pesticides because they want to control the pests with knock down effect instead of prolonged and safe way.
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The combination of use of hazardous pesticide in addition to lack of availability of appropriate precautionary gear and tools was detrimental to the farmers‘ health. The re- entry of farmers into the field for work after pesticides use was sometimes the following day. The continuation of pesticides spraying and other farming activities concurrently in the field, can lead to exposure to pesticides as the droplets in the form of mist may still be available in air of farmers spraying arena. From the instant study it was also concluded that the respondents were not aware of how and when to spray in order to achieve the proper results. Thus most of the farmers rely on salesman and agriculture extension agents. In this connection, it is also worth mentioning that most of the salesman may never be highly qualified or have an agriculture background to properly recommend when and how much spray the crops requires thus increasing the misuse of pesticides. On the other hand they mostly focus on business and profit thus they never care about the health and environment hazards of the pesticides. Similarly, agriculture extension department didn‘t train majority of the farmers which is documented in this study i.e. the use and handling of pesticides with lack of training, proper storage and disposal of pesticide containers, in addition to poor use of personal protective devices. All these lead to the miss use of pesticides.
From the instant study it was also concluded that majority of the respondents didn‘t focus on applying pesticides at the time close enough to harvest and putting life of the consumers at risk; specifically in vegetables and fruits. During the present study it was found that mostly the farmers were busy using pesticides from Class III, Class II, Class Ib, U and O and mostly rely on the pesticides from Organophasphates group which are dangerous for health. Similarly, it was also concluded from the present study that farmers were busy in overdosing and low dosing which in both cases cause problems for the farming community. In both the cases misuse of pesticides occurs i.e. by applying pesticides indiscriminately, is the violation of the scientific recommendations, storing them unsafely for the upcoming season and ignoring risks, safety instructions, and protective devices when applying pesticides and disposing containers seriously leads to the health and environmental issues.
Moreover, it can also be concluded from the instant study that majority of the farming community were not properly aware of the alternative techniques to the use of synthetic pesticides. If the exposure of the farming community may increase regarding
193 alternative techniques to synthetic pesticides the misuse of the pesticides may be dramatically controlled. IPM technique can significantly bring a change in the control of pests if properly followed. But from the present scenario, the IPM was not the matter of concern for the farming community thus they go for pesticides for direct, immediate and less laborious control. Similarly, it can also be concluded from the instant findings that majority of the respondents were not fully agreed with the facts that it harm the human, animal, wildlife, water life health, and accumulate in food chain etc. Overall, it can be concluded from the instant study that the farming community though were not mostly using pesticides from Class Ia or Ib but due to the lack of the precautionary measures, PPE, were not following the instruction etc. were the leading inputs which were posting pesticides as threat to the health and environment of the farming community.
5.3 Recommendations
Based on the present study findings, the following recommendations were put forward:
The farming community was in practice of direct use of chemical pesticides irrespective of their proper application time. This should be discouraged through massive campaign by the agriculture extension agents. Each and every category of pesticides is freely available in the market. The government should restrict the pesticide dealers to the sale of only slightly and moderately toxic pesticides whereas, the highly and extremely toxic pesticides need to be taken into account by the Agriculture Extension Department itself. The farmers have no knowledge of the alternate opportunities to reduce the health and environmental risks. They must be educated to reduce the use of pesticides and ultimately reduce the health and environmental risks due to misuse of pesticides. As the farmers were using the pesticides directly because they have no idea of using sticky traps, pheromone traps etc. thus they must be trained well to minimize the heavy use of pesticides and dependency over it. Farmers have very less use of PPEs which should be provide by the agriculture extension department on subsidized rates through MFSC/FSC or on rental basis.
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The results of present study showed that some of the farmers were using more toxic pesticides i.e. from WHO Class Ib. The Government regulatory authority should not only enact such rules but also implement those rules in true letter and spirit to eliminate/ban such highly toxic pesticides belonging to this class. As in the present study all of the respondents were literate and still they were not aware about the majority of precautionary measures and labels. Therefore, Agriculture Extension Department can take the help of mass media i.e. print and electronic media in order to aware the farmers regarding the hazard and safe use of pesticides. Trainings may be arranged specifically on the topics like, disposal of pesticides containers, selection of pesticides, how to read and identify the labels, ban and restricted pesticides, various precautionary measures, calibration, formulation, mixing of pesticides, what to do in emergency cases, teaching them how to calculate the requirements in order to avoid extra purchase and avoiding storing or disposing later on etc. The farming community must be properly trained. Above all, the Agriculture Extension Department should also make mandatory on the pesticide dealers to create awareness regarding the health and environmental issues of pesticides. Field days and demonstrations were reported by few of the respondents therefore, a need is felt to fill the gap by arranging the demonstrations and field days on the pesticides use. This is because demonstration is one of the best technique in which farmers learn practically. Seasonal slogans may be painted on the walls and places near farmers‘ fields regarding the recommended pesticides of those particular crops, along with precautionary measures. Seasonal farm clinics, FFS and Farmers Trainings Centers need to be established for long time in order to change the attitude of the farming community that they fully depend on pesticides. Introduction and utilization of drone technology for the application of pesticides under the supervision of Agriculture Extension Department with proper SOPs need to be initiated because it will help to minimize the occupational risk of the farming community and application by the professionals of the Agriculture Extension Department will help to minimize the miss-use of pesticides.
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Future research must be conducted for identifying the main factors which hinders the safe use of applying pesticides, identifying the constraints and gaps that why not the farming community are following the instructions of labels or reluctant to adopt precautionary measures.
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WHO. 2010. The WHO Recommended Classification of Pesticides by Hazard and Guidelines to Classification - 2009. ISBN 978-92-4-154796-3.
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Yamamoto, H. 2003. Assessing the Side Effect of Pesticide on Microbial Ecosystem in the Soil Environment. Journal of Pesticide Science. 28: 215–216.
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ANNEXURE-I
INTERVIEW SCHEDULE
INVESTIGATION INTO HEALTH & ENVIRONMENTAL HAZARDS OF PESTICIDES USE TO FARMING COMMUNITY IN KHYBER PAKHTUNKHWA, PAKISTAN
Note: The information gathered will be set confidential and the identity of the respondents will not be disclosed. All the results will be shown in overall manner.
Agro-Ecological Zone ______District______Date______Tehsil______Union Council______Village______
Personal Variables
1 Age ______a. <35 Years b. 35-45 Years c. >45 Years 2 Literacy Level ______a. Middle b. Matric c. Intermediate d. Above Intermediate 3 Family system:______a. Nuclear b. Joint 4 Tenancy Status:______a. Owner b. Owner cum Tenant c. Tenant 5 Land Holdings (Acres)______a. <6 Ha b. 6-10 Ha
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c. >10 Ha 6 Involvement in Farming:______a. Part Time b. Full Time 7 Farming Experience (years):______a. <11 Years b. 11-20 Years c. >20 Years 8 Major Source of Income:______a. Agriculture b. Govt. Employee c. Business d. Any other 9 What type of crop/vegetables/Fruit do you grow? (mention more than one)
Sr.# Crop/vegetable/fruit Yes No 9.1 Wheat 9.2 Rice 9.3 Sugarcane 9.4 Tomato 9.5 Onion 9.6 Gram 9.7 Maize 9.8 Okra 9.9 Lentil 9.10 Cucumber 9.11 Sponge gourd 9.12 Bitter gourd 9.13 Grapes 9.14 Mango 9.15 Date Palm 9.16 Palm
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9.17 Peach 9.18 Pear 9.19 Apricot 9.20 Pepper 9.21 Citrus 9.22 Apple
10 Since how long you are been using pesticides? (Years)______
a. <6 Years
b. 6-10 Years
c. >10 Years
11 Which pesticides you use most commonly.
a. Insecticides
b. Weedicides
c. Fungicides
d. Rodenticides
e. Any other
12 From where you bought pesticides
a. Local market b. FSC c. Directly from Companies sale man
13 At which stage you use pesticides
Sr.# Crop/Vegetable Seed treatment Just after sowing Any Other Stage 13.1 Wheat
13.2 Rice
13.3 Sugarcane
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13.4 Tomato
13.5 Onion
13.6 Gram
13.7 Maize
13.8 Okra
13.9 Lentil
13.10 Cucumber
13.11 Sponge gourd
13.12 Bitter gourd
13.13 Mango
13.14 Date Palm
13.15 Plam
13.16 Peach
13.17 Pear
13.18 Apricot
13.19 Persimmon
13.20 Turnip
13.21 Radish
13.22 Potato
13.23 Pepper
13.24 Citrus
13.25 Apple
14 What type of pesticides you use most commonly (mention brand name or AI)
a. ______b. ______c. ______
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d. ______e. ______f. ______g. ______h. ______i. ______j. ______k. ______l. ______
15 Who decide when to spray?
m. Self-decision n. Fellow farmer o. Agriculture extension agent p. Pesticide dealer q. Any other
16 From where you know about the doze of pesticide?
a. Agriculture Extension agent
b. Pesticides Label
c. Fellow Farmer
d. Pesticides Sales man
e. Other
17 Which of the spray time you follow?
a. Morning
b. After Noon
c. Evening
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18 On average how many time you spray or use chemical in a single crop/vegetables/fruit (per seasons)?
Sr.# Crop/vegetables/fruit No. of Sprays 1-2 3-5 Above 5 18.1 18.2 18.3 18.4 18.5 18.6 18.7 18.8 18.9 18.10
19 After how much time of pesticides application you use to pick produce?
No of Days Sr.# Vegetable/Fruit 1-2 3-5 Above 5 19.1
19.2
19.3 19.4
19.5
19.6 19.7
19.8
19.9 19.10
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20 Mark the Pictogram which you understand
Sr. # Pictogram Meaning Yes No Activity Pictogram
20.1 Handle Carefully-Liquid Product
Handle Carefully- powder or granules 20.2 product
20.3 Use a sprayer
Advisory Pictogram
20.4 Use protective gloves
20.5 Wash after use
20.6 Wear a mask
20.7 Wear a protective overall
20.8 Use a shield
20.9 Wear glasses
20.10 Wear boots
20.11 Wear respirator
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20.12 Wear Protective Clothing
Enviromental & Other hazards
20.13 Dangerous for livestock and poultry
20.14 Dangerous for wildlife
Dangerous for fish/do no contaminate 20.15 water
Keep locked away or out of reach from 20.16 children
20.17 Poison
20.18 Corrosive
20.19 Flammable
20.20 Explosive
Toxicity Levels Pictorgram
20.21 Slightly Hazardous (Caution)
20.22 Moderate Hazard (Warning)
20.23 Highly Hazard (Danger)
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Toxicity Levels Color Pictogram
Sr. # Pictogram Meaning Yes No
Red 20.24 Extremely Toxic (Oral Lethal Dose 1-50mg/kg)
Yellow 20.25 Highly Toxic (Oral Lethal Dose 50-500 mg/kg)
Blue 20.26 Moderately Toxic (Oral Lethal Dose 501-5000 mg/kg)
Green 20.27 Slightly Toxic (Oral Lethal Dose >5000 mg/kg)
21 Do you check the labels of the pesticides before applying?
a. Yes
b. No
22 If Yes do you follow those instructions?
a. Yes
b. No
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23 Farmer‘s dose of pesticides and purpose for which they use.
Farmer’s Recommended Sr.# Active ingredient Brand Name Pest Doze/Ha Dose/Ha 23.1 CHLORPYRIFOS 23.2 MONOCROTOPHOS 23.3 METHAMIDOPHOS 23.4 MANCOZEB 23.5 LAMBDA-CYHALOTHRIN 23.6 CYPERMETHRIN 23.7 TRICHLORFON 23.8 DIMETHOATE 23.9 FENVALERATE 23.10 ENDOSULFAN 23.11 DDT 23.12 DIMETHOATE 23.13 CYFLUTHRIN 23.14 DIALDRIN 23.15 METHYL PARATHIAN 23.16 CARBOFURAN 23.17 FURADON 23.18 CARBOSULFAN
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23.19 METALAXY 23.20 PROFENOFOS 23.21 FENIROTHION 23.22 BIFENTHRIN 23.23 PROFENOFOS 23.24 THIABENDAZOLE 23.25 PROPICONAZOL 23.26 FENVALERATE 23.27 EDIMETHOATE, 23.28 DELTAMETHRIN, 23.29 FENOXAPROP 23.30 ACETAMIPRID 23.31 FENPROPATHRIN 23.32 ABAMECTIN 23.33 BUPROFEZIN 23.34 BUTACHLOR 23.35 PENDIMETHALIN 23.36 PROFENOFOS 23.37 BETA – CYFLUTHRIN 23.38 TRIAZOPHOS 23.39 EMAMECTIN BENZOATE
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23.40 FENVALERATE 23.41 PYRIDABEN 23.42 BIFENTHRIN 23.43 INDOAXACARB 23.44 Any Other
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24. Precautionary measures farmers used during pesticides practices
Sr.# Particulars Categories Mark Yes 24.1 Using Mask during Spraying No Yes 24.2 Wearing Separate clothes for spray purpose No Do Nothing Action when pesticides came in contact with 24.3 Washing with water body Consult doctor Hand cover with clothes Hand cover with Hand covering material while Mixing of 24.4 Plastic bag pesticides Hand cover with Gloves Bear Hand Yes 24.5 Taking a bath after pesticide application No Yes 24.6 Smoking during pesticides application No Burned Disposed with usual What you do with empty bottles etc. of trash 24.7 pesticides Use in house Throwing away alongside fields Yes 24.8 Change clothes after application of pesticides No Yes 24.9 Wearing Boots while spraying No Yes 24.10 Using mixture equipment No
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Cover nose and mouth with any other thing Yes 24.11 (cloth) No Do you know in which direction of wind to Yes 24.12 apply spray No Do you mix pesticides in open air or close Open air 24.13 room? Close room Yes 24.14 Do you use to eat or drink while spraying? No Yes 24.15 Using Goggles No Yes 24.16 Using glasses No Yes 24.17 Face shield No Yes 24.18 Do you use Respirator No 24.19 Any Other
25 Farmers knowledge about miss use of pesticides
Sr.# Items Yes No
25.1 Using of banned agriculture pesticides
25.2 Knowledge of proper nozzles
25.3 Knowledge of ET level of particular pest
25.4 Knowledge about mode of action
25.5 Knowledge about the expiry of pesticides
25.6 Knowledge of pesticides concentration and proper solution preparation
25.7 Using high doze than recommended
25.8 Knowledge about the toxicity levels of pesticides
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26 Entrance to the field after application of pesticides?
a. On the following day
b. After two days
c. More than two days
27 What do you think how pesticides enter the body?
a. Skin
b. Breath
c. Eye
d. Mouth
28 Self-reported symptoms of pesticides poisoning
Sr.# Symptom Yes No 28.1 Headache 28.2 Excessive sweating 28.3 Itching 28.4 Sneezing 28.5 Cough 28.6 Stomach ach 28.7 Nausea 28.8 Dizziness 28.9 Feeling weak 28.10 Excessive sweating 28.11 Diarrhea 28.12 Difficulty in Seeing 28.13 Eye irritation 28.14 Fatigue 28.15 Shortness of Breath 28.16 Fever 28.17 Sleeplessness/insomnia
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28.18 Chest pain 28.19 Blisters 28.20 Catarrh 28.21 Body pain 28.22 Burning sensation 28.23 Any Other
29 Among the following mark the extent about harmful environmental effect of pesticides according to the best of your knowledge.
Don’t Sr.# Hazards Low Medium High Know 29.1 Cause damage to human health 29.2 Cause damage to animal health 29.3 Cause damage to wildlife 29.4 Cause damage to water life 29.5 Kills pollinators 29.6 Effects soil fertility 29.7 Damage to the useful organisms in soil 29.8 Accumulates in food chain 29.9 Pesticides usage causes resurgence of pest population after removing natural enemies. 29.10 Cause air contamination 29.11 Any Other
30 Where do you dispose the left over pesticides?
a. In the Field
b. In canalization
c. In solid waste disposal
d. Re-spray
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e. Other Specify
31 Judicious use of pesticides
Sr.# Particulars Yes No 31.1 Applying chemical at Economic Threshold Level 31.2 Knowledge about the Compatibility of chemicals with natural enemies 31.3 Recommended doze 31.4 Right Time of application 31.5 Proper Application technology 31.6 Use of soft insecticide 31.7 Integration of Pesticides with IPM techniques 31.8 Any Other
32 Do you have you knowledge about the alternative techniques to synthetic pesticides?
Sr.# Alternative techniques 1 2 3 4 5 32.1 Bio pesticides (prepared out of plants) 32.2 Organic farming 32.3 Crop rotation 32.4 Cultivating crop mixtures 32.5 Cultivation of trap crops 32.6 Using traps 32.7 Light traps 32.8 Hot and cold treatment 32.9 Cultivation of insect resistant variety 32.10 Cultivation of disease resistant variety (in case of diseases) 32.11 Cultivation of weeds free seed (in case of weeds) 32.12 Crop residual removal 32.13 Using parasites
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32.14 Avoiding imbalance doze of pesticides 32.15 Only those pesticides should be sprayed which are registered (in case of high risk) 32.16 Timely shallow tillage to reduce weeds population 32.17 Timely sowing to reduce pest pressure at their optimum stage 32.18 Parasitoids 32.19 Use of soap for control of pests. 32.20 Any Other
33 Was any training given to you by Extension department regarding pesticides application?
a. Yes
b. No
If yes what type of training?
Sr.# Training Yes No 33.1 How to use 33.2 Health and safety 33.3 IPM 33.4 Trained in disposal 33.5 Application technology 33.6 Trained on environmental effects 33.7 Symptoms and treatment for poisoning 33.8 Environmental hazards due to use of pesticides 33.9 How to calibrate pesticides 33.10 Application techniques 33.11 Safety measures to be taken while spraying 33.12 Understanding the labels 33.13 Biological Control
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33.14 Augmentative measures 33.15 Any Other
34 Do any field day conducted regarding the safe application of pesticides?
a. Yes
b. No
35 Do any FFS activity conducted by extension department regarding application of pesticides?
a. Yes
b. No
36 Do extension workers visit your field for monitoring regarding pesticides application?
a. Yes
b. No
37 Do you contact Extension department right before spraying?
a. Yes
b. No
38 Do extension department ever demonstrated pesticides application to you?
a. Yes
b. No
39 Do extension worker provide information regarding pest resistant varieties?
a. Yes
b. No
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40 Do Extension worker provide information regarding mechanical control of pests?
a. Yes
b. No
41 Do extension worker provide information regarding cultural practices to minimize the pest attack?
a. Yes
b. No
42 Do extension worker provide information regarding highly toxic pesticides?
a. Yes
b. No
43 Do extension worker provide information regarding time of pesticides application?
a. Yes
b. No
44 Any Suggestion______
______
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ANNEXURE-II
GLOSSARY
Acetyl Cholinesterase: Acetylcholinesterase (HGNC symbol ACHE), also known as AChE or acetylhydrolase, is the primary cholinesterase in the body. It is an enzyme that catalyzes the breakdown of acetylcholine and of some other choline esters that function as neurotransmitters.
Acetylcholine: Acetylcholine (ACh) is an organic chemical that functions in the brain and body of many types of animals, including humans, as a neurotransmitter—a chemical released by nerve cells to send signals to other cells.
Acne: is a long-term skin disease that occurs when hair follicles are clogged with dead skin cells and oil from the skin.
Acute Poisoning: Acute toxicity describes the adverse effects of a substance that result either from a single exposure or from multiple exposures in a short period of time (usually less than 24 hours). To be described as acute toxicity, the adverse effects should occur within 14 days of the administration of the substance
Aluminium Phosphate: Aluminum Phosphate is an odorless, white crystalline solid which is often used in liquid or gel form. It is used in ceramics, dental cements, cosmetics, paints, paper and pharmaceuticals.
Anxiety: Anxiety is a general term for several disorders that cause nervousness, fear, apprehension, and worrying.
Attention Deficit Hyperactive Disorder: Attention deficit hyperactivity disorder (ADHD) is a mental disorder of the neurodevelopmental type. It is characterized by problems paying attention, excessive activity, or difficulty controlling behavior which is not appropriate for a person's age.
Avermectins: Any of a group of compounds with strong anthelmintic properties, isolated from a strain of bacteria.
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Carbamates: A carbamate is an organic compound derived from carbamic acid. A carbamate group, carbamate ester, and carbamic acids are functional groups that are inter-related structurally and often are interconverted chemically.
Carcinogenic Action: Producing or tending to produce cancer. The carcinogenic action of certain chemicals.
Catarrh: Excessive discharge or build-up of mucus in the nose or throat, associated with inflammation of the mucous membrane
Central nervous system: the complex of nerve tissues that controls the activities of the body. In vertebrates it comprises the brain and spinal cord.
Chromium-Copper-Arsenate: Chromated copper arsenate is a wood preservative that has been used for timber treatment since the mid-1930s. It is a mix of chromium, copper and arsenic formulated as oxides or salts, and is recognizable for the greenish tint it imparts to timber.
Chronic Poisoning: Chronic toxicity is the development of adverse effects as the result of long term exposure to a toxicant or other stressor.
Citronella: Citronella oil is one of the essential oils obtained from the leaves and stems of different species of Cymbopogon (lemongrass).
Cloracne: Chloracne is an acne-like eruption of blackheads, cysts, and pustules associated with over-exposure to certain halogenated aromatic compounds, such as chlorinated dioxins and dibenzofurans.
Contact pesticides: A contact pesticide is a pesticide designed to exterminate pests directly upon contact.
Convulsions: A sudden, violent, irregular movement of the body, caused by involuntary contraction of muscles and associated especially with brain disorders such as epilepsy, the presence of certain toxins or other agents in the blood, or fever in children.
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Cramps: Menstrual cramps happen because of contractions in the uterus, or womb, which is a muscle. If it contracts too strongly during your menstrual cycle, it can press against nearby blood vessels. This briefly cuts off the supply of oxygen to the uterus. It's this lack of oxygen causes your pain and cramping.
Cross Sectional Data: A type of data collected by observing mini subjects (Such as individuals, firms, countries or regions) at the same point of time, or without regard to differences in time.
Cyanide: is a chemical compound that contains the group C≡N. This group, known as the cyano group, consists of a carbon atom triple-bonded to a nitrogen atom.
Cytogenetic: Cytogenetics is a branch of genetics that is concerned with how the chromosomes relate to cell behaviour, particularly to their behaviour during mitosis and meiosis.
Defoliant: a chemical that removes the leaves from trees and plants
Deoxyribonucleic Acid: Deoxyribonucleic acid is a thread-like chain of nucleotides carrying the genetic instructions used in the growth, development, functioning and reproduction of all known living organisms and many viruses
Depression: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act.
Desiccant: a hygroscopic substance used as a drying agent
Disorientation: the condition of having lost one's sense of direction.
Dithio-carbamates: A dithiocarbamate is a functional group in organic chemistry. It is the analog of a carbamate in which both oxygen atoms are replaced by sulfur atoms
Electrophiles: An electrophile is a reagent attracted to electrons. Electrophiles are positively charged or neutral species having vacant orbitals that are attracted to an electron rich centre. It participates in a chemical reaction by accepting an electron pair in order to bond to a nucleophile.
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Endocrine: Endocrine glands are glands of the endocrine system that secrete their products, hormones, directly into the blood rather than through a duct. The major glands of the endocrine system include the pineal gland, pituitary gland, pancreas, ovaries, testes, thyroid gland, parathyroid gland, hypothalamus and adrenal glands.
Enzyme: Enzymes are macromolecular biological catalysts. Enzymes accelerate chemical reactions.
Error term: it is the difference between observed Y and the true regression equation (The expected value of Y). Error term is a theoretical concept that is never be observed.
Esters: An organic compound made by replacing the hydrogen of an acid by an alkyl or other organic group.
ETL: The economic threshold is the density of a pest at which a control treatment will provide an economic return.
Farm Field School: The Farmer Field School (FFS) is a group-based learning process that has been used by a number of governments, NGOs and international agencies to promote various agricultural activities.
Farm Services Center: A public private partner approach through which farmers are been benefited by providing them the inputs at subsidized rates, trainings and services.
Fatality Rate: The ration of deaths in an area to the population of that area; expressed per 1000 per year.
Genetic Material: In terms of modern molecular biology and genetics, a genome is the genetic material of an organism. It consists of DNA. The genome includes both the genes and the noncoding DNA, as well as the genetic material of the mitochondria and chloroplasts.
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Genotoxic Effect: In genetics, genotoxicity describes the property of chemical agents that damages the genetic information within a cell causing mutations, which may lead to cancer.
Heavy Metals: a metal of relatively high density, or of high relative atomic weight
Hepatorenal Disorders: is the development of renal failure in patients with advanced chronic liver disease, occasionally fulminant hepatitis, who have portal hypertension and ascites
Homogeneity of data: In data analysis, a set of data is also consideredhomogeneous if the variables are one type (i.e. binary or categorical); if the variables are mixed (i.e. binary + categorical), then the data set is heterogeneous.
Hydroxyl group: A hydroxy or hydroxyl group is the entity with the formula OH. It contains oxygen bonded to hydrogen.
Hypersensitivity: Hypersensitivity (also called hypersensitivityreaction or intolerance) undesirable reactions produced by the normal immune system, including allergies and autoimmunity. They are usually referred to as an over- reaction of the immune system and these reactions may be damaging, uncomfortable, or occasionally fatal.
Immune system: the organs and processes of the body that provide resistance to infection and toxins. Organs include the thymus, bone marrow, and lymph nodes.
Immune: Resistant to a particular infection or toxin owing to the presence of specific antibodies or sensitized white blood cells.
Integrated Pest Management: Integrated pest management (IPM), also known as integrated pest control (IPC) is a broad-based approach that integrates practices for economic control of pests. IPM aims to suppress pest populations below the economic injury level (EIL).
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Leukemia: Leukemia is a malignancy (cancer) of blood cells. Inleukemia, abnormal blood cells are produced in the bone marrow.
Livelihood: a means of securing the necessities of life.
Metabolic: relating to or deriving from the metabolism of a living organism.
Methyl Bromide: Bromomethane, commonly known as methyl bromide, is an organobromine compound with formula CH₃Br. This colorless, odorless, nonflammable gas is produced both industrially and particularly biologically.
Mutagenic: is a physical or chemical agent that changes the genetic material, usually DNA
Mutagens: An agent, such as radiation or a chemical substance, which causes genetic mutation.
Mutations: a mutation is the permanent alteration of the nucleotide sequence of the genome of an organism, virus, or extrachromosomal DNA or other genetic elements.
Neuritis: inflammation of a peripheral nerve or nerves, usually causing pain and loss of function.
Neurodegenerative: resulting in or characterized by degeneration of the nervous system, especially the neurons in the brain.
Neurology: Neurology is a branch of medicine dealing with disorders of the nervous system.
Neurotransmitter: Also known as chemical messengers, are endogenous chemicals that enable neurotransmission.
Nicotine Sulfate: Nicotine Sulfate is a white, sand-like solid. It is used as an insecticide, fumigant and medication for animals.
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Nicotinoid: The neonicotinoid family includes acetamiprid, clothianidin, imidacloprid, nitenpyram, nithiazine, thiacloprid and thiamethoxam. Imidacloprid is the most widely used insecticide in the world. Compared to organophosphate and carbamate insecticides, neonicotinoids cause less toxicity in birds and mammals than insects.
OLS: The ordinary least square or OLS is also called as the linear least squares. This method is used for approximately determining the unknown variables located in linear regression model.
Organochlorines: large group of pesticides and other synthetic organic compounds with chlorinated aromatic molecules.
Organochlorines: Any of a large group of pesticides and other synthetic organic compounds with chlorinated aromatic molecules.
Organophosphates: An organophosphate or phosphate ester is the general name for esters of phosphoric acid. Organophosphates are the basis of many insecticides, herbicides, and nerve agents.
Organophosphates: Organophosphates are the basis of many insecticides, herbicides, and nerve agents.
Organophosphorus chemical group: Denoting synthetic organic compounds containing phosphorus, especially pesticides and nerve gases of this kind.
Paranoid behavior: Paranoid personality disorder (PPD) is a mental disorder characterized by paranoia and a pervasive, long-standing suspiciousness and generalized mistrust of others.
Parkinson’s disease: Parkinson's disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system
Perspiration: the process of sweating
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Plant-Growth Regulator: There are currently five recognized groups of plant hormones: auxins, gibberellins, cytokinins, abscisic acid (ABA) and ethylene. They work together coordinating the growth and development of cells.
Psychiatric: Psychiatry is the medical specialty devoted to the diagnosis, prevention, study, and treatment of mental disorders.
Pyrethroids: A pyrethroid is an organic compound similar to the natural pyrethrins produced by the flowers of pyrethrums. Pyrethroids constitute the majority of commercial household insecticides
Rotenone: A derivative of roots of tropical vegetables
Salivation: The act or process of salivating
Standard Deviation: In statistics, the standard deviation (SD, also represented by the Greek letter sigma, σ for the population standard deviation or s for the sample standard deviation) is a measure that is used to quantify the amount of variation or dispersion of a set of data values
Standard Error: The standard error (SE) is the standard deviation of the sampling distribution of a statistic, most commonly of the mean. The term may also be used to refer to an estimate of that standard deviation, derived from a particular sample used to compute the estimate.
Systematic Pesticides: Systemic pesticides are chemicals that are actually absorbed by a plant when applied to seeds, soil, or leaves. The chemicals then circulate through the plant's tissues, killing the insects that feed on them.
Triazoles: A triazole (Htrz) refers to any of the heterocyclic compounds with
molecular formula C2H3N3, having a five-membered ring of two carbon atoms and three nitrogen atoms.
Ultra Low Volume processor: Ultra-low volume application of pesticides has been defined as spraying at a Volume Application Rate (VAR) of less than 5 L/ha for
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field crops or less than 50 L/ha for tree/bush crops. VARs of 0.25 – 2 l/ha are typical for aerial ULV application to forest or migratory pests.
Xenobiotic: Relating to or denoting a substance, typically a synthetic chemical, which is foreign to the body or to an ecological system.
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ANNEXURE-III
Map of Pakistan and KP Province is highlighted in Box.
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ANNEXURE IV
Map of KP Province Showing the Sampled Districts
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ANNEXURE V
Map of district D.I.Khan Showing the sampled Tehsil
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ANNEXURE VI
Map of Charsada District Showing the Sampled Tehsil
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ANNEXURE VII
Map of District Mansehra showing the Sampled Tehsil
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ANNEXURE VIII
Fig. 3.6 Map of District Swat showing the Sampled Teshsil
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ANNEXURE-IX
PESTICIDES RECOMMENDED FOR VARIOUS PESTS
INSECTICIDES RECOMMENDED FOR DIFFERENT INSECT PESTS
Insect Insecticide (Brand Name) Dose
Thrips Carbosulfan 20 EC (Advanatage) 500ml/acre Endosulphan 35 EC (Thiodan) 800 ml/acre Imidacloprid 200SL (Confidor) 80-100ml/acre Thrips and mites Chloropyrifos+Cypermthrin 440 EC 500-600ml/acre (Polytrin C)(Nurelle D 505 EC) Mites Diafenthiuron 500EC (Polo) 200ml/acre: Spray twice Jassids Carbosulfan 20 EC (Advanatage) 500ml/acre Buprofezin2 5 WP (Fuzin) 500gm/acre Imidacloprid 70 WS Seed Treatment: 8-10g/Kg seed Whitefly Imidacloprid 200SL (Confidor) 250ml/acre Buprofezin2 5 WP (Fuzin) 500gm/acre Acetamiprid 20 SL (Acelan) 125 to150 ml/acre Aphids Carbosulfan 20 EC (Advanatage) 500ml/acre Buprofezin2 5 WP (Fuzin) 500gm/acre
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Cotton Bollworm Emmamectin Benzoate 5 EC (Timer) 75ml/acre Triazophos 40 EC (Diplomat) 1000 ml/acre Spotted Bollworm Bifenthrin + Abametin 56EC (Novastar) 500ml/acre Army worm Emmamectin Benzoate 5 EC (Timer) 75ml/acre Thiodicarb 80 DF (Larvan) 400gm/acre Abamectin 1.8 EC (Shevar) 200-250ml/acre Chlorpyrifos 40 EC(Lorsban) 700-1000 ml/acre Cotton Mealy Bug Profenofos 500 EC (Curacron) 800-1000ml/acre +50 ml Dettol or 50 ml Surf for effective control Bipheathrin 10 EC (Talstar) 250-300ml/acre(For Better results mix one table spoon Surf per 20 liters) Pink bollworm Chloropyrifos+Cypermthrin 440 EC 500-600ml/acre (Polytrin C)(Nurelle D 505 EC) Stem Borers Carbofuran 3G (Furadan) 1st Application: 10 Kg/ Acre 30-35 days after first transplantion. 2nd Application: 10 Kg/ Acre 55-60 days after first transplantion. White Backed Plant Hopper Carbosulfan 20 EC (Advanatage) 500ml/acre Cutworm Chlorpyrifos 40 EC (Helmet) Chemigation @1 to 1.5 Lit/acre Carbaryl 85% 1 Kg/ acre
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Whitefly Acetamiprid 20SL (Rani) 125 ml/acre Leafminer Cyromazine 75 WP (Fon) 20-30 gms/100 liter water or 20-30kg/acre Jassid and aphids Imidacloprid 200 SL (Crown) 80 ml/acre Tomato Fruit Borer Emmamectin Benzoate 5 EC 50ml/acre (Timer) Fruitfly Indoxacarb 150 SC (Stward) 1 ml/liter water Codling Moth Carbosulfan 20 EC (Advanatage) 300ml/ 100 Lit Water Abamectin 1.8 EC (Shaver) 200-250ml/100 liter water Apple Mite Bifenthrin 10 EC (Talstar) 60 ml/120 Lit Water Budworms Chlorpyrifos 40 EC (Helmet) Chemigation @ 1.5 to 2 Lit/acre, when the crop is 15-20 days old Top Borer Carbofuran 3G (Furadon) 1st Application: 10 Kg/acre at sowing or when crop has completed emeregence 2nd Application: 14 Kg/acre at last hoeing at the time of earthing up 3rd Application: Emergency conditions apply Root borer Carbofuran 3G (Furadon) 1st Application: 10 Kg/acre at sowing or when crop has completed emeregence 2nd Application: 14 Kg/acre at last hoeing at the time of earthing up
260
3rd Application: Emergency conditions apply Stem Borer Carbofuran 3G (Furadon) 1st Application: 10 Kg/acre at sowing or when crop has completed emeregence 2nd Application: 14 Kg/acre at last hoeing at the time of earthing up 3rd Application: Emergency conditions apply Termites Biphenthrin 10 EC (Talstar) Chemigation:250ml/acre Maize Borer Carbofuran 3G (Furadon) 1st Application: Apply with seed at the time of sowing 2nd Application: 5 Kg/acre at 3-5 leaf crop stage3rd Application: 8 Kg/acre when the crop is at 2-3 ft height. Termites Bipheathrin 10 EC (Talstar) 250ml/acre Mango Hopper Biphenthrin 10 EC (Talstar) 20ml/100Lit Water Citrus Leaf Miner Biphenthrin 10 EC (Talstar) 20ml/100Lit Water Diamond Blackmoth Methomyl 40 SP (Lannate) 330-500gm/100 liter water per acre Fenvalerate 25 EC 100ml/100lit H2o peracre Indoxacarb 150 SC (Stward) 1.0ml/liter water
261
FUNGICIDES RECOMMENDED FOR DIFFERENT DISEASES
Diseases Fungicides (Brand Name) Dose Rust Triadimefon (Bayleton 25 WP (S)) 4gm/liter Late Blight Azoxystrobin (Primacy 25% SC) 200 ml Loose Smut Benomyl(Benlate 50 WP) 2 gm/kg seed Powdery Mildew Bupirmate(Nimrod 25 EC) 100 ml (or 1 ml/lit. water) Early Blight Carbendazim 40%+ triadimefon 10% (Soleton 50% WP) 240 gm Citrus Canker Copper Hydroxide (Champion 77% WP) 200 gm Anthracanose Copper Hydroxide (Champion 77% WP) 200 gm Rice Blast Difenoconazole (Score 250 EC) 20 ml/lit. water Downy Mildew Difenoconazole (Score 250 EC) 20 ml/lit. water Brown Leaf-spot Difenoconazole (Score 250 EC) 20 ml/lit. water Late & Early Blight Propiconazole(Spectrum 30% EC) 200 ml Gummosis Fosetyl-aluminium (Aleitte 80 WP) 250 gm/ 100 lit. water Collar Rot Fosetyl-aluminium + Mancozeb (Alligate 70 WP) 400 gm Sheath Blight Hexaconazole 400 ml Bark Splitting Mancozeb (Dithane M-45 80 WP) 2 gm/lit. water
262
Black Scurf Penflufen (Emesto 24% FS) 10 ml/100 kg seed Brown Leaf Spot Sulphur (Thiovit 80% WG) 1000 gm Yellow Rust Tebuconazole (Folicure 430 SC) 120 ml Gummosis & Withertip Metiram+ Pyraclostrobin(Cabrio Top 60% WDG (55% w/w +5% w/w) 300gm
WEEDICIDES RECOMMENDED FOR DIFFERENT WEEDS
Weed Weedicide (Brand Name) Dose Broad leaf,weeds & grasses in onion Oxyfluorfen(Oxygen 24% EW) 30 ml Broad leaf,weeds & grasses in Cotton, Acetochlor (Caster Gold 50% EW) 500 ml Maize Broad leaf,weeds & grasses,sedges in Nicosulfuron 2% + Atrazine 20% + Propisochlor 15% (Shift 37% OD) 800 ml maize Broad leaf,weeds in Maize Atrazine(Clark plus 80% WDG) 180 g Broad leaf,weeds in wheat Tribenuron Methyl 3.5% + Fenoxaprop-P-Ethyl 15% (Forward 18.5% WP) 300 g Broad leaf,weeds & grasses,sedges in Mesotrion 5% + Atrazine 50% (Fallisto Gold 55% SC) 400 ml maize Broad leaf,weeds & grasses,sedges in S-Metolachlor (Dual Gold 960 EC) 800 ml Chillies Broad leaf weeds in wheat Bromoxynil + MCPA (Buctril super) 500 ml
263
ANNEXURE-X
LIST OF REGISTERED PESTICIDES COMPANIES IN KHYBER PAKHTUNKHWA
Abdul Haseeb Agro Chemical Advance Agro tech Ag Nova Life Sciences Ag Pharma Agreen Pakistan Agri Force Chemicals Agri Tas Enterprises Agrica Chemicals Agrotree Life Sceiences Agro Limited Al Abbas Agro Chemicals Ali Akbar Enterprises AMB Agro Division Anqa Agro pesticides Arysta Life Sciences Auriga Chemical Enterprises Ayan Crop Sciences Bayer Pakistan (Pvt) Limited Bio Care Services Bio Track Enterprises Bravo CS Corporation Capricon Associates Agro Chemical Division Chem and Chem Private Limited Cherwel Enterprises Private Limited Chinar Agro Trade Crop Care Pesticides Crop Max Pesticides Crop Top Agro Services Cropsy
264
Dada Jee Corporation Data Jee Coporation Dela Agro Services Eden Bio Sciences EDGRO Private Limited Exin Chemicals Corporation FMC United Private Limited Four Brother Agri Services Pakistan Four Star Agro Services Friends Agro Chemicals Gallan International Global Care Grace Chemical Company Green Crop Agri Services Green EVO Chemicals Green Gro Private Limited Green Land Protection Green Revolution Private Limited Green Zone Greenlet International Hashir International Haven Chemicals Hextar Chemical Enterprises HR Pakistan Limited ICI, Pakistan Limited Imerial Agro Sciences (Tara) Jaffar Agro Services Jullundar Private Limited Kanzo AG Kareem Chemical Khan Agro Chemical Leader Ag
265
LT Enterprises Private Limited M and A Agri Products Co M.I Corporation Mag Agro Chemicals Market Development Solution Matanza Life Sciences Monsonto Pakistan Private Limited Multi-Max Enterprises National Chemicals NEO Life Sign Agritrading International Private Limited Nova Tech Crop Technology Nuchem Private Limited Orange Protection Private Limited Pak Farming Care Pak Pansy Enterprises Patron Chemicals Pearl Agro Tech Private Limited Plant for life Private Limited Prime Agri Services R.B Avari Enterprises Private Limited Roots International Roshan Crop Sciences Royal Chemicals Private Limited Royal Crop Sciences Rudolf Life Sciences Saver Agro Services Sayban International Shafique and Co Sino Pak Chemicals Sky Agro Chemicals Solex Chemical Private Limited STEDEC Technology Commercialization Corporation of Pakistan (Pvt.) Ltd.
266
Sun Crop Pesticides Sungro Private Limited Sunway Agro Chemicals Company Swat Agro Chemicals Syngenta Pakistan Limited Tara Crop Sciences Private Limited Tara Imperial Industries Private Limited Top Sons Agro Chemicals Company Private Limited Topsun Chemical Enterprises Total Care Pesticides UK Chemicals United Distributors Pakistan Vantage Chemicals Private Limited Ventus Agro Private Limited Victorri Chemicals Private Limited Warble Private Limited Weal-AG Corporation Welcon Chemicals Private Limited Zaryab Agro Services Ag Spark Crop Protection Division Al Noor Chemicals Comega Life Sciences Private Limited United Agro Services
267
ANNEXURE-XI
WORLD’S RANKING OF PESTICIDE USE PER ACRE Sr. No Country Ranking Pesticides use Kg/acre 1 Costa Rica 1 51.2 2 Colombia 2 16.7 3 Netherlands 3 9.4 4 Ecuador 4 6 5 Portugal 5 5.3 6 France 6 4.6 7 Greece 7 2.8 8 Uruguay 8 2.7 9 Suriname 9 2.6 10 Honduras 10 2.5 11 Germany 10 2.5 12 Austria 12 2.4 13 Dominican Republic 13 2.1 14 Ireland 14 1.8 15 Slovakia 14 1.8 16 Paraguay 16 1.5 17 Denmark 17 1.4 18 Jordan 17 1.4 19 Czech Republic 19 1.3 20 Pakistan 19 1.3 21 Turkey 19 1.3
268
ANNEXURE-XII
IMPORTS OF PESTICIDES TO PAKISTAN Year Qty. (Tonnes) Value (Million Rs.) 2000-01 21,255 3,477 2001-02 31,783 5,320 2002-03 22,242 3,441 2003-04 41,406 7,157 2004-05 41,561 8,281 2005-06 33,954 6,804 2006-07 29,089 5,848 2007-08 27,814 6,330 2008-09 28,839 8,981 2009-10 38,227 13,473 2010-11 36,183 13,178 2011-12 32,152 12,255 2012-13 17,882 8,507 2013-14 23,546 12,572 2014-15 23,157 14,058 2015-16 15,540 12,089 Source: Nation Master, 2000
269
ANNEXURE-XIII GENERAL DESCRIPTIONS OF PESTICIDES Pesticides used in Formulations Concentrations Containers different settings Agricultural liquid, gel, paste, from 2% to 80% of glass, plastic or metal Veterinary chalk, powder, active ingredient flasks, bottles, drums, Domestic granules, pellets, traps, plastic bags or Institutional baits paper bags
ANNEXURE-XIV ACUTE TOXICITY OF PESTICIDES
LD for the rat (mg/kg body weight) Class Classification 50 Oral Dermal
Ia Extremely Hazardous <5 <50
Ib Highly Hazardous 5–50 50-200
II Moderately Hazardous 50-2000 200-2000
III Slightly Hazardous Over 2000 Over 2000 U Unlikely to Present Acute Hazard 5000 or Higher WHO classification (Adapted from WHO, 2009)
270
ANNEXURE-XV BANNED PESTICIDE IN PAKISTAN
Sr.# Active Ingredient Sr. # Active ingredient
1 BHC 15 Dicrotophos
2 Binapacryl 16 Ethylenedichloride+Carbontetrachloride
3 Bromophos 17 Leptophos
4 Ethyl 18 Mercury compound 5 Captafol 19 Mevinphos
6 Chlordimeform 20 Toxaphene
7 Chlorobenzilate 21 Zineb
8 Chlorthiophos 22 Heptachlor
9 Cyhexatin 23 Methyl 10 Dalapon 24 Parathion 11 DDT 25 Monocrotophos
Dibromochloropropane+ 12 26 Methamidophos Dibromochloropropene
13 Dieldrin 27 Endosulfan
14 Disulfoton 28 Endrin Source: GOP, 2015
271
ANNEXURE XVI WHO PESTICIDES HAZARD CLASSIFICATION
Extremely hazardous (Class Ia) technical grade active ingredients in pesticides
Common name CAS no UN Chem Phys Main GHS LD50 Remarks no type state use mg/kg
DS 53; EHC 121; HSG 64; IARC 53; ICSC 94; JMPR 1993, Aldicarb [ISO] 116-06-3 2757 C S I-S 1 0.93 1996a
Brodifacoum [ISO] 56073-10-0 3027 CO S R 1 0.3 DS 57; EHC 175; HSG 93
Bromadiolone [ISO] 28772-56-7 3027 CO S R 1 1.12 DS 88; EHC 175; HSG 94
Bromethalin [ISO] 63333-35-7 2588 S R 1 2
Calcium cyanide [C] 592-01-8 1575 S FM 2 39 Adjusted classification; see note 1; ICSC 407
Captafol [ISO] 2425-06-1 S F 5 5000 Adjusted classification; see note 2; HSG 49; IARC 53; ICSC 119; JMPR 1978, 1986a; see note 3
Extremely hazardous by skin contact (LD50 = 12.5 mg/kg); ICSC Chlorethoxyfos [ISO] 54593-83-8 3018 OP L I 1 1.8 1681 Chlormephos [ISO] 24934-91-6 3018 OP L I 2 7 ICSC 1682
Chlorophacinone [ISO] 3691-35-8 2588 S R 1 3.1 DS 62; EHC 175
Difenacoum [ISO] 56073-07-5 3027 CO S R 1 1.8 EHC 175; HSG 95
Difethialone [ISO] 104653-34-1 2588 S R 1 0.56 EHC 175
Diphacinone [ISO] 82-66-6 2588 S R 1 2.3 EHC 175
Disulfoton [ISO] 298-04-4 3018 OP L I 1 2.6 DS 68; JMPR 1992, 1997a; ICSC 1408
EPN 2104-64-5 2783 OP S I 2 14 See note 4; ICSC 753
Ethoprophos [ISO] 13194-48-4 3018 OP L I-S 2 D26 DS 70; JMPR 2000; ICSC 1660; [Oral LD50 = 33 mg/kg] Flocoumafen 90035-08-8 3027 S R 1 0.25 EHC 175; ICSC 1267
Adjusted classification (notes 3 and 5); IARC 79; ICSC 895; EHC Hexachlorobenzene [ISO] 118-74-1 2729 OC S FST 5 D10000 195
Mercuric chloride [ISO] 7487-94-7 1624 HG S F-S 1 1 See note 3; ICSC 979
272
Mevinphos [ISO] 26718-65-0 3018 OP L I 1 D4 DS 14; ICSC 924; JMPR 1998b; [Oral LD50 = 3.7 mg/kg] See note 3; DS 6; HSG 74; IARC 30, Suppl. 7; ICSC 6; JMPR Parathion [ISO] 56-38-2 3018 OP L I 2 13 1996b
See note 3; DS 7; EHC 145; HSG 75; ICSC 626; JMPR 1985c, Parathion-methyl [ISO] 298-00-0 3018 OP L I 2 14 1996b Phenylmercury acetate [ISO] 62-38-4 1674 HG S FST 2 24 Adjusted classification; see notes 3 and 6; ICSC 540
Phorate [ISO] 298-02-2 3018 OP L I 1 2 DS 75; JMPR 1997b, 2005; ICSC 1060
Phosphamidon 13171-21-6 3018 OP L I 2 7 See note 3; DS 74; ICSC 189; JMPR 1987b CAS Nos for E and Z isomers 297-99-4 and 23783-98-4
Sodium fluoroacetate [C] 62-74-8 2629 S R 1 0.2 DS 16; ICSC 484
Sulfotep [ISO] 3689-24-5 1704 OP L I 1 5 ICSC 985
Tebupirimfos [ISO*] 96182-53-5 3018 OP L I 1 1.3 Extremely hazardous by skin contact (LD50 9.4 mg/kg in rats) Terbufos [ISO] 13071-79-9 3018 OP L I-S 1 c2 JMPR 1991, 2004
EHC = Environmental Health Criteria Monograph; DS = Pesticide Data Sheet; HSG = Health and Safety Guide; IARC = IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; ICSC = International Chemical Safety Card; JMPR = Evaluation by the Joint FAO/WHO Meeting on Pesticide Residues.
273
Highly hazardous (Class Ib) technical grade active ingredients in pesticides
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks No type state use mg/kg
Acrolein [C] 107-02-8 1092 L H 2 29 EHC 127; HSG 67; IARC 63; ICSC 90
Highly irritant to skin and eyes; ICSC 95; Adjusted Allyl alcohol [C] 107-18-6 1098 L H 3 64 classification (see note 3)
Azinphos-ethyl [ISO] 2642-71-9 2783 OP S I 2 12 DS 72; JMPR 1974
Azinphos-methyl [ISO] 86-50-0 2783 OP S I 2 16 DS 59; ICSC 826; JMPR 1992, 2009b
Blasticidin-S 2079-00-7 2588 S F 2 16
Butocarboxim [ISO] 34681-10-2 2992 C L I 3 158 JMPR 1986a; Adjusted classification (see note 3)
Butoxycarboxim [ISO] 34681-23-7 2992 C L I 3 D288 Adjusted classification (see note 3)
Cadusafos [ISO] 95465-99-9 3018 OP L N,I 2 37 JMPR 1992
Calcium arsenate [C] 7778-44-1 1573 AS S I 2 20 EHC 18, 224; IARC 84; ICSC 765; JMPR 1969
Carbofuran [ISO] 1563-66-2 2757 C S I 2 8 DS 56; ICSC 122; JMPR 1997b, 2003b, 2009a; See note 2.
Chlorfenvinphos [ISO] 470-90-6 3018 OP L I 2 31 ICSC 1305; JMPR 1995b
3-Chloro-1,2-propanediol 96-24-2 2689 L R 3 112 Adjusted classification (see notes 1 and 3) [C]
Coumaphos [ISO] 56-72-4 2783 OP S AC,MT 2 7.1 ICSC 422; JMPR 1991
Coumatetralyl [ISO] 5836-29-3 3027 CO S R 2 16
Cyfluthrin [ISO] 68359-37-5 PY S I 2 c15 JMPR 2008; See note 9, p. 8
Beta-cyfluthrin [ISO] 68359-37-5 PY S I 2 c11 JMPR 2008; See note 9, p. 8
Zeta-cypermethrin [ISO] 52315-07-8 3352 PY L I 3 c86 See note 9, p. 8; HSG 22; ICSC 246; JMPR 2008; Adjusted classification (see note 3)
Demeton-S-methyl [ISO] 919-86-8 3018 OP L I 2 40 DS 61, EHC 197; ICSC 705; JMPR 1990
Volatile, DS 2; EHC 79; HSG 18; IARC 20, 53; ICSC 690; Dichlorvos [ISO] 62-73-7 3018 OP L I 3 56 JMPR 1994; Adjusted classification (see note 3)
Dicrotophos [ISO] 141-66-2 3018 OP L I 2 22 ICSC 872
274
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
DNOC [ISO] 534-52-1 2779 NP S I-S,H 2 25 JMPR 1965a; EHC 220; ICSC 462. See note 2.
Edifenphos [ISO] 17109-49-8 3018 OP L F 3 150 JMPR 1982. Adjusted classification (see note 3)
Ethiofencarb [ISO] 29973-13-5 2992 C L I 3 200 JMPR 1983. Adjusted classification (see note 3)
Famphur 52-85-7 2783 OP S I 2 48
Fenamiphos [ISO] 22224-92-6 2783 OP S N 2 15 DS 92; ICSC 483; JMPR 1998b, 2003b
JMPR 1986b; see note 9, p.8; Adjusted classification (see note Flucythrinate [ISO] 70124-77-5 3352 PY L I 3 c67 3)
Fluoroacetamide [C] 640-19-7 2588 S R 2 13 ICSC 1434. See note 2
Formetanate [ISO] 22259-30-9 2757 C S AC 2 21
Furathiocarb 65907-30-4 2992 C L I-S 2 42
Heptenophos [ISO] 23560-59-0 3018 OP L I 3 96 Adjusted classification (see note 3)
Isoxathion [ISO] 18854-04-8 3018 OP L I 3 112 Adjusted classification (see note 3)
Lead arsenate [C] 7784-40-9 1617 AS S L 2 c10 EHC 18, 224; IARC 84; ICSC 911; JMPR 1969
Mecarbam [ISO] 2595-54-2 3018 OP Oil I 2 36 JMPR 1987a
Mercuric oxide [ISO] 21908-53-2 1641 HG S O 2 18 ICSC 981; CICAD 50. See note 2
Methamidophos [ISO] 10265-92-6 2783 OP S I 2 30 HSG 79; ICSC 176; JMPR 1991, 2003b; See note 2
Methidathion [ISO] 950-37-8 3018 OP L I 2 25 JMPR 1998b; ICSC 1659
Methiocarb [ISO] 2032-65-7 2757 C S I 2 20 JMPR 1999
Methomyl [ISO] 16752-77-5 2757 C S I 2 17 DS 55, EHC 178; HSG 97; ICSC 177, JMPR 1989, 2002
Monocrotophos [ISO] 6923-22-4 2783 OP S I 2 14 See note 2; HSG 80; ICSC 181; JMPR 1996b
Nicotine [ISO] 54-11-5 1654 L 1 D50 ICSC 519
Omethoate [ISO] 1113-02-6 3018 OP L I 2 50 JMPR 1997a
Oxamyl [ISO] 23135-22-0 2757 C S I 2 6 DS 54; JMPR 1986b, 2003b
Oxydemeton-methyl [ISO] 301-12-2 3018 OP L I 3 65 JMPR 1990, 2003b; Adjusted classification (see note 3)
Paris green [C] 12002-03-8 1585 AS S L 2 22 Copper-arsenic complex
Pentachlorophenol [ISO] 87-86-5 3155 S I,F,H 2 D80 See note 2; Irritant to skin; EHC 71; HSG 19; IARC 20, 53
275
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks No type state use mg/kg
Propetamphos [ISO] 31218-83-4 3018 OP L I 3 106 Adjusted classification (see note 3)
Sodium arsenite [C] 7784-46-5 1557 AS S R 2 10 EHC 224; IARC 84; ICSC 1603
Sodium cyanide [C] 143-33-9 1689 S R 2 6 ICSC 1118; CICAD 61
Strychnine [C] 57-24-9 1692 S R 2 16 ICSC 197
Tefluthrin 79538-32-2 3349 PY S I-S 2 c22 See note 9, p. 8
Thallium sulfate [C] 7446-18-6 1707 S R 2 11 DS 10, EHC 182; ICSC 336
Thiofanox [ISO] 39196-18-4 2757 C S I-S 2 8
DS 67; ICSC 580; JMPR 1980; Adjusted classification (see note Thiometon [ISO] 640-15-3 3018 OP Oil I 3 120 3)
Triazophos [ISO] 24017-47-8 3018 OP L I 3 82 JMPR 1994, 2003b; Adjusted classification (see note 3)
Vamidothion [ISO] 2275-23-2 3018 OP L I 3 103 JMPR 1989; ICSC 758; Adjusted classification (see note 3)
Warfarin [ISO] 81-81-2 3027 CO S R 2 10 DS 35, EHC 175; HSG 96; ICSC 821
Zinc phosphide [C] 1314-84-7 1714 S R 2 45 DS 24, EHC 73; ICSC 602
EHC = Environmental Health Criteria Monograph; DS= Pesticide Data Sheet; HSG = Health and Safety Guide; IARC = IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; ICSC = International Chemical Safety Card; JMPR = Evaluation by the Joint FAO/WHO Meeting on Pesticide Residues.
276
Moderately hazardous (Class II) technical grade active ingredients in pesticides
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Acephate [ISO] 30560-19-1 OP S I 4 945 JMPR 1991, 2003b, 2006b; ICSC 748
Acifluorfen [ISO] 50594-66-6 S H 4 1370 Strong irritant to eyes
Alachlor [ISO] 15972-60-8 2588 S H 4 930 See note 1; DS 86; IARC 19, 36, 63; ICSC 371
Alanycarb [ISO] 83130-01-2 C S I 4 330
Allethrin [ISO] 584-79-2 PY Oil I 4 c685 See note 9, page 8; EHC 87; HSG 24; ICSC 212; JMPR 1965a
Ametryn [ISO] 834-12-8 T S H 4 110
Amitraz [ISO] 33089-61-1 S AC 4 800 ICSC 98; JMPR 1999
Anilofos [ISO] 64249-01-0 OP S H 4 472
Azaconazole 60207-31-0 S F 4 308
Azamethiphos [ISO] 35575-96-3 OP S I 4 1010
Bendiocarb [ISO] 22781-23-3 2757 C S I 3 55 DS 52
Benfuracarb [ISO] 82560-54-1 2992 C L I 3 205
Bensulide [ISO] 741-58-2 2902 L H 3 270 ICSC 383
Bensultap [ISO] 17606-31-4 S I 4 1100
Bentazone [ISO] 25057-89-0 S H 4 1100 HSG 48; ICSC 828; JMPR 1999, 2005
Bifenthrin 82657-04-3 3349 PY S I 3 c55 JMPR 1993
Bilanafos [ISO] 71048-99-2 S H 3 268
Bioallethrin [C] 584-79-2 PY L I 4 c700 See note 2; note 9, p. 8; ICSC 227
Bromoxynil [ISO] 1689-84-5 2588 S H 3 190
Bromuconazole 116255-48-2 S F 4 365 ICSC 1264
Bronopol 52-51-7 S B 3 254 ICSC 415
Butamifos [ISO] 36335-67-8 OP L H 4 630
Butralin [ISO] 33629-47-9 S H 4 1049
277
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Butroxydim [ISO] 138164-12-2 S H 4 1635
Butylamine [ISO] 13952-84-6 1992 L F 4 380 Irritant to skin; ICSC 401; JMPR 1982, 1985b
DS 3; EHC 153; HSG 78; IARC 12, Suppl.7; ICSC 121; Carbaryl [ISO] 63-25-2 2757 C S I 3 c300 JMPR 1997b, 2002
Carbosulfan [ISO] 55285-14-8 2992 C L I 3 250 JMPR 1987a, 2004
Cartap [ISO] 15263-53-3 S I 4 325 EHC 76; JMPR 1996a
Chloralose [C] 15879-93-3 S R 4 400
See notes 3 and 4; DS 36; EHC 34; HSG 13; IARC 79; ICSC Chlordane [ISO] 57-74-9 2996 OC L I 4 460 740; JMPR 1995a
Chlorfenapyr [ISO] 122453-73-0 S I,MT 4 441
Chlormequat (chloride) [ISO] 999-81-5 S PGR 4 670 ICSC 781; JMPR 2000
Chloroacetic acid [C] 79-11-8 1751 S H 4 650 Irritant to skin and eyes; data refer to sodium salt; ICSC 235
Chlorphonium chloride [ISO] 115-78-6 2588 S PGR 3 178 Irritant to skin and eyes
Chlorpyrifos [ISO] 2921-88-2 2783 OP S I 3 135 DS 18; ICSC 851; JMPR 2000
Clomazone [ISO] 81777-89-1 L H 4 1369
Copper hydroxide [C] 20427-59-2 CU S F 4 1000
Copper oxychloride [C] 1332-40-7 CU S F 4 1440
Copper sulfate [C] 7758-98-7 CU S F 3 300 ICSC 751
4-CPA [ISO] 122-88-3 PAA S PGR 4 850
Cuprous oxide [C] 1317-39-1 CU S F 4 470 ICSC 421, EHC 200
Cyanazine [ISO] 21725-46-2 T S H 3 288 ICSC 391
Cyanophos [ISO] 2636-26-2 OP L I 4 610
Cyhalothrin [ISO] 68085-85-8 3352 PY Oil Ix 3 c144 See note 9, p. 8; EHC 99; HSG 38; ICSC 858; JMPR 1985c;
278
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
See note 9, p. 8; DS 58; EHC 82; HSG 22; ICSC 246; JECFA Cypermethrin [ISO] 52315-07-8 3352 PY L I 3 c250 1996
Alpha-cypermethrin [ISO] 67375-30-8 3349 PY S I 3 c79 See note 9, p 8; EHC 142; JECFA 1996; JMPR 2008
Cyphenothrin [(1R)- isomers] 39515-40-7 3352 PY L I 4 318 [ISO]
Cyproconazole 94361-06-5 S F 4 1020
DS 37; EHC 29, 84; HSG 5; IARC 41, Suppl. 7; ICSC 33; 2,4-D [ISO] 94-75-7 3345 PAA S H 4 375 JMPR 1998b
Dazomet [ISO] 533-74-4 S F-S 4 640 Irritant to skin and eyes; ICSC 786
2,4-DB 94-82-6 S H 4 700
See notes 3 and 4; DS 21; EHC 9, 83; IARC 53; ICSC 34; DDT [ISO] 50-29-3 2761 OC S I 3 113 JMPR 1985c, 2001
See note 9, p. 8; DS 50; EHC 97; HSG 30; IARC 53; ICSC Deltamethrin [ISO] 52918-63-5 3349 PY S I 3 c135 247; JMPR 2001
Diazinon [ISO] 333-41-5 3018 OP L I 4 300 DS 45, EHC 198; ICSC 137; JMPR 1994, 2002, 2008
Dicamba [ISO] 1918-00-9 S H 4 1707 ICSC 139
Mixture of isomers: ortho (3) 95-50-1, meta (3) 541-73-1, para Dichlorobenzene [C] 106-46-7 S FM 4 500-5000 (2B) 106-46-7; ICSC 37
Dichlorophen [ISO] 97-23-4 OC S F 4 1250
Dichlorprop [ISO] 7547-66-2 S H 4 800 ICSC 38
Diclofop [ISO] 40483-25-2 S H 4 565
Dicofol [ISO] 115-32-2 OC S AC 4 c690 DS 81; IARC 30; ICSC 752; JMPR 1993
Difenoconazole [ISO] 119446-68-3 S F 4 1453 JMPR 2009b
279
Difenzoquat [ISO] 43222-48-6 2588 S H 4 470
Dimepiperate [ISO] 61432-55-1 TC S H 4 946
Dimethachlor [ISO] 50563-36-5 S H 4 1600
Dimethipin [ISO] 55290-64-7 S H 4 1180 JMPR 2000, 2005
Dimethenamid [ISO] 87674-68-8 L H 4 371 LD50 of P isomer is 429 mg/kg bw; JMPR 2006b Dimethylarsinic acid [C] 75-60-5 1572 AS S H 4 1350
Dimethoate [ISO] 60-51-5 2783 OP S I 3 c150 DS 42; EHC 90; HSG 20; ICSC 741; JMPR 1997b, 2004
Diniconazole [ISO] 83657-24-3 S F 4 639
Dinobuton [ISO] 973-21-7 2779 NP S AC,F 3 140
Dinocap [ISO] 39300-45-3 NP S AC,F 4 980 ICSC 881; JMPR 1999
Diphenamid [ISO] 957-51-7 S H 4 970 ICSC 763
Irritant to skin and eyes and damages nails; DS 40; EHC 39; Diquat [ISO] 2764-72-9 2781 BP S H 3 231 HSG 52; JMPR 1994; ICSC 1363
Dithianon [ISO] 3347-22-6 S F 4 640 JMPR 1993
Dodine [ISO] 2439-10-3 S F 4 1000 JMPR 2001
Endosulfan [ISO] 115-29-7 2761 OC S I 3 80 DS 15; EHC 40; HSG 17; ICSC 742; JMPR 1999
Endothal-sodium [(ISO)] 125-67-9 2588 S H 3 51
EPTC [ISO] 759-94-4 TC L H 4 1652 ICSC 469
Esfenvalerate [ISO] 66230-04-4 3349 PY S I 3 87 JMPR 2003b; ICSC 1516
Ethion [ISO] 563-12-2 3018 OP L I 3 208 ICSC 888; JMPR 1991
Fenazaquin [ISO] 120928-09-8 2588 S AC 3 134
Fenitrothion [ISO] 122-14-5 OP L I 4 503 DS 30; EHC 133; HSG 65; ICSC 622; JMPR 2001
Fenobucarb 3766-81-2 C S I 4 620
Fenothiocarb [ISO] 62850-32-2 C S L 4 1150
Fenpropidin [ISO] 67306-00-7 L F 4 1440
Fenpropathrin [ISO] 64257-84-7 3349 PY S I 3 c66 See note 9, p. 8; JMPR 1994
Highly toxic by inhalation (LC50 = 0.21-0.36 mg/l); JMPR Fenpyroximate [ISO] 134098-61-6 S AC 3 245 2007
280
Fenthion [ISO] 55-38-9 3018 OP L I,L 3 D586 DS 23; ICSC 655; JMPR 1998b
Fentin acetate[(ISO)] 900-95-8 2786 OT S F 3 125 DS 22; EHC 15; JMPR 1992; CICAD 13
Fentin hydroxide[(ISO)] 76-87-9 2786 OT S F 3 108 DS 22; EHC 15; ICSC 1283; JMPR 1992; CICAD 13
See note 9, p. 8; DS 90; EHC 95, HSG 34; IARC 53; ICSC Fenvalerate [ISO] 51630-58-1 3352 PY L I 4 c450 273; JMPR 1986c
Ferimzone [ISO] 89269-64-7 S F 4 725
Fipronil 120068-37-3 2588 S I 3 92 JMPR 1998b, 2001; ICSC 1503
Fluchloralin [ISO] 33245-39-5 S H 4 1550
Flufenacet [ISO] 142459-58-3 S H 4 600 May cause skin sensitization
Fluoroglycofen 77501-60-1 S H 4 1550
Flurprimidol [ISO] 56425-91-3 S PGR 4 709
Flusilazole 85509-19-9 S F 4 672 JMPR 1996b, 2009b
Flutriafol [ISO] 76674-21-0 S F,FST 4 1140
Fluxofenim [ISO] 88485-37-4 oil H 4 670
Fomesafen [ISO] 72178-02-0 OC S H 4 1250
Fuberidazole [ISO] 3878-19-1 S F 4 336
Furalaxyl [ISO] 57646-30-7 S F 4 940
Gamma-HCH [ISO], Lindane 58-89-9 2761 OC S I 3 88 ICSC 53; JMPR 2003b; See note 3
Glufosinate [ISO] 53369-07-6 S H 4 1625 JMPR 2000
Guazatine 108173-90-6 S FST 3 230 LD50 value refers to triacetate; JMPR 1998b Haloxyfop 69806-34-4 S H 4 300 JMPR 1996b, 2008 (includes Haloxyfop-R and esters)
See notes 3, 4 and 5; EHC 123; IARC 5, 20, 42; ICSC 487; HCH [ISO] 608-73-1 2761 OC S I 3 100 JMPR 1974
Hexazinone [ISO] 51235-04-2 S H 4 1690
Hydramethylnon 67485-29-4 S I 4 1200
Imazalil [ISO] 35554-44-0 2588 S F 3 227 ICSC 1303; JMPR 2001, 2002, 2006b
Imidacloprid [ISO] 138261-41-3 S I 4 450 JMPR 2002; ICSC 1501 281
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Iminoctadine [ISO] 13516-27-3 S F 3 300 Eye irritant
JMPR 2006b; LD50 applies to 3:1 mixture of isomers in Indoxacarb [ISO] 173584-44-6 S I 3 268 commercial use
Ioxynil [ISO] 1689-83-4 2588 S H 3 110 ICSC 900
Ioxynil octanoate [(ISO)] 3861-47-0 S H 4 390
Iprobenfos 26087-47-8 S F 4 600
Isoprocarb [ISO] 2631-40-5 2757 C S I 4 403
Isoprothiolane [ISO] 50512-35-1 S F 4 1190
Isoproturon [ISO] 34123-59-6 S H 4 1800
Isouron [ISO] 55861-78-4 S H 4 630
Lambda-cyhalothrin 2164-08-1 3349 PY S I 3 c56 See note 9, p. 8; EHC 142; HSG 38; JMPR 2009b; ICSC 859
MCPA [ISO] 94-74-6 PAA S H 4 700 IARC 30, 41; ICSC 54
MCPA-thioethyl [ISO] 25319-90-8 PAA S H 4 790
MCPB [ISO] 94-81-5 S H 4 680
Mecoprop [ISO] 7085-19-0 S H 4 930 ICSC 55
Mecoprop-P [ISO] 16484-77-8 S H 4 1050
Mefluidide [ISO] 53780-34-0 S H 4 1920
Mepiquat [ISO] 15302-91-7 S PGR 4 1490
Mercurous chloride [C] 10112-91-1 2025 HG S F 3 210 See note 3; ICSC 984; CICAD 50
Metalaxyl [ISO] 57837-19-1 S F 4 670 JMPR 1983, 2003b
Metaldehyde [ISO] 108-62-3 S M 3 227 DS 93
Metamitron [ISO] 41394-05-2 S H 4 1183 ICSC 1361
Metam-sodium [(ISO)] 137-42-8 2771 S F-S 3 285
Metconazole [ISO] 125116-23-6 S F 4 660
Methacrifos [ISO] 62610-77-9 OP L I 4 678 JMPR 1991
282
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Methasulfocarb [ISO] 66952-49-6 2757 S F 3 112
Methylarsonic acid [ISO] 124-58-3 AS S H 4 1800 ICSC 755; EHC 224
Methyl isothiocyanate [ISO] 556-61-6 2588 S F-S 3 72 Skin and eye irritant; see note 6
Metolcarb [ISO] 1129-41-5 C S I 3 268
Metribuzin [ISO] 21087-64-9 S H 4 322 ICSC 516
Molinate [ISO] 2212-67-1 TC L H 4 720
Myclobutanil 88671-89-0 S F 4 1600 JMPR 1993
Nabam [ISO] 142-59-6 2771 S F 4 395 Goitrogenic in rats
Naled [ISO] 300-76-5 3018 OP L I 4 430 DS 39; ICSC 925
2-Napthyloxyacetic acid [ISO] 120-23-0 S PGR 4 600
Nitrapyrin [ISO] 1929-82-4 S B-S 4 1072 ICSC 1658
Nuarimol [ISO] 63284-71-9 S F 4 1250
Octhilinone [ISO] 26530-20-1 S F 4 1470
Oxadixyl 77732-09-3 S F 4 1860
Paclobutrazol [ISO] 76738-62-0 S PGR 4 1300 JMPR 1989
See note 7; DS 4; EHC 39; HSG 51; ICSC 5; JMPR 1987a, Paraquat [ISO] 1910-42-5 2781 BP S H 3 150 2004
Pebulate [ISO] 1114-71-2 TC L H 4 1120
Pendimethalin [ISO] 40487-42-1 S H 4 1050
See note 9, p. 8; DS 51; EHC 94; HSG 33; IARC 53; ICSC Permethrin [ISO] 52645-53-1 3352 PY L I 4 c500 312; JMPR 2000
Phenthoate [ISO] 2597-03-7 3018 OP L I 4 c400 DS 48; JMPR 1985c
Phosalone [ISO] 2310-17-0 2783 OP S I 3 120 ICSC 797; JMPR 1998b, 2002
Phosmet [ISO] 732-11-6 2783 OP S I,AC 3 113 ICSC 543; JMPR 1999, 2004
Phoxim [ISO] 14816-18-3 OP L I 4 D1975 DS 31; JECFA 2000a
283
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Pirimicarb [ISO] 23103-98-2 2757 C S AP 3 147 JMPR 1983, 2005
Pirimiphos-methyl [ISO] 29232-93-7 OP L I 4 1667 DS 49; JMPR 1993, 2008
Prallethrin [ISO] 23031-36-9 3352 PY oil I 4 460
Prochloraz [ISO] 67747-09-5 S F 4 1600 JMPR 1985a
Profenofos [ISO] 41198-08-7 3018 OP L I 4 358 JMPR 1991, 2008
Propachlor [ISO] 1918-16-7 S H 4 1500 DS 78; EHC 147; HSG 77; JMPR 2002
Propanil [ISO] 709-98-8 S H 4 c1400 ICSC 552
Propiconazole [ISO] 60207-90-1 L F 4 1520 JMPR 1988, 2005
Propoxur [ISO] 114-26-1 2757 C S I 3 95 DS 25; ICSC 191; JMPR 1990
Prosulfocarb [ISO] 52888-80-9 TC L H 4 1820
Prothiofos [ISO] 34643-46-4 OP L I 4 925
Pyraclofos [ISO] 77458-01-6 3018 OP L I 3 237
Pyrazophos [ISO] 13457-18-6 2784 S F 4 435 JMPR 1993
Pyrazoxyfen [ISO] 71561-11-0 S H 4 1644
Pyrethrins [C] 8003-34-7 L I 4 500-1000 See note 8; DS 11; JMPR 2000, 2004; ICSC 1475
Pyridaben [ISO] 96489-71-3 S AC 4 820
Pyridaphenthion 119-12-0 OP S I 4 769
Pyroquilon [ISO] 57369-32-1 S F 4 320
Quinalphos [ISO] 13593-03-8 2783 OP S I 3 62
Quinoclamine [ISO] 2797-51-5 S H 4 1360
Quizalofop 76578-12-6 S H 4 1670
Quizalofop-p-tefuryl [ISO] 119738-06-6 L H 4 1012
Rotenone [C] 83-79-4 2588 S I 3 132-1500 See note 9; HSG 73; ICSC 944
Simetryn [ISO] 1014-70-6 T S H 4 1830
Sodium chlorate [ISO] 7775-09-9 1495 S H 4 1200 ICSC 1117
284
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Spiroxamine [ISO] 118134-30-8 L F 4 500 Dermal LD50 1068 mg/kg; may cause skin sensitisation Sulfluramid [ISO] 4151-50-2 S I 4 543
2,3,6-TBA [ISO] 50-31-7 S H 4 1500
TCA [ISO] (acid) 76-03-9 1839 S 4 400 See note 5 to Table 4, p. 38; ICSC 586
Tebuconazole [ISO] 107534-96-3 S F 4 1700 JMPR 1995b
Tebufenpyrad [ISO] 119168-77-3 S MT 4 595
Tebuthiuron [ISO] 34014-18-1 S H 4 644
Terbumeton [ISO] 33693-04-8 T S H 4 483
Tetraconazole [ISO] 112281-77-3 Oil F 4 1031
Thiacloprid 111988-49-9 S I 4 396 JMPR 2008
Thiobencarb [ISO] 28249-77-6 TC L H 4 1300
Thiocyclam [ISO] 31895-22-4 S I 4 310
Thiodicarb [ISO] 59669-26-0 2757 C S I 3 66 JMPR 2001
DS 71; EHC 78; IARC 12, 53; ICSC 757; JMPR 1993; See Thiram [ISO] 137-26-8 S F 4 560 note 3
Tralkoxydim [ISO] 87820-88-0 S H 4 934
Tralomethrin 66841-25-6 3349 PY S I 3 c85
Triadimefon [ISO] 43121-43-3 S F 4 602 JMPR 1986b, 2005
Triadimenol [ISO] 55219-65-3 S FST 4 900 JMPR 1990, 2005
Triazamate [ISO] 112143-82-5 2588 S AP 3 50-100
DS 27; EHC 132; HSG 66; IARC 30, Suppl 7; ICSC 585; Trichlorfon [ISO] 52-68-6 OP S I 3 250 JMPR 1979; JECFA 2000b, 2003
Triclopyr [ISO] 55335-06-3 S H 4 710
Tricyclazole [ISO] 41814-78-2 S F 4 305
Tridemorph [ISO] 81412-43-3 Oil F 4 650
Triflumizole 99387-89-0 S F 4 695 ICSC 1252
285
LD Common name CAS no UN Chem Phys Main GHS 50 Remarks no type state use mg/kg
Uniconazole [ISO] 83657-22-1 S PGR 4 1790
XMC 2655-14-3 C S I 4 542
Xylylcarb 2425-10-7 C S I 4 380
Irritant to skin; DS 73; EHC 78; IARC 12, 53; ICSC 348; Ziram [ISO] 137-30-4 S F 4 1400 JMPR 1997b
EHC = Environmental Health Criteria Monograph; DS= Pesticide Data Sheet; HSG = Health and Safety Guide; IARC = IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; ICSC = International Chemical Safety Card; JECFA = Evaluation by the Joint FAO/WHO Expert Committee on Food Additives; JMPR = Evaluation by the Joint FAO/WHO Meeting on Pesticide Residues.
286
Slightly hazardous (Class III) technical grade active ingredients in pesticides
LD Common name CAS no UN Chem Phys Main use GHS 50 Remarks no type state mg/kg
Acetochlor [ISO] 34256-82-1 L H 5 2950
Alloxydim 55634-91-8 S H 5 2260
Ammonium sulfamate 7773-06-0 S H 5 3900
Ancymidol [ISO] 12771-68-5 S PGR 5 4500
Asulam [ISO] 3337-71-1 S H 5 4000
Atrazine [ISO] 1912-24-9 T S H 4 c2000 DS 82; HSG 47; IARC 53; ICSC 99
Bacillus thuringiensis (Bt) 68038-71-1 S I 5 >4000 EHC 217
Benalaxyl [ISO] 71626-11-4 S F 5 4200 JMPR 1988, 2006
Benazolin [ISO] 3813-05-6 S H 5 3200 Irritant to skin and eyes
Benfuresate 68505-69-1 S H 5 2031
Biphenyl 92-52-4 S F 5 3280 ICSC 106
Bispyribac 125401-75-4 S H 5 2635
Borax [ISO] 1303-96-4 S F 5 4500 ICSC 567
Bupirimate [ISO] 41483-43-6 S F 5 c4000
Buprofezin [ISO] 69327-76-0 S I 5 2200 JMPR 1992
Butachlor 23184-66-9 L H 5 3300
Butylate [ISO] 2008-41-5 TC L F 5 >4000
Carboxin [ISO] 5234-68-4 S FST 5 3820
Chinomethionat [ISO] 2439-01-2 S AC,F 5 2500 JMPR 1988
Chloridazon [ISO] 1698-60-8 S H 5 2420
Chlorimuron 99283-00-8 S H 5 4102
Chlorpyrifos methyl [ISO] 5598-13-0 OP S I 5 >3000 DS 33; JMPR 1993
Chlorthal-dimethyl [ISO] 1861-32-1 S H 5 >3000
Chlozolinate 84332-86-5 S F 5 >4000
287
LD Common name CAS no UN Chem Phys Main use GHS 50 Remarks no type state mg/kg
Cinmethylin 87818-31-3 L H 5 3960
Clofentezine [ISO] 74115-24-5 S AC 5 >3200 JMPR 1987a, 2006b
Clopyralid 57754-85-5 S H 5 4300 Severe irritant to eyes; ICSC 443
Cycloate [ISO] 1134-23-2 TC L H 4 >2000
Cycloxydim 101205-02-1 S H 5 3900 JMPR 1993
Cyromazine 66215-27-8 S L 5 3300 JMPR 1991
Diafenthiuron [ISO] 80060-09-9 S AC 5 2068
Dichlobenil [ISO] 1194-65-6 S H 5 3160 ICSC 867
Dichlormid 37764-25-3 L H 5 2080
Dicloran 99-30-9 S F 5 4000 ICSC 871; JMPR 1999
Diethyltoluamide [ISO] 134-62-3 L RP 4 c2000 DS 80 (insect)
Diflubenzuron 35367-38-5 S L 5 >4640 DS 77, EHC 184; HSG 99; JMPR 2002
Diflufenican [ISO] 83164-33-4 S H 4 >2000
Dimefuron [ISO] 34205-21-5 S H 4 >2000
Dimethametryn [ISO] 22936-75-0 T L H 5 3000
Dimethirimol 5221-53-4 S F 5 2350
Dimethomorph [ISO] 110488-70-5 S F 5 3500 JMPR 2009b
Dinitramine [ISO] 29091-05-2 S H 5 3000
Diuron [ISO] 330-54-1 S H 5 3400
Dodemorph [ISO] 1593-77-7 L H 5 4500
Empenthrin [(1R) isomers] [ISO] 54406-48-3 PY Oil I 5 >2280
Esprocarb [ISO] 85785-20-2 TC L H 4 >2000 Skin and eye irritant
Ethephon 16672-87-0 S PGR 5 >4000 JMPR 2004; 2003b
Etridiazole [ISO] 2593-15-9 L F 4 2000
288
LD Common name CAS no UN Chem Phys Main use GHS 50 Remarks no type state mg/kg
Fenarimol [ISO] 60168-88-9 S F 5 2500 JMPR 1996b
Fenbuconazole 114369-43-6 S F 4 >2000 JMPR 1998
Fenbutatin oxide [ISO] 13356-08-6 OT S MT 5 2630 EHC 15; JMPR 1993
Fenpropimorph 67564-91-4 oil F 5 3515 JMPR 1995b, 2002, 2005
Flamprop-M 90134-59-1 S F 5 >3000
Fluazifop-p-butyl [ISO] 83066-88-0 L H 5 2451
Flufenoxuron 101463-69-8 S I 5 >3000
Flurochloridone 61213-25-0 S H 5 4000 tau-Fluvalinate 102851-06-9 PY oil I 5 >3000 Skin and eye irritant
Fosamine [ISO] 25954-13-6 OP S H 5 2400
Glyphosate [ISO] 1071-83-6 S H 5 4230 EHC 159, DS 91; ICSC 160; JMPR 1987a
Halofenozide 112226-61-6 S I 5 2850
Hexaconazole 79983-71-4 S F 5 2180 JMPR 1991
Hymexazol 10004-44-1 S FST 5 3900
Iprodione [ISO] 36734-19-7 S F 5 3500 JMPR 1996b
Linuron [ISO] 330-55-2 S H 5 4000 ICSC 1300
Malathion [ISO] 121-75-5 3082 OP L I 5 c2100 See note 1; DS 29; IARC 30; ICSC 172; JMPR 1998b, 2004
Metazachlor 67129-08-2 S H 5 2150
Methabenzthiazuron [ISO] 18691-97-9 S H 5 >2500
Methyldymron 42609-73-4 S H 5 3948
Metobromuron [ISO] 3060-89-7 S H 5 2500
Metolachlor [ISO] 51218-45-2 L H 5 2780 ICSC 1360
Metoxuron 19937-59-8 S H 5 >3200
Monolinuron 1746-81-2 S H 5 2250 ICSC 1273
289
LD Common name CAS no UN Chem Phys Main use GHS 50 Remarks no type state mg/kg
1-Naphthylacetic acid 86-87-3 S PGR 5 c3000
N-octylbicycloheptene 113-48-4 L SY 5 2800 dicarboximide [C]
Ofurace 58810-48-3 S F 5 2600
Oxycarboxin [ISO] 5259-88-1 S F 4 2000
Penconazole 66246-88-6 S F 5 2120 JMPR 1993
2-Phenylphenol [C] 90-43-7 S F 5 2480 ICSC 669; IARC 30; JMPR 2000
Pimaricin 7681-93-8 S F 5 2730 See note 2
Probenazole 27605-76-1 S F 5 2030
Prometon [ISO] 1610-18-0 T S H 5 2980
Prometryn [ISO] 7287-19-6 T S H 5 3150
Propargite [ISO] 2312-35-8 L AC 5 2200 JMPR 2000
Pyridate [ISO] 55512-33-9 S H 5 c2000
Pyrifenox [ISO] 88283-41-4 L F 4 2900
Pyrimethanil [ISO] 53112-28-0 S F 5 4150 JMPR 2009b
Pyrithiobac sodium [ISO] 123343-16-8 S H 5 3200
Quinclorac 84087-01-4 S H 5 2680
Resmethrin [ISO] 10453-86-8 PY S I 4 2000 See note 3; EHC 92, DS 83, HSG 25; ICSC 324
Sethoxydim [ISO] 74051-80-2 L H 5 3200
For Spinosyn A and D, CAS numbers are 131929-60-7 Spinosad [ISO] 168316-95-8 S I 5 3738 and 131929-63-0; JMPR 2002; ICSC 1502
Spirotetramat [ISO] 203313-25-1 S I 4 >2000 JMPR 2009a
Skin and mucous membrane irritant. See note 4; ICSC Sulphur 7704-34-9 1350 S F,I 5 >3000 1166
TCA (sodium salt) [ISO] 650-51-1 S H 5 3200 ICSC 1139; Irritant to skin and eyes: see note 5
290
LD Common name CAS no UN Chem Phys Main use GHS 50 Remarks no type state mg/kg
Terbuthylazine [ISO] 5915-41-3 T S H 5 2160
Terbutryn [ISO] 886-50-0 T S H 5 2400
Tetrachlorvinphos [ISO] 22248-79-9 OP S I 5 4000
Thiabendazole [ISO] 148-79-8 S F 5 3330 JECFA 1997, 2002
Thidiazuron 51707-55-2 S PGR 5 >4000
Tri-allate [ISO] 2303-17-5 TC L H 5 2165 HSG 89; ICSC 201
Trietazine [ISO] 1912-26-1 T S H 5 2830 ICSC 202
Triticonazole [ISO] 131983-72-7 S F 4 >2000
Undecan-2-one [C] 112-12-9 Oil RP, (dogs,cats) 5 2500
EHC = Environmental Health Criteria Monograph; DS = Pesticide Data Sheet; HSG = Health and Safety Guide; IARC = IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; ICSC = International Chemical Safety Card; JECFA = Evaluation by the Joint FAO/WHO Expert Committee on Food Additives; JMPR = Evaluation by the Joint FAO/WHO Meeting on Pesticide Residues.
291
Technical grade active ingredients of pesticides unlikely to present acute hazard in normal use
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Aclonifen 74070-46-5 S H 5 >5000
Acrinathrin [ISO] 101007-06-1 PY S MT 5 >5000
Aminopyralid [ISO] 150114-71-9 S H 5 >5000 JMPR 2009b
Amitrole [ISO] 61-82-5 S H 5 5000 EHC 158, DS 79; HSG 85; IARC 79; ICSC 631; JMPR 1998b
Anthraquinone 84-65-1 S RP (birds) 5 >5000 ICSC 1605
Azimsulfuron [ISO] 120162-55-2 S H 5 >5000
Azoxystrobin [ISO] 131860-33-8 S F 5 >5000 JMPR 2009a
Benfluralin [ISO] 1861-40-1 S H 5 >10000
EHC 148, DS 87; HSG 81; ICSC 382; JMPR Benomyl [ISO] 17804-35-2 S F 5 >10000 1996b. See note 1
This molecule is not an active substance as such Benoxacor [ISO] 98730-04-2 S H 5 >5000 but is a ―safener‖
Bensulfuron-methyl 83055-99-6 S H 5 >5000
Bifenazate [ISO] 149877-41-8 S AC 5 >5000 JMPR 2008
Bifenox [ISO] 42576-02-3 S H 5 >6400
Bioresmethrin [ISO] 28434-01-7 PY L I 5 >7000 DS 34; EHC 92; HSG 25; ICSC 229; JMPR 1992
Bitertanol 55179-31-2 S F 5 >5000 JMPR 1999
Boscalid [ISO] 188425-85-6 S F 5 >5000 JMPR 2008
Bromacil [ISO] 314-40-9 S H 5 5200 ICSC 1448
Bromobutide 74712-19-9 S H 5 >5000
Bromopropylate [ISO] 18181-80-1 S AC 5 >5000 JMPR 1994
Captan [ISO] 133-06-2 S F 5 9000 Irritant to skin; DS 9; HSG 50; IARC 30, Suppl 7;
292
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
DS 89; EHC 149; HSG 82; ICSC 1277; JMPR Carbendazim [ISO] 10605-21-7 S F 5 >10000 1996b, 2006b
Carbetamide [ISO] 16118-49-3 C S H 5 >10000
Carpropamid [ISO] 104030-54-8 L F 5 >5000
Chloransulam methyl 14750-35-4 S H 5 >5000
Chlorantraniliprole [ISO] 500008-45-7 S I 5 >5000 JMPR 2009a
Chlorfluazuron 71422-67-8 S IGR 5 8500
EHC 183; HSG 98; IARC 30; ICSC 134; JMPR Chlorothalonil [ISO] 1897-45-6 S F 5 >10000 1993
Chlorotoluron [ISO] 15545-48-9 S H 5 >10000 ICSC 1327
Chlorpropham [ISO] 101-21-3 C S PGR 5 >5000 IARC 12; JMPR 2001; ICSC 1500
Chlorsulfuron 64902-72-3 S H 5 5545
Cinosulfuron [ISO] 94593-91-6 S H 5 >5000
Clomeprop 84496-56-0 S H 5 >5000
Cloxyfonac 32791-87-0 PAA S PGR 5 >5000
Cryolite [C] 15096-52-3 S I 5 >10000
Cycloprothrin 63935-38-6 PY L I 5 >5000
Cyclosulfamuron [ISO(*)] 136849-15-5 S H 5 >5000
Cyhalofop [ISO] 122008-85-9 S H 5 >5000
Daimuron 42609-52-9 S H 5 >5000
Dalapon 75-99-0 S H 5 9330
Daminozide [ISO] 1596-84-5 S H 5 8400 JMPR 1993
Desmedipham [ISO] 13684-56-5 S H 5 >9600
Dichlofluanid [ISO] 1085-98-9 S F 5 >5000 JMPR 1985a
Diclomezine 62865-36-5 S F 5 >10000
Diclosulam [ISO] 145701-21-9 S H 5 >5000
293
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Dikegulac [ISO] 18467-77-1 S PGR 5 >10000
Dimethomorph [ISO] 110488-70-5 S F 5 >5000
Dimethyl phthalate [C] 131-11-3 L RP 5 8200 ICSC 261 (insect)
Dipropyl isocinchomerate [C] 3737-22-2 L RP (fly) 5 5230
Dithiopyr [ISO] 97886-45-8 S H 5 >5000
Ethalfluralin [ISO] 55283-68-6 S H 5 >10000
Ethirimol [ISO] 23947-60-6 S FST 5 6340
Ethofumesate [ISO] 26225-79-6 S H 5 >6400
Ethyl butylacetylaminopropionate 52304-36-6 L RP 5 >5000 (insect)
Etofenprox 80844-07-1 S I 5 >10000 JMPR 1994
Famoxadone [ISO(*)] 131807-57-3 S F 5 >5000 JMPR 2004
Fenchlorazole [ISO] 103112-35-2 S H 5 >5000
Fenclorim 3740-92-9 S H 5 >5000
Fenfuram [ISO] 24691-80-3 S FST 5 >10000
Fenhexamid [ISO] 126833-17-8 S F 5 >5000 JMPR 2006b
Fenoxycarb 79127-80-3 C S I 5 >10000
Fenpiclonil 74738-17-3 S FST 5 >5000
Ferbam [ISO] 14484-64-1 S F 5 >10000 DS 94; EHC 78; IARC 12, 42; ICSC 792; JMPR 1997b
Florasulam 145701-23-1 S H 5 >5000
Flucarbazone-sodium 181274-17-9 S H 5 > 5000
Flucycloxuron [ISO] 94050-52-9 S AC 5 >5000
Fludioxonil [ISO] 131341-86-1 S F 5 >5000 JMPR 2006a
Flumetralin 62924-70-3 S PGR 5 >5000
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LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Flumetsulam [ISO] 98967-40-9 S H 5 >5000
Fluometuron [ISO] 2164-17-2 S H 5 >8000
Flupropanate 756-09-2 S H 5 >10000
Flupyrsulfuron [ISO] 144740-54-5 S H 5 >5000
Flurenol [ISO] 467-69-6 S PGR 5 >5000
Fluridone [ISO] 59756-60-4 S H 5 >10000
Fluroxypyr 69377-81-7 S H 5 >5000
Fluthiacet 149253-65-6 S H 5 >5000
Flutolanil 66332-96-5 S F 5 >10000 ICSC 1265; JMPR 2003b
Folpet 133-07-3 S F 5 >10000 HSG 72; ICSC 156; JMPR 1996b
Fosetyl 15845-66-2 S F 5 5800
Gibberellic acid 77-06-5 S PGR 5 >10000
Hexaflumuron [ISO] 86479-06-3 S I 5 >5000 ICSC 1266
Hexythiazox 78587-05-0 S AC 5 >5000 JMPR 1992, 2009a
Hydroprene [ISO] 41205-09-8 L IGR 5 >10000
2-Hydroxyethyl octyl sulphide [C] 3547-33-9 L RP 5 8530 (insect)
Imazamethabenzmethyl [(ISO)] 81405-85-8 S H 5 >5000
Imazapyr 81334-34-1 S H 5 >5000 Irritant to eyes
Imazaquin 81335-37-7 S H 5 >5000
Imazethapyr 81335-77-5 S H 5 >5000
Imibenconazole [ISO] 86598-92-7 S F 5 >5000
Inabenfide 82211-24-3 S PGR 5 >10000
Iprovalicarb 140923-17-7 S F 5 >5000
Isoxaben 82558-50-7 S H 5 >10000
295
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Kasugamycin 19408-46-9 S F 5 >10000
Lenacil [ISO] 2164-08-1 S H 5 >10000
Maleic hydrazide [C] 123-33-1 S PGR 5 6950 IARC 4, 42; JMPR 1997b CAS10071-13-3
Irritant to skin on multiple exposure; DS 94; EHC Mancozeb 8018-01-7 S F 5 >8000 78; ICSC 754; JMPR 1994
Mandipropamid [ISO] 374726-62-2 S F 5 >5000 JMPR 2009a
Irritant to skin on multiple exposure; DS 94; EHC Maneb [ISO] 12427-38-2 S F 5 6750 78; ICSC 173; JMPR 1994
Mefenacet 73250-68-7 S H 5 >5000
Mepanipyrim [ISO] 110235-47-7 S F 5 >5000
Mepronil [ISO] 55814-41-0 S F 5 >10000
Methoprene [ISO] 40596-69-8 L IGR 5 >10000 DS 47; JMPR 1987b, 2002
Methoxychlor [ISO] 72-43-5 OC S I 5 6000 DS 28; IARC 5, 20; ICSC 1306; JMPR 1978
Methozyfenozide 161050-58-4 S I 5 >5000 Dermal LD50 > 5000; JMPR 2004 Metiram 9006-42-2 S F 5 >10000 JMPR 1994
Metosulam 139528-85-1 S H 5 >5000
Metsulfuron methyl 74223-64-6 S H 5 >5000
2-(1-Naphthyl) acetamide 86-86-2 S PGR 5 6400
Napropamide 15299-99-7 S H 5 5000
Naptalam 132-66-1 S PGR 5 8200
Neburon [ISO] 555-37-3 S H 5 >10000
Niclosamide [ISO] 50-65-7 S M 5 5000 DS 63
Nicosulfuron [ISO] 111991-09-4 S H 5 >5000 Irritant to eyes
Nitrothal-isopropyl [ISO] 10552-74-6 S F 5 6400
Norflurazon [ISO] 27314-13-2 S H 5 >8000
296
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Noviflumuron 121451-02-3 S I 5 >5000 Dermal LD50 > 5000 Oryzalin [ISO] 19044-88-3 S H 5 >10000
Oxabetrinil 74782-23-3 S H 5 >5000
Oxadiazon [ISO] 19666-30-9 S H 5 >8000
Oxine-copper [ISO] 10380-28-6 CU S F 5 7792
Oxyfluorfen [ISO] 42874-03-3 S H 5 >5000
Pencycuron 66063-05-6 S F 5 >5000
Penoxsulam 219714-96-2 S H 5 >5000 Dermal LD50 > 5000 Pentanochlor 2307-68-8 S H 5 >10000
Phenmedipham [ISO] 13684-63-4 S H 5 >8000
Phenothrin [ISO] 26002-80-2 PY L I 5 >5000 DS 85; EHC 96; HSG 32; ICSC 313; JMPR 1989
Phosphorus acid [C] 13598-36-2 L F 5 >5000
Phthalide 27355-22-2 S F 5 >10000
Picloram [ISO] 1918-02-1 S H 5 8200 ICSC 1246
Piperonyl butoxide 51-03-6 Oil SY 5 >7500 IARC 30; JMPR 1996b; ICSC 1347
Pretilachlor [ISO] 51218-49-6 L H 5 6100
Primisulfuron [ISO] 113036-87-6 S H 5 >5050
Procymidone [ISO] 32809-16-8 S F 5 6800 JMPR 1990, 2009b
Prodiamine [ISO] 29091-21-2 S H 5 >5000
Propamocarb 24579-73-5 S F 5 8600 JMPR 1987a
Propaquizafop 111479-05-1 S H 5 >5000 ICSC 1271
Propazine [ISO] 139-40-2 T S H 5 >5000 ICSC 697
Propham [ISO] 122-42-9 S H 5 5000 IARC 12; JMPR 1993
Propineb [ISO] 12071-83-9 S H 5 8500 DS 94; EHC 78; JMPR 1994
Propyzamide [ISO] 23950-58-5 S H 5 5620
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LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Prothioconazole [ISO] 178928-70-6 S F 5 >6200 JMPR 2009a
Pyrazolynate [ISO] 58011-68-0 S H 5 9550
Pyrazosulfuron [ISO] 98389-04-9 S H 5 >5000
Pyriminobac 136191-56-5 S H 5 >5000
Pyriproxyfen [ISO] 95737-68-1 S I 5 >5000 ICSC 1269; JMPR 2000
Quinmerac [ISO] 90717-03-6 S H 5 >5000
Quinoxyfen [ISO] 124495-18-7 S F 5 >5000 JMPR 2008
EHC 41; HSG 23; IARC 5; JMPR 1996b; ICSC Quintozene [ISO] 82-68-8 S F 5 >10000 745
Rimsulfuron [C] 122931-48-0 S H 5 >5000
Siduron [ISO] 1982-49-6 S H 5 >7500
Simazine [ISO] 122-34-9 T S H 5 >5000 ICSC 699
Spinetoram [ISO] 187166-40-1 S I 5 >5000 JMPR 2009a
Sulfometuron 74223-56-6 S H 5 >5000
Tebufenozide 112410-23-8 S I 5 >5000 Dermal LD50 > 5000; JMPR 1997b, 2004
Tebutam 35256-85-0 Oil H 5 6210
Tecnazene [ISO] 117-18-0 S F 5 >10000 EHC 42; HSG 12; JMPR 1995b
Teflubenzuron 83121-18-0 S I 5 >5000 JMPR 1995b
Terbacil [ISO] 5902-51-2 S H 5 >5000
Tetradifon [ISO] 116-29-0 S AC 5 >10000 EHC 67; HSG 11; ICSC 747
Tetramethrin [ISO] 7696-12-0 PY S O 5 >5000 EHC 98; HSG 31; ICSC 334
Thifensulfuron-methyl 79277-27-3 S H 5 >5000
Thifluzamide 130000-40-7 S F 5 >5000 Dermal LD50 > 5000 Thiophanate-methyl [ISO] 23564-05-8 S F 5 >6000 JMPR 1996b, 1999, 2008
Tiocarbazil 36756-79-3 TC L H 5 10000
Tolclofos-methyl [ISO] 57018-04-9 S F-S 5 c5000 JMPR 1995b
298
LD Common name CAS no UN no Chem Phys Main use GHS 50 Remarks type state mg/kg
Tolylfluanid [ISO] 731-27-1 S F 5 >5000 JMPR 1989, 2003b
Transfluthrin [ISO] 118712-89-3 PY S I 5 >5000
Triasulfuron 82097-50-5 S H 5 >5000
Tribenuron [ISO] 106040-48-6 S H 5 >5000
Trifloxystrobin [ISO] 141517-21-7 S F 5 >5000 JMPR 2006a
Triflumuron 64628-44-0 S PGR 5 >5000
Trifluralin [ISO] 1582-09-8 S H 5 >10000 IARC 53; ICSC 205
Triflusulfuron-methyl [ISO] 126535-15-7 S H 5 >5000
Triforine [ISO] 26644-46-2 S F 5 >6000 JMPR 1998b
Validamycin 37248-47-8 S F 5 >10000
Vinclozolin [ISO] 50471-44-8 S F 5 10000 JMPR 1996b
Zineb [ISO] 12122-67-7 S F 5 >5000 DS 94; EHC 78; IARC 12; ICSC 350; JMPR 1994
Zoxamide [ISO] 156052-68-5 S F 5 >5000 JMPR 2009b
EHC = Environmental Health Criteria Monograph; DS= Pesticide Data Sheet; HSG = Health and Safety Guide; IARC = IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; ICSC = International Chemical Safety Card; JMPR = Evaluation by the Joint FAO/WHO Meeting on Pesticide Residues.
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International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub.net Vol. 14, No. 2, p. 197-208, 2019
RESEARCH PAPER OPEN ACCESS
Pesticides use in Khyber Pakhtunkhwa Province Pakistan: present scenario
Rehmat Ullah* , Khalid Nawab
Department of Agriculture Extension Education and Communication, The University of Agriculture Peshawar, Pakistan
Key words: Pesticides, Khyber Pakhtunkhwa, Carbofuran, Cartap, Class. http://dx.doi.org/10.12692/ijb/14.2.197-208 Article published on February 12, 20199
Abstract
Use of pesticide is common to control diseases, weeds and insects in crop, vegetables and fruits, but usually at the expense of the human health. This present study was conducted in 2018 which was an attempt to find out the present scenario of pesticides use in Khyber Pakhtunkhwa. Khyber Pakhtunkhwa Province was selected as a universe of study. A total of 384 respondents were selected through unknown population sampling formulae i.e. 96 from each Union Council. Data were collected using well-structured interview schedule through personal interview method whereas simple frequencies, percentages and One Sample t-test were applied. The results showed that overall 49 different sorts of pesticides were reported by the farming community as the most commonly used by them and majority were insecticides. Mostly the insecticides were from Class-II of the pesticides toxicity level followed by the Class III and Class U. Only two insecticides i.e. Carbofuron and Cartap from Cartap Hydrochloride chemical group were from Class-Ib which are highly hazardous. Similarly, in 13 pesticides overdose was observed whereas in 8 pesticides low dose was observed in comparison to the recommended dose. It is suggested that the Agriculture Extension Department should initiate massive awareness campaign regarding health and environmental peril of pesticides use alongside the trainings to the farming community in safe use of pesticides. Furthermore, it was also suggested that the Agriculture Extension Department ought to strictly check the sub-standard and highly toxic pesticides in the local market. * Corresponding Author: Rehmat Ullah [email protected]
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Introduction 500000 suffered from poisoning (Dawn, 2004). Thus, Pesticides are poisonous by nature and constitute one due to the adverse effect pesticides the present study of the most hazardous groups of toxin to the was designed to examine the most commonly used ecosystem and human health (UNU, 2003; Belmonte pesticides in the region by farming community and its et al., 2005; Pimentel, 2005; Ahouangninou et al., comparison with WHO toxicity classes, and to 2012). Likewise, the other developing countries the compare the actual vs recommended dose of hazard of pesticides use is also increasing day by day pesticides use by farming community. (e.g. Karlsson, 2004; Hoi et al., 2013; Rı´os- Gonza´lez et al., 2013; Jansen and Dubois 2014). Due Material and methods to its diversity in nature the pesticides is widely used Population of study for to fight against pest in agriculture, gardening, The population of the study was the respondents from homes, and soil (Cooper and Dobson, 2007). But the province of Khyber Pakhtunkhwa (KP) province inspite of these returns, pesticide poisoning is of Pakistan which is divided into 4 Agro Ecological definitely a public health problem globally and its use Zones Viz. Northern Mountainous Zone, Eastern is still increasing day by day (Wesseling et al., 2001). Mountainous Zone, Central Plain Valley and Southern Pesticides act like a double edge sword i.e. on one side Piedmont Plain. Therefore a Multistage Sampling it fights against the agricultural pests but on the other technique was utilized for selection of the hand it also has an adverse effect both on the health respondents. of the human beings and the environment as well. Agricultural pests can cause considerable reductions Multistage sampling in farm yields and income. As a result, pesticides are Multistage sampling technique was used in the profoundly used in attempts to alleviate this problem. present study. The multistage or cluster sampling is Use of pesticide is a cheaper way to increase farm imperative because it is economically apt and productivity. Pesticide is a poison but its use is secondly it is suitable when the sampling frame of the essential and increasing day by day. According to an individual elements is not available. It is the selection estimate, 85-90% of pesticides never even arrive at of sample from the subset at each stage. The their intention organisms (Repetto and Baliga, 1996). multistage sampling of the respondents is as under It is very likely that many non-target organisms are Stage 1. Selection of districts: One district was exposed to multiple pesticides throughout their selected from each Agro ecological zones. In this lifetimes. connection District Dera Ismail Khan (D.I.Khan) was selected from Southern Piedmont Plain, District According to WHO in estimates in 1973 the human Charsadda was selected from Central Plain Valley, poisoning cases reported annually were 500000 District Mansehra was selected from Eastren whereas in 1986 the figure crossed the one million Mountainous Zone whereas District Swat was mark plus 20,000 deaths. Furthermore, three million selected from Northern Mountainous Zone. Stage II: cases has also been reported in a joint study of WHO Selection of tehsils: Single Tehsil was selected from and UNEP (WHO, 1990). The situation is more each district keeping in mind the time and financial alarming in developing countries where the people resource. The tehsils selected were as; Tehsil death rate is high instead of infections. As farmers use Paharpur, selected from district D. I. Khan, Tehsil increasing quantity of pesticides, poisonings will Charsada was selected in district Charsada, Tehsil continue to increase (WHO, 1990). Unsafe use of Mansehra was selected in Mansehra whereas Tehsil pesticides i.e. low dosing, high dosing and not using Matta was selected in Swat district. All these tehsils personal protective equipment is posting sever threat were selected in collaboration of Agriculture to the farmer’s health and other local inhabitants and Extension Department Govt. of KP and these were the thus resulting in annual deaths of 10,000 whereas agriculture rich tehsils.
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Stage III: Selection of Union councils: From each expectations and respondents interests. The cross selected Tehsils single Unions council was selected sectional survey is also most appropriate in a view to i.e. Union council Band Kurai, Baidara, Khanmai, establish correlation between two and more variables Baffa was selected from tehsil Paharpur, Matta, and could be examined by a range of methods. It is Charsadda and Mansehra respectively. These UCs also useful for small as well as for large population by were selected purposively with the collaboration of selecting studying samples, to discover the incidence Agriculture Extension Department that these UCs are distribution and relationships of various social and the agriculturally rich. psychological aspects.
Stage IV: Selection of Sample size and respondents: Research instrument Due to no proper study available regarding the Keeping in view the importance of interview schedule selection of the potential respondents as sampling and objectives of the present study, well-structured units, the sample size was determined on assumed interview schedule was developed which was based on variability such as 50 % for the farmers those are open, close and partially open ended questions. The involved in the use of pesticides on their farms as farmers were queried regarding these suggested by Kasely and Kumar (1989). questions/information. The questions were based on Consequently, the number of farmers (respondents) the precautionary measures and PPE used while using included in the present study were determined using pesticides and self-reported acute poisoning cases. formula for unknown population which is defined in Face and content validity of the interview schedule the following Equation (i). was measured. Face validity was measured by asking questions from the respondents who were not actually n = Z2 σ 2/ d2------(i) involved in the study and appropriate response was Where, Z2= statistic for a level of confidence. (For the obtained whereas for content validity the research level of confidence of 95%, which is conventional, Z instrument was checked by the panel of experts from value is 1.96). Agriculture Extension Education and Communication, The University of Agriculture n = Sample size Peshawar and necessary amendments were made σ= estimated standard deviation that thereafter. For reliability of the research instrument, 50% of the farmers would apply pesticides in their data from 30 farmers were collected which was not fields included in actual study. After collection of the data, d = precision. (d is considered 0.05 to produce the data were subjected to SPSS ver. 20 for scale good precision and smaller error of estimate) (5%) reduction test i.e. Cronbach’s alpha test. Cronbach alpha value obtained was 0.831 representing good = 384 internal consistency.
Therefore through equal allocation formula, 96 Data collection respondents were selected from each of the selected Data collected for the present study was based on Tehsil. The respondents were selected using both primary and secondary data. Various published convenience sampling technique. and unpublished sources were used for the purpose of secondary data whereas primary data were collected Research design using well developed interview schedule. Face to face Cross sectional survey design was utilized as a part of interviews were conducted in order to record the current investigation. Data collection at one point firsthand information and to remove any ambiguity of is the fundamental concept of cross sectional survey. the respondents as and when prevails regarding any It is best suited in determining the perceptions, question.
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Statistical analysis of the data pesticides toxicity classes. It consists of extremely Statistical Package for Social Sciences (SPSS) ver. 20 hazardous (Class Ia), highly hazardous (class Ib), was used for analysis of the data. Simple frequency, moderately hazardous (Class-II), slightly hazardous percentages and one sample t-test was utilized. (Class-III), unlikely to present acute serious hazards in normal use (Class-U) whereas obsolete chemicals Results and discussion to be considered as pesticide are included in Class-O Most commonly used pesticides (WHO, 2009). Nearly 90 percent ofthe banned Toxicity of pesticides based on their formulation are pesticides fall into category of Class-Ia, Class-Ib and been classified by the WHO and been termed as WHO Class-II of the WHO hazard grades.
Table 1. Overall Sketch of the Sampling Procedure Using Multistage Sampling Technique. Sr. # Zones Districts Tehsils Union Council Sample 1 Northern Mountainous Zone Swat Matta Baidara 96 2 Eastern Mountainous zone Mansehra Mansehra Baffa 96 3 Central Plain valley Charsadda Charsadda Khanmai 96 4 Southern piedmont Plain D.I.Khan Paharpur Bandkurai 96 Total 384
Results in Table 2, 3 and 4 showed the various types with that of Chitra et al. (2013) who reported in their of pesticides in use by the farming community. The study that majority of the respondents were using instant survey depicts that there were 49 different pesticides from highly hazardous Class of WHO. sorts of pesticides most commonly in use by the farming community as per the present study. Among Similarly, 25 different sorts of insecticides were the 49 various pesticides 14 were weedicides (Table reported by the respondents (Table 3). Among them 2), 25 were insecticides (Table 3) whereas 10 were the majority (14) of the insecticides were from Class- fungicides (Table 4). Instant results showed that II of the pesticides toxicity level followed by the Class majority of the pesticides in use were insecticides III and Class U i.e. 4 each respectively. Only two which showed the prevalence of insect pest in the area insecticides i.e. Carbofuron and Cartap from Cartap is high enough in contrast to the diseases and weeds. Hydrochloride chemical group were from Class-Ib Similarly, majority (5) of the weedicides were from which represents highly hazardous (WHO, 2009). Class III of hazardous followed by 3No.s weedicides which were from Class II whereas 5 were from Class The insecticides were from the chemical group of U. only one weedicides from Class-O was observed in Anthranilic Diamide, Nicotinoid, Pyrethroid, the present study. These weedicides were from Organophosphates, Neonicotinoids,Organochlorines, different chemical groups i.e. Triazine, Amide, Avermectins and Urea. The insecticides used for Dinitroanilin, Organic, Phenylpyrazolin, various pests as reported by the respondents were Aryloxyphenoxypropionate, Organophosphorus, presented in Table 2. Our results are in conformity Chloroacetamide, Nitrile, Phenoxy, with that of Jamali et al. (2014) who also reported Pyridinecarboxylic acid, Sulfonylurea, Diphenylether that majority of the pesticides were from Class-II of and Sulfonylurea. The weedicides used for various WHO toxicity classification. Similarly, Mengistie et al. purposes are showed in the Table 2. This showed that (2017) reported that most commonly used pesticides the farming community was using pesticides from were Mancozeb, Karate, Malathion and Ridomil Gold moderately hazardous and slightly hazardous classes which are in conformity with our results. Moreover, (WHO Recommended Classification of Pesticides by they also reported that majority of the pesticides were Hazard, 2009). The instant results are in contrast from Class-II of WHO toxicity classes.
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Table 2. Status of the most commonly used weedicides. Active ingredient Brand name Chemical group Pest WHO class Atrazine+Smetolachlor Primextra gold 720 SC Triazine and amide Controls certain annual grasses and broadleaf weeds III in Maize, Sugarcane and Sweet Corn, Barnyard Grass, Blackberry Nightshade, Caltrop, Common Thornapple, Crowsfoot Grass, Liverseed Grass Pendimethalin Stomp 455 g/l CS Dinitroaniline A pre-emergent herbicide for the control of grass III weeds S metolachlor Dual gold 960 EC Organic Annual grasses and some annual broad-leaved III weeds Penoxaden Axial 050 EC Phenylpyrazolin Controls wild oats and ryegrasses in winter and - spring wheat and winter and spring barley. Controls blackgrass in winter and spring barley as part of an integrated control strategy Fenoxaprop Puma super 69 EW Aryloxyphenoxypropionate Annual and perennials grass weeds O
Glyphosate Round up PM 540 g/l SL Organophosphorus Annual and perennial weeds III Atrazine+Smetolachlor Primextra gold 720 SC Triazine+chloroacetamide Controls certain annual grasses and broadleaf weeds III in maize, sugar cane and sweet corn, also in sorghum Bromoxynil+MCPA Buctril super 60 EC 60 Nitrile+ Phenoxy Broad leaf weeds II Aminopyralid+florasulam Lancelot 45 WG Pyridinecarboxylic acid Crow pea, Common U Goosefoot, Field bindweed Fluroxypyr+MCPA Harvester 50 EC Pyridinecarboxylic acid+ Crow pea, Jungle onion, Common vetch, U+II Phenoxy Metsulfuron+ tribenuron Allymax 66.7 WG Sulfonylurea Common Goosefoot, Field bindweed, Broadleaf U dock, Blue pimpernel, Fathen, nettle leaved goosefoot, Bur clover, Yellow sweet clover Fumitory, Oxyfluorfen Axifin 24 EC Diphenylether Field bindweed U Triasulfuron Logran 75 WG Broadleaf dock, Blue pimpernel, Fathen, U Sulfonylurea nettleleaved goosefoot, Jungle onion, Haloxyfop Percept 10.8 EC Aryloxyphenoxypropionate Bermuda grass, Water couch, Johnson grass, II
From the instant results, it can be seen that majority used in agriculture, most are insecticides &miticides, of the respondents rely on Organophosphorus group and their way of joining these organizations is by of chemical in order to fulfill their needs which are ingestion and contact. High levels of exposure to the esters derived from phosphoric acid. This is toxic organochlorines (one type of pesticides) have been because of the fact that it effect on human being shown to cause cloracne, a type of acne cause by central nervous system by inhabiting acetyl chlorine containing chemicals and skin rashes. There cholinesterase. Acetyl cholinesterase is an enzyme is some evidence that organophosphate insecticides which modulates the level of neurotransmitter affect the immune system and can cause psychiatric acetylcholine, thus disrupting the nerve impulse by problems such as paranoid behaviour, disorientation, serine phosphorylation of the hydroxyl group in the anxiety and depression (Garcia et al., (2012). active site of the enzyme (Sorgob and Vilanova, 2002). This results in loss of reflexes, head ach, Among ten fungicides as reported by the farming dizziness, nausea and even death (Perry et al., 1998). community the majority (8) were from the Class-II Organophosphorus compounds are most commonly whereas only two were from Class-U (Table 4).The
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fungicides reported by the farming community were reported by the respondents which were being used in from Dithio-carbamates, Triazoles, Oximino-acetates, the locality yet but it could be lower than actual Methoxy-acrylates and Organophosphorus chemical number of pesticides in use because of the fact that group. The results of the present study indicated a different farmers have different interest of applying wide variety of chemicals were utilized as pesticides in pesticides and due to the sample of 384 respondents the area. Although 49 different pesticides were only 49 were reported.
Table 3. Status of the most commonly used insecticides. Active ingredient Brand name Chemical group Pest WHO class Chlorantraniliprole+Thiamethoxam Voliam Flexi 300 SC Anthranilicdiamide key sucking, chewing and lepidopteran pests in U citrus and tree fruit Imidacloprid Confidor 200 SL Nicotinoid Spinola bug, pod bug, Mango hopper, Citrus psylla, WB Plant hopper, Aphids, White fly, Mango mealy II bug, Cotton mealybug, S. cane Leaf hopper, Red pumpkin beetle, Mirid bug Bifenthrin Talstar10 EC Pyrethroid Spinola bug, pod bug, Black bug, Cutworm, Shoot II fly, Citrus leaf miner, Vegetable leaf miner, Lemdacyhalothrin Karate 5 CS Pyrethroid Plant hopper, Green leaf, hopper, Thrips, sucking II insects/wide range of insects, Hairy caterpillar, Rice leaf folder, Capsule borer, Mango hopper, Rice grass hopper, Cutworm, Citrus leaf miner, Gamacyhalothrin+chlorpyrifos Bolten 31EC Pyrethroid+ Black bug, Brinjal stem borer, Pink bollworm, II Organophosphates Cabbage butter fly, Chlorantraniliprole Coragen 20 SC Anthranilicdiamide Protects a variety of vegetable crops, corn and U canola from insects such as, cutworms and armyworms. Trichlorfon Dipterex 30 T 60 Organophosphates Fruit fly II Gama cyhalothrin Proaxis 60 SC Pyrethroids Spinola bug, pod bug, Rice leaf folder II Cypermethrin Cypermethrin 10 EC Pyrethroid Defoliators, Green leaf Hopper II Chlorantraniliprole+Thiamethoxam Virtako 0.6 Gr Anthranilicdiamide White stem borer, Yellow stem borer, Top borer, U Stem borer, Sugarcane root borer Chlorantraniliprole Ferterra 0.4 G Diamides White stem borer, Yellow stem borer U Thiamethoxam Actara 25 WG Neonicotinoids A broad spectrum of sucking soil and leaf-feeding III pests like Aphids, Jassids Chlorpyrifos Larsbin 40 EC 40 EC Organophosphates Stalk borer, termites, soil born insects II Malathion Malathion 57 EC Organophosphates Green leaf hoppers, III Thrips, Rice bug Endosulfan Thionex 35EC Organochlorines Ball worm, thrips, II Emamectin Several Avermectins Lepeidopterous fruit worm III Acetamiprid Several Nicotiamide Sucking pests and mites II Profesofos+Cypermethrin Polytrin C Pyrethroids Caterpillars, aphids, mites and sucking pests II Emamectin benzoate Proclaim Avermectins armyworms, pinworms, diamondback moths, - fruitworms and leafrollers Dimethoate Dimethoate4C Organophosphate Key insect pests in a variety of crops including II citrus, soybeans, corn, cotton Carbofuron Furadan 3 G Cartap hydrochloride Meloidogyne species, Root, stem, top, Ib Cartap Padan 4 G Cartap hydrochloride Plant hopper, Green leafHopper Ib Profenophos curacran 500 EC Organophosphorus Against lepidopterous larvae II Lufenuron Match 50 EC Urea Against lepidopterous larvae II Diafenthiuron Diafenthiruron 50% SC Urea Sucking pests & mites III
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The vegetable and fruits farmers depended heavily on were busy in spraying various sort of pesticides. use of pesticides for control of different pests and diseases and over 49 different formulations were The same was also reported by the Jamali et al., 2014 used. This might be because of the reason that their that farmers were much interested to control the attitude has been developed that solely the pesticides pests by using pesticides and thus were using diverse use is the solution of the controlling pests thus they pesticides in the study area.
Table 4. Status of the most commonly used fungicides. Active ingredient Brand name Chemical group Pest WHO class Propineb Antracol 70 WP Dithio-carbamates Early blight U Difenoconazole Score 250 SC Triazoles Powdery mildew, early blight, Decline, II Trifloxystrobin+Tebuconazol Nativo 75 WG Oximino-acetates+ Leaf spot, Rice blast, Powdery mildew II triazoles Azoxystrobin+flutriafol Nanok 25 SC Methoxy-acrylates Leaf spot, Rice blast, Downy mildew II Mencozeb+metalaxal Ridomil gold 68 WG Dithiocarbamate +Anilide Late blight, powdery mildew, Collar rot II Copper hydroxide Champion 77 WP - Bacterial leaf blight II Propeconazol Tilt Organophosphorus Blast, Rust II Copper Oxychloride Several Inorganic Early blight II Delamethrin Pyrethroid Inorganic Chewing and sucking pest II Thiophanate methyl Several Benzimidazole Powdery Mildew U Note: Ia = Extremely hazardous, Ib = Highly Hazardous, II = moderately hazardous;III = Slightly hazardous; U = Unlikely to present acute hazard in normal use;O = Obsolete as pesticide, not classified.
The present research study authenticate that the 2000). This situation is also true in many developed pesticides sellers who aim at business profit, shy away countries where the choice of pesticides to be used by the environmental and health risk that are entailed farmers is influenced by the suppliers (Epstein and due to excessive use of pesticides. It is in conformity Bassein, 2003). with similar pattern in African countries (Abate et al.,
Table 5. One Sample t-test of recommended Vs actual used weedicides dose by the respondents. Brand name Active ingredient Recommended Mean farmers dose/Ha±SD Difference t-value Freq. (%) Use/Ha Primextra gold 720 SC Atrazine+Smetolachlor 1600 ml 1612.71±30 +12.71 4.891** 103(26.82) Stomp 455 g/l CS Pendimethalin 2000 ml 1997.9±80 +2.09 0.297NS 129(33.59) Dual gold 960 EC S metolachlor 1600 ml 1611.95±18.67 +11.95 7.09** 123(32.03) Axial 050 EC Penoxaden 660 ml 636.78±20.88 -23.21 11.92** 115(29.95) Puma super 69 EW Fenoxaprop 1000 ml 1001.54±8.33 +1.54 1.827NS 97(25.26) Round up PM 540 g/l SL Glyphosate 4000 ml 3993.82±27.03 -6.17 -2.157* 89(23.18) Buctril super 60 EC 60 Bromoxynil+MCPA 800 ml 802.43±5.91 +2.43 2.53* 123(32.03) Lancelot 45 WG Aminopyralid+florasulam 25 g 26.27±3.1 +1.27 3.143** 59(15.36) Harvester 50 EC Fluroxypyr+MCPA 800 ml 799.71±8.21 -0.285 -0.206NS 68(17.71) Allymax 66.7 WG Metsulfuron+ tribenuron 16 gram 16.45±1.05 +0.45 1.97NS 128(33.33) Axifin 24 EC Oxyfluorfen 600 ml 603±13.01 +3 1.01NS 86(22.40) Logran 75 WG Triasulfuron 32 gram 34.35±0.81 +2.35 12.93** 113(29.43) Percept 10.8 EC Haloxyfop 700 ml 696±13.13 -4 -1.361NS 39(10.16)
It is because of the pest and disease which badly subsidized rates but still farmers relied continuously affects the vegetable yield hence the farmers are on pesticides dealers. Because of the illiteracy and compelled to apply and spray pesticides excessively, lack of knowledge farmers do not select the right in order to have better crop. In Pakistan there is pesticides and right amount of the dose, in order to public agriculture extension wing which upholds the avoid the bad effect upon the environment and facilities for the farmers to provide pesticides on health. That fact has also been rightly pointed out by 203 Ullah and Nawab
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Epstein and Bassein (2003), wherein they had (Mukherjee and Gopal, 2003). Monitoring of observed that farmers prefer the application of pesticides is conducted globally to assess the pesticides upon their own settled out method of environmental load of their residues. Currently calendar rather keeping in view the effect upon health pesticides wide use in the world as an alternative pest and environment. control replaying persistent organochlorines (Toan et al., 2007). Because of wide spread use of pesticides, A wide range of pesticides are globally used for crops the presence of their toxic residues have been protection during the cultivation of vegetables due to reported in various environmental component/ heavy pest infestation throughout the season of crop commodities (Kumari et al., 2006; Kumari and and food (Agnihotri, 1999), Literature reveals that in Kathpal, 2009; Wang et al., 2008). most of the vegetables the Maximum Residual Limit (MRL) were crossed by the residues of the pesticides These pesticide residues find their way into the and this may pose severe health hazards to consumers human body through food, water, and environment.
Table 6. One Sample t-test of recommended Vs actual used insecticides dose by the respondents. Brand Name Active Ingredient Recommended Mean Farmers Difference t-value Freq. (%) Use/Ha dose/Ha±SD Voliam Flexi 300 SC Chlorantraniliprole+Thiamethoxam 160 ml 162.5±9.24 +2.5 1.209NS 143(37.23) Confidor 200 SL Imidacloprid 400 ml 418±15.07 -18 -5.339** 137(35.67) Talstar10 EC Bifenthrin 500 ml 492.25±14.82 -7.5 -2.26* 82(21.35) Karate 5 CS Lemdacyhalothrin 500 ml 519.25±8.87 +19.25 9.831** 172(44.79) Bolten 31EC Gamacyhalothrin+chlorpyrifos 1000 ml 1014.5±42.48 +14.5 1.526NS 88(22.91) Coragen 20 SC Chlorantraniliprole 100 ml 98.32±1.31 -1.68 -0.96NS 171(44.53) Dipterex 30 T 60 Trichlorfon 200 g 206.5±14.24 +6.5 2.041NS 42(10.93) Proaxis 60 SC Gama cyhalothrin 200 ml 210.5±12.76 +10.5 3.67** 21(5.46) Cypermethrin 10 EC Cypermethrin 500 ml 509±12.09 +9 3.327** 182(47.39) Virtako 0.6 Gr Chlorantraniliprole+Thiamethoxam 8 kg 7.9±0.30 -0.1 -1.45NS 31(8.07) Ferterra 0.4 G Chlorantraniliprole 8 kg 7.8±0.42 -0.2 -1.49NS 17(4.42) Actara 25 WG Thiamethoxam 50 g 55.3±6.07 +5.3 3.49** 172(44.79) Larsbin 40 EC 40 EC Chlorpyrifos 4 litre 4.21±3.72 +0.21 1.031NS 71(18.48) Match 050 EC Lufenuron 400 ml 411.24±16.17 +11.24 2.45* 46(11.97) Malathion Malathion 57 EC 8 litre 8.03±0.23 -0.03 -0.92NS 21(5.46) Polytrin C Profesofos + Cypermethrin 1 liter 0.98±0.32 -0.02 -0.23NS 73(19.01) Diafenthiuron 50% SC Diafenthiuron 1600ml 1618.19±23.12 +18.19 2.981* 41(10.67) Proclaim Emamectin benzoate 260gm 252.19±12.34 -6.81 -1.29* 27(7.03) Furadan 3 G Carbofuron 18 kg 19.9±1.57 +1.9 2.93* 61(15.88) Diafenthiruron 50% SC Diafenthiuron 400ml 391.2±6.91 -8.8 -1.02NS 38(9.89) Padan 4 G Cartap 9 kg 9.78±1.38 -0.78 -2.013* 74(19.27)
Dosage of Pesticides use in KP Lamdacyhalothrin insecticide were the most Similarly the respondents were also investigated that frequently applied by the respondents i.e. 172 what dose you applied in controlling the pest and respondents and highly significantly (P≤0.01) above then was checked with the recommended dose in the recommended dose with the mean difference of order to find out the difference. The results of one +19.25 ml ha-1 and t-value of 9.831 (Table 6). sample t-test were presented in Table 5, 6 and 7. It Similarly highly significant (P≤0.01) difference was was found that majority of the respondents were also observed in Primextra gold 720 SC with mean using high dose then the recommended dose. difference of +12.71ml ha-1, Dual gold 960 EC (+11.95
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ml ha-1), Lancelot 45 WG(+1.2g ha-1), Logran 75 WG was observed in Buctril super 60 EC 60 (+2.43 ml ha- (+2.35 g ha-1), Proaxis 60 SC (+10.5 ml ha-1), 1), Match 050 EC (+11.24 ml ha-1), Diafenthiuron 50% Cypermethrin 10 EC (+9 ml ha-1), Actara 25 WG (+5.3 SC (+18.19 ml ha-) and Furadan 3 G (+1.9 kg ha-1) g ha-1) and Score 250 SC (+11.5 ml ha-1) (Table 5, 6 then the recommended. and 7). Moreover, significantly (P≤0.05) high dose
Table 7. One Sample t-test of recommended Vs actual used fungicides dose by the respondents. Brand Name Active Ingredient Recommended Mean Farmers Difference t-value Freq. (%) Use/Ha dose/Ha±SD Antracol 70 WP Propineb 1000 g 986.23±66.35 -13.77 -0.91NS 134(34.9) Score 250 SC Difenoconazole 200 ml 211.5±13.48 +11.5 3.81** 171(44.53) Nativo 75 WG Trifloxystrobin+Tebuconazol 130 g 128.92±0.76 -1.08 -0.79NS 178(46.35) Nanok 25 SC Azoxystrobin+flutriafol 400 ml 403.29±5.21 +3.29 1.76NS 128(33.33) Ridomil gold 68 WG Mencozeb+metalaxal 500 g 483.5±20.07 -16.5 -3.676** 181(47.14) Champion 77 WP Copper hydroxide 500 g 486.5±19.54 -13.5 -3.09** 51(13.28) Tilt 250 EC Propiconazole 500 g/L 492±17.94 -8 -1.993NS 121(31.51)
It was a matter of serious concern that Furadan 3 G honey bees. Instant results showed that the problem were from the Class-Ib (Table 3) and still farmers is not the pesticide but how it is been handled. The were busy to use high dose then the recommended; indiscrimation in violation of recommendations thus affecting the environment and their health as effects the agriculture sustainability, health of well. Furadan is a systemic insecticide; it is been growers/consumers and environment itself. This absorbed through roots and carried out to the other situation calls for a transformation of these practices. parts of the plants where insecticidal concentrations Moreover, farmers were using inappropriate doses of are attained. Moreover, carbofuran also serve as pesticide. Overdosing ha-1 introduces surplus contact activity against pests. Furthermore, highly pesticides to the environment and may result in crop significantly (p≤0.01) low dose was observed in Axial damage. Furthermore, inaccurate dilution can reduce 050 EC (-23.21 ml ha-1), Confidor 200 SL (-18 ml ha- pesticide efficiency or can increase residues and speed 1), Ridomil gold 68 WG (-16.5 g ha-1) and Champion up the development of pesticide resistance. 77 WP (-13.5 g ha-1). Significantly (p≤0.05) low dose then the recommended was recorded in Round up PM Conclusion 540 g/l SL (-6.17 ml ha-1), Proclaim (-6.81 gm ha-1) It is concluded from the present study that most of and Padan 4 G (-0.78 kg ha-1). Using below the the farmers were busy using pesticides from Class III, recommended dose of pesticides results in creating Class II, Class Ib, U and O and mostly rely on the resistance against the pest which ultimately results in pesticides from Organophasphates group which is increasing number of pesticide spray. Therefore it can dangerous for health. Similarly, it was also concluded be concluded that the farming community were not from the present study that farmers were busy in following the exact recommended dose and thus overdosing and low dosing which in both cases causes misusing the pesticides. Among the sample problems for the farming community. In both the respondents majority (47.39%) of the respondents cases, misuse of pesticides occurs i.e. by applying reported Cypermethrin 10 EC followed by the Ridomil pesticides indiscriminately is the violation of the gold 68 WG (47.14%), Nativo 75 WG (46.35%), Actara scientific recommendations. By applying the low dose 25 WG (44.79%), Karate 5 CS (44.79%), Coragen 20 of pesticides it initiates resistivity in the target pest SC(44.53%) and Score 250 SC (44.53%) (Table 5, 6 & whereas with overdosing create environmental 7). The increased use of pesticides i.e. cypermethrin, problems i.e. kills other non-targeted organisms and can also be associated with failure of breeding in give stress to crops. It is suggested that the massive
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Int. J. Biosci. 2019 campaign should be launched in order to bring Pesticides and Its Impact on Health of Farmers in awareness among the farming community regarding South India. International Journal of Occupational the classes of WHO toxicity prior to selection of and Environmental Health 12(3), 228-233. pesticides for their crops. Moreover, Agriculture Extension Department should take initiative by taking Cooper J, Dobson H. 2007. The Benefits Of the pesticides companies onboard for arrangement of Pesticides To Mankind And The Environment. Crop scheduled trainings in order to train the farming Protection, 26(9), 1337-1348. community in safe handling and scientific application of pesticides. Dawn. 2004. Deaths from Poisoning of Agro- Chemicals on the Rise. The Daily Dawn, Internet Authors’ contribution Edition, July 29. The present study was the part of PhD dissertation, the whole study was conducted under the supervision Devine GJ, Furlong MJ. 2007. Insecticide Use: of the Prof. Dr. Khalid Nawab. The study was Contexts and Ecological Consequences. Agriculture designed by Prof. Dr. Khalid Nawab whereas data and Human Values 24(3), 281-306. collection, analysis and write-up was done by Rehmatullah. Moreover, final revision before Epstein L, Bassein S. 2003. “Patterns of Pesticide submission was also given by Prof. Dr. Khalid Nawab. Use in California and the Implications for Strategies for Reduction of Pesticides”, Annual Review of References Phytopathology 41, p 351–375. Abate T, Huis A, Ampofo JKO. 2000. “Pest Management Strategies In Traditional Agriculture: Garcia FP, Sandra Y, Ascencio C, John C, An African Perspective”, Annual Review of Oyarzun G, Hernandez AC, Alavarado PV. Entomology 45, p 631–659. 2012. Pesticides: Classification, Uses and Toxicity. Measures of Exposure and Genotoxic Risks. Journal Agnihotri NP. 1999. “Pesticide safety evaluation of Research in Environmental Science and Toxicology and monitoring”, Published all India coordinated 1(11), 279-293. research project of pesticide residues division of agricultural chemical, 1999, New Delhi: Indian Hoi PV, Mol APJ, Oosterveer P, Brink PVD. Agricultural Research Institute, p 119–146. 2009. Pesticide Distribution and Use In Vegetable Production in the Red River Delta Of Vietnam. Ahouangninou C, Martin T, Edorh P. 2012. Renewable Agriculture and Food Systems 24(3), Characterization of Health and Environmental Risks 174–185. of Pesticide Use In Market-Gardening In The Rural City Of Tori-Bossito In Benin, West Africa. Journal of Hoi PV, MolA PJ, Oosterveer P. 2013. State Environmental Protection 3, 241–248. Governance of Pesticides Use and Trade in Vietnam. NJAS - Wageningen Journal of Life Sciences 67, 19– Belmonte A, Vega A, Garrido F, Martinez L. 26. 2005. Monitoring of Pesticides In Agriculture Water And Soil Samples From Andulasia By Liquid Jamali AA, Solangi AR, Memon N, Nizamani Chromatography Couple To Mass Spectrometry. SM. 2014. Current Scenario of Pesticide Practices Analytica Chemica Acta 53(8), 117-127. among Farmers for Vegetable Production: A Case Study in Lower Sindh, Pakistan. International Chitra GA, Muraleedharan VR, Journal of Development and Sustainability 3(3), Swaminathan T, Veeraraghavan D. 2013. Use of 493-504.
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UCD School of Agriculture and Food Science Agriculture and Food Science Centre, University College Dublin, Belfield, Dublin 4, Ireland.
Tel: + 353 – 1 - 716 7784 E-Mail: [email protected]
16 August 2019 Prof Dr Shaukat Hussain, Controller of Examinations, The University of Agriculture, Peshawar-Pakistan
RE: PhD thesis evaluation; Mr. Rehmat Ullah
I am very pleased to write this report on the PhD thesis of Mr. Rehmat Ullah. The title of the thesis is “Investigation into Health and Environmental Hazards of Pesticides Use to Farming Community in Khyber Pakhtunkhwa, Pakistan”. Having read this thesis my overall impression is that the candidate has undertaken a very significant amount of original research and collected an enormous amount of data in completion of this work.
1. The research topic investigated is of immense practical importance to the target population (farmers who apply pesticides in Khyber Pakhtunkhwa) and indeed likely to be relevant to all farmers in Pakistan and adjacent countries. The findings that emerged from this research and presented so cogently in this thesis illustrate an alarming situation in the level of Khyber Pakhtunkhwa farmers’ knowledge of the use and dangers of pesticide applications and clearly present a case for an increased role for the local Extension Department to become more involved in training and publicity campaigns to address this situation. Thus, this is research topic is most certainly appropriate for a PhD research project.
2. The main thesis is presented in five chapters. Chapter 1 presents an introduction to the thesis and a clear justification for this research. Objectives, clearly linked to this justification are presented together with the research hypotheses. Chapter 2, the Review of the Literature, appears to be quite brief. Unusually in a PhD thesis, this review is presented author by author, rather than thematically. Chapter 3, Materials and Methods, presents the methodology employed in conducting this research. This is very well presented and defended. Chapter 4 presents the results and discussion. This is a very substantial chapter (161 pages out of a total of 215 for the main body of the thesis) and is very comprehensive. This chapter presents a far better review of literature than Chapter 2, which is titled Review of the Literature! Most sections of Chapter 4 commence by summarizing what the academic literature on this issue has found, then presents the findings from the present research and concludes by comparing both – this is done very effectively. It contributed to a very enjoyable and logical approach to presenting and discussing the findings. Chapter 5 succinctly summarized the findings, drew conclusions and issued some pertinent recommendations.
Dr Pádraig Wims, Associate Professor (Rural Development)
UCD School of Agriculture and Food Science Agriculture and Food Science Centre, University College Dublin, Belfield, Dublin 4, Ireland.
Tel: + 353 – 1 - 716 7784 E-Mail: [email protected]
Overall, the thesis is presented in a scholarly style. The sections and sub-sections are appropriate for the work presented in the thesis. The main weakness is the manner in which the present Chapter 2 (Review of Literature) is presented. However, it subsequently emerged that an outstanding review of literature was conducted by the researcher but this was presented in a later chapter (Chapter 4).
3. This thesis presents original research that clearly builds on previous relevant research that has been conducted elsewhere. However, it is localized to the research site.
4. The candidate has clearly undertaken a comprehensive review of previous research on this topic which informed his research objectives and helped to refine and develop his own research instruments. I consider that an enormous amount of data was collected and presented for the purposes of this research and it clearly illustrates the breadth and depth of the candidate’s knowledge of this specialized area.
5. The candidate has ably demonstrated a thorough understanding of the subject of this research. He has established beyond doubt his knowledge of the health and environmental hazards of pesticide use among the farming community and in addition has demonstrated his understanding of social research methods used by the academic community and statistical methods employed by researchers.
6. The body of research is very well referenced. The references extend from peer- reviewed journal articles to research theses to published reports. They cover an appropriate time period and an ample proportion are of recent origin. The style of referencing both in the text and in the References section is excellent.
7. The language used throughout the thesis is acceptable. There are some instances of incorrect usage but this is not excessive and certainly with the bounds of what would be considered tolerable.
Based on the above comments, I have no hesitation in recommending that the degree of PhD be awarded to this candidate. In my university system and in other universities in Europe where I have experience, the criterion for awarding a PhD degree is that the thesis is worthy of publication, in whole or in part, as a work of serious scholarship. On this basis, the research presented in this thesis is clearly a work of serious scholarship. A large volume of data has been collected, analysed and presented in this thesis. This research is of such importance among the academic community and ultimately among the farming community who, on the basis of the findings presented here, are at serious risk from their lack of knowledge of pesticides that I
Dr Pádraig Wims, Associate Professor (Rural Development)
UCD School of Agriculture and Food Science Agriculture and Food Science Centre, University College Dublin, Belfield, Dublin 4, Ireland.
Tel: + 353 – 1 - 716 7784 E-Mail: [email protected]
urge that this researcher, together with his mentors and supervisors start to publish papers in peer-reviewed journals from this thesis. It is obvious that there are several high-quality papers that could be published from the data collected for this thesis, with a little more bivariate analysis. I strongly encourage these researchers to consider this while the data are still current.
In the event that the candidate or his supervisory committee wishes to make changes to the thesis, I will be very pleased to review these changes.
Finally, I would like to take this opportunity to thank you for the privilege of examining this thesis and I wish the candidate a very successful career pursuant to obtaining his PhD degree.
Yours sincerely,
Dr Pádraig Wims, Associate Professor (Rural Development) Tokyo University of Agriculture and Technology
3-5-8, Saiwai-cho, Fuchu, Tokyo 183-8509 Japan
5 April, 2019
Evaluation of Ph.D. Dissertation of Rehmat Ullah
Title of the Thesis: INVESTIGATION INTO HEALTH & ENVIRONMENTAL HAZARDS OF PESTICIDES USE TO FARMING COMMUNITY IN KHYBER PAKHTUNKHWA, PAKISTAN Evaluating the thesis, according to me this describes a wide-ranging study of risk of pesticides in farming community in Pakistan. The candidate has carried out a valuable practical research. The thesis comprises of four chapters. In Chapter 1, the introduction to topic, problem statement, research hypothesis. The Chapter 2 is review of literature. The Chapter 3, materials and methods of this study. The Chapter 4 are results and conclusions. Sample size of 384 respondents was selected for the study. Statistical analysis of the data revealed that majority of the respondents were using pesticides from the last 10 years. The respondents were not using proper personal protection measures thus increases the odds of health issues to the farming community and were suffered from various acute poisoning cases. Moreover, the knowledge of the farming community regarding the health and environmental hazards was low. Overall 49 different sorts of pesticides were reported by the farming community as the most commonly used by them and majority were insecticides. Almost half of the respondents got training regarding the pesticide’s application, and other health and environmental issues related to pesticides but still the respondents were not fully aware of the knowledge about the highly toxic pesticides, calibration of pesticides, pesticides application techniques, safety measures, understanding the labels/instructions on pesticides containers.
I understand laborious work in this study, but there are many mistakes in statistical digit (I recommend three digits and showed in red in Tables) and unit (for example g and gram in Table 4.7.2, after parenthesis should be half space). As there are so many mistakes, I did not change after this Table (please correct by himself). As these are only technical mistakes, I recommend that the candidate should be awarded Ph.D. degree.
Professor Yoshiharu FUJII, Ph.D (Agr.)
Tokyo University of Agriculture and Technology
3-5-8, Saiwai-cho, Fuchu, Tokyo 183-8509 Japan
Phone & Fax: +81-42-367-5625
E-mail: [email protected] Plagiarism Undertaking
This is verified that the thesis is product of original research and no work under the same title is conducted earlier. The thesis or part of the thesis is not plagiarized, checked by the Turnitin Software with the following results:
Supervisor’s Name: Prof. Dr. Khalid Nawab
Department: Agricultural Extension Education and Communication
Signature ______Stamp / Seal______
Undertaking by Student: I do hereby solemnly declare that my thesis is plagiarism free and I have not been involved in cut/copy and paste in my thesis, if any part of my thesis found plagiarized at any stage, I will be responsible for that and will be liable for penalty as per HEC policy.
Student’s Name Rehmat Ullah Degree: Doctor of Philosophy
Department: Agricultural Extension Education and Communication
Similarity Index: 17%
Signature ______Date ______/______/______