ISSN : 0021-3721 JNKVV Volume : 47 Research Journal Number(3) : 2013 (September - December, 2013)
Volume 47 Number 3 2013
Contents
Review Paper
Rice based cropping system and climate change 239-247 R.K. Tiwari, Amit Jha, S.K. Tripathi, I.M. Khan, and S.K. Rao
Oncolytic virotherapy in veterinary practice 248-254 Sonal Shrivastava, P.C. Shukla, Debosri Bhowmick and Manisha Nakul
Research Paper
Genetic analysis of CIMMYT based bread wheat genotypes for yield and its contributing traits 255-259 R.S. Shukla and P.K.Moitra
Investigation on ethno medicinal remedies to cure diseases by tribes of eastern Madhya Pradesh with special reference to threat assessment of leguminosae family 260-262 Karuna S. Verma and Lekhram Kurmi
Phytochemical screening of different plant parts of munga (Moringa oleifera Lam.) 263-268 Karuna S. Verma and Rajni Nigam
Multiple regression analysis a selection criteria for wheat improvement 269-273 Varsha Patil, P.K. Moitra and R.S. Shukla
Association analysis studies in indigenous and exotic germplasm lines of rice 274-277 Pankaj Nagle, S.K. Rao, G.K. Koutu and Priya Nair
Influence of zinc application on yield attributes, yield, chemical composition and protein content of wheat grown on Typic Haplustert of Kymore plateau, Madhya Pradesh 278-283 K.S. Keram and B.L. Sharma
Effect of in-situ moisture conservation for improving niger productivity in Kymore plateau, Madhya Pradesh 284-287 M.R. Deshmukh, Alok Jyotishi and A.R.G. Ranganatha
Water productivity of early, medium and hybrid rice varieties under aerobic condition 288-290 R.K. Tiwari, B.S. Dwivedi, I.M. Khan, S.K. Tripathi and Deepak Malviya
Wine production from over ripe guava fruits using Saccharomyces cerevisiae 291-297 Yogesh Kalyanrao Patil, L.P.S. Rajput, Yogendra Singh and Keerti Tantwai
Investigations on the nutritional characteristics of kodo millet based traditional fermented food by tribals of Madhya Pradesh, India 298-302 Deepali Agrawal, A. Upadhyay and Preeti Sagar Nayak Effect of different micronutrients on the incidence of major sucking insect pests of tomato 303-307 A.S. Thakur, S.K. Barfa, Amit Kumar Sharma and R. Pachori
Efficacy of some new molecules against the infestation of bringal shoot and fruit borer (Leucinodes orbonalis Guenee) 308-311 R. Pachori, Sapna Tanve, Amit Kumar Sharma and A.S. Thakur
Insect pest complex on Acacia 312-314 H. Dayma and R. Bajpai
Genetic resources of okra for the utilization in the management of Okra Yellow Vein Mosaic Virus disease under climatic conditions of Kymore plateau zone, Madhya Pradesh 315-320 Usha Bhale, Priyanka Dubey and S.P. Tiwari
Effect of weather parameters on development of ber powdery mildew and its control by fungicides 321-324 P.K. Amrate, Amarjit Singh and Chander Mohan
Population dynamics and management of lesion nematode (Pratylenchus thornei) in chickpea 325-329 Jayant Bhatt, Arvind Jaware and S.P. Tiwari
Modelling and forecasting of area, production and yield of soybean in India 330-336 P.Mishra, H.L.Sharma, R.B. Singh and Siddarth Nayak
SWOT analysis for lac cultivation in Madhya Pradesh 337-340 Arvind Dangi Thakur, S.C. Meena and Ashutosh Shrivastava
Performance of National Agricultural Insurance Scheme in Raisen District of Madhya Pradesh- An economic evaluation 341-345 Govind Prasad Namdev, P.K. Awasthi and N.K. Raghuwansi
Growing degree days (GDD) measurement system to predict plant stages 346-349 Bharati Dass and A.K. Rai
Issued : 30 December 2013
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JNKVV Research Journal Editorial Board
Patron Prof. Vijay Sigh Tomar Vice Chancellor, JNKVV, Jabalpur Chairman Dr. S.K. Rao Dean, Faculty of Agriculture, JNKVV, Jabalpur Members Dr. S.S. Tomar Director Research Services, JNKVV, Jabalpur Dr. O.P. Veda Director Instruction, JNKVV, Jabalpur Dr. P.K. Mishra Director Extension Services, JNKVV, Jabalpur Dr. R.V. Singh Dean, College of Agriculture, JNKVV, Jabalpur Dr. G.S. Rajput Dean, College of Agricultural Engineering, JNKVV, Jabalpur
Editor Mohan S. Bhale Co-Editor Abhishek Shukla
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ISSN : 0021-3721 Registration No. : 13-37-67
Published by: Dr. SK Rao, Dean, Faculty of Agriculture, JNKVV, Jabalpur 482004 (M.P.), India JNKVV Res J 47(3): 239-247 (2013)
Rice based cropping system and climate change
R.K. Tiwari, Amit Jha*, S.K. Tripathi, I.M. Khan, and S.K. Rao** Jawaharlal Nehru Krishi Vishwa Vidayalya College of Agriculture Rewa (MP) *College of Agriculture Jabalpur ** Dean, Faculty of Agriculture Jabalpur Email: [email protected]
Abstract intensification/ diversification have to be studied. Thus, ample scope exists for improving the total land productivity through Rice (Oryza sativa L.) is the most important staple food crop generation of appropriate production technologies for diverse in India that holds key to food security. Rice-based production agro-climatic situations. systems provide livelihood for more than 50 million households. In India, rice is grown on more than 44 m ha Keywords : Rice, cropping system and climate under three major ecosystems; rainfed uplands (16% area), irrigated medium lands (45%) and rainfed lowlands (39%), with a productivity of 0.87, 2.24 and 1.55 t ha-1, respectively. The continuing population pressure in the country will The change in climate has been attributed to global warming demand substantial increase in food, feed, fodder, fiber and has many facts, including changes in long term trend in and fuel production over the next few decades to be temperature and rainfall regimes as well as increasing year- able to maintain self-sufficiency and also meet export to- year variability and a greater prevalence of extreme events. requirement. Our population has already crossed one Agricultural systems will be affected by both short and long billion mark and is estimated to stabilize around 1.5 term changes in climate, and will have serious implications billion by the year 2030. The demand for food grains is on rural livelihoods, particularly of the poor being the most estimated at 240 m t by the end of XI plan period. vulnerable. The impact of climate change poses serious Keeping this in view, the government of India launched threats to productivity and sustainability of various rice- based the National Food Security Mission to achieve the cropping systems including rice- wheat cropping system, the production of additional 10, 8 and 2 m t of rice, wheat backbone of food security of India. Despite some projected and pulses, respectively. The task is quite challenging increase in photosynthesis caused by increased and the options available are very limited in view of concentrations of carbon dioxide, increased temperature will plateauing rend of yield in high productive areas, have a far greater detrimental effect, resulting reduced crop decreasing and degrading land, water, labour and other productivity. The rice - based cropping systems will continue inputs. Among the various possible approaches to to be important cropping systems in India in the years to come. achieve this target is to increase the productivity per Therefore, there is a strong need to monitor these systems in unit time and area i.e.e, by raising two or more crops terms of nutrient dynamics and to develop efficient integrated per year through multiple, relay and intercropping both nutrient supply and management system in different grgions in irrigated and rain fed areas; and by utilizing the using locally available resources like compost, farm yard manure, farm wastes, crop residues and green manures. available resources more efficiently. With the availability There is also a need to monitor insect, disease and weed of shorter duration varieties of different crops the scope problems, water table and water harvesting techniques. Crop for growing two or more crops in a year is continuously establishment of succeeding crops after rice and dry seeding increasing. Hence, emphasis needs to be laid on methods of rice need greater attention. There is a need for identification of suitable cropping systems with higher the choice of genotypes and introduction of short duration, and stable yields and / or profit in different agro- photoperiod insensitive varieties, the possibilities for crop ecological regions. Further, in response to 239 commercialization of agriculture also, it is important to irrigation in the eastern and southern states, but the shift from routine food grain production system to never kharif crop is grown under a wide range of soil and crops/ cropping systems depending upon the climatic climatic conditions throughout the country. Rice conditions as well as agro- ecosystems under different cultivation in eastern India is characterized by rice- based production system in order to make predominantly rainfed culture (70%), mono-cropping, low fertilizer use and traditional varieties. On the other agriculture an attractive, profitable and sustainable hand under irrigated conditions, input intensive rice- business. based cropping systems involving cereals, pulses, oilseeds tuber and fiber crops are practiced. The change in climate has been attributed to global warming and has many facts, including changes in long Rice and rice- based cropping systems term trend in temperature and rainfall regimes as well as increasing year- to- year variability and a greater prevalence of extreme events. Agricultural systems will Based on rational spread of crops in different agro- be affected by both short and long term changes in climatic regions of the country, about 500 cropping climate, and will have serious implications on rural systems have been identified by the PDCSR, but only livelihoods, particularly of the poor being the most 30 cropping systems are important because of their vulnerable. The impact of climate change poses serious sizable area. (Yadav et al. 1998). Among them, different threats to productivity and sustainability of various rice- rice based cropping systems such as rice-wheat, rice- based cropping systems including rice- wheat cropping rice, rice-chickpea/lentil, rice-mustard/linseed and rice- system, the backbone of food security of India. Despite groundnut etc. Together occupy the largest area in the some projected increase in photosynthesis caused by country. Rice-wheat and rice-rice cropping systems increased concentrations of carbon dioxide, increased contribute to major share of food grain pool of the nation, temperature will have a far greater detrimental effect, while other rice based cropping systems have their resulting reduced crop productivity. Conservation significance to contribute the national production of oil- agriculture involving continuous minimum mechanical soil disturbance, permanent organic soil cover and diversified crop rotations provides opportunities for mitigating green house gas emission and climate change adaptation. Rice (Oryza sativa L.) is the most important staple food crop in India that holds key to food security. Rice- based production systems provide livelihood for more than 50 million households. In India, rice is grown on more than 44 m ha under three major ecosystems; rainfed uplands (16% area), irrigated medium lands (45%) and rainfed lowlands (39%), with a productivity of 0.87, 2.24 and 1.55 t ha-1, respectively. The crop in Fig 2. Area, Production and Productivity of Rabi/Sum- rabi/summer is grown on nearly 3 m has mostly with mer Rice during 2006-07 to 2010-11 of India
Fig 1. Area, Production and Productivity of Kharif Fig 3. Rice area , production and productivity scenario Rice during 2006-07 to 2010-11 of India during last 50 years
240 seed and pulse crops. 42% of the total national rice and wheat production, respectively. Rice-rice cropping system is next to it, With the introduction of high yielding photo and covering an area of about 6 million ha. in Kerla, thermo insensitive rice varieties of relatively shorter Tamilnadu, A.P. states during kharif and rabi seasons; duration, there was remarkable changes in the cropping and in Assam, West Bengal, Orissa, Maharashtra states system concept (Sharma et al, 2004). A large number during kharif and summer seasons. Among other rice of crops are now being grown after rice under different based cropping systems, rice-chickpea in Jharkhand, ecologies based on soil and prevailing agro- climatic M.P., West Bengal and Bihar states; rice-mustard in conditions in major rice growing states of the country. West Bengal, Orissa, Chhatisgarh and rice-groundnut Out of the major cropping systems identified by the in Tamilnadu, A.P. states are prevalent. All rice based Project Directorate for Farming Systems Research, rice- cropping systems are practiced under both irrigated and based system occupies the largest area of about 28 m rainfed production systems depending on the agro- ha in India. Among the rice- based cropping systems, climatic suitability. Several issues/constraints such as the major ones are rice- wheat (9.8 m ha), rice-rice (5.9 land degradation, decline in soil productivity, inefficient m ha), rice - fallow (4.4 m ha), rice-pulses (4.4 m ha), land use pattern, low water use efficiency, build up of rice vegetables (1.2 m ha), rice groundnut (1.0 m ha), diseases/insects/weeds infestation and decline in rice -mustard (0.5 m ha), rice- potato (0.5 m ha) and environmental quality etc are emerging in the areas rice -sugarcane (0.4 m ha) Yadav & Subba Rao, 2001). covered under different rice based cropping systems.
Issues in rice based cropping systems The specific issues needing careful attention of researchers for dominant rice based cropping systems Rice-wheat sequence is the most widely adopted could be listed as below:- cropping system in the country and has become 1. Deterioration of soil physical properties by mainstay of cereal production. The U.P., Punjab, formation of hardpan in sub surface because of Haryana, Bihar, M.P. and West Bengal state are the soil puddling for rice cultivation. heartland of this cropping system with an estimated area of about 12 million ha. This system is spreaded in 123 2. Difficulties for tillage and poor crop stand in wheat districts of these states and contributes about 25 and cultivation.
Table 1. Rice based cropping system in different agro-ecological zone of India
Agro ecological zone Soil Predominant rice based cropping system Western Himalayan region Hill soil, sub-mountain Rice-fellow, maize-wheat and rice-potato East Himalayan Broon hill, acidic soil, alluvial red Rice-fellow, rice-rice and rice-pulse/ sandy, red yellow oilseed Lower gangetic plains Red alluvial, red, yellow loamy soil Rice-rice and rice-wheat, rice-potato-jute and rice-potato-vegetables Mid gangetic plains Alluvial, calcareous, tarai soil Rice-wheat, rice maize, rice-potato- sunflower Upper gangetic plains Alluvial, tarai soil Rice-wheat Trans gangetic plains Alluvial, calcareous Rice-wheat Eastern plateau and hills Red, yellow, sand loam to laterite Rice-black gram /niger/linseed, rice-groundnut and rice-vegetables Suthern plateau and hills Medium to deep black, red sandy to Rice-bengal gram/green gram, rice-rice loamy coastal and deltaic alluvium Eastern coast plains and hills Delta coastal, alluvial laterite red Rice-groundnut-green gram, rice-green and medium black soil gram/black gram and rice-rice Andman and Nicobar island Medium to very deep red loamy and Rice-fellow sandy soil
241 3. Development of multiple nutrients (secondary and rice straw alsohelps to conserve the soil moisture under micro) deficiency. such situations. In bunded uplands, where there is still 4. Declining water table in some areas due to possibility for giving at least one or two irrigation through indiscriminate exploitation of underground water harvested rain water, crops like sunflower, gram, tomato, for irrigation. etc. can be successfully grown after harvest of wet season rice. The short duration impoved varieties of 5. Buildup of infestation of Phalaris minor and wild the above crops can give a good return under such out in wheat. sitations, Intercropping of upland rice with pigeon pea 6. Imbalance or low use of fertilizers. (4:1 row ratio ) recorded higher rice equivalent yield and net return over sole crop. 7. Lack of appropriate varietal adjustment for crop components. Irrigated medium lands
Rice Ecosystem Under irrigated condition majority of rice is grown in wet season ( June to October) but around 4 m ha is Preference of rice based cropping systems in different under dry season ( November to May) . The important parts is based on location advantage facilities. For cropping systems followed under irrigated medium land example, rice - wheat and rice - rice systems are situations are rice- rice, rice - wheat , rice- winter maize, practiced in irrigated ecology whereas rice - lathyrus, rice- groundnut , reice - sunflower, rice- potato, rice- rice- gram or rice - blackgram etc. are practiced in mustard, rice- gram , rice - winter vegetables, etc. with rainfed uplands and lowlands. 200% cropping intensity. There is still scope to introduce a third crop of short duration pulses like cowpea, greengram, blackgram or oilseed crops like sesame in Rainfed uplands areas where irrigation facilities are available to provide 1-2 life saving irrigation to the third crop. In M.P., rice - In India, 85% of the upland rice area is located in the potato- wheat, rice- wheat- grengram, onion- wheat - states of Assam, Bihar, West Bengal, Odisha and jute are found to be remunerative. eastern Parts of Madhya Pradesh and Uttar Pradesh. In Assam ( rice- rice - rice cropping sequence The rainfall in this zone is in the range of 1000 to 2000 with 300% cropping intensity) to meet household food mm or more and temperature ranges from 25 to 41 0C security and year round employment generation for in July and from 6 to 25 0C in January. Red lateritec small and marginal farmers with land holding less than and lateritic soil such as mixed red and yellow, red 1 ha. In Punjab, the cropping system with 300% intensity sandy, red loam, lateritic and mixed red and brown hill such as rice- potato - sunflower, rice- potato- winter soils account for about 55% of the total rice area in The maize and rice- toria- sunflower have been found to be East Zone .Next in the order of occurrence is alluvial more productive than conventional systems of 200% soil, which occupies about 27% of the total rice area. cropping intensity with rice- wheat or rice - winger maize. Rice is grown under rain fed condition in these uplands Early medium to medium duration (120-135 days) rice in monsoon season. varieties like Naveen, Ratna, IR 36, Padmini, Khitish, Shatabdi, Tapaswini provides good scope to advance In rain fed uplands, shorter duration (90-105 the sowing time of the second crop by late October to days) rice varieties like Vandana, Dhanteshari, Kalinga early November so that the third crop ( 70-90 days) can III, Anjali, NDR 97, Annada are to be grown by sowing be accommodated during February - April. during the onset of monsoon, so that the field should be vacated early for the second crop (Saha et al. 2003). Crops like mustard, castor, linseed, safflower, Rainfed lowlands balckgram, lentil, horsegram can be grown by taking advantage of residual soil moisture and late monssom Rainfed lowland rice is grown in around 13 m ha, mostly rains. The second crop should be sown as early as in eastern India, where soil moisture is available for possible (within a week) after harvest of rice to get the longer period, rice varieties of 140 days duration , mostly advantage of residual soil moisture. Mulching by using photosensitive types are grown and harvested from mid
242 November to mid December. The water depth varies in groundnut, watermelon, seasame, etc during the dry rainfed lowlands and it can be shallow up to 25 cm, and season ( January- early April). The salt affected coastal medium - deep waterlogged up to 50 cm. Deep- water areas are generally rainfed and mono- cropped with rice is grown in areas where water depth is more than rice, Land mostly remains fallow during the dry season 50 cm up to 2 m, and around 4 m ha area is under due to soil salinity and unavailability of fresh water. cultivation in eastern India with an average productivity However, rice and certain salt tolerant crops like of 0.8 t ha-1. Most of the deep water rice area in West sunflower, chilli watermelon, sugat beet, cotton , etc. Bengal, Assam, North- east Bihar, and coastal Odisha are grown in pockets depending on the availability of isnow being under boro and dry season rice due to low harvested rainwater, soil and climatic conditions productivity of deep water rice. (Singhet al. 2006) Pulses like blackgram, greengram, Farmers traditionally grow tall indica types, which cowpea, etc. and groundnut is also grown in some areas are prone to lodging and are of low productivity. The having mild salinity. varieties grown in these land situations are generally medium to long (130-180 days) duration depending Sustainability issues in cropping systems upon the water depths in the fields where they are grown and should have tolerance to drought initially and to submergence at later stage; photosensitivity; moderate • In semi- arid ecosystem intensive water use in to high tailoring abilities; tolerance to drought initially rice - wheat cropping system led to increased and to submergence at later stage; photosensitivity; salinization in many areas. There are indications moderate to high tillering abilities; tolerance to pests of yield declines where balanced nutrient and diseases and elongation ability in semi- deep and application has not been made. Deficiency of deep situations. The ideal plant height for shallow micronutrients has been observed. lowlands is 110-130 cm, 130 -150 cm for medium deep • The problem of depletion of underground water situations and > 150 cm for deep water areas. in semi- arid areas of Punjab and Haryana needs Medium to long duration (140-155 days) rice to be addressed through development of varieties like Swarna, Vijeta, Surendra, Moti, Pooja, alternate cropping system under limited water Pankaj, etc. are usually grown in rainfed shallow supply. lowlands of eastern India. Short duration pulses like • To reduce the use of purchased inputs by small greengram, blackgram, etc. can be grown after rice farmers, green manure should be introduced in harvest with residual soil moisture. There is a little scope the rice - wheat, rice- rice system. Fifty percent to take a second crop in areas where soil moisture of nitrogen requirement of rice could be recedes fast during November onwards. Under such substituted by growing sesbania before situation , crops like lathyrus, field pea, linseed, lentil, transplanting rice. blackgram can be raised as relay / paira crop by sowing the second crop in the standing crop of rice 10-15 days • In the sub- humid exosystem, reduction in wheat before harvesting 9 (Saha & Moharana, 2005) . In yield following rice is due to delayed wheat certain areas of eastern India, crops like sunflower, planting, low plant stand and poor nutrient groundnut, watermelon, okra, sweet potato can be management . Delayed wheat planting is raised with limited irrigation (2-3) by utilizing the associated with excess soil moisture at the time harvested rainwater stored in small farm ponds. of rice harvest. Higher seed rate and nutrient can compensate wheat yield losses to some extent. Long duration (155-180 days) photosensitive rice varieties like Varshadhan, Gayatri, Savitri, sarala, Panidhan, Durga, Tulsi, Kalashree, Sabita and Nalini Management of rice - based cropping systems are grown predominantly intermediate deep and deep water rice ecology of east coast and lower Gangetic The rice - based cropping systems will continue to be Plains of India. These areas are having potential to important cropping systems in India in the years to come. harvest rainwater during monsoon period ( June- Therefore, there is a strong need to monitor these September) that can help to grow several winter systems in terms of nutrient dynamics and to develop vegetables like pumpkin, bitter gourd , okra, chilli, along efficient integrated nutrient supply and management with other crops like blackgram, greengram, sunflower, system in different grgions using locally available
243 resources like compost, farm yard manure, farm wastes, Laser land leveling crop residues and green manures. There is also a need to monitor insect, disease and weed problems, water Laser leveling of uneven field reduces water use table and water harvesting techniques. Crop allowing crop to grow in water limited condition. It also establishment of succeeding crops after rice and dry reduces fuel consumption because of efficient use of seeding methods of rice need greater attention. There tractor and reduces GHGs emission , particularly CO2. is a need for the choice of genotypes and introduction Several other benefits such as operational efficiency, of short duration, photoperiod insensitive varieties, the weed control efficiency, water use efficiency, nutrient possibilities for crop intensification/ diversification have use efficiency, crop productivity and economic returns to be studied. Thus, ample scope exists for improving and environmental benefits have also been reported the total land productivity through generation of due to laser aided land leveling compared to appropriate production technologies for diverse agro- conventional practice of land leveling. climatic situations.
Direct Seeded Rice Conservation agriculture
Direct drill seeding of rice (DSR) could be a potential Conservation agriculture is characterized by three option for reducing Ch4 emission. Methane Is emitted priciples which are linked to each other, namely from soil when it is continuously submerged as in the continuous minimum mechanical soil disturbance, case of conventional puddle transplanted rice. The DSR permanent organic soil cover and diversified crop crop does not require continuous soil submergence, rotations in the case of annual crps or plant associations thereby either reducing or totally eliminating CH4 in case of perennial crops which provides opportunities emission when it is grown as an aerobic crop. More- for mitigatin greenhouse gases (GHGs) emission and over, deeper root growth of DSR crop provides better climate change adaptation.. Recent research efforts tolerance to water and heat stress. Besides the have attempted to develop resource conserving unpadded soil in DSR does not crack with moisture technologies (RCTs), which are more resource efficient, stress unlike puddle soil which helps to increase yield use less inputs, improve production and income, and significantly. reduce GHGs emission compared to the conventional practices. Some of these technologies are being Crop Diversification adopted by the farmers on large scale, which would help farmers in combating climate chage to a Diversification is growing a range of crops suited to considerable extent . Specific impacts of various RCTs different sowing and harvesting times, assists in on GHGs mitigation are briefly discussed below. achieving sustainable productivity by allowing farmers to employ biological cycles to minimize inputs, maximize Zero tillage yields, conserve the resource base, reduce risk due to both environmental and economic factors. The RCTs such as bed planting and zero tillage expand the Conventional land preparation practices for wheat after windows of crop diversification. The farmers of rice- rice involves as many as 10-12 tractor passess. wheat belt have taken the initiative to diversify their Changing to a zero- till system on 1 ha of land would agriculture by including short duration crops such as save 98 liters of diesel and approximately 1 million liters potato, soybean, blackgram, greengram, cowpea, pea, of irrigation water besides reducing about a quarter mustard, and maize into different combinations. Such tonne less emission of carbon dioside (CO2), The diversification wouild not only improve income, principal contributor to global warming. However, impact employment and soil health but also reduce water use or zero tillage on methane (CH4) and nitrous oxide (N20) and GHGs emission and more adaptability to heat and emissions have showed contrasting results with lower, water stress. equal and higher compared to the conventional systems depending upon the soil type and water management. Raised bed planting Zero tillage also allows rice - wheat farmers to so wheat sooner after rice harvest, so the crop heads and fill the grain before the onset of pre monsoon hot weather. In raised bed planting a part of soil surface always 244 remains unsubmerged. Thus it not only reduces water in agriculture. use and improves drainage but also reduces methane emission. Crops on beds with residue retained on Takkar et al. (1998) considered a conceptual surface is less prone to lodging and more tolerant to framework of IPNS which includes four distinct integral water stress, thereby making it more adaptable to components viz. (i) on-site nutrient resource generation. unfavorable climate. (ii) mobilization of off - site nutrient resources, (iii) resource integration and (iv) resource management. On - site nutrient resource generation is mostly achieved Leaf color chart through green manuring and recycling of crop residues. Mobilization of off - site nutrient resources includes three The most efficient management practice to minimize categories of sources of nutrients viz, bio- organic plant N uptake and minimize N loss is to synchronize wastes (FYM and compost), bio- organisms (bio- supply with plant demand. The use of leaf colour chart fertilizers) and mineral resources (synthetic and mineral (LCC) promotes a need based N application to rice crop fertilizers). Resource integration, the guiding principle that saves N and increases N use efficiency. As a result of INM not only supplements the fertilizer use but also there will be less accumulation of mineral forms on N provides the benefits of positive interaction for various (NH and NO ) within the crop root zone and hence less nutrient sources in restoring soil fertility. It also ensures 4 3 balanced crop nutrition and synergetic interaction in a losses of N and N2O emission. Besides, because of healthier plant growth due to timely application of N cropping system for sustainable agriculture. The nutrient fertilizer, damages caused by insects were reported to resource management improves the nutrient use have been reduced. efficiency by decking nutrient losses from soil, optimizing nutrient resource combination and monitoring plant nutrient flows. It also addresses the sil related problems Integrated nutrient management limiting, crop growth such as soil acidity , salinity, alkalinity, soil compaction, etc. Ultimately, it imparts Food security and soil health are two important concerns resilience against the soil degrading processes and in Indian agriculture. Integrated nutrient management promotes quality of the environment. (INM) in crop production, particularly in rice- based Because of several reasons including those of cropping systems, plays a crucial role in the pursuit of soil bealth care and high crop yield, it is necessary to these two set missions. Integrated nutrient management supplement / complement chemical fertilizer application is achieved through combined use of different sources with the other components of INM which are mostly of plant nutrients such as chemical fertilizers, organic organic in nature. Results of research on INM in irrigated manures, green manures, crop residues, bio- fertilizers, rice revealed that at N level of 60 kg ha-1, combined industrial wastes and soil conditioners depending upon application of urea and dhaincha green manure/ Azolla/ their availability and suitability in a specific agro- FYM at 1:1 ratio on N level basis, produced comparable ecological situation (Hegde and Dwivedi 1992), Panda grain yield to that of urea alone. However, at N level of and Singh 1998). It also includes scientific management 90 kg ha-1, INM practices involving dhaincha green of these sources of nutrients for securing optimum crop manure or Azolla dual crop were superior to the yield and soil fertility improvement. According to Roy chemical source on N (Panda et al. 1991) and Ange (1991). The basic concept underlying integrated plant nutrient supply and management system (IPNS) is the maintenance or adjustment of soil Weed Management fertility and of plant nutrient supply to an optimum level for sustaining the desired crop productivity through Climate change will also affect the weed communities optimization of the benefits from all possible sources of in the rice based cropping system. A review on the effect plant nutrients in an integrated manner. Economic of weed growth on yield suggested losses in the range viability and ecological sustainability are also major 28-74% in rice and 15-80% in wheat 5,6. Improving considerations in INM. In a holistic approach , the INM weed control in farmers' field has shown to increase practices are designed and adpted to increase the rice and wheat yield by 15-30%.Northwest India quantity and of crop produce, decrease nutrient losses, annually contributes more than 50-60% of rice and increase the efficiency of applied and native nutrients, wheat to the central food grain reserve, making it the improve soil health , economize on fertilizer use, protect 'bread basket' of the country. Therefore, if productivity the environment and minimize the energy consumption of these crops is affected, Indian food security is bound
245 to be affected. Given that the demand for food is the nutrient resource base and soil qualities in rice- projected to rapidly outpace increase in supply, effective based cropping systems have to be strengthened. weed control is a priority in this system. Important weeds Climate change poses serious threats to of rice include Echinochloa crusgalli, E. colona, E. productivity and sustainability of various cropping glabrescens, Ammanniaspp., Eragrostis spp., Ludwigia sp., Ischaemum rugosum, Leptochloa chinensis, systems. Recent efforts have attempted to develop and deliver resource conservation technologies involving no Paspalum distichum, Cyperus iria, C.difformis, - or minimum tillage with direct seeding and bed planting Fimbristylis miliacea, Scirpusmaritimus, Eleocharis spp., Eclipta prostrata, Sphenoclea zeylanica and with residue mulch, innovations in residue management to avoid straw burring and crop diversification as Monochoriavaginalis. Important weeds ofwheat include alternatives to the conventional management practices Phalaris minor, Avena ludoviciana, Poa annua, Loliumtemulentus, Chenopodium album, for improving productivity and sustainability of important rice-based cropping systems. The wide scale adoption Rumexdentatus, R. spinosus, Medicago denticulata, of any improved cropping system by the farming Melilotus alba, Anagallis arvensis, Lathyrus aphaca, Fumaria parviflora, Vicia sativa, Coronopus didymus, community depends mostly on socio-economic factors such as labour availabiltity, credit requirement, cost of Malvaparviflora and Cirsium arvense. Common weed inputs, processing, marketability and price of produce, management practices in the rice based cropping system include soil tillage, flooding, summer risk involved and social acceptability of the new system. Thus before designing a particular cropping system, ploughing,crop rotation and use of herbicides; these care should be given on its economic feasibility. practices are often used in combination. Integrated weed management strategies need to be developed Emphasis should also be given for developing suitable rice- based farming system model by incorporation which target the prevention of weed invasion, animal components into the system to enhance the recruitment and reproduction. Such strategies may include combination of optimal fertilizer schedule, overall economy and standard of living of poor farm community. summer ploughing, crop rotation, land preparation, modifying plant geometry, stale seedbed technique, planting time, seed rate and use of weed-competitive References cultivars18. Knowledge of weed ecology and biology could be used as a tool for effective weed Hegde D M, Dwivedi B S (1992) Nutrient management in rice managementin futuristic climate change. - wheat cropping system in India. Fertilizer News 37, 27-41 Conclusion Panda D, Singh D P (1998) In Rainfed rice for sustainable food Security. (pp. 239-258). Cuttack: Central Rice The overwhelming importance of rice and rice - based Research Institute cropping systems for the food security of India requires Panda D, Samantaray R N Mohanty S K, Patnaik S (1991) a through assessment of the rice resource base and Green manuring with sesbania aculeate: Its role in the impact of rice cultivation on the environment. The nitrogen nutrition and yield of rice. In S.K. dutta, C. decline in soil and water quality in rice - based systems Sloger (Eds.). Biological nitrogen fixation associated is a major global issue. The situation is going to be with rice production. (pp. 305-313). New Delhi: oxford worse in the event of possible global warming, which and IBH Pub Co has negative impact on yield and soil fertility. Therefore, Roy R N, Ange A L (1991) Integrated plant nutrition systems the systems should be constantly monitored in terms of (IPNS) and sustainable agriculture, In Proceedings their natural resource base. Suitable quantitative models of FAI Annual Seminar. New Delhi: Fertilizer that incorporate the relevant bio-physical and association of India socioeconomic interactions to permit quantitative Saha S, Moharana M (2005) Utera cultivation - A viable assessment of rice cultivation in relation to the technology option for rainfed shallow lowland of environment and natural resources need to be coastal Orissa. Indian Farming 56 (3) 13-15 19 developed. An environmental impact assessment should include a social impact assessment, strategic Saha S, Dani R C, Beura J (2003) Integrated crop environmental assessment, and life cycle analysis of management for rainfed upland rice NATP Technical the implementation of rice technologies. Holistic and Bulletin No. 14. Central Rice Research Institute ecoregional strategies to manage, preserve and improve Sharma S K , Subbaiah S V , Rao K S, Gangwar K S (2004)
246 Rice- based cropping system for rainfed upland, rainfed lowland and irrigated areas of different states of India. In Proceedings of National symposium on "Recent advances in rice - based farming systems". Central Rice Research Institute (Cuttack. P. 36-57 Singh D JP, Mahata KM R , Saha S, Is mail A M (2006) Crop diversification options for rice- based cropping system for higher land and water productivity in coastal saline areas of eastern India. In Abrtr. 2nd International Rice Congress on "Science, Technology and trade for peace and prosperity" 475 New Delhi IARI Takkar P, Kundu S, Biswas A K (1998) In A Swarup et al. (Eds.), Long term soil fertility management through Integrated Plant Nutrient Supply . (pp. 78-88). Bhopal, India: Indian Institute of Soil Science Yadav R , Subba Rao A V M (2001) Atlas of cropping systems in India. (pp. 96) . Modipuram, Meerut, India: Project Directorate for Cropping Systems Research Yadav RL, Kamata Prasad and Singh R K (1998) Predominant cropping system of India. Project directorate cropping system research(PDCSR), Meerut
(Manuscript Receivd : 30.8.13; Accepted : 11.11.13)
247 JNKVV Res J 47(3): 248- 254 (2013)
Oncolytic virotherapy in veterinary practice
Sonal Shrivastava, P.C. Shukla, Debosri Bhowmick and Manisha Nakul Department of Veterinary Medicine College of Veterinary Science & Animal Husbandry Nanaji Deshmukh Veterinary Science University Jabalpur 482001 (MP) Email : [email protected]
Abstract Viral oncolytic therapy is under intense investigation as a novel anticancer strategy. Both alone and in Oncolytic virotherapy is an emerging treatment modality that combination with other conventional treatment uses replication-competent viruses to destroy cancers. modalities, viral oncolytics exploit the natural cytotoxicity Oncolytic viruses are therapeutically useful viruses that of viruses to directly kill tumor cells. Results from selectively infect and damage cancerous tissues without preclinical studies demonstrating the intricate interaction causing harm to normal tissues. The specific tumour targeting between oncolytic viruses, the targeted tumors and their can be achieved by targeting various molecular steps/ hosts, has resulted in new strategies being developed regulators of cell cycle eg. pro-apoptotic, translational, to overcome the challenges of maximizing oncolytic viral transductional and transcriptional targeting, and strategies efficacy while ensuring safety (Woo et al. 2006). based on tumour micro-environment and use of carrier cells as cellular vehicle for oncolytic viruses. Oncolytic viruses such as various human and canine adenoviruses, canine distemper History of oncolytic virotherapy virus and vaccinia virus strains have been preclinically tested for canine cancer therapy. Several research groups and biotechnology companies have engineered therapeutic viruses One of the first inklings that viruses could be useful in and armed them with genes that make the cells they infect combating cancer came in 1912, when an Italian uniquely susceptible to chemotherapy. These viruses are gynecologist observed the regression of cervical cancer under clinical trial phase I, II or III. Oncolytic viral therapy is in a woman who was inoculated with a rabies vaccine capable of increasing the therapeutic index between tumor made from a live, crippled form of the rabies virus cells and normal cells when viral replication proceeds preferentially in tumor cells. Armed therapeutic viruses or (Nettelbeck et al. 2000). Physicians first injected viruses genetically engineered viruses represent a very appealing into cancer patients intentionally in the late 1940s, but tumor targeting approach and a novel opportunity to generate only a handful appeared to benefit. In 1996, the first agents that could potentially cure canine cancers. approval was given in Europe for a clinical trial using
the oncolytic herpes simplex virus (HSV1716). From 1997 to 2003, strain HSV 716 was injected into tumors Keywords: Canine, Oncolytic virotherapy, Tumour 1 of patients with glioblastoma multiforme, a highly malignant brain tumor, with no evidence of toxicity or Oncolytic virotherapy is an emerging treatment modality side effects, and some long-term survivors. Other safety that uses replication-competent viruses to destroy trials have used HSV1716 to treat patients with cancers. Oncolytic viruses are therapeutically useful melanoma and squamous-cell carcinoma of head and viruses that selectively infect and damage cancerous neck (Rampling et al. 2000). tissues without causing harm to normal tissues (Russell and Peng 2007). Oncolytic viruses have been The first oncolytic virus to be approved by a suggested to have great potential for cancer therapy, regulatory agency was a genetically modified not only by direct destruction of the tumor cells, but adenovirus named H101 by Shanghai Sunway Biotech. also to deliver other genes, for example genes It gained regulatory approval in 2005 from China's State expressing anticancer proteins and as immunotherapy Food and Drug Administration (SFDA) for the treatment (Melcher et al. 2011). of head and neck cancer (Frew et al. 2008). Other
248 oncolytic viruses based on HSV have also been Direct cell lysis due to viral replication developed and are in clinical trials, most notably OncoVex GM-CSF, developed by Amgen, which has Viruses infect tumor cells and replicate themselves in successfully completed a pivotal Phase III trial in March tumor cells. Upon lysis of infected tumor cells, new virion 2013, for advanced melanoma with a very high degree particles burst out and proceed to infect additional tumor of statistical significance. cells. This cycle then can repeat, by infection of adjacent cells and their subsequent destruction by the same Characteristics of an ideal oncolytic virus mechanism. This feature of viral replication provides continuous amplification of the input dose which continues until stopped by the immune response or a Oncolytic viruses induce an anti-tumor therapeutic effect lack of susceptible cells. through a subtle equilibrium between anti-viral and anti- tumor immune responses (Fulci et al. 2006). An ideal oncolytic virus should demonstrate efficient, safe and Direct cytotoxicity of viral protein complete destruction of tumor tissue by selective replication in cancer cells, eliciting strong immune Second mechanism, in which some oncolytic viruses responses against tumor cells and efficient clearance synthesize certain proteins during replication that are from the body preventing latent or recurrent infection. It directly cytotoxic to cancer cells e.g. adenoviruses should be propagation-deficient in immunocompromised generate the death protein E3 and the E4ORF4 protein patients with large recombinant gene carrying capacity late in the cell cycle; both these proteins are toxic to and easily engineering to express antitumor agents. cell (Shtrichman and Kleinberger 1998). Furthermore, cost effectiveness and economy for widespread use, easy monitoring with respect to successful tumor colonization and potent anti-tumor Induction of antitumoral immunity activity either alone or combined with conventional therapies, such as surgical resection, chemotherapy, Tumor cells are inherently weakly immunogenic and radiotherapy are desirable. because they express low levels of major histocompatibility complex (MHC) antigens and Mechanisms of oncolytic efficacy stimulatory signals such as cytokines which activate a local immune response. Adenoviruses express E1A protein during replication, which mediates killing of Oncolytic viruses mediate the destruction of tumor cells tumor cells by increasing their sensitivity to tumor by several potential mechanisms (Table 1). In order to necrosis factor (TNF). In addition, lysates of virus- achieve efficient oncolytic activity a viral vector must infected tumor cells (oncolysates) have been used as obey three main principles: (1) selectively target the active specific immunotherapy in the treatment of neoplastic tissue while presenting minimal local and patients with melanoma and ovarian carcinoma in systemic toxicity, (2) remain active despite inducing host clinical models. Lysates of virus-infected allogeneic anti-viral immune response, and (3) reach all tumor foci human tumor cells elicit humoral immune responses beyond the tumor resection border (Dey et al. 2011). against tumor-cell-associated antigens, virus-
Table 1. Mechanisms of antitumoral efficacy of oncolytic viruses (Kirn 1996)
Mechanism Examples Direct cell lysis due to viral replication Adenoviruses, Herpes simplex viruses Direct cytotoxicity of viral protein Adenovirus E4ORF4 Induction of antitumoral immunity Nonspecific (e.g., TNF): Adenovirus (E1A) Specific (e.g., CTL response): Herpes simplex virus Sensitization to chemotherapy and radiation therapy Adenovirus (E1A), Adenovirus (AdTK-RC) Transgene expression Herpes simplex virus (rRp450), Vaccinia virus (GM-CSF)
249 associated antigens, and antigens that may be virus several suicide gene systems (Duarte et al. 2012). induced, and these immune responses can improve the outcome of patients with melanoma in a surgical Suppression of angiogenesis adjuvant setting (Gooding 1994).
Angiogenesis is an essential part of the formation of Sensitization to chemotherapy and radiation therapy large tumor masses. Angiogenesis can be inhibited by the expression of several genes, which can be delivered The adenovirus E1A gene product is a potent to cancer cells in viral vectors, resulting in suppression chemosensitizer, particularly in cells with functional p53 of angiogenesis, and oxygen starvation in the tumor. (Lowe et al. 1994). The E1A gene product can induce Enhanced antitumor activities have been demonstrated high levels of p53 in these cells and render them in a recombinant vaccinia virus encoding anti- susceptible to DNA damage from chemotherapy and angiogenic therapeutic antibody and with an HSV1716 radiation. Enhanced chemosensitivity following viral variant expressing an inhibitor of angiogenesis (Conner infection has been observed in vivo in a phase II clinical and Braidwood 2012). trial of intratumoral adenovirus (ONYX-015) in combination with cisplatin and 5-fluorouracil in patients with head and neck cancer (Khuri et al. 2000). Expression of sodium-iodide symporter
Transgene expression Addition of the sodium-iodide symporter (NIS) gene to the viral genome causes infected tumor cells to express NIS and accumulate iodine. When combined with Some researchers have incorporated prodrug radioiodine therapy it allows local radiotherapy of the converting enzymes, such as viral thymidine kinase and bacterial cytosine deaminase (CD), into replication tumor, as used to treat thyroid cancer. The radioiodine conditional adenoviruses to augment tumor cell killing can also be used to visualise viral replication within the via the "bystander effect". Other groups have introduced body by the use of a gamma camera. This approach various immune stimulatory genes such as interleukins- has been used successfully preclinically with 4 (IL-4) and -12 (IL-12) into oncolytic herpes viruses in adenovirus, measles virus and vaccinia virus (Li et al. an attempt to augment the antitumor immune response 2010). of the host. Mechanisms of oncolytic specificity Modifications to improve oncolytic activity There are two general mechanisms that are employed Oncolytic viruses can be used against cancers in ways to achieve tumor-selective viral replication: that are additional to lysis of infected cells. Deletion of viral genes that are dispensable upon infection of neoplastic cells but are critical for viral Suicide genes replication in non-neoplastic cells An elegant example of this strategy is the Viruses can be used as vectors for delivery of suicide oncolytic adenovirus ONYX-015, which is an attenuated genes, encoding enzymes that can metabolise a adenovirus with two mutations in the E1B-55 kD gene. separately administered non-toxic pro-drug into a potent cytotoxin, which can diffuse to and kill neighbouring Placement of tumor-specific promoters upstream cells. One herpes simplex virus, encoding a thymidine of viral genes that are critical for efficient viral replication kinase suicide gene, has progressed to phase III clinical trials. The herpes simplex virus thymidine kinase An oncolytic adenoviral mutant has been phosphorylates the pro-drug, ganciclovir, which is then developed in which the E1A gene, the expression of incorporated into DNA, blocking DNA synthesis which is critical for viral replication, is under the control (Freeman et al. 1996). The tumor selectivity of oncolytic of the tumor-specific a-fetoprotein (AFP) gene promoter. viruses ensures that the suicide genes are only This mutant, AvE1A04i, replicates preferentially in AFP- expressed in cancer cells, however a 'bystander effect' expressing cells such as hepatocellular carcinoma on surrounding tumor cells has been described with (HCC) cells (Hallenbeck et al. 1999).
250 Engineering of oncolytic viruses Non-transductional targeting/ Transcriptional targeting
The specific tumour targeting can be achieved by Oncolytic viruses can be rendered tumour selective by targeting various molecular steps/regulators of cell cycle placing essential viral gene under the regulation of eg. pro-apoptotic, translational, transductional and tumour specific promoter. However, this technique is transcriptional targeting, and strategies based on limited to DNA viruses (excluding pox viruses). Certain tumour micro-environment and use of carrier cells as tumour specific gene promoters like human telomerase cellular vehicle for oncolytic viruses. reverse transcriptase (hTERT) and survivin are active in a variety of tumour types while others are specific for particular tumours, e.g. Prostrate specific antigen (PSA) Pro-apoptotic targeting for prostrate, foetoprotein for liver and tyrosinase for skin (Dalba et al. 2005). Many viruses delay apoptosis of infected cells in order to assist their replication. These encode certain proteins Double targeting which alter the activity of important regulators of programmed cell death such as p53 and pRb. It is unlikely to be possible to make a virus entirely Adenoviral proteins E1A and E1B inactivate pRb and specific toward any tissue type by using just one form p53 in normal cells, respectively, to delay premature of targeting. Double targeting with both transductional apoptosis (Russell and Peng 2007). and non-transductional targeting methods is more effective than any one form of targeting alone. Translational targeting Targeting strategies based on tumour microenvironment HSV-1 can be made tumour selective by mutating the 134.5 gene (designated as R3616). The product of this To support uncontrolled growth and tissue invasion, gene (ICP34.5) binds with protein phosphatase-1 and tumour cells develop a modified microenvironment such inhibits phosphorylation of eukarykotic initiation factor- as hypoxia, activation of certain proteases and 2 (eIF-2) by activated PKR (ds RNA induced protein angiogenesis. This can be harnessed for developing kinase). This unphosphorylated eIF-2 cannot inhibit strategies for tumour targeting. A dual regulated translation of viral transcripts unlike its phosphorylated oncolytic Ad CNHK500 was developed in which the E1b counterpart. Cancer cells are resistant to the PKR gene is controlled by a hypoxia responsive promoter activated inhibition of viral replication due to the high and the E1a gene is controlled by a human telomerase level of Ras activity which inhibits autophosphorylation reverse transcriptase (hTERT) promoter (Singh et al. of PKR. Thus mutant having deleted 134.5 cannot 2012). multiply in normal cells but tumour cells remain permissive (Sarinella et al. 2006). Targeting tumour using carrier cells as cellular vehicle for oncolytic viruses Transductional targeting Cancer cell secretes a number of chemokines which This approach to tumor selectivity has mainly focused helps in trafficking of immune cells to tumour. These on adenoviruses and HSV-1, although it is entirely viable immune cells can be used as cellular vehicle for efficient with other viruses. For instance, many cancer cells over- delivery of OVs to tumour cells. Other types of cells express intracellular adhesion molecule-1 (ICAM-1) and such as stem cells (mesenchymal, endothelial decay accelerating factor (DAF), the receptors for progenitor cells) have also been developed as cellular vehicles to deliver OVs (Komarova et al. 2006). coxsackie virus A21 (CAV21). Transductional targeting can be done in one of two ways: Bi-specific adapter molecules administered along with the virus to redirect Oncolytic virotherapy in veterinary medicine viral coat protein tropism; and Coat-protein modification involving genetically modifying the fiber knob domain of the viral coat protein to alter its specificity (Wickham Cancer still remains frequently lethal disease of human 2003). as well as animals, especially pet animals, despite the
251 significant progress made in its diagnosis and treatment Canary Pox Viruses in recent years. It is a leading cause of death in animals and endemic in both developed and developing The effect of recombinant canary pox viruses (ALVAC) countries (Merlo et al. 2008). Cancer is considered as was analyzed clinically in canine cancer patients. the second most frequent cause of death in humans Intratumoral administration of this recombinant poxvirus and the first one in canines and felines. Spontaneous in dogs with melanoma revealed localized distribution cases of tumors in domestic animals especially in canine of virus into tumor tissue (Jourdier et al. 2003). tumors of which are mostly similar to those of humans, offer an interesting opportunity for comparative studies Translation of oncolytic virotherapy from dogs to humans and to understand cancer biology and drug development and the reverse (Pawaiya and Kumar 2008).
Canine cancers share many features in common with Canine Adenoviruses human cancers including histological appearance, tumor genetics, molecular targets and response to Adenoviruses are being tested as therapeutic agents conventional therapy. In both species, tumor initiation for canine cancers. Human adenovirus 5 has been and progression is influenced by similar factors like age, shown to productively replicate in canine osteosarcoma nutrition, sex and environmental exposure (Khanna et and canine mammary carcinoma cells. Furthermore, al. 2006). Furthermore, carcinogenesis and tumor biologic behaviour in dogs have more features in canine adenovirus 2 (CAV-2), transcriptionally targeted common with humans than with laboratory rodents. to canine osteosarcoma cells by inserting osteocalcin Despite evidence of oncolytic virus efficacy in mouse promoter, was tested as therapeutic agent for canine models of cancers, many viruses fail in human trials osteosarcoma (Smith et al. 2006). due to unacceptable toxicity or lack of efficacy (Wildner et al. 2003). Hence, pet dogs with tumors are necessary Canine Distemper Virus models to demonstrate efficacy of oncolytic viruses for human cancers.
Canine distemper virus binds to a cellular receptor, Signalling Lymphocyte Activation Molecule (SLAM or Many of the treatment options used in veterinary medicine resemble protocols used to treat human CD 50). Canine lymphoid cell lines and B and T 1 cancer patients. In addition, public release of nearly lymphocytes established from dogs with lymphoma have 99% canine genome sequences provided a window of been shown to express CD 50 receptors. Attenuated 1 opportunity to expand the scope of comparative CDV has been tested for oncolytic property in the oncology. Comparison of canine genome sequences lymphoma cells and was able to infect and induce with the human genome suggests that around 19000 apoptosis in these cells. It may therefore be used to genes identified in the dog match to similar or treat canine lymphoma patients. orthologous genes in the human genome (Lindblad et al. 2005). Taking into consideration the value of comparative oncology, data obtained from human Vaccinia Virus clinical trials can be effectively transferred to canines.
Two oncolytic vaccinia virus strains, namely JX-594 Biosafety (Jennerex Biotherapeutics, Inc. USA) and GLV-1h68 (Genelux Corporation, USA), have shown promising preclinical data and are now undergoing clinical trials It is important that precautions for infectious material in humans (Dranoff 2002). Significant inhibition of tumor and biological safety, and biosafety guidelines or their equivalent, be followed when administering oncolytic growth and damage of tumor tissues was observed after viruses. Respective institutional, country, state, and systemic administration of GLV-1h68 in tumor bearing local regulations should be followed. Generally, as part nude mice (Gentschev et al. 2010). Additionally, the of the clinical protocol, all regulatory authorities require opportunity to localize GLV-1h68 viruses via optical some form of barrier contraception for the duration of imaging might be utilized in metastasis detection (Kelly the clinical trial as a standard precaution to prevent et al. 2009). person-to-person transmission. Non-clinical viral
252 shedding studies can be useful in preparing for clinical glioma virotherapy by inhibiting innate immune studies and evaluating detection methods. It is advisable responses. PNAS 103:12873-12878 to integrate monitoring for shed virus into the clinical Gentschev I, Ehrig K, Donat U, Hess M, Rudolph S, Chen N, development plan (Vile et al. 2002). Yu YA, Zhang Q, Bullerdiek J, Nolte I, Stritzker J, Szalay AA (2010) Significant Growth Inhibition of Canine Mammary Carcinoma Xenografts following Conclusion Treatment with Oncolytic Vaccinia Virus GLV-1h68. J. Onc 2010:1-10 Gentschev I, Stritzker J, Hofmann E, Weibel S, Yu YA, Chen Chemotherapy and radiation therapy are current N, Zhang Q, Bullerdiek J, Nolte I, Szalay AA (2009) mainstays in the treatment of advanced cancers but are Use of an oncolytic vaccinia virus for the treatment limited by tumor cell resistance to these agents and a of canine breast cancer in nude mice: preclinical relatively narrow therapeutic index. Thus, dose- development of a therapeutic agent. Canc Gen Ther escalation or combination therapies designed to 16:320-328 overcome resistance or increase tumor cell kill are Gooding LR (1994) Regulation of TNF-mediated cell death limited by toxicity to normal tissues. Oncolytic viral and inflammation by human adenoviruses. Infectious therapy, on the other hand, is capable of increasing agents and disease3:106-115 the therapeutic index between tumor cells and normal Hallenbeck PL, Chang YN, Hay C, Golightly D, Stewart D, Lin cells when viral replication proceeds preferentially in J, Phipps S ,Chiang YL (1999) A novel tumor-specific tumor cells. Armed therapeutic viruses or genetically replication-restricted adenoviral vector for gene engineered viruses represent a very appealing tumor therapy of hepatocellular carcinoma. Hum Gen Ther 10: 1721-1733 targeting approach and a novel opportunity to generate agents that could potentially cure canine cancers. It is Jourdier TM, Moste C, Bonnet MC, Delisle F, Tafani JP, Devauchelle P, Tartaglia J, Moingeon P (2003) Local hoped that collective efforts will contribute to the immunotherapy of spontaneous feline fibrosarcomas development of effective and safe viruses for both using recombinant poxviruses expressing interleukin human and animal cancer therapy. 2 (IL2). Gen Ther 10:2126-2132 Kelly KJ, Brader P, Woo Y, Li S, Chen N, Yu YA, Szalay AA, Fong Y(2009) Real-time intraoperative detection of melanoma lymph node metastases using References recombinant vaccinia virus GLV-1h68 in an immunocompetent animal model. Intl J. Canc Conner J, Braidwood L (2012) Expression of inhibitor of growth 124:911-918
4 by HSV1716 improves oncolytic potency and Khanna C, Lindblad TK, Vail D, London C, Bergman P, Barber enhances efficacy. Canc Gen Ther 19: 499-507 L, Breen M, Kitchell B, McNeil E, Modiano JF (2006) Dalba C, Klatzmann D, Logg CR , Kasahara N (2005) Beyond The dog as a cancer model. Nat Biotech 24:1065- oncolytic virotherapy: replication-competent 1066 retrovirus vectors for selective and stable Khuri FR, Nemunaitis J, Ganly I, Arseneau J, Tannock IF, transduction of tumors. Curr Gen Ther 5:655-667 Romel L, Gore M, Ironside J, MacDougall RH, Heise Dey M, Ulasov IV, Tyler MA, Sonabend AM, Lesniak MS (2011) C, Randlev B, Gillenwater A M, Bruso P, Kaye S B, Cancer stem cells: the final frontier for glioma Hong WK, Kirn DH (2000) A controlled trial of virotherapy. Stem Cell Reviews 7:119-129 intratumoral ONYX-015, a selectively-replicating Dranoff G (2002) GM-CSF-based cancer vaccines. Immunol adenovirus, in combination with cisplatin and 5- Rev 188:147-154 fluorouracil in patients with recurrent head and neck cancer. Nat Med 6: 879 - 885 Duarte S, Carle G, Faneca H, De-Lima MC, Pierrefite-Carle V (2012) Suicide gene therapy in cancer: where do Kirn DH (1996) Replicating oncolytic viruses: an overview. we stand now? Canc lett, 324(2):160-170. Exp Opi Invest Drugs 5:753-762 Freeman SM, Whartenby KA, Freeman JL, Abboud CN , Komarova S, Kawakami Y, Stoff-Khalili MA, Curiel DT, Marrogi AJ (1996) In situ use of suicide genes for Pereboeva L (2006) Mesenchymal progenitor cells cancer therapy. Semi in onc 23 : 31-45 as cellular vehicles for delivery of oncolytic adenoviruses. Mol Canc Ther 5:755-766 Frew SE, Sammut SM, Shore AF, Ramjist JK, Al-Bader S, Rezaie R, Daar AS, Singer PA (2008) Chinese health Li H, Peng KW, Dingli D, Kratzke RA, Russell SJ (2010) biotech and the billion-patient market. Nat Biotech Oncolytic measles viruses encoding interferon ? and 26:37-53 the thyroidal sodium iodide symporter gene for mesothelioma virotherapy. Canc Gen Ther 17:550- Fulci G, Breymann L, Gianni D, Kurozomi K, Rhee SS, Yu J, 558 Kaur B, Louis DN, Weissleder R, Caligiuri MA Chiocca EA (2006) Cyclophosphamide enhances Lindblad KT, Wade CM, Mikkelsen TS, Karlsson EK, Jaffe
253 DB, Kamal M, Clamp M, Chang JL, Kulbokas EJ, Sarinella F, Calistri A, Sette P, Palu G, Parolin C (2006) Zody M (2005) Genome sequence, comparative Oncolysis of pancreatic tumour cells by a gamma 5- analysis and haplotype structure of the domestic dog. deleted HSV-1 does not rely upon Ras-activation, Nat 438:803-819 but on the PI 3-kinase pathway. Gen Ther13:1080- Lowe SW, Bodis S, McClatchey A, Remington L, Ruley HE, 1087 Fisher DE, Housman DE, Jacks T (1994) p53 status Shtrichman R, Kleinberger T (1998) Adenovirus type 5 E4 and the efficacy of cancer therapy in vivo. Sci open reading frame 4 protein induces apoptosis in 266:807-810 transformed cells. J. Viro 72:2975-2982 Melcher A, Parato K, Rooney CM, Bell JC (2011) Thunder Singh PK, Doley J, Kumar GR, Sahoo AP, Tiwari AK (2012) and Lightning: Immunotherapy and Oncolytic Viruses Oncolytic viruses and their specific targeting to Collide. Mol Ther 19:1008-1016 tumour cells. Indian J. Med Res 136:571-584 Merlo DF, Rossi L, PellegrinoC, Ceppi M, Cardellino U, Smith BF, Curiel DT, Ternovoi VV, Borovjagin AV, Baker HJ, CapurroC, Ratto A, Sambucco PL, Sestito V, Tanara Cox N, Siegal GP (2006) Administration of a G, Bocchini V (2008) Cancer incidence in pet dogs: conditionally replicative oncolytic canine adenovirus findings of the Animal Tumor Registry of Genoa, Italy. in normal dogs. Canc Bio Radio 21:601-606 J. Vet Int Med 22:976-984 Vile R, Ando D, Kirn D (2002) The oncolytic virotherapy Nettelbeck DM, Jerome V, Muller R (2000) Gene Therapy: treatment platform for cancer: unique biological and Designer Promoters for Tumour Targeting. Tren biosafety points to consider. Canc Gen Ther 9:1062- Genetics 16:174-181 1067 Pawaiya RVS, Kumar R (2008) Relevance of veterinary Wickham TJ (2003) Ligand-directed targeting of genes to the oncology in human cancer research. Indian J Vet site of disease. Nat Med, 9:135-139 Path 32:200-205 Wildner O, Hoffmann D, Jogler C, Uberla K (2003) Comparison Rampling R, Cruickshank G, Papanastassiou V, Nicoll J, of HSV-1 thymidine kinase-dependent and - Hadley D, Brennan D, Petty R, MacLean A, Harland independent inhibition of replication-competent J, McKie E, Mabbs R , Brown M (2000) Toxicity adenoviral vectors by a panel of drugs. Canc Gen evaluation of replication-competent herpes simplex Ther 10:791-802 virus (ICP 34.5 null mutant 1716) in patients with Woo Y, Adusumilli PS, Fong Y (2006) Advances in oncolytic recurrent malignant glioma. Gen Ther 7:859-866 viral therapy. Curr opin invest drugs 7:549-559 Russell SJ, Peng KW (2007) Viruses as anticancer drugs. Tren Pharma Sci 28:326-333
(Manuscript Receivd : 30.8.13; Accepted : 19.12.13)
254 JNKVV Res J 47(3): 255-259 (2013)
Genetic analysis of CIMMYT based bread wheat genotypes for yield and its contributing traits
R.S.Shukla and P.K.Moitra Department of Plant Breeding and Genetics Jawaharlal Nehru KrishiVishwavidyalaya Jabalpur 482004 (MP)
Abstract In India wheat is being grown in 29.9 million hectare area and produce 93.9 million tones and 3.1 The experimental materials comprised of 76 CIMMYT based tones/ha productivity. Madhya Pradesh area,production promising lines of wheat received from Mexico and 6 checks and productivity is 53 lakh hectare, 131 lakh tones and these lines were planned to assess their potential under high productivity 3.1tones/ha (Anonymous, 2013).Rain-fed fertility timely sown condition during rabi 2012-13 under wheat area in India and MP is 67 and 70% respectively out of Improvement Project Department of Plant Breeding and which 60 - 65 percent is under restricted irrigation. Water Genetics, JNKVV, Jabalpur. The experiment were laid out use efficient wheat varieties for such large areas are with three replication under randomized complete block deign and observations were recorded on yield and its contributing the need of the state for sustainable wheat production traits and subjected to analysis for the genetic analysis. The and food security. analysis of variance for 14 characters revealed highly significant differences for all the characters. Phenotypic and The productivity of wheat MP is increasing genotypic coefficient of variation was found to be higher for gradually due to increase in irrigation facilities but the number of tillers per plant, spike density, number of ears per area under restricted irrigation is still needs to be plant and high PCV % for grain yield per plant. Heritability enhanced by developing suitable wheat varieties.The estimates was high for tillers per meter number of grains per reason of low productivity in these areas is lack of high ear ,harvest index, biological yield per plant, seed yield per yielding varieties for restricted irrigation, high plant, spike length, 1000 grain weight and days to flower temperature during early vegetative phase, initiation. High heritability coupled with high genetic advance unavailability of water and power etc. Many modern as percentage of mean was observed for tillers per meter, numbers of grains per ear, harvest index, biological yield per cultivars in wheat and in other crops as well, are often plant, seed yield per plant and numbers of ears per plant and genetically similar, with a rather narrow genetic base. spike density. It indicates role of additive gene action and Therefore, in wheat breeding there is needed to utilize selection of promising genotypes and its use in hybridization sources of new diversity. New variation can be created programme shall be effective. by hybridization between different parental cultivars. Yield is a complex polygenic quantitative trait, Keywords: Bread wheat, genetic analysis, CIMMYT, considerably affected by environment. Therefore, Genetic variability, genotypic and phenotypic coefficient selection of genotypes based on yield is not effective. of variation, genetic advance Selection has to be made for the components of yield. The availability of genetic variability is the basic pre- requisite for any genetic improvement through Wheat (Triticum aestivum L emThell.) is the world's systematic breeding programme. second most important staple food crop for more than 35 percent of world's population next to the rice. It is The correlation between traits reveals the type, cultivated under a wide range of climatic conditions nature and magnitude of association between yield favored by cool, moist weather followed by dry warm components with yield and among themselves. To weather. Wheat generally accorded a special emphasis increase the yield, contributes of direct and indirect among cereal crops.It produces about 20% food effects of yield components provides the basis for its resources of the world, high productivity and the successful breeding programme and hence the problem prominent position it holds in the international food grain of yield increase can be more effectively tackled on the trade. 255 basis of performance of yield components and selection Result and discussion for closely related characters (Choudhary et al 1986). On the other hand, path coefficient analysis measures One of the important purposes of present investigation the direct and indirect effect for one variable upon was to find out the extent of variability present in 81 another and permits the partitioning of thetotal advance generation genotypes of wheat with regards correlation coefficient into direct and indirect effect to 14 characters (Table 1). (Dewey and Lu 1959). The analysis of variance for 14 characters Yield being a complex character is a function of revealed highly significant differences for all the several component characters and their interaction with characters. It indicated the existence of sufficient genetic environment. Probing of structure of yield involves variability for the characters studied which provides assessment of mutual relationship among various ample scope for selecting superior and desired characters contributing to the yield. In this regard genotypes by the plant breeders for further genotypic and phenotypic correlation reveals the degree improvement. of association between different characters and thus aid in selection to improve the yield and yield attributing The assessment of heritable and non-heritable characters simultaneously. Further, path coefficient components in the total variability observed is analysis helps in partitioning of correlation coefficients indispensable in adapting suitable breeding procedure. into direct and indirect effects and in the assessment of The heritable portion of the overall observed variation relative contribution of each component character to can be ascertained by studying the components of the yield.Considering the above facts in the proposed variation such as GCV, PCV, heritability and predicted study, an effort is made to screen advance and uniform genetic advance. elite bread wheat lines. Present study revealed that phenotypic and genotypic coefficient of variation was found to be higher Material and methods for number of tillers/plant,spike density, number of ears/ plant and high PCV % for grain yield /plant. Similar The experimental material comprises of 75 elite wheat observations were reported by Shukla et al (2000), diverse lines (31st ESWYT- 20, 5EBWYT-6, 2CSISA- Kumar et al (2003), Singh and Chaudhary (2006), Khan HT-EM-4, 32nd ESWYT-20 and 6EBWYT-25) received et al (2007), Ali et al (2008), Riaz et al (2010), Zecevic from CIMMYT with six check varieties viz. GW-366, et al (2010), Tripathi et al (2011), they have reported GW273, GW322, HI1544, MP1201 and UFAN. The high genotypic coefficient of variation for number of experiment was laid out in randomized complete block grains per spike, grain yield/plant and harvest index design of two rows of 2.5m length and 20 cm apart with (Table 2). three replications under high fertility timely sowing The coefficient of variation indicates only the condition under Wheat Improvement Project to explore extent of variability present for the characters and does the genetic potential.The seed was hand dibbled and not indicate the heritable portion. This could be recommended cultural packages were followed to raise ascertained from heritability estimates which in broad the healthy crop. sense. Phenotypic variation in the population is the The observations were recorded on five randomly result of genotypic and environmental effects. The selected plants from each plot and from each replication portion of total variation caused by genotypes is called for characters viz; days to flower initiation (days) days heritability and estimated as the ratio of genotypic to maturity (days), plant height (cm), number of tillers / variance to the total phenotypic variance. Broad sense plant, ear length (cm), number of grains/ear, number heritability includes both additive and non-additive gene of spikelets/spike, spike density, number of spikelets/ effects. The knowledge of heritability is helpful in spike, thousands grain weight (g), seed yield/plant assessing merits and demerits of a particular trait as it (g), biological yield/plant (g), harvest index (%) and enables the plant breeder to decide the course of tillers/meter. The data were subjected to statistical selection procedures to be followed under a given analysis for PCV and GCV (Burton, 1952), heritability situation. in broad sense (Allard, 1960 and Hanson et al. 1956) In present investigation heritability estimates was and expected genetic advance as suggested by high for tillers/meter, number of grains/ear, harvest Johnson et al. (1955). index, biological yield /plant, seed yield/plant, spike
256 14 7.15 9.93 X 6.64 8.22 23.95 76.82 14.13 12.07 11.41 44.80 32.04 17.36 15.01 20.10 26.89 23.51 15.68 26.04 39.11 26.64 of mean 354.37** GA asGA % 13 X GA 0.307 1.073* 1.00 0.816 1.61 1.13 8.23 8.87 7.99 3.32 2.06 1.65 2.72 6.39 3.14 8.62 6.15 0.72 11.04 19.34 54.42 12 4.46 8.82 6.20 X 35.62 29.93 12.90 119.65** (bs) (%) 2 61.39 54.67 41.91 44.45 67.11 52.83 57.71 69.72 67.51 72.82 64.74 78.56 46.42 80.63 h 11 X 3.87 7.65 5.37 12.07 48.80** 22.50 12.09 (%) 10 9.02 5.90 9.52 PCV 48.95 23.17 15.96 12.63 13.99 19.34 15.67 11.76 16.09 40.89 16.04 X 4.23 8.37 5.88 16.07 81.06** 26.94 14.16 9 X 5.99 4.98 1.82 3.59 2.52 (%) 7.06 4.36 6.16 9.56 9.46 GCV 12.01** 19.07 32.64 18.98 11.60 11.69 15.89 13.38 14.26 27.86 14.40 8 X 3.46 6.84 4.81 18.61 47.54** 18.02 13.33 p 2 2.22 2.29 5.25 5.11 0.56 42.35 62.01 85.65 13.16 19.85 33.00 21.27 46.54 135.64 7 X 6.65 2.10 4.16 2.92 12.52 11.30** 14.21 e 2 6 Mean sumMean of square X 7.31 0.73 1.08 2.22 6.01 1.66 8.98 7.50 9.98 0.33 16.35 28.11 49.75 26.28 5.37 4.70** 3.24 1.47 2.90 2.04 19.01 5 X g 2 1.86 5.19** 2.20 1.21 2.39 1.68 23.05 5.85 1.49 1.21 3.03 3.45 0.26 26.00 33.90 35.90 13.84 24.03 13.77 36.56 109.36 4 X 3.82 7.55 5.30 24.85** 21.92 63.16 129.97 8.93 2.48 79.00 10.63 11.80 21.76 43.30 15.64 45.46 45.33 56.16 96.33 138.66 104.23 3 Maximum X 9.97 19.70 13.84 12.58 Range 158.64 157.45* 149.25 2.88 1.43 3.23 8.83 4.91 1.61 2 43.66 64.80 19.06 20.85 21.20 17.06 45.33 125.00 X Minimum 7.49 6.88 90.52 84.33 14.80 10.40 129.81** = Harvest (%) index = 1000grainin (g)weight = Numberof grains / ear densitySpike= meters/ Tillers = 1 = Biological= plant./ yield = yieldplantSeed / 8 9 10 11 12 13 14 X 7.41 6.43 9.48 1.83 X X X X X X X Mean 72.13 97.20 18.14 31.83 11.69 36.65 39.22 42.40 72.60 133.46 5.71 7.93 9.710 19.38 94.37** 49.05 11.29 ) ) 1 8 ) 11 ) ) ) 4 7 ) 10 ) ) 3 ) ) 12 9 2 5 ) ) ) 6 (r-1)=2 (v-1)=80 (r-1) (v-1)=160 Degree ofDegree freedom 14 13 : Analysis of variance for Yield and attributes yield for 81CIMMYT based bread wheat genotypes Parameters of forGenetic and variability yield its component characters of CIMMYT based bread wheat genotypes = Days to =initiationflower Days maturityDays to = = Plant height (cm) = Number of tiller /plant = Number of ear /plant = Ear length (cm) = Numberof spiklets /ear eplication CV CV % 1 2 3 4 5 6 7 Table 1. Table Sources of variation R Genotypes Error SE of Difference atCD 5% atCD 1% E X X X X X X X * Significant at 5% level * * Significant at 1% level 2. Table Character initiationflower Days to (X maturity(X to Days Plant height (cm) (X No. of tillers / plant (X No of ear / plant (X Ear length cm) (X spikleth/No of ear (X (X Biologicalyield/plant(g) plant(X yield/ Seed Harvest (%) index (X 1000 grainweight (g) (X grainsNo of /ear (X (X density Spike (X meter / Tillers
257 length, number of ear/plant, 1000 grain weight and days biological yield, harvest index and test weight. to flower initiation. In confirmation with results of earlier workers Krishnawat and Sharma (1998) for weight of grain/spike, grain yield/plant, biological yield/plant and lhehV esfDldks vk/kkfjr xsgw¡ dh 76 vk'ktud fd'eksa dk 6 fu;a=.k harvest index, Prasad and Pandey (2001) for plant fd'eksa ds lkFk mudh mit {kerk vkdyu dk v/;;u 2012&13 height, productive tillers/plants, 1000-grains weight, esa xsgq¡ vuqla/kku ifj;kstuk] ikS/k iztuu ,oa vuqoaf'kdh foHkkx] t- Pawar et al (2002) for length of spike, number of us-—-fo-fo-] tcyiqj esa fd;k x;k A mijksDr v/;;u rhu jsIyhds'ku spikelet/spike, grains/ear, number of tillers/m, Shukla esa mit ,oa mit esa lgk;d ?kVdks ds vuqokaf'kd fo'kys"k.k gsrq fd;k and Singh (2004) for number of grains/spike, grain yield/ plant, Kumar et al (2010) for grain yield/plant, Sahu x;k A fo'kys"k.k ds rgr mit c<+kus okys xsgq¡ ds 14 fofHkUu ?kVdksa (2011) for number of grains/ear, biological yield/plant, esa egRoiq.kZ fofo/krk ikbZ xbZ A QhuksVhfid ,oa thuksVhfid lwpukad harvest index, Nafde (2012) for number of grains/ear, esa 'kk[kk,a izfr ikS/k] ckyh /kuRo] ckyh izfr ikS/k] gsrq mPp fofof/ grain yield/plant, biological yield/plant, harvest index, krrk ikbZ xbZ A Tsegaye et al (2012) 1000 grain weight, biological yield also reported high heritability estimates in wheat. 'kka[kk,a izfr ikS/k] nkuk izfr ckyh] mit lw¡ph] tSfod mit Genetic advance is the difference of mean izfr ikS/k] Qwy f[kyus dk le;] mit izfr ikS/k] ckyh dh yackbZ ,oa genotypic value of the selected genotypes over the base gtkj nkus dk otu esa mPp ca'kkxr vuqekfur ik;k x;k A blh population. Heritability estimates are useful in deciding izdkj oa'kkuqxr ,oa vuqokaf'kd izxfr nksuksa ds vk/kkj ij 'kk[kk izfr the characters to be considered while making selection, but selection based on this factor alone may limit the ehVj] nkus izfr ckyh] mit lw¡ph] tSfod mit] cht mit izfr progress, as it is prone for changes with environment, ikS/k ckyh izfr ikS/k] rFkk ckyh /kuRo esa mPp ,d :irk ikbZ xbZ tks material etc. so, heritability needed sufficient genetic bu ?kVdks ds peu esa ,oa ladj }kjk okaf'kd lq/kkj dks n'kkZrh gS A advance attributable to additive gene action for desirable gain from selection. Therefore, genetic Acknowledgement advance as a percentage of mean worked out thus genetic information would support for an effective selection.An estimate of genetic advance is valid for Authors are thankful to BISA, CIMMYT, Lakhanwara, only one generation and largely depends of intensity of Jabalpur for providing the promising genotypes. selection. Heritability for traits and phenotypic variance are available in population. References In the present study high heritability coupled with high genetic advance as percentage of mean was Anonymous (2013) Project Directorate Report, DWR p 4 observed for tillers/meter, numbers of grains/ear, Ali YB, Manzooratta J, Akhter PH, Monneveux, Lateef Z (2008) harvest index, biological yield/plant, seed yield/plant and Genetic variability, association and diversity studies numbers of ears/plant and spike density. in wheat (Triticum aestivum L) germplasm. Pak J Bot 40 : 2087-2097 The results were in accordance with the results Allard RW (1960) Principles of plant breeding. John Wiley of various research workers on wheat viz. Krishnawat and Sons Inc Newyor. and Sharma (1998) for weight of grain/spike, grain yield/ Bakshi SMA, Barai BK, Murmu K (2008) Genetic variability in plant and biological yield/plant and harvest index, Pawar wheat (Triticum aestivum L) under new alluvial zone of West Bengal. Environment and Ecology 26(1): et al. (2002) for plant height, Mondal et al. (2004) for 58-60 root weight and grain yield/plot. Shukla and Singh Burton GW (1952) Quantitative inheritance in grasses. Proc (2004) for number of grains/spike, grain yield/plant, total Int Grass land Congr 6: 277- 283 biomass/plant and spike weight, Singh and Chaudhary Choudhary R, Shah AH, Ali L, Basshir M (1986) Path (2006) Ali et al. (2008) for plant height, number of coefficient analysis of yield and yield component in spikelets/spike, spike length, number of grains/spike, wheat. Pak J Agric Res 7(2): 71-75 1000 grain weight and yield/plant. Bakshi et al. (2008) Dewey DR, Lu KH (1959) A correlation and path coefficient for number of spikelets/panicle and grain yield/plant, analysis of components of crested wheat grass seed Manal (2009) for spike length and 1000 grain-weight, production. Agron J 51: 515-518 Tripathi et al. (2011) for plant height, grain yield/plant Hanson WD, Johnson HW (1957) Method of calculating and evaluating a general selection index obtained by
258 pooling information from two or more experiments. Sahu S (2011) Genetic studies on advanced lines of bread Genetics 42: 421-432 wheat under restricted and irrigated condition. MSc Johnson HW, Robinson HF, Comstock RE (1955) Estimation (Ag) thesis JNKVV Jabalpur of genetic and environmental variability in soybean. Singh GP, Chaudhary HB (2006) Selection parameters and Agron J 47: 314-318 enhancement of wheat (Triticum aestivum L) under Khan AJ, Muhammad T (2007) Grain yield stability analysis different moisture stress conditions. AsianJournal of of wheat (Triticum aestivum L) genotypes from Plant Sciences 894-898 NWFP of Pakistan. Pakistan J Agricul Res 20(3/4): Shukla RS, Mishra Y, Singh CB (2000) Variability and 105-109 association in bread wheat under rainfed condition. Krishnawat BRS, Sharma SP (1998) Genetic variability in Crop Res (Hisar) 19(3): 512-515 wheat under irrigated and moisture stress conditions. Shukla RS, Singh CB (2004) Genetic analysis for screening Crop Res 16(3): 314-317 of high temperature and moisture stress tolerance Kumar SD, Singh V, Dhivedi K (2010) Analysis of yield crop in bread wheat. JNKVV Res J 38(1):22-25 plants and there association in wheat for Tripathi SN, Marker S, Pandey P, Jaiswal KK, Tiwari DK (2011) architechering the desirable plant type. Indian J Agric Relationship between some morphological and Res 44(4): 267-273 physiological traits with grain yield in bread wheat Kumar S, Dwivedi VK, Tyagi N (2003) Genetic variability in (Triticum aestivum L emThell). Trends in Applied Sci some metric traits and its contribution to yield in Res 6: 1037-1045 wheat. Progressive Agriculture 39 (1/2): 152-153 Tsegaye D, Dessalegn T, Dessalegn Y, Share G (2012) Manal HE (2009) Estimation of heritability and genetic advance Genetic variability, correlation and path analysis in of yield traits in wheat (Triticum aestivum L) under durum wheat germplasm (Triticum durum). Agric drought condition. International J Genetics and Res Rev 1(4): 107-112 Molecular Biol 1(7):115-120 Zecevic V, Boskovic J, Dimitrijevic M, Petrovic S (2010) Nafde A (2012) Studies on growth and yield components of Genetic and phenotypic variability of yield bread wheat under restricted irrigation. M Sc (Ag) components in wheat (Triticum aestivum L). Thesis JNKVV Jabalpur Bulgarian J Agricul Sci 16(4): 422-428 Pawar SV, Patil SC, Naik RM, Jambhale VM (2002) Genetic variability and heritability in wheat. J Maharashtra Agricull Universities 27(3): 324-325 (Manuscript Receivd : 16.8.13; Accepted : 22.12.13) Riaz-ud-Din M, Khan A, Wasim SN, Ahmad AR (2010) Selection criterion for high yielding wheat genotypes under normal and heat stress conditions. SAARC J Agric 5(2): 101-110
259 JNKVV Res J 47(3): 260-262 (2013)
Investigation on ethno medicinal remedies to cure diseases by tribes of eastern Madhya Pradesh with special reference to threat assessment of leguminosae family
Karuna S. Verma and Lekhram Kurmi Aeroallergens, Immunology and Angiosperms Diversity Laboratory Rani Durgawati University Jabalpur 482001 (MP)
Abstract loss of habitat through increasing livestock, deforestation, a requirement for more land for housing and cultivation. An ethno botanical study was conducted from 2009 to 2012 to investigate the uses of threatened medicinal plants by local Less-than-threatened categories are Near tribal people in Eastern Madhya Pradesh. The results obtained Threatened, Least Concern, and the no longer assigned revealed that 27 plants were used as a cure of 15 ailments category of Conservation Dependent. Species which belonging to Leguminosae (Fabaceae) family. All the plants have not been evaluated (NE), or do not have sufficient collected from the study area were either endemic or data (Data Deficient) also are not considered threatened. The need for the conservation of these threatened "threatened" by the IUCN. In the present study plants plants cannot be over emphasized as most tribal people in were categorized according to Red List categories of the study area depend mostly on Plants of these species. IUCN version 4.0 (2001 - 2012). The list of plants which Proper conservation and management plans are suggested have been considered as CR- Critically Endangered, to conserve the medicinal plant resources before it lost forever. EN- Endangered, VU- Vulnerable are given on the basis of frequent survey and available literature.
Keywords: Conservation, Threatened medicinal plants, Eastern Madhya Pradesh. Material and methods
The increase of human population in the last few Survey and collection of plants - Extensive surveys and decades demanding development in various spheres field work involved collection of plants for preparing an has resulted directly or indirectly in the sudden and often account of the threatened Leguminous (Fabacious) far-reaching disturbances in natural ecosystems, the plants field trips were undertaken in tribal areas of the Eastern Madhya Pradesh is one of them it has 10,160 Eastern Madhya Pradesh during 2009 to 2012. At each sq. km. with of population 2,460,714 of which male and time of visit, different tribal hamlets and forest pockets female were 1,278,448 and 1,182,266 respectively were choose in different seasons to collect more information on plants. Information was compiled through (2011 Census). Geographically it is located by 230 - scientifically guided questionnaires (Jain 1991), 100 North & 79°57° East & 411 meters high above mean interviews and general conversations with several tribal sea level. herbal healers, village heads, elder women and other Jabalpur has Geological formations such as; local informants collected by interview. The plants were Archeans, Gondwanas, Lametas, Decan traps and initially identified by their vernacular names through Vindhyans, the forest division with Jabalpur, Sihora and consultations with the local people. Voucher specimens Bargi occupies the 1551.78 sq.km. area under reserve were prepared and deposited in the Herbarium cum and protected forest, the forest division is classified as Museum, Department of Biological Science Rani Dry Tropical forests (Champion and Seth 1968). Due to Durgawati Vishva Vidyalaya Jabalpur for further record increasing threats to plant diversity in the area include and references.
260 Identification of plant specimen - After collection an was recorded. The plants were enumerated attempt was made to identify plants. From fresh material alphabetically with their botanical name with author those could not be identified with the help of "Flora of citation, family name, local name, habit, source of British India, by Sir Hooker (1872) Flora of Bhopal collection, part used, medicinal uses and threat status (Oomachan 1977), Flora of Jabalpur (Oommachan and (Table 1). Shrivastava 1996), B.S.I. (Madhya-Pradesh Vol. I -III. 1993-2001), Khanna et al. (2001).The threat status of Result and Discussion the identified plant species in the study area was defined after consultation with relevant literature (Jain and Rao 1983, Nayar and Shastry 1990, Jadhav et al. 2001, The results of the study have revealed 27 plant species Leaman 2005) and Conservation Assessment and belonging to Fabaceae family distributed in 15 genera Management Planning (CAMP) reports of India. The that are frequently used for treatment of 15 diseases source of plant collection from respective forest types by local tribes, herbalists and traditional healers (Table
Table 1. Threatened plants used ethno medicinally in Eastern Madhya Pradesh.
Sub-family - Papilionaceae S.N. Botanical name Local Name Habit Part used Ethno -medicinal uses TS 1. Abrus precatorius L. Gumchi, Ratti C R., Sd. Cough & Cold EN 2. Alhagi maurorum Medic D.C. Jawasa S R Piles EN 3. Butea monosperma Lam. Taub. Palash ,Teshu, T Rb Haematuria,Piles VUL 4. Butea superva Roxb. Safed palashbel C Fl Skindisoder CR 5. Canavalia gladiate (Benth)Baker Jangli sem C L Gonorrhea VUL 6. Clitoria ternata L. Aprajita C L Fever VUL 7. Clitoria biflora Dalz. Kajroti H Sd Inflammation VUL 8. Dalbergia latifolia Roxb. Safed Shisham T R Diarrhea EN 9. Dalbergia paniculata Roxb. Dhobin T Sd Fever VUL 10. Dalbergia lanceolaria (L.F.) Dhamosi T Rb Skin- disease EN 11. Erythrina indica Lamk. Pangara T L Urinary troubles EN 12. Erythrina suberosa L. Gadha palash T L Menstrual flow CR 13. Mucuna pruriens L. Dc.Prodr. Kauch H Sd Dysentery EN 14. Pueraria tuberosa Roxb.willd Bidari kand C Rb Foothache VUL Sub family Caesalpiniaceae 15. Bauhinia racemosa Lamk. Asta T Sb Teethache VUL 16. Bahunia purpurea L. Sp. Keolar T Rb Diarrhoea VUL 17. Bahunia variegate L. Sp. Kachnar T Sd Skin- disease VUL 18. Bahunia vahlii Wight &Arn. Mahul patta C L Fever EN 19. Cassia occidentalis L. Sp Chirotha S S Skin- disease EN 20. Cassia javanica L. Sp. Java cassia T Sb Skin- disease VUL SubFamily - Mimosaceae 21. Acacia catechu ( L.f) Willd Sp. Khair T Sb Skin- disease VUL 22. Acacia pennata L. Willd. Sp. Chhoti Chilati S Sb Diarrhoea VUL 23. Albizia lebbeck L. Benth. KalaSiris T L Skin- disease VUL 24. Albizia procera Roxb. , Benth. Safed Siris T L Skin- disease VUL 25. Neptunia triquetra Benth. Lajalu H Fl Eye disease CR 26. Prosopis juliflora (SW.) DC. Pro Khejra T Sb Stomach pain VUL 27. Prosopis cineraria (L.) Druce. Shami T Rb Fever CR
H = Herb, C = Climber, S =Shrub, Fl= Flower, L= Leaf, R= Root, Rb= Root bark, S= Stem, Sb= Stem bark, Sd= Seed, EN = Endangerd, CR = Critical Endangerd, VUL = Vulnerable. TS= Threat status.
261 1). Among them 03 were herbs, 15 were trees, 06 were References climbers and 3 were shrubs. Members of the family Fabaceae are the most commonly used. As seen in Table Champion H G, Seth, S K (1968) A Revised Survey of the 1, common health ailments in the study area were skin Forest Types of India. Govt. of India. Publications, problems such as eczema, wounds and cuts. This is New Delhi because of Tribals are maintaining ancient style of living Hooker J D (1872) The flora of British India. 1 (7): 1904, A i.e., forest dwelling and hence are more prone to get sketch of the flora of British India. In the imperial skin cuts and skin allergies because of spiny and thorny Gazette, London plants and so also due to the different pollen grains or Jadhav S N, Ved D K, Ghate U, Reddy K N, Reddy C S (2001) stinging hairs of some plants. Proceedings of the Conservation Assessment and Management Planning Workshop: Medicinal The second important disorder observed is of Plants of Andhra Pradesh. EPTRI Hyderabad stomach complaints viz. dysentery, Diarrhoea, stomach Jain S K, Sastry A R K (1980) Threatened plants of India-A pain, etc. This may be because of poor hygiene and state of the Art Report. Botanical Survey of India. sometimes use of contaminated water. A total of 5 plants Calcutta are employed for various stomach complaints. Hence, Jain S K (1991) Dictionary of Indian Folk Medicine and there is always search for powerful remedies by trial Ethnobotany. Deep Publi., New Delhi p 311 and error method, which has resulted in the Jain S K, Rao R R (1983) An Assessment of Threatened development of reliable ethnomedicine for treating Plants of India. Botanical Survey of India, Calcutta different diseases. Kala C P (2000) Status and conservation of rare and Present study has revealed that medicinal plants endangered medicinal plants in the Indian Trans- still play a vital role in the primary healthcare of the Himalaya. Biological Conservation 93 (3): 371-379 people of this region. During the survey, it was observed Khanna K K, Kumar A, Dixit R D, Singh N P (2001) Supplement to the Flora of Madhya Pradesh. BSI, Calcutta that more than half of the total number of people questioned regularly used medicinal plants to treat many Leaman D (2005) International standard for sustainable wild collection of medicinal and aromatic plants (ISSC- ailments. Therefore, this study is important to preserve MAP). Medicinal Plant Conservation Newsletter 11: the knowledge of medicinal plants used by the people 4-5 in the Eastern Madhya Pradesh. Also, it is of significance Mudgal V, Khanna K K, Hajara P K (1997) Flora of Madhya to exploit novel pharmacological compounds from these Pradesh Vol. II.BSI, Calcutta plants for various treatments of diseases. Nayar M P, Shastry A R K (1990) Red Data Book of Indian The threatened categories have been assessed Plants, Vol. III. BSI Calcutta using the IUCN Red List Criteria, Version 4.0. (2001- Oommachan M, Srivastava J L (1996) Flora of Jabalpur, Sci. 12). All the species identified in the present study were Pub. Jodhpur p 1 - 354 endemic and/or threatened. Out of 27 plant species, Oommachan M (1977) The Flora of Bhopal, J.K. Jain Bro. 15 are of Vulnerable, 08 Endangered and 4 critically Bhopal p 1- 475 endangered. Pattanaik C, Reddy C S, Reddy K N (2009) Ethno-medicinal Survey of Threatened Plants in Eastern Ghats, India Our Nature 7:122-128 Acknowledgements Singh N P, Khanna K K, Mudgal V, Dixit, R D (2001) Flora of Madhya Pradesh Vol. III.BS, Calcutta The authors are thankful to Head, Department of PG Verma D M , Balakrishan N P, Dixit R P (1993) Flora of Madhya Pradesh Vol. I.BSI, Calcutta. Studies and Research in Biological Science, and Dean Faculty of Life Science Rani Durgawati University, Verma K S, Dahake D, Sinha R (2010) Survey of Ethno- medicinal plants of selected sites of Jabalpur district Jabalpur (MP) for generous help during the execution (MP). Indian Journal of Tropical Biodiversity 196/10 of the work. Verma K S, Iqbal Y, Khare D (2010) Ethno- medicinal importance of weeds and their present status in Jabalpur. Vegetos 23 (2)
(Manuscript Receivd : 11.9.13; Accepted : 30.12.13)
262 JNKVV Res J 47(3): 263-268 (2013)
Phytochemical screening of different plant parts of munga (Moringa oleifera Lam.)
Karuna S. Verma and Rajni Nigam Aeroallergens Immunology & Angiosperm's Diversity laboratory Department of Post Graduate Studies and Research in Biological Science Rani Durgawati University Jabalpur 482001 (MP)
Abstract phytochemical constituents. The plant has been described traditionally for the various medicinal and general purpose uses. However, the link between the Aqueous, methanol, ethyl acetate and petroleum ether extracts traditional knowledge and the current scientific of leaf, stem, root, fruit and seeds of a common tree "Munga" perspective is missing. To create the link, different parts (Moringa oleifera Lam.) were used for determination of phytochemical constituents. In the present study thirteen of the plant were screened for the presence of primary principles phytochemicals were investigated. Aqueous extract and secondary metabolites. Since this plant is native to showed presence of saponins, tannins and sterols in all plant most of the Indian regions, this comprehensive parts. Cardiac glucosides were present in fruit and seed only. comparative study will add to the current knowledge Methanolic extract showed sterols in all plant parts. Ethyl bank of Moringa oleifera. acetate and petroleum ether extract showed presence of glycerol, starch and sterol in plant parts. Out of all, lipids and sterols were found to be positive in all four extracts of leaf. Material and methods Alkaloids, anthraquinones and flavonoids were other important secondary metabolites. The whole plants of Moringa oleifera were purchased from the local nursery of Jabalpur (MP) during rainy Keywords: Phytochemistry, secondary metabolites, season of 2012. From these young plants (approx. bioactive metabolites, Moringa oleifera Lam length of 1 to 1.5 meter) roots, stem and leaves were obtained. The whole plants were taken out of the soil, Phytochemistry is concerned with compounds washed and root, stem and leaves were separated synthesized and accumulated by plants with the manually. For fruit and seeds, the fully grown pods of structural characterization of these molecules (Awoyinka the M. oleifera from fully grown trees were used. These et al. 2007, Edeoga et al. 2005, Kalkar et al. 2009). pods were picked during the summer of 2012. From Although Moringa oleifera is native to the sub Himalaya the fully developed pods (drumsticks), the seeds were tracts of India, Pakistan, Bangladesh and Afghanistan, separated and rest of the pod was used a fruit source. where it is used as folk medicine (Fahey 2005), it is The plant parts were dried under shade till constant now widely distributed all over the world (Lockelt et al. weight is achieved. The dried parts were cut into small 2000). M. oleifera is referred as a "miracle tree" or a pieces (wherever required), dried and grounded to a "wonder tree" (Fuglie 2001) with significant socio- fine powder of less than 100 µM as described by economic importance because of its several nutritional, Harborne (1998). The dried powder was stored in a cool pharmacological (Caceres et al. 1991, Fuglie 2001) and and dry place in an airtight container until used. industrial applications (Makkar and Becker 1997, Foidl 2001). The leaves of this plant contain a profile of Phyto-extracts were prepared from 10 g of dry important trace elements, and are a good source of powder of each plant part in a sequential manner with proteins, vitamins, b-carotenes, amino-acids and different polar to non-polar solvents i.e. water, methanol, various phenolics (Anwar 2007). ethyl acetate and petroleum ether (Mdlolo et al. 2008, Sreelata and Padma 2009). Aqueous extracts were The present study is aimed at comparing all the prepared by cold percolation method whereas methanol, major plant parts of Moringa oleifera for its ethyl acetate and petroleum ether extracts were
263 prepared using Soxhlet extractor. All the extracts were Methanolic extracts of root, fruit and seed showed concentrated under vacuum to 20 ml to get a presence of alkaloids through Mayer's test and only the concentration of 500 mg dry weight ml-1. fruit extract showed Dragendroff's test positive. Saponins were found in root and fruits extract. Sterols The qualitative phytochemical tests for major were reported in all plant parts whereas resin, primary and secondary metabolites were performed as triterpenes and coumerins were found absent in all described by Trease and Evans (1983), Harborne (1998) methanolic extracts. Extract of leaf, root, fruit and seed and Thimmaiah (2004). show presence of flavonoids. Presence of tannins was found in stem, root and seed extract. Gelatin test was Results and discussion positive only in root extracts while lead acetate test was positive for stem, root and seed. Presence of cardiac glucosides was reported through Keller- Killiani test and In the present study, the phytochemical constituents of was positive for root, fruit and seed methanolic extracts. Moringa oleifera were sequentially extracted with solvents of different polarity. The results suggest that The presence of phytochemicals in ethyl acetate the aqueous, ethyl acetate and petroleum ether could extracts of M. oleifera. Only leaf and root extract showed extract more numbers of primary and secondary presence of protein. Among lipids, only presence of metabolites than the methanol. The various plant parts glycerol could be established in all extracts except fruit. (leaf, stem, root, fruit and seed) of M. oleifera varied in The seed extract also showed positive Sudan III test composition of primary and secondary metabolites. Table for lipids. For carbohydrates, all plant part showed 1 shows the presence of phytochemicals in aqueous positive results through Molisch's test and only leaf extracts of M. oleifera. Protein was completely absent showed additional positive Fehling's test (Table 3). in all five plant parts. Among lipids, only presence of Extract of leaf, root, fruit and seed showed glycerol could be found in fruit, seed and leaf aqueous presence of flavonoids. Tannin presence was found in extracts. The presence of carbohydrates in all plant part stem, root and seed extract. Gelatin test was positive was reported through Molisch's, Benedict's and only in root extracts while lead acetate test was positive Fehling's test. Only fruit and seed showed positive test for stem, root and seed. Leaf and seed extract showed for carbohydrates and these plant parts were found rich positive test for sterols. Alkaloid, saponins, flavonoids, sources for sugars. Molisch's test was found positive resins, tannins, cardiac glucosides, triterpenes and only in root extract. coumerins were found absent in all ethyl acetate Alkaloids were reported through Mayer's, extracts. Dragendroff's and Wagner's test. All these tests were The presence of phytochemicals in petroleum positive for seed extracts. Remaining plant parts showed ether extracts of different plant parts of M. oleifera. absence of alkaloids. Presence of saponins and sterols Protein was reported only in root extract through biuret were found in all plant parts' aqueous extracts whereas test and was completely absent in all remaining plant flavonoids, resins, triterpenes, coumerins and parts. Solubility test for lipids was positive for leaf and anthraquinones were found absent in all aqueous stem extracts. Presence of glycerol could be found in extracts. Among tannins, presence was found in all five extract of leaf and root while Sudan III test was positive parts through lead acetate test. Gelatin test was positive for leaf and stem. Only root extract showed positive with fruit aqueous extracts while ferric chloride test was result through Molisch's test for carbohydrates and for positive for root and fruit extracts. Presence of cardiac presence of flavonoids. Tannins, resins, cardiac glucosides was reported through Keller- Killiani test and glucosides, coumerins and anthraquinone were absent it was positive for fruit and root aqueous extract. in all plant part extracts. Presence of triterpenes could The presence of phytochemicals in methanolic be seen only in seed extract (Table 4). extracts of M. oleifera. Only seed extract showed This study established the presence of major presence of protein through xanthoprotic test. Protein phytochemicals which have been identified by other was completely absent in all remaining plant parts. researches in various plants and in different parts of Among lipids, only presence of glycerol could be plants (Benett et al. 2003, Hassan et al. 2007, Devbhuti established in extract of leaf, stem and root. Seed shows et al. 2009). Santos et al. (2005) discovered that extracts positive test for carbohydrates through Molisch's and obtained by water soaking of M. oleifera intact seeds Fehling test and fruit shows positive through Benedict's showed presence of tannin as well as antioxidant test (Table 2). activity. Similarly leaves of Moringa oleifera were shown
264 Table 1. Phyto-chemical screening of different part of Table 2. Phyto-chemical screening of different part of Munga (Moringa oleifera Lam.) aqueous extracts Munga (Moringa oleifera Lam.) methanolic extract
Qualitative test Aqueous extracts Qualitative test Methanol extract Leaf Stem Root Fruit Seed Leaf Stem Root Fruit Seed Alkaloids Alkaloids Mayer' test - - - - + Mayer' test - - + + + Dragendroff's - - - - + Dragendroff's - - - + - Wagner's test - - - - + Wagner's test - - - - - Carbohydrates Carbohydrate Molisch's test - - + + + Molisch's test - - - - + Benedict's test + - - + + Benedict's test - - - + - Fehling's test - - - + + Fehling's test - - - - + Protein Protein Xanthoprotic test - - - - - Xanthoprotic test - - - - + Biuret test - - - - - Biuret test - - - - - Lipids Lipids Solubility test - - - - - Solubility test - - - - - Glycerol test + - - + + Glycerol test + + + - - Sudan III test - - - - - Sudan III test - - - - - Saponins - Saponins - Foam test + + + + + Foam test - - + + - Flavinoids - - - - - Flavinoids + - + + + Resins - - - - - Resins - - - - - Tannins Tannins Gelatin test - - - + - Gelatin test - - + - - Lead acetate test + + + + + Lead acetate test - + + - + Ferric chloride test - - + + - Ferric chloride test - - - - - Sterols Sterols Salkowski's test + + + + + Salkowski's test + + + + + Liebermann's test + + + + + Liebermann's test + + + + + Cardiac glucosides Cardiac glucosides Keller-Killiani test - - - + + Keller-Killiani test - - + + + Triterpenes - - - - - Triterpenes - - - - - Coumerins - - - - - Coumerins - - - - - Anthraquinone + - - - - Anthraquinone - - - - -
+ = Phytochemical detected, - = Not detected + = Phytochemical detected, - = Not detected 265 Table 3. Phyto-chemical screening of different part of Table 4. Phyto-chemical screening of different part of Munga (Moringa oleifera Lam.) ethyl acetate extract Munga (Moringa oleifera Lam.) petroleum ether extracts
Qualitative test Ethyl acetate extract Qualitative test Petroleum ether extract Leaf Stem Root Fruit Seed Leaf Stem Root Fruit Seed Alkaloids Alkaloids Mayer' test - - - - - Mayer' test - - - - - Dragendroff's - - - - - Dragendroff's - - - - - Wagner's test - - - - - Wagner's test - - - - - Carbohydrate Carbohydrate Molisch's test + + + + + Molisch's test - - + - - Benedict's test - - - - - Benedict's test - - - - - Fehling's test + - - - - Fehling's test - - - - - Protein Protein Xanthoprotic test - - - - - Xanthoprotic test - - - - - Biuret test + - + - - Biuret test - - + - - Lipids Lipids Solubility test - - - - - Solubility test + + - - - Glycerol test + + + - + Glycerol test + - + - - Sudan III test - - - - + Sudan III test + + - - - Saponins - Saponins - Foam test - - - - - Foam test - - - - - Flavinoids - - - - - Flavinoids + - - - - Resins - - - - - Resins - - - - - Tannins Tannins Gelatin test - - - - - Gelatin test - - - - - Lead acetate test - - - - - Lead acetate test - - - - - Ferric chloride test - - - - - Ferric chloride test - - - - - Sterols Sterols Salkowski's test + - - + - Salkowski's test + - - - - Liebermann's test + - - - - Liebermann's test + - - - - Cardiac glucosides Cardiac glucosides Keller-Killiani test - - - - - Keller-Killiani test - - - - - Triterpenes - - - - - Triterpenes - - - - + Coumerins - - - - - Coumerins - - - - - Anthraquinone - - - - - Anthraquinone - - - - -
+ = Phytochemical detected, - = Not detected + = Phytochemical detected, - = Not detected 266 to contain kaempferol, which is a known phenolic group Brown (Coraceae). Acta Pol Pharm 64 : 183-185 phytochemical (Bajpai et al. 2005). Sultana et al. (2009) Bajpai M, Pande A, Tiwari S K (2005) Phenolic contents and investigated effects of four extracting solvents [absolute antioxidant activity of some food and medicinal ethanol, absolute methanol, aqueous ethanol (ethanol: plants. Int J Food Sci Nutri 56: 287-291 water, 80:20 v/v) and aqueous methanol (methanol: Bennett R, Mellon F, Pratt J, Dupont M, Pernins L, Kroon P water, 80:20 v/v)] and two extraction techniques (2003) Profiling glucosinolates and phenolics in (shaking and reflux) on the antioxidant activity of extracts vegetative and reproductive tissues of multipurpose of roots of Moringa oleifera along with other plants. The trees Moringa oleifera L. (Horseradish tree) and Moringa stenopetal L. J Agric Food Chem 51 : 3546- tested plant materials contained appreciable amounts 3553 of total phenolic contents and flavonoids. Singh et al. Caceres A, Saravia A, Rizzo S, Zabala L, De Leon E, Nave F (2009) investigated the aqueous extract of leaf, fruit and (1992) Pharmacologic properties of Moringa oleifera seed of Moringa oleifera. The HPLC and MS/MS 2: Screening for antispasmodic, anti inflammatory analysis showed the presence of gallic acid, chlorogenic and diuretic activity. J Ethnopharmacol 36 : 233-237 acid, ellagic acid, ferulic acid, kaempferol, quercetin and Devbhuti D, Gupta JK, Devbhuti P, Bose A (2009) vanillin. The leaf extract was with comparatively higher Phytochemical and acute toxicity study on Tinospora total phenolics content, flavonoids content and ascorbic tomentosa Miers. Acta Pol Pharm 66 : 89-92 acid content. Edeoga H O, Okwa D E, Mbaebie B O (2005) Phytochemical constituents of some Algerian medicinal plants. Afr Most of the earlier studies related to J Biotechnol 4 : 685-688 phytochemical screening from Moringa tree have Fahey J (2005) Moringa oleifera:A review of the medical concentrated either on one plant part i.e. seed or for evidence for its nutritional, therapeutic and the presence of certain phytochemicals only i.e. prophylactic properties, part I. Trees for life J 1:5 phenolic group compounds that possess antioxidant Foidl N, Makkar HPS, Becker K (2001) The potential of Moringa activity. The present study presents a comprehensive oleifera for agricultural and industrial uses. In: phytochemical screening of all major plant parts of a Proceedings of the international workshop "What common tree; Munga (Moringa oleifera Lam.) using development potential for Moringa products?" Dar- different solvents and thereby extracting most of the es-Salaam, Tanzania pp 47-67 phytochemicals. The findings in this study agree with Fuglie LJ (2001) The Miracle tree: The multiple attributes of earlier studies which found that not all phytochemicals Moringa, Church World Service, Dakar p 172 are present in all plant parts and that those present Harborne JB (1998) Phytochemical methods. Chapman and differ according to the type of the extracting solvents Hall, New York used (Ayinde et al. 2007). Hassan SW, Ladan MJ, Dogondaji RA, Umar RA, Bilbis LS, Massan LG, Ebbo AA, Matazu IK (2007). Phytochemical and toxicological studies of aqueous Acknowledgement leaves extracts of Erythrophleum africanum. Kak J Biol Sci 10 : 3815-3821 The authors are thankful to Dean, Faculty of life science Kalkar SA, Mishra A, Kshirsagar NV (2009) Phytochemical investigation of proteins and amino acids in pollen and Head, Department of Post Graduate Studies and grains of some members of family Cucurbitaceae. Research in Biological Science, Rani Durgawati The Botanique 13 (1): 74-77 University, Jabalpur for providing all facilities and Lockelt CT, Calvert CC, Grivetti LE (2000) Energy and encouragement. micronutrient comparison of dietary and medicinal wild plants consumed during drought. Study of rural Fulani, Northeastern Nigeria. Int J Food Sci Nutri References 51(3) : 195-208 Makkar H P S, Becker K (1997) Nutrients and antiquality Anwar FL, Ashraf M, Gilan A (2007) Moringa oleifera, a food factors in different morphological parts of the Moringa plant with multiple medicinal uses. Phytotherapy Res oleifera tree. J Agri Sci 128 : 311-322 21 : 17-25 Mdlolo CM, Shandu JS, Oyedeji OA (2008) Phytochemical Awoyinka OA, Balogun IO, Ogunnuwo AA (2007) constituents and antimicrobial studies of two South Phytochemical screening and in vitro bioactivity of African Phyllanthus species. Afri J Biotech 7(5) : 639- Cnidoscolus aconitifolius (Euphorbiaceae). J 643 Medicinal Plants Res 1(3) : 063-065 Santos AF, Argolo AC, Coelho LC, Paiva PM (2005) Detection Ayinde BA, Onwakaeme DN, Omogbai EKI (2007) Isolation of water soluble lectin and antioxidant component and characterization of two phenolic compounds from Moringa oleifera seeds. Water Res 39 (6) : from the stem bark of Musanga Cecropioides R. 975:980
267 Singh BN, Singh BR, Singh RL, Praksh D, Dhakarey R, Upadhyay G, Singh HB (2009) Oxidative DNA damage protective activity, antioxidant and anti- quorum sensing potentials of Moringa oleifera. Food Chem Toxicol 47(6) : 1109-1116 Sreelatha S, Padma PR (2009) Antioxidant activity and total phenolic content of Moringa oleifera leaves in two stages of maturity. Plant Food Human Nutri 64 : 303- 311 Sultana B, Anwar F, Ashraf M (2009) Effect of extraction solvent/technique on the antioxidant activity of selected medicinal plant extracts. Molecules 14 : 2167-2180 Thimmaiah SR (2004) Standard methods of biochemical analysis. Kalyani Publications, New Delhi Trease GE, Evans WC (1983) Pharmacognosy magazine. 12th ed. Bailliere Tindal, London, 622 pp
(Manuscript Receivd : 21.9.13; Accepted : 30.12.13)
268 JNKVV Res J 47(3): 269-273 (2013)
Multiple regression analysis a selection criteria for wheat improvement
Varsha Patil, P.K.Moitra and R.S.Shukla Department of Plant Breeding and Genetics Jawaharlal Nehru Krishi Vishwavidyalaya Jabalpur 482004 (MP)
Abstract realized that sustaining the productivity of wheat growing areas in existing cropping system and under Multiple regression analysis was carried out taking 40 climate change of country particularly in MP essential genotypes of wheat which are in seed production chain taking to provided food security to the population of India which seven important traits viz flag leaf length (X1), flag leaf width by the year 2020 A.D. will be 1.25 billion and thus the (X2), number of seeds/pike (X3), 1000 seed weight (X4), projected demand for wheat by the year 2020 A.D. will biological yield/plant (X5) and harvest index (X6) and spike be 95-109 million tones. length (X7) and seed yield/ plant (y). Multiple regression equations were construction taking 2,3,4,5,6 and all the seven Wheat is the world's second most important traits at a time. Relative construction in predicting yield/plant staple food crop and contributes to the extent of about was calculated for each situation. Among individual traits 27% of the total food grain production. The productivity biological yield/plant (X5) and harvest index (X6) contributed of wheat in M.P. is low (2.7) in comparison of productivity 47.60 and 49.70% respectively in predicting yield/plant. Among at national level (3.1 tones/ha. (Anonymous 2012) two character combination biological yield/plant (X5 & X6) and harvest index was the best combinations which predicted Yield is a quantitatively inherited complex trait 98.20% variation in yield. Among 3 characters flag leaf breadth which is governed by polygenes, with very minute effect (X2), biological yield/plant (X5) & harvest index (X6) contributed and as such governed by environment effect. In order 98.20% in yield prediction. Hence it can be concluded that to improve wheat yield it is essential to know the relative biological yield/plant (X5) and harvest index (X6) percent are contribution of yield component characters viz, 1000 the most important traits, since these traits has positive seed weight, biological yield/plant, number of seeds/ significant correlation with yield high heritability values. Hence spike, spike length, flag leaf length and flag leaf breadth. due emphasis should be given to biological yield/plant and Morphological features of seed and plant parts are the harvest index while selecting genotypes for wheat major components of identification of cultivar. The improvement. success of wheat breeding programme depends up on the magnitude and nature of genetic variability in the Keywords: Multiple regression analysis, correlation, desired direction is the prerequisite for planning any heritability, coefficient of determination, additive gene successful and effective crop improvement programme. action. In order to judge the role of yield components biometrical studies such as correlation analysis and path analysis is practiced. Wheat (Triticm aestivum L.) is grown under wide range of climatic condition but the favorable one adapted for Expressed correlation is due to linkage of genes growing in cool and dry environment. It is staple food or pleiotropic effect and it expresses nature of for nearly 40 per cent of world population covering at association between variables. However, regression least, 43 countries and provides 20 per cent of food analysis measure changes in dependent variable due calories to the mankind. India is maintaining its second to unit change in independent variable (yield position of wheat producing nations since last 10 years components). In the present study multiple regression and continuous record breaking wheat harvest to the equation considering taking yield as dependent variable tune of 93 million tones during 2011-12 crop seasons and set of independent yield contributing traits could from 29.3 million ha (Anonymous 2012). It is now explain the total variation in yield. Individual contribution
269 towards yield is also expressed taking single character & harvest index (X6) followed by flag leaf length (X1) at a time. Any multiple regression equation for set of and biological yield/plant (X5), flag leaf breadth (X2) independent traits is more effective which can explain and harvest index (X6), 1000 seed weight (X4) and higher percentage of variation in plant yield of wheat. biological yield (X5) and number of seeds/pike (X3) and Hence present investigation was under taken to harvest index (X6). It is evident from two character determine relative contribution of set of independent combinations that the value of expressed variability in traits through multiple regression analysis. seed yield was higher when ever one of the character out of two was harvest index (X6) or biological yield/ plant (X5). When harvest index and biological yield/ Material and methods plant were considered alone were able to express 49.70 and 47.60 percent of variation in seed yield respectively Forty wheat varieties in seed production chain and some which was maximum among all traits when single promosing lines were used as planting material character was taken into account. experiment was carried out at Wheat Improvement Project at seed breeding farm, College of Agriculture, Among three traits combinations flag leaf length Jabalpur (MP) during rabi 2010-2011 in randomized (X1) biological yield /plant (X5) & harvest index (X6) block design with three replications under irrigated 98.20%, flag leaf breadth (X2), biological yield/plant (X5) timely sown condition. The recommended package of and harvest index (X6) 98.20% and number of seeds/ practices was followed to raise the good crop. spike (X3) biological yield/plant (X5) and harvest index Observations were recorded on ten randomly selected (X6) 98.20% were the best combinations in explaining competitive plants for Flag leaf length (X1), flag leaf total variability in seed yield/plant. breadth (X2) number of seeds per spike (X3), 1000 seed A total of twenty five multiple regression weight (X4), biological yield/ plant (X5) harvest index equations taking four characters together were (X6) and spike length (X7) and seed yield/ plant (y). constructed. The best combination was 1000 seed The data were analyzed to workout multiple regression weight (X4), coupled with biological yield/plant (X5), analysis as per method suggested by Panse and harvest index (X6) and spike length (X7) which explains Sukhatme (1967) 98.20% variability in seed yield/plant. Other four character combinations flag leaf breadth (X2) 1000 seed Result and discussions weight (X4), biological yield/plant (X5), harvest index (X6) and spike length (X7), number of seeds/spike (X3), 1000 seed weighs (X4), biological yield/plant (X5) and Analysis of variance for all the traits under study harvest index (X6), all of them were able to express revealed men square due to genotypes were highly 98.30% of total variation in yield. significant for all the traits indicating presence of sufficient genetic variability in material used under study. Among five character combination flag leaf breadth (X2) 1000 seed weight (X4), biological yield/ Multiple regression analysis was carried out plant (X5), harvest index (X6) and spike length (X7) taking yield/plant as dependent variable and all other and number of seeds/spike (X3), 1000 seed wt (X4), characters as independent variables. Multiple biological yield/plant (X5), harvest index (X6) and spike regression analysis has become one of the most widely length (X7) were best able to express 98.40% of used statistical tools for analyzing functional relationship variation in yield/plant. There was no further increased among variables, which is expressed in the form of in prediction power for 6 and all 7 characters considered equations connecting dependent variable and one and together in construction of multiple regression equation. more independent variable (Table -1). Multiple regression equations were constructed taking 2,3,4,5 and 6 It is clear that biological yield/plant (X5) and character combinations together. harvest index (X6) were the most important traits in explaining the variation in seed yield, which clearly Among various two characters (21 combinations) suggests that where ever biological yield/plant (X5) and combination relative contribution towards yield/plant harvest index (X6) were included in equation it resulted ranged from 7.40 to 98.20 percent. The best two in increased value of coefficient of determination. These character combination was biological yield/plant (X5) and harvest index (X6) which accounted for 98.20 finding are in agreement with findings of Batter et al percent of total variation in seed yield/plant. Other (1984), Budak and yildirim (1995) and Rastogi (1997) combinations among two character combinations which also reported that these two traits viz biological yield/ were next to best combination were 1000 seed wt (X4) plant and harvest index shall be given due importance 270 6.10 19.20 49.70 12.10 57.20 11.60 20.00 55.70 25.20 50.50 51.40 19.70 47.70 27.80 56.50 30.30 50.50 60.20 30.50 59.10 25.50 56.20 51.70 21.20 47.80 53.50 27.20 49.50 98.30 58.60 to yield to Relative per plant per contribution R 0.248 0.439 0.705 0.348 0.756 0.340 0.447 0.747 0.502 0.710 0.717 0.443 0.691 0.527 0.751 0.550 0.710 0.776 0.553 0.769 0.505 0.749 0.719 0.461 0.691 0.732 0.521 0.703 0.991 0.766 Equations Y=54.906+54.500x2 Y=18.458+2.771x4 Y=-0.426+3.334x6 Y=36.451+2.256x1+0.546x3 Y=-66.861+2.464x1+0.395x5 Y=71.479+2.852x1-1.529x7 Y=-0.149+20.286x2+2.546x4 Y=-74.176+54.311x2+3.333x6 Y=-48.615+1.040x3+2.852x4 Y=-20.934+0.386x3+3.252x6 Y=-41.839+1.332x4+0.354x5 Y=26.676+2.845x4-1.002x7 Y=0.981+0.401x5-0.463x7 2.653x4 Y=-35.009+2.362x1-2.668x2+ +3.547x6 Y=-71.379-0.807x1+61.650x2 +2.708x4 Y=-71.811+1.892x1+0.705x3 +3.281x6 Y=-19.875-0.122x1+0.402x3 +0.355x5 Y=-97.921+2.361x1+1.181x4 -2.636x7 Y=-25.375+2.765x1+2.795x4 -2.154x7 Y=-53.858+2.829x1+0.400x5 +2.710x4 Y=-58.301+12.683x2+1.010x3 +3.274x6 Y=-86.909+52.829x2+0.278x3 +0.362x5 Y=-31.852-12.295x2+1.437x4 -1.901x7 Y=3.686+33.103x2+2.546x4 -0.678x7 Y=-4.472+7.268x2+0.394x5 +0.337x5 Y=-79.048+0.621x3+1.449x4 -2.193x7 Y=-41.563+1.210x3+3.029x4 -0.986x7 Y=-25.556+0.586x3+0.390x5 +3.329x6 Y=-140.682+0.223x4+0.386x5 Y=-59.763+1.964x4+3.023x6-0.618x7 02 04 06 02 04 06 08 10 12 14 16 18 20 02 04 06 08 10 12 14 16 18 20 22 24 26 28 30 32 34 S. No. S. Two character combinations character Two Three character combinations character Three 4.90 9.00 7.40 10.60 47.60 12.80 27.80 49.70 10.00 47.60 49.00 51.00 58.40 98.20 49.70 14.30 58.30 15.70 57.30 13.60 58.50 98.20 49.70 49.00 12.80 60.40 98.20 57.00 59.80 98.20 50.50 51.80 98.30 to yield to Relative per plant per contribution R 0.326 0.222 0.690 0.267 0.358 0.527 0.705 0.317 0.690 0.272 0.700 0.227 0.764 0.991 0.705 0.379 0.763 0.396 0.757 0.368 0.765 0.991 0.705 0.700 0.358 0.777 0.991 0.755 0.774 0.991 0.710 0.720 0.991 Multiple Multiple regression equations multiple correlation coefficients relative contribution of important traits to express variation in in yield/plant Equations Y=61.199+2.591x1 Y=71.325+0.94x3 Y=-3.818+0.399x5 Y=126.988+0.177x7 Y=24.875+2.180x1+34.647x2 Y=-36.771+2.333x1+2.626x4 Y=-2.112+0.107x1+3.306x6 Y=9.462+50.002x2+0.840x3 Y=-6.276+2.326x2+0.397x5 Y=58.738+67.331x2-1.904x7 Y=-31.826+0.513x3+0.389x5 Y=76.209+0.995x3-0.740x7 Y=-65.055+1.915x4+0.031x6 Y=-135.725+0.403x5+3.365x6 Y=-2.635+3.334x6+0.197x7 0.550x3 Y=-0.176+1.841x1+34.790x2+ +0.418x5 Y=-47.462+2.760x1-25.510x2 -2.893x7 Y=26.674+2.472x1+51.485x2 +0.394x5 Y=-70.301+2.411x1+8.816x3 -1.926x7 Y=45.020+2.525x1+0.643x3 +2.989x6 Y=-67.594+0.156x1+1.918x4 +3.388x6 Y=-134.437-8.512x1+0.404x5 +0.153x7 Y=-3.309+7.403x1+3.314x6 +0.388x5 Y=-32.601+0.773x2+0.513x3 -2.877x7 Y=5.643+68.437x2+1.019x3 +3.092x6 Y=-97.795+33.858x2+1.523x4 +3.365x6 Y=-137.333+1.527x2+0.402x5 -1.871x7 Y=-70.352+66.921x2+3.331x6 +2.910x6 Y=-94.900+0.515x3+1.990x4 +3.382x6 Y=-132.042-7.978x3+0.405x5 -0.171x7 Y=-19.720+0.399x3+3.249x6 -0.970x7 Y=-33.856+1.405x4+0.354x5 -0.448x7 Y=-131.066+0.404x5+3.365x6 Table 1. Table wheat S.No. 01 03 05 07 01 03 05 07 09 11 13 15 17 19 21 01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 31 33 35
271 58.30 18.20 59.90 62.70 30.80 61.40 98.20 98.30 98.30 98.30 98.30 98.30 61.90 98.20 98.30 98.30 58.60 98.30 54.70 98.30 98.40 63.60 to yield to Relative per plant per contribution R 0.763 0.427 0.774 0.792 0.555 0.784 0.991 0.991 0.992 0.992 0.991 0.991 0.787 0.991 0.991 0.992 0.765 0.992 0.740 0.992 0.992 0.797 +0.207x4 +0.397x5+3.344x6 +0.207x4 Equations +5.888x3+0.417x5 Y=-49.916+2.722x1-25.304x2 +0.724x3-3.428x7 Y=-5.977+2.080x1+54.784x2 +1.991x4+2.944x6 Y=-93.668-0.145x1+0.534x3 +1.506x4+0.381x5 Y=-75.036+2.812x1-41.354x2 +2.667x4-2.967x7 Y=-33.461+2.663x1+14.412x2 +1.628x4+2.984x6 Y=-119.113+30.153x2+0.429x3 +0.403x5-3.383x6 Y=-133.821+1.770x2-8.160x3 +0.396x5+3.328x6 Y=-139.995-0.806x2+0.230x4 +3.364x6-0.629x7 Y=-135.629+6.117x2+0.399x5 Y=-137.667-5.770x3 -0.405x7+3.376x6 Y=-129.265-4.883x3+0.405x5 +3.376x6+0.405x5 Y=-129.265-4.883x3-0.405x7 0.502x3+1.549 Y=-118.838-0.688x1+37.083x2 x4+3.165x6 -7.135x3+0.403 Y=-133.886-8.222x1+2.863x2 x5+3.402x6 +0.220x4+0.396 Y=-139.530-7.675x1+6.304x2 x5+3.350x6 +0.208x4+0.397 Y=-137.255-4.779x1-5.121x3 x5+3.356x6 +0.504x3+3.444x6-2.020x7 Y=-90.283-0.827x1+72.752x2 +0.399x5+3.377x6-0.611x7 Y=-135.458-4.861x1+6.467x2 +0.756x4+0.337x5-1.578x7 Y=-70.017-5.096x2-5.121x3 +0.400x5+3.373x6-0.587x7 Y=-133.979+5.932x22-4.101x3 +0.396x5+3.325x6-0.534x7 Y=-135.506-1.104x3+0.262x4 +0.627x3+1.615x4+3.060 Y=-121.743-0.441x1+48.750x2 -2.294x7 x6 02 04 06 08 10 12 14 16 18 20 22 24 02 04 06 08 10 12 14 16 18 02 S. No. S. Six character combinations character Six Five character combinations character Five Four character combinations character Four 30.30 57.20 60.40 34.20 60.60 53.90 28.60 49.60 51.90 57.90 54.70 60.50 98.40 62.90 34.60 59.50 64.00 63.60 61.70 98.30 63.40 98.40 64.50 98.40 98.40 to yield to Seven character combinations character Seven Relative per plant per contribution R 0.550 0.757 0.777 0.585 0.779 0.734 0.535 0.704 0.720 0.761 0.740 0.778 0.992 0.793 0.588 0.771 0.800 0.797 0.786 0.992 0.796 0.992 0.803 0.992 0.992 Equations +0.707x3+2.748x4 Y=69.388+1.933x1-3.818x2 +0.398x3+3.523x6 Y=-88.843-1.032x1+6.567x2 +1.229x4+0.349x5 Y=-107.449+2.228x1+0.212x3 +2.937x4-3.236x7 Y=-66.557+2.313x1+0.881x3 +1.463x4+3.215x6 Y=-95.383-0.427x1+38.548x2 +1.589x4+0.346x5 Y=-67.798-15.797x2+0.648x3 +2.740x4-3.047x7 Y=-63.101+31.797x2+1.200x3 +0.381x5-1.290x7 Y=-33.560+9.923x2+0.598x3 +0.358x5-0.789x7 Y=-29.944-6.648x2+1.448x4 +3.241x6-2.277x7 Y=-88.965+67.392x2+0.424x3 +0.333x5-1.720x7 Y=-73.162+0.759x3+1.604x4 +2.869x6+2.102x4 Y=-90.246+0.618x3-1.247x7 -3.322x6-0.545x7 Y=-135.986+0.266x4+0.396x5 +0.196x3+1.549 Y=-84.002+2.686x1-41.116x2 x4+0.375x5 +0.894x3+2.790 Y=-76.566+2.187x1+16.778x2 x4-3.630x7 -0.168x3+0.407 Y=-52.087+2.837x1-12.695x2 x5-1.934x7 +1.538x4+0.373 Y=-73.227+3.00x1-29.401x2 x5-1.943x7 +1.452x4+0.345 Y=-102.310+2.597x1+0.374x3 x5-2.874x7 +1.498x4+3.143 Y=-93.093-0.182x1+47.977x2 x6-1.798x7 +0.211x40.398 Y=-137.334-0.447x2-5.679x3 x5+3.343x6 +1.668x4+2.942 x3 Y=-122.093+45.187x2+0.590 x6-2.436x7 +0.393x5+3.326x Y=-138.353+3.824x2+0.240x4 6-0.648x7 +0.327x3+1.613x4+ Y=-87.901+2.817x1-27.342x2 -2.213x7 0.363x5 +0.237x4+0.393x5+ Y=-137.924+3.813x2-9.717x3 -0.638x7 3.329x6 -1.104x3+0.238x4+0.394 Y=-137.938+1.437x1+3.689x2 +3.325x6-0.642x7 x5 S.No. 01 03 05 07 09 11 13 15 17 19 21 23 25 01 03 05 07 09 11 13 15 17 01 03 01
272 while selecting genotypes for wheat improvement. These two traits also showed highly positive significant correlation with yield/plant, high positive direct effect from path analysis was maximum for harvest index and biological yield/plant. These two character also exhibited high broad sense heritability estimates which indicates that due emphasis should be given for wheat improvement as these traits are governed by additive gene action.
References
Anonymous (2012) Project Directorate Report, DWR, Karnal p 3 Batten GD, Khan MA, Cullis BR (1984) Yield responses by modern wheat genotypes to phosphate fertilizer and their implication for breeding. Euphytica 33 (1): 81- 89 Budak N, Yildirim MB (1995). Harvest index, biomass production and their relationships with grain yield in wheat. Ege universities Ziraat Fakultesi Dergisi 33 (2): 25-28 Panse VG, Sukhatme PV (1667) Stastical method for agricultural workers. ICAR publication 152-161 Rastogi NK (1997) Multiple regression analysis as screening tool for yield improvement in wheat. Advances in plant sciences 10 (2): 211-213
(Manuscript Receivd : 30.8.13; Accepted : 30.12.13)
273 JNKVV Res J 47(3): 274-277 (2013)
Association analysis studies in indigenous and exotic germplasm lines of rice
Pankaj Nagle, S. K. Rao, G. K. Koutu and Priya Nair Department of Plant Breeding and Genetics Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP) Email : [email protected]
Abstract provides better understanding of yield and its components and its association with each other. Based on these important aspects, the present study was Rice is the staple food crop of India, providing 43% of caloric requirement for more than 70% Indian population. The success undertaken to estimate association amongst seed yield of any crop improvement programme depends on nature and and its various attributing traits. magnitude of genetic variability, heritability, genetic advance, characters associations of yield and its component traits. Material and methods Association analysis study provide better understanding of yield components and furnishes information of influence of each contributing trait to yield directly as well as indirectly The material used in the present study comprised of 71 and also enables breeders to rank the genetic attributes exogenous and 9 indigenous lines (Table1) received from according to their contribution. The estimates of coefficient IRRI, Philippines under the project INGER. The of correlation revealed the highest significant positive correlation of grain yield plant-1 was obtained with biological experiment was carried out at Seed Breeding Farm, yield plant-1, harvest index, number of grains panicle-1, number Department of Plant Breeding and Genetics, College of filled grains panicle-1, panicle length, panicle index and of Agriculture, JNKVV, Jabalpur (M.P.) in randomized spikelet density. Positive association of these traits with grain complete block design with three replications. The yield plant-1 revealed that these characters can be used as observations was recorded on fifteen quantitative traits architecture for yield improvement. viz., plant height (cm), panicle length (cm), panicle weight plant-1 (g), number of tillers plant-1, number of -1 Germplasm characterization, correlation effective tillers plant , 1000 grain weight (g), number of Keywords: -1 - analysis, Oryza sativa filled grains panicle , number of unfilled grains panicle 1, number of grains panicle-1, spikelet density, days to 50 % per cent flowering, biological yield plant-1 (g), grain Rice (Oryza sativa L.) is the staple food crop of India, yield plant-1 (g), harvest index (%) and panicle index. providing 43% of caloric requirement for more than 70% Indian population. The success of any crop improvement Correlation coefficients were calculated for all programme depends on nature and magnitude of quantitative characters combinations at phenotypic, genetic variability, heritability, genetic advance, genotypic and environmental level by the formula given characters association, direct and indirect effects on by Miller et al. (1958). yield and its attributing traits of the genotypes. Yield of paddy is a complex quantitative character controlled Result and discussion by many genes interacting with the environment and is the product of many factors called yield components. Selection of parents based on yield alone is often The development of a high yielding genotype through misleading. Hence, the knowledge about relationship rice breeding which is an autogamic species requires a between yield and its contributing characters is needed thorough knowledge of the association of yield for an efficient selection strategy for the plant breeders components. Grain yield in rice is a complex character, to evolve an economic variety. Association analysis quantitative in nature and an integrated function of a 274 number of component traits. Therefore, selection for yield per se may not be much rewarding unless yield components are taken into consideration.
Correlation coefficient analysis
The correlation coefficient estimates the degree and direction of association between a pair of characters and helps simultaneous improvement of the correlated traits through selection. High magnitude of positive correlation coefficient at genotypic level indicates strong linkage at genetic level, but high values at phenotypic
Name of Germplasm IR 73885-1-4-3-2-1-6 9) (MATATAG 81330-19-2-1-3 IR BONDOYUDO 80694-44-1-2-2 IR 78091-120-3-2-2-3 IR 79482-106-2-2-1 IR CIMELATI 79247-107-1-2-1 IR 81173-33-1-2-3 IR 76939-98-1-1-1 IR 158) 71186-122-2-2-3 (NSICRC IR CELEBES IR 5900 OM Balaghat Shankar Jeera Ramker Peeso Kaketi Pandri Bindu Urai level may not always show strong association and it may be broken up with change in environment. The
S.No. 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 estimates of genetic correlation coefficients along with phenotypic ones, also gives a clear picture of the extent of inherent association and also indicates to what extent the phenotypic correlation coefficients are influenced by the environment. The results of correlation coefficients revealed the characters viz., days to 50 % flowering and number of unfilled grains panicle-1 showed no correlation with grain yield plant-1(Table 2). The characters viz., plant height,; panicle length, number of tillers plant-1, number of effective tillers plant-1, number of filled grains panicle- 1, number of grains panicle-1, 1000 grain weight, spikelet -1 Name of Germplasm 79253-55-1-4-6 IR 81350-95-2-1-2 IR 77542-167-1-1-1-1-3 IR 80914-6-3-1-2 IR 79253-19-3-3-5 IR 79193-83-1-1-1 IR 82355-5-2-3 IR 75386-14-3-2-2 IR 80397-87-1-2-3 IR 28) 56381-139-2-2 RC IR (PSB 78119-24-1-2-2-2 IR 76993-49-1-1 IR 5625 OM IR 74284-10-1-2-3-2 IR 81373-119-2-2-1 IR GADIS BATANG 78555-68-3-3-3 IR 81174-125-2-3-1 IR 5935 OM IR 81173-64-2-1-2 IR density, biological yield plant , harvest index , panicle index and spikelet fertility % had significant positive associations with grain yield plant-1.These results were S.No. 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 in conformity with the results of Basavaraja et al. (1997), Kumar et al. (1998), Samonte et al. (1998), Bagali et al. (1999), Gupta et al. (1999), Bastian et al. (2000), Rao (2000), Tomar et al. (2000), Nayak et al. (2001), Babu et al. (2002), Islam et al. (2002), Samo et al. (2002), Chaudhary and Motiramani (2003), Chand et al.(2004),Tyagi et al. (2004), Madhavilatha et al. (2005b), Satyanarayana et al. (2005), Shashidhar et al. (2005), Vaithiyalingan and Nadarajan (2005), Name of Germplasm 77498-127-3-2-3-2 IR 5636 OM 82355-9-1-2 IR 80692-64-3-2-1 IR 81350-9-3-3-3 IR 80922-3-2-2-3 IR 79532-21-2-2-1 IR 72906-32-1-3-3 IR 81852-120-2-1-3 IR 81890-26-3-3-1 IR 78545-49-2-2-2 IR SUNGGAL 7954-65-1-3-2 IR 79648-35-2-1-1 IR 73004-3-1-2-1 IR 75288-38-3-1 IR 79854-382-1-4 IR 79089-149-2-3-3-3 IR 79643-39-2-2-3 IR 78091-6-2-3-1-1 IR Gazafrodi et al. (2006), Muthuswamy and Ananda Kumar (2006b), Agahi et al. (2007), Khan et al. (2009), S.No. 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Sabu et al.( 2009) and Chakraborty et al. (2010).Spikelet sterility % showed a very low negative association.
gekjk ns'k ,d —f"k iz/kku ns'k gS A gekjs ns'k dh 70% vkcknh vius 43% Å"ek mko';drk dh iwfrZ ds fy, bl Qly ij fuHkZj gS A fdlh Hkh Qly ds mUufrdj.k dk;ZØe esa ml Qly esa ikbZ tkus okyk vkuqokaf'kd fofo/kRrk] vkuqokaf'kd fodkl dk egRoiw.kZ ;ksxnku Germplasms used in study Germplasms in used gksrk gS A Name of Germplasm 5936 OM KONAWE 64 IR ANGKE 77542-127-1-1-1-1-2 IR 71677-161-2-3 IR IR-50 80914-8-3-2-1 IR 80909-8-2-2-3 IR 77504-36-3-3 IR 68 PSBRC Local201CheckJR 81171-42-1-2-3 IR 78585-98-2-2-1 IR 72176-307-4-2-2-3 IR 79088-36-1-1-3-2 IR 72 IR 76928-74-3-2-1 IR 81166-60-3-1-2 IR 77542-234-1-1 IR lglac/k fo'ys"k.k ,oa i; xq.kkad ,slh egRoiw.kZ i)fr gS ftuds }kjk Table 1. Table S.No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
275 GW 0.1708 0.1489* 0.1033 0.0823 0.0625 0.0543 0.0563 0.0433 0.1406 0.1194 0.2574 1.000 1.000 -0.590 -0.0453 -0.4640 -0.4289 -0.0415 -0.0342 -0.2887 -0.1129 -0.0915 -0.2632 -0.1785 -0.1188 0.2195** -0.3250** -0.3246** -0.2224** -0.2241** 0.0611 0.0618 0.8752 0.7818** 0.2944 0.2510** 0.8707 0.7760** 0.1944 0.1819** 0.1294 0.1153 0.2161 0.1970** 0.0462 0.0431 1.000 1.000 SD% -0.1454 -0.1415* -0.0731 -0.0689 -0.0998 -0.0277 -0.0732 -0.0151 -0.0436 -0.0402 SS% 0.3604 0.3392** 0.2303 0.2172** 0.2034 0.1834** 0.1892 0.1463* 0.1977 0.1567* 0.9296 0.8464** 0.0910 0.0843 0.2253 0.2100** 1.000 1.000 -0.1670 -0.1615* -0.0508 -0.0442 -0.1399 -0.1357* -1.000 -0.2991** SF% 0.1556* 0.1686 0.1632* 0.0466 0.1385 0.1343* 1.000 1.000 -0.3647 -0.1445** -0.2308 -0.2183** -0.2059 -0.1851** -0.1879 -0.1451* -0.1964 -0.2298 -0.2468** -0.0896 -0.0829 -0.2277 -0.2124** -0.0540 PI% 0.0111 0.0100 0.1056 0.1028 0.1951 0.1920** 0.1609 0.1580* 1.000 1.000 -0.0157 -0.0137 -0.4585 -0.3662** -0.4585 -0.3782** -0.0617 -0.0577 -0.2566 -0.2467** -0.4746 -0.2397** HI% 0.0002 0.0087 0.0338 0.0284 0.0338 0.0369 0.0219 0.0214 1.000 1.000 -0.2059 -0.1873** -0.2951 -0.2556** -0.1577 -0.1000 -0.0334 -0.0442 -0.4054 -0.4045** BY/P 0.1586 0.1523* 0.4791 0.4440** 0.5047 0.4461** 0.2680 0.2556** 0.2572** 0.2391** 0.3898 0.3705** 0.3767 0.3393** 0.4518 0.4278** 1.000 1.000 NG/P 0.0018 0.2895 0.2736** 0.4695 0.4344** 0.9672 0.9640** 0.4699 0.4680** 1.000 1.000 -0.0027 -0.0578 -0.0412 -0.0480 -0.0282 0.3114 0.2759** 0.3591 0.3240** 0.3894 0.3394** 0.1148 0.0831 0.1157 0.0977 0.2304 0.2161** 1.000 1.000 NUFG/P 0.2159 0.2048** 0.4056 0.3778** 1.000 1.000 NFG/P -0.0876 -0.0860 -0.0967 -0.0706 -0.0862 -0.0606 -.0201 0.0637 0.0433 1.0029 0.9682** 1.000 1.000 -0.1788 -0.1223 -0.0555 NOET/P 0.0545 0.0072 1.000 1.000 NOT/P -0.0357 -0.1830 -0.1213 -0.0251 PL 0.2651 0.2488** 0.4550 0.4208** 1.000 1.000 PH 1.000 1.000 -0.306 -0.0295 1.000 1.000 D50%F G P G P G P G P G P G P G P G P G P G P G P G P G P G P G P Genotypic Genotypic (G) and (P)Phenotypic correlation for morphological and floral traits of germplasm lines of rice Table 2. Table D50%F PH PL NOT/P NOET/P NFG/P NUFG/P NG/P BY/P HI% PI% SF% SS% SD% GW * Significant at 5 per cent ** Significant at 1 per cent
276 ge mit ij izR;{k ,oa vizR;{k vlj Mkyus okys xq.kksa dk v/;;'u set of rice genotypes assessed over sowing dates. J of Agric Sci 15(1):61 - 66 djrs gS ,oa mu dkjdksa dk cks/k djrs gS ftuds }kjk vit c<+kbZ tk Khan S, Imran AM, Ashfaq M (2009) Estimation of genetic ldrh gS A variability and correlation for grain yield components in rice (Oryza sativa L.). American-Eurasian J Agric iFk xq.kkad fo'ys"k.k ls ;g Kkr gksrk gS fd cht mit izfr ikS/kk Environ Sci 6 (5):585 - 590 tSfod mit izfr ikS/kk] iSnkokj lwphdkad] Hkjs nkus izfr iq"i xqPN] Kumar GS, Mahadevappa M, Rudraradhya M (1998) Studies on genetic variability, correlation and path analysis nkus izfr iq"i&xqPN] iq"i xqPN lwpdkad dqN ,ls dkjd gS gks mit in rice during winter across the locations. Karnataka ij vfr egkRoiw.k ,oa ldkjkRed izHkko Mkyrs gS A vr% bl lQy Agric Sci J 11 (1):73 - 77 mUufrdj.k dk;ZØe esa bu dkjdksa vFkok xq.kksa dk n{krk ls iz;ksx dj Madhavilatha L, Sekhar MR, Suneetha Y, Srinivas T (2005b) Genetic variability, correlation and path analysis for ge /kku mit dks c<+k ldys gS A yield and quality traits in rice (Oryza sativa L.). Res on Crops 6 (3):527 - 534 Muthuswamy A, Ananda Kumar CR (2006b) Correlation and References path analysis among the drought resistant rice cultures. Res. on Crops 7 (1):133 - 136 Agahi K, Farshadfar E, Fotokian MH (2007) Correlation and Nayak AR, Chaudhury D, Reddy JN (2001) Correlation and path coefficient analysis for some yield-related traits path analysis in scented rice. Indian J Agric Res in rice genotypes (Oryza sativa L.). Asian J Plant 35:190 - 193 Sci 6 (3):513 - 517 Rao SS (2000) Estimation of grain yield and inter-relationship Babu S, Netaji SVRK, Philip B, Rangasam P (2002) with yield components in upland rice. Mysore J Agri Intercorrelation and path coefficient analysis in rice Sci 34 (2):142 - 146 (Oryza sativa L.). Res on Crops 3 (1):67 - 71 Sabu KK, Abdullah MZ, LS Lim, Wickneswari R (2009) Bagali G, Hittalmani S, Shashidhar HE (1999) Character Analysis of heritability and genetic variability of association and path coefficient analysis in indica x agronomically important traits in Oryza sativa x O. japonica doubled haploid population of rice. Oryza rufipogon cross. Agro Res 7(1):97 - 102 36:10 - 12. Samo MA, Oad FC, Zia-ul-Hassan, Pompesta, Cruz and Oad Basavaraja P, Rudraradhya M, Kulkarni RS (1997) Genetic NL (2002. Correlation and Path Analysis of variability, correlation and path analysis of yield Quantitative Characters of Rice Ratoon Cultivars and components in two F4 populations of fine grained Advance Lines. Int J Agri Biol 4 (2): 204 - 207 rice. Mysore J Agric Sci 31:1 - 6 Samonte SOPB, Wilson LT, Mc Clung AM (1998). Path Bastian D, Rangasamy P, Sakila M, Backiyarani S (2000) analysis of yield and yield related traits of fifteen Correlation studies in rice. Res on Crops 1(2):261 - diverse rice genotypes. Crop Sci 38: 1130 - 1136 262 Satyanarayana PV, Srinivas T, Reddy RP, Madhavilatha L, Chakraborty R, Chakraborty S (2010) Genetic variability and Suneetha Y (2005) Studies on variability, correlation correlation of some morphometric traits with grain and path coefficient analysis for restorer lines in rice yield in bold grained rice (Oryza sativa L.) gene pool (Oryza sativa L.). Res on Crops 6(1): 80 - 84 of Barak valley. American- Eurasian J Sustain Agric Shashidhar HE, Pasha F, Janamatti, Vinod MM, Kanbar S 4(1): 26-29 (2005) Correlation and path coefficient analysis in Chand SP, Roy SK, Mondal GS, Mahato PD, Panda S, Sarkar traditional cultivar and doubled haploid lines of G, Senapati BK (2004) Genetic variability and rainfed lowland rice (Oryza sativa L.). Oryza 42: 156 character association in rainfed lowland Aman paddy - 158 (Oryza sativa L.). Environment and Ecology 22 (2): Tomar JB, Dabas BS, PL Gautam (2000) Genetic variability, 430 - 434 correlation coefficient and path analysis for Chaudhary M, Motiramani NK (2003) Variability and quantitative characters under rainfed ecosystem in association among yield attributes and grain quality the native land races of rice. Indian J Pl Genet Resour in traditional aromatic rice accessions. Crop Improv 13 (3): 229 - 246 30 (1): 84 - 89 Tyagi K, Kumar B, Ramesh B, Tomar A (2004) Genetic Gazafrodi A, Honarnegad AR, Fotokian MH, Alami A (2006) variability and correlations for some seedlings and Study of correlations among agronomic traits and mature plant traits in 70 genotypes of rice. Res on path analysis in rice (Oryza sativa L.). J Sci and Crops 5 (1): 60 - 65 Technol Agric Nature Resour 10 (2):107 - 110 Vaithiyalingan M, Nadarajan N (2005) Correlation and path Gupta A, Sharma RK, Mani VP, Chauhan VS (1999) Pattern analysis in inter sub-specific rice hybrids. Res on of genetic diversity and variability in rice germplasm Crops 6 (2):287 - 289 of U. P. hills. Crop Improv 26: 81 - 87 Islam A, Duara PK, Barua PK (2002) Genetic variability in a (Manuscript Receivd : 10.9.13; Accepted : 5.12.13)
277 JNKVV Res J 47(3): 278-283 (2013)
Influence of zinc application on yield attributes, yield, chemical composition and protein content of wheat grown on Typic Haplustert of Kymore plateau, Madhya Pradesh
K. S. Keram and B. L. Sharma Department of Soil Science and Agricultural Chemistry Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract use of old technology like unawareness about the application of balanced micro and macro-nutrients are more effective in terms of getting maximum yield and A field experiment was conducted for two successive years on a Typic Haplustert at the Research Farm of Department of reduce losses. But the average yield of wheat is low Soil Science and Agricultural Chemistry, J.N. Krishi Vishwa due to many factors. Nutrient deficiency is one of the Vidyalaya, Jabalpur (M.P.) to study the effect of zinc important factors. Zinc is the most common deficient application on yield attributes, yield, chemical composition and micronutrient elements in soil in the world and about protein content of wheat. Wheat variety GW-273 was sown 50% soils of India are deficient in Zn (Sarkar and Singh during Rabi season, 2010-11 and 2011-12 with recommended 2003). inputs. The recommended doses of fertilizers were applied -1 @ 120 N: 60 P2O5: K2O 40 kg ha in all treatments. Zn was Zinc is one of the eight important essential trace applied @ 1.25, 2.5, 5.0, 10.0 and 20.0 kg ha-1 as zinc sulphate element for both plants and humans (Hao et al., 2007). at the time of sowing in all treatments except control Zinc plays an important role in the production of biomass (recommended NPK). The results indicated that combined (Cakmak 2008). Zinc is essential for the synthesis of application of recommended NPK and Zn significantly and plant growth regulator also called auxin (IAA); such positively affected the yield attributing characters, yield and compound regulates the growth and development of chemical composition as well as protein content of wheat, as compared to NPK alone. The maximum number of effective plants. Zinc is involved in a large number of enzymes tillers, 1000-grain weight, yield (grain and straw), chemical as a cofactor. For example, it is involved in activation composition (N, K and Zn), crude and true protein was of different enzymes such as dihydrogenase, aldolase, achieved by the application of 20 kg Zn ha-1 with recommended isomerase, transphosphorase and DNA polymerase NPK as compare to control, except P concentration in grain (Marschner 1995). Total Zn concentration is sufficient in and straw that was reduced at highest level of Zn. many agricultural areas, but available Zn concentration is deficient because of different soil and climatic Key words: Zinc, yield attributes, yield, chemical conditions. Soil pH, lime content, organic matter content, composition, protein, wheat, Kymore plateau. clay type and amount and the amount of applied phosphorus fertilizer affect the available Zn concentration in soil. Wheat (Triticum aestivum L.) is cultivated worldwide primarily as a food commodity and a strategic However, Zn deficiency appears to be the most commodity. The acceptance of wheat in Asia as a basic widespread and frequent micronutrient deficiency in food stuff led to its widespread dissemination as food crops worldwide, resulting in severe losses in yield and aid to developing countries. Wheat is an important nutritional quality. The Zn deficiency in soils of Kymore staple food crop of the entire world as well as India. plateau of Madhya Pradesh is about 70.3% (Khamparia Wheat is the world's leading cereal crop cultivated over et al. 2010). Limited information is available regarding an area of about 226.54 m ha-1 with a production of zinc requirement of wheat crop in soils of the Kymore 161.9 m tonnes. In India, the production is about 72 m plateau. Therefore, the present investigation was tonnes from an area of 25 m ha (Singh et al. 2011). The undertaken to contemplate the optimum dose of zinc current problem of wheat contributing in low yield is the under the semi-arid and sub-tropical climate for 278 12 12 9.35 9.71 1.18 9.43 9.77 1.24 2011- 10.22 10.66 11.47 11.76 10.53 10.12 11.06 11.60 12.24 10.70 2011- True ) Straw -1 8.99 9.24 9.54 1.17 2010-11 10.19 10.94 11.42 10.05 8.88 9.10 9.50 9.78 1.11 10.05 10.54 10.67 2010-11 Zn (mgZn kg 3.35 2011-12 22.23 25.02 27.96 31.92 35.32 39.49 30.32 Protein Protein (%) 1.31 10.55 11.00 11.74 12.51 12.94 13.08 11.97 Grain 2011-12 2.96 2010-11 20.76 22.36 24.58 27.62 30.89 34.81 26.84 Crude 9.50 9.83 1.17 10.43 11.21 11.50 11.59 10.68 2010-11 0.78 0.79 0.82 0.84 0.89 0.91 0.84 0.10 2011-12 Straw 0.74 0.75 0.76 0.77 0.82 0.84 0.78 0.09 2010-11 4.93 4.96 5.04 5.37 5.56 5.59 5.24 0.90 2011-12 K (%)K Straw ) -1 0.54 0.55 0.56 0.58 0.62 0.65 0.58 0.07 2011-12 4.60 4.66 4.73 4.80 5.28 5.29 4.89 0.88 2010-11 Grain 0.51 0.51 0.52 0.53 0.58 0.60 0.54 0.06 2010-11 Yield Yield (t ha 4.00 4.06 4.19 4.49 4.77 4.79 4.38 0.74 2011-12 NS 2011-12 0.088 0.085 0.083 0.073 0.070 0.068 0.078 Grain Straw 3.75 3.80 3.89 3.98 4.48 4.52 4.07 0.70 NS 2010-11 2010-11 0.098 0.095 0.093 0.088 0.080 0.078 0.088 P (%)P NS 6.90 0.31 0.30 0.29 0.28 0.26 0.24 0.28 2011-12 37.77 38.05 39.11 40.90 44.48 44.59 40.82 2011-12 Grain NS 0.33 0.32 0.30 0.28 0.26 0.24 0.29 2010-11 6.62 1000-grain 1000-grain weight (g) 35.45 36.14 36.66 40.07 42.43 42.58 38.89 2010-11 0.66 0.67 0.69 0.73 0.77 0.80 0.72 0.08 2011-12 Straw 0.57 0.58 0.60 0.63 0.66 0.69 0.62 0.07 2010-11 66.21 364.64 368.55 375.73 394.18 409.05 428.18 390.05 2011-12 N (%) 1.85 1.93 2.06 2.20 2.27 2.30 2.10 0.23 2011-12 64.66 Grain 346.33 349.13 359.25 371.98 414.40 414.45 375.92 2010-11 1.67 1.73 1.83 1.97 2.02 2.03 1.87 0.21 2010-11 No. No. of effective tillers (m-2) -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 Yield attributing characters, and yield ofquality wheat grown in Typic Haplustert as influence by different levels of Zn during year 2010- Chemical composition of wheat grown in Typic Haplustert as influence differentby levels of Zn during year 2010-11 and 2011-12 Table 1. Table 11 and 2011-12 Treatments NPK (Control) NPK+1.25 kg Zn ha NPK+2.50 kg Zn ha kgNPK+5 Zn ha NPK+10 kg Zn ha NPK+20 kg Zn ha Mean C.D. (5%) Table 2. Table Treatments NPK (Control) NPK+1.25 kg Zn ha NPK+2.50 kg Zn ha kgNPK+5 Zn ha NPK+10 kg Zn ha NPK+20 kg Zn ha Mean C.D. (5%)
279 obtaining sustainable wheat yield at Kymore plateau. weight. Grain and straw yield were recorded and samples of grains and straws were kept at 600C for 48 hrs and then ground with a grinding mill and analysed Materials and methods for N, P, K and Zn content by adopting standard procedure. Nitrogen in grain and straw was determined This research work was carried out on a Typic Haplustert by microkjeldal method (AOAC 1965), phosphorus was at the Research Farm of Department of Soil Science determined by Vanadomolybdate yellow colour method and Agricultural Chemistry, J.N. Krishi Vishwa of Koenig and Johnson (1942) on spectrophotometer, Vidyalaya, Jabalpur (MP) which lies between 23o10" N potassium as described by Black (1965) and Zn by using latitude and 79o57" E longitude, during the successive atomic absorption spectrophotometer. Crude protein year. The experiment was laid out in complete percentage was calculated multiplying the N content randomized block design with four replications. The by constant factor of 5.70 and true protein was experimental soil (0-15 cm depth) was analyzed for initial calculated by deducing non- protein nitrogen form crude soil physico-chemical properties. Soil texture was clayey protein. The entire data was analysed statistically by having the following characteristics: sand-25.3%, silt- using ANOVA technique. -1 17.90%, clay-56.8%, pH-7.2, OC-4.5 g kg , CaCO3-20.5 g kg-1, EC-0.22 dS m-1, available N 223.0-kg ha-1, Results and discussion available P 18.9-kg ha-1, available K-314.3 kg ha-1, DTPA extractable Zn-0.66 mg kg-1. Wheat GW-273 was sown during Rabi season, 2010-2011 and 2011-2012 Yield attributes and yield on 15 and 20 December, respectively, with hand drill using seed rate 120 kg ha-1. A basal dose of 60:60:40 The results indicated that the yield attributing characters N, P O , and K O was applied before sowing of wheat, 2 5 2 ,yield and quality expect of number of effective tillers, through urea, super phosphate and muriate of potash 1000-grain weight, grain and straw yield in wheat were fertilizers. Remaining 60 kg N was applied to wheat crop influenced by Zn application in both year (Table 1 and in two split doses during crop growth. The doses of Zn Fig. 1). @ 0, 1.25, 2.50, 5, 10 and 20 kg ha-1 were given through zinc sulphate fertilizer before sowing of wheat alongwith It is evident from the data of two consecutive year basal dose of N, P2O5, and K2O. All crop management 2010-11 and 2011-12, that the number of effective tillers and protection measures were followed. Weed control (414.45 and 428.018) and 1000-grain weight (42.58 and practices were included physical method i.e., hoeing 44.59 g) was recorded with treatment comprising along with weedicides. The crop was harvested at NPK+20 kg Zn ha-1, which was significantly higher than maturity, 120 days after sowing. At harvesting time, one control at maturity stage, respectively. The treatment meter square was randomly selected from each with 10 kg Zn ha-1 was statistically at par with 20 kg Zn experimental plot to estimate the yield attributing ha-1 in number of effective tillers and 1000-grain weight, characters viz. number of effective tillers and 1000-grain during 2010-11 only. The lowest number of effective
6.00 14 Treatments NPK (Control) 5.00 12 Treatments NPK+1.25 kg Zn ha-1 Treatments NPK+2.50 kg Zn ha-1 10 Treatments NPK+5 kg Zn ha-1 4.00 -1 NPK (Control) 8 Treatments NPK+10 kg Zn ha-1 NPK+1.25 kg Zn ha-1 Treatments NPK+20 kg Zn ha-1 3.00 NPK+2.50 kg Zn ha-1 6 Yield t ha t Yield NPK+5 kg Zn ha-1 (%) Protein 2.00 4 NPK+10 kg Zn ha-1 NPK+20 kg Zn ha-1 2 1.00 0 0.00 2010-11 2011-12 2010-11 2011-12 2010-11 2011-12 Crude True
Fig 1. Effect of different levels of Zn on Grain yield of Fig 2. Effect of different levels of Zn on protein content wheat during year 2010-11 and 2011-12 of wheat during year 2010-11 and 2011-12
280 Effect of different levels of Zn on Zn content of wheat during Effect of different levels of Zn on P content of wheat during year Fig 6. year 2010-11 and 2011-12 Fig 4. 2010-11 and 2011-12 Effect of different levels of Zn on K content of wheat during year Effect of different levels of Zn on N content of wheat during year Fig 5. 2010-11 and 2011-12 Fig 3. 2010-11 and 2011-12
281 tillers (346.33 and 364.64) and 1000-grain weight (35.45 in small amounts in plants, it involved and activates a and 37.77 g) was recorded in control at maturity stage large number of enzymes as a cofactor. For example, it in both the years, respectively. The treatments 5, 2.50 is involved in activation of different enzymes such as and 1.25 kg Zn ha-1 was statistically at par with control dihydrogenase, aldolase, isomerase and at maturity stages in both number of effective tillers and transphosphorase. It is inferred that plant not to be able 1000-grain weight. to survive with inadequate Zn because they are essential to the synthesis of DNA and RNA and to Similarly, the highest the grain (4.52 and 4.79 t metabolizing protein. Decline in P concentration in grain ha-1) and straw (5.29 and 5.59 t ha-1) yield was observed -1 and straw may be due to antagonistic effect between in treatment consisting NPK+20 kg Zn ha , which was Zn and P. The results achieved in this work are partially significantly higher than the control during the year - compatible with those obtained by Alam et al (2000), 2010-11 and 2011-12. The treatment with 10 kg Zn ha Habib (2009) and Seadh et al (2009). 1 was at par to 20 kg Zn ha-1 only in grain yield. No Zn fertilization treatment showed significant result towards straw yield. The lowest grain (3.75 and 4.00 t ha-1) and vuqla/kku iz{ks=] e`nk foKku ,oa d`f'k jlk;u"kkL= foHkkx] straw (4.60 and 4.93 t ha-1) yield was recorded in control. t-us-d`-fo-fo- tcyiqj ¼e-iz-½ ds fVfid gsIywLVVZ e`nk esa The treatments with application of 5, 2.50 and 1.25 kg flafpr xsgw¡ esa vuq'kaflr moZjdksa dh ek=k Zn ha-1 seems equally in their effect and the difference ¼120%60%40 u=tu % LQqj % iksVk'k fd- xzk- izfr gs-½ between them were insignificant and statistically at par ds lkFk 10 ,oa 20 fd-xzk- tLrk izfr gs- dk mi;ksx djus ij with control in grain yield. Such effect of Zn fertilization mit fu/kkZfjr djus okys dkjd ¼dkjxj fdYyks dh la[;k izfr might be due to its critical role in crop growth, involving oxZ eh- rFkk 1000&nkus dk Hkkj½] mit ¼vukt ,oa Hkwlk in photosynthesis process, chlorophyll formation, N- Vu izfr gs-½] jlk;fud laxBu ¼u=tu] iksVk'k ,oa tLrk½ viDo fixation, respiration and other biochemical and rFkk ;FkkFkZ izksVhu dh izfr'kr vfHkO;atd ,oa vf/kdre physiological activities and thus their importance in ik;k x;k gS] tcfd tLrk ds mi;ksx ls Qly esa LQqj izfr"kr achieving higher and sustainable yield. The results are esa deh ikbZ xbZ gSA in conformity with the findings of Seadh et al. (2009) and Gul et al. (2011). Reference
Chemical compositions and quality AOAC (1965) Official methods of analysis of the association of official agricultural chemists. 10th Ed., 744 Chemical composition i.e. N, K and Zn concentration in Alam SM, Zafar I, Latif A (2000) Effect of P and Zn application grains and straw and quality parameter of grain i.e. by fertigation on P use efficiency and yield of wheat. crude and true protein percentage show positive Trop Agric Res and Exten 3(2): 115-120 response with increasing levels of Zn fertilizer in both Black CA (1965) Methods of soil analysis. Part I and part II years as shown in Table 1,2 and Fig.2 to 6, whereas, Agronomy series No. 9, Ame Soc Agron Inc. Madison, Wisconsin, USA the magnitude of P concentration was in decreasing Cakmak I (2008) Enrichment of cereal grains with zinc: order with increasing levels of Zn. Agronomic or genetic biofortification. Plant and Soil The application of recommended dose of NPK 302: 1-17 alongwith 20 kg Zn ha-1 resulted in the maximum values Gul H, Said A, Saeed B, Ahmad I, Ali K (2011) Response of of traits N, K and Zn concentration as well as crude and yield and yield components of wheat towards foliar true protein percent with significant differences spray of nitrogen, potassium and zinc. ARPN J Agric and Bio Sci 6(2): 23-25 compared with control in two growing seasons. Generally, it was observed that the importance of Zn Habib M (2009) Effect of foliar application of Zn and Fe on wheat yield and quality. African J Biotech 8(24): 6795- fertilization with recommended NPK in terms of N, K, 6798 Zn and crude protein content assorted as: NPK+20 kg Hao MD, Wei XR, Dang TH (2003) Effect of long-term applying Zn > NPK+10 kg Zn > NPK+5 kg Zn > NPK+2.50 kg Zn zinc fertilizer on wheat yield and content of zinc in > NPK+1.25 kg Zn > NPK alone in both season, while dryland. Plant Nut and Ferti Sci 9(3): 377-380 P concentration was in decreasing order and Khamparia RS, Singh MV, Sharma BL, Kulhare PS, Sharma insignificant with increasing levels of Zn. This GD (2010). Four decades of research on micro and improvement in grain quality and chemical composition secondary nutrients and pollutant elements in soil of may be due to the role of Zn in maintaining balanced M.P. Res Publi No. 9 AICRP micro- and secondary plant physiological growth. Even though Zn is present nutrients and pollutant elements in soil and plant, IISS Bhopal 6: 1-113
282 Koenig D, Johnson PP (1942). Distribution of phosphorus in biological materials. Ind Eng Chem 14: 155 Marschner H (1995) Mineral Nutrition of Higher Plants. 2nd ed. Acad. Press, London. 301-306 Sarkar, Singh (2003) Crop response of secondary and micronutrient in acidic soil of India. Ferti News 48: 47-54 Seadh SE, El-Abady MI, El-Ghamry AM and Farouk S (2009). Influence of micronutrient application and nitrogen fertilization on wheat yield, quality of grain and seed. J Bio Sci 9(8): 851-858 Singh CM, Sharma PK, Kishor P, Misra PK (2011). Impect of integrated nutrient manage ment on growth, yield and nutrient uptake by wheat. Asian J Agric Res 5(1):76-82
(Manuscript Receivd : 10.8.12; Accepted : 30.12.13)
283 JNKVV Res J 47(2): 284-287 (2013)
Effect of in-situ moisture conservation for improving niger productivity in Kymore plateau, Madhya Pradesh
M.R. Deshmukh, Alok Jyotishi and A.R.G. Ranganatha Project Coordinating Unit (Sesame and Niger) Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482 004 (MP) Email : [email protected]
Abstract Materials and methods
Experiments were conducted on niger with the objective to Field experiments were conducted on niger cv. JNC-6 evaluate suitable moisture conservation practices for at Research Farm of Project Coordinating Unit (Sesame improving the productivity and monetary returns. Results and Niger), JNKVV, Jabalpur for two consecutive years revealed that normal sowing of seed with one handweeding (HW) at days after sowing (DAS) followed by vegetative during winter season of the year 2007 and 2008 with mulching (use of incorporated weeds) proved significantly the objective to evaluate the moisture conservation superior over normal sowing followed by two handweedings techniques. The soil of the experimental field was clay at 15 and 30 DAS with regard to seed yield and monetary loam in texture, neutral in reaction (pH 7.2) and returns. It produced seed yield of 650 kg/ha with NMR of Rs analyzing in low organic carbon (0.39%), available N 5214/ha and B:C ratio of 1.66 against normal sowing with seed yield of 541 kg/ha fetching NMR of Rs 2942/ha and B:C 220 kg/ha and available P 7.85 kg/ha and high available ratio of 1.37. Other moisture conservation practices viz., K (345 kg/ha) contents. Six treatments of moisture normal sowing with one H.W. at 15 DAS followed by saw conservation techniques viz., normal sowing with two dust mulching or soil stirring also proved equally effective to hand weedings (H.W.)-T1; one H.W. at 15 days after farmers practice with regard to seed yield and monetary sowing (DAS) + dust mulching within and between rows returns. after weeding-T2; one H.W. at 30 DAS + dust mulching-
T3; one H.W. at 15 DAS + vegetative mulch 4 t/ha-T4; Keywords: Moisture conservation, Mulch, Stirring, one H.W. at 15 DAS + soil stirring after each irrigation Economics, Niger upto 50 DAS-T5 and keeping dead furrow after 6 rows-
T6 were tested in randomized block design with three Niger is an important oilseed crop for tribals of Jabalpur replications. The seeds were treated with Thiram 3 g/ area in the kymore plateau zone of Madhya Pradesh. kg seed and sown on October 16, 2007 and October, Generally it is grown in hill-slopes, hillocks and 6, 2008 in rows 30 cm apart by drilling 5 kg seed/ha at degraded lands, where soil depth is very shallow having about 3 cm depth. Just after sowing the seeds were very low moisture holding capacity. The rainfall of the well covered in the soil and a light irrigation was given niger growing area is often highly erratic and results in for germination of seed. A uniform dose of fertilizers as moisture stress during growing season of cropping 40 kg N + 30 kg P O + 20 kg K O/ha was applied to frequently because of long dry spells. It causes great 2 5 2 each plot. Half quantity of N and total P and K fertilizers reduction in yield of niger. As niger crop is sensitive to were applied as basal, while remaining N was given as moisture stress particularly increases if desirable top dressing. Data on various yield attributes and yield moisture condition is maintained at critical growth stages of crop-growth (Rath et al 2006). Agricultural drought were recorded. The oil yield was also determined occurred due to early cessation of monsoon rains can treatment wise on the basis of oil content in seed. The be managed for growth through conserved rain water economics was calculated using the prevailing prices (Grewal et al 1989). Therefore, the present study was for the inputs and produce during that period of time. taken up to find out the efficient method of moisture Finally data were statistically analysed for the conservation for improving niger productivity of the zone.
284 NS 4.4 4.5 4.6 4.8 4.3 4.3 0.12 0.3 B:C Mean ratio 1.33 1.63 1.53 1.66 1.51 1.37 0.11 (g) NS 4.5 4.6 4.7 4.8 4.3 4.4 0.13 2008 Test weight Test NS 4.3 4.4 4.6 4.9 4.4 4.2 286 864 0.11 2007 2942 4824 4264 5214 4146 2556 returns (Rs/ha) Net monetary Net 24.5 24.7 25.1 25.4 24.9 25.0 0.19 0.59 Mean 12 37 195 225 219 234 216 181 Mean (#) 23.9 35.7 36.8 36.9 36.2 36.1 0.24 0.73 2008 11 34 236 243 245 265 237 212 Seeds/capitula 2008 23.1 34.9 35.5 35.9 35.0 35.6 0.20 0.62 (kg/ha) 2007 Oil yield Oil 14 43 154 210 194 204 195 151 2007 32.9 34.9 35.5 35.9 35.0 35.6 0.28 0.85 Mean (#) 33.6 35.3 35.6 36.1 34.6 34.7 0.31 0.96 2008 - - Mean 35.84 36.06 35.86 36.01 35.60 35.55 Capitule/plant 32.3 34.6 35.3 35.7 34.5 35.4 0.39 1.24 2007 - - (%) 2008 36.79 36.82 36.39 36.31 35.76 36.03 7.0 8.6 8.8 8.9 8.5 8.3 Oil content 0.31 0.95 Mean - - 2007 34.89 35.29 35.32 35.71 35.43 35.06 7.5 8.9 9.2 9.3 8.6 8.6 0.23 0.71 2008 plant (#) 6.5 8.2 8.3 8.5 8.3 8.4 0.36 1.16 Basal branches/ 2007 25 78 541 623 610 650 607 510 Mean 8.1 116 134 132 136 134 131 28 86 25.4 642 675 672 729 663 589 Mean 2008 (kg/ha) Seed yield Seed 6.3 122 141 144 142 143 139 19.2 (cm) 2008 21 65 440 571 548 572 552 431 2007 Plantheight 7.9 110 126 120 130 125 122 24.8 2007 Effect of different moisture conservation practices on plant-height, basal branches and yield attributes of niger during 2007and 2008 at Effect of different moisture conservation practices on seed (kg/ha),yield oil and yield economics of niger during 2007and 2008 at Normal sowing with two hand weedings One hand weeding at 15 DAS + saw dust mulching One hand weeding at 30 DAS + saw dust mulching One hand weeding at 15 DAS + vegetative mulching One hand weeding at 15 DAS + soil stirring up to 50 DAS Keeping dead furrow after sixth row SEm± (P=0.05) CD Normal sowing with two hand weedings One hand weeding at 15 DAS + saw dust mulching One hand weeding at 30 DAS + saw dust mulching One hand weeding at 15 DAS + vegetative mulching One hand weeding at 15 DAS + soil stirring up to 50 DAS Keeping dead furrow after sixth row SEm± (P=0.05) CD ------1 2 3 4 5 6 1 2 3 4 5 6 Table Table 1. Jabalpur Treatment T T T T T T # = Number = # Table 2. Table Jabalpur Treatment T T T T T T
285 interpretation of the results. produced numerically inferior yield attributes and thus, resulting in lesser seed yield. These results are in close conformity with the findings of Panda and Mohanty Results and discussion (2009).
Seed yield Oil yield
The moisture conservation practices viz., one H.W. at Oil yield depend on the seed yield and oil content of 15 DAS followed by saw dust mulching - (T ), H.W. at 2 seed. Oil content of seed did not vary due to different 30 DAS followed by saw dust mulch - (T ), one H.W. 15 3 moisture conservation practices, but oil yield DAS followed by vegetative mulching - (T ) and one 3 significantly varied, mainly due to variations in seed yield H.W. 15 DAS followed by soil stirring upto 50 DAS - (Table 2 and Fig 2). Because of significantly higher seed (T ) produced significantly higher seed yield over normal 5 yield with T , T , T and T moisture conservation sowing with 2 H.W. - (T ) during both years of 2 3 4 5 1 practices, oil output were also significantly higher, over investigation (Table 1 and Fig 1). Based upon two years T - control as well as T - keeping dead furrow after 6th data on seed yield, keeping dead furrow after six rows. 1 6 row for sowing of seed. These results also corroborated T produced lowest seed yield 510 kg/ha which was at 6 the findings of Trivedi and Ahlawat (1991 and 1993) par to T (541 kg/ha). Seed yield significantly increased 1 and Deshmukh et al (2007). with the treatments adopting soil conservation practices as T2 (623 kg/ha), T3 (610 kg/ha), T4 (650 kg/ha) and T5 (607 kg/ha) over the former two treatments. However, Economics variation in seed yield were not significant between four soil conservation practices, however T produced 4 Different moisture conservation practices viz., T (Rs numerically higher seed yield. The superiority in seed 4 5214/ha), T (Rs 4824/ha), T (Rs 4264/ha) and T (Rs yield due to different soil conservation practices over 2 3 5 4146/ha) fetched significantly higher net monetary control (normal sowing with H.W. only) were mainly returns (NMR) over normal sowing - T (Rs 2942/ha). attributed to higher plant-height, basal branches/plant, 1 Though, cost of cultivation slightly increased with the capitula/plant, seeds/capitula (Table 1). The test weight inclusion of different moisture conservation practices of seed was not affected by different soil conservation over T , significant increase in seed yield resulted into practices. Different soil conservation practices viz., use 1 marked increase in the NMR values. Consequently, the of dust mulching (T and T ), vegetative mulching (T ) 2 3 4 B:C ratio were also significantly greater with different and soil stirring (T ) helped to improve the growth 5 water conservation practices (T , T , T and T ) over parameters viz., plant-height and branches/plant which 2 3 4 5 control. also improved the yield attributes viz., capitule/plant and seeds/capitula. Keeping dead furrow after each sixth row-T6 did not compensate the losses caused by Hkwfe esa ueh laj{k.k djus ds fofHkUu rjhdksa dk ewY;kadu jkefry dh reducing the population. Stirring of soil after H.W. at 15 Qly ls vf/kd mRikndrk ,oa vkfFkZd vk; izkIr djus ds mn~ns'; DAS upto 50 DAS - T and dust mulching after the H.W. 5 ls o"kZ 2007&08 ds nkSjku lrr~ ijh{k.k iz;ksx fd;s x;s A ifj.kkeksa at 30 DAS-T3 probably conserved lesser moisture and
Seed yield (kg/ha) Oil content (%) Oil yield (kg/ha) Plant height (cm) Basal branches/plant (#) Capitule/plant (#) NMR (Rs/ha) Seeds/capitula (#) Test weight (g) B:C ratio
140 6000 2 120 5000 100 1.5 4000 80 60 3000 1
40 2000 0.5 20 1000 ratio B:C Yield attributes Yield 0 0 T1 T2 T3 T4 T5 T6 0 Yield and Yield
Economics T1 T2 T3 T4 T5 T6 Treatments Treatments Fig 1. Effect of different moisture conservation practices on Fig 2. Effect of different moisture conservation practices on mean ancillary characters and yield attributes of niger mean seed, oil yield and economics of niger
286 ls Kkr gqvk dh jkefry dh cksuh ds 15 fnu i'pkr~ funakbZ ds lkFk okuLifrd iyokj dk 4 Vu@gsDVs;j ds eku ls iz;ksx djus ij jkefry dh cksuh ds 15 ls 30 fnu i'pkr~ nks ckj fuankbZ ds djus ds mipkj ds rqyuk esa vf/kd mit ,oa vkfFkZd vk; izkIr djus es mi;qDr ik;k x;k A igys mipkj ls 650 fdxzk@gSDVs;j mit] 5214 :Ik;s 'kq) ykHk rFkk 1-66 ykHk&O;; vuqikr nqljs mipkj ls izkIr mit 541 fdxzk@gSDVs;j] 2942 :i;s@gSDVs;j 'kq) ykHk ,oa 1-37 ykHk&O;; vuqikr ds fo:) ntZ fd;k x;k A vU; ueh lja{k.k djus ds rjhdkass ;Fkk jkefry dh lkekU; cksuh ds 15 fnu i'pkr~ fuankbZ ds lkFk ydMh ds Hkqls dk iyokj vFkok Hkwfe foyksMu djus ls izkIr mit LFkkuh; —"kd rjhdksas ls izkIr gksus okyh cht mit rFkk 'kq) ykHk ds lerqY; gksuk ik;k x;kA
References
Deshmukh MR, Pandey A.K, Sharma RS, Duhoon S.S (2007) Effect of integrated nutrient management on productivity and economic viability of niger. JNKVV Res J 41(1):32-35 Grewal S.S, Mittal SP, Agnihotri Y, Dubey LN (1989) Rain water harvesting for the management of agricultural droughts in the foot hills of northern India. Agril Water Mang 16:309-322 Panda S, Mohanty LK (2009) In-situ moisture conservation techniques for improving niger, [Guizotia abyssinica (L.f.)] Cass productivity. J Oilseeds Res 26:316-317 Rath BS, Garhayak LM, Sahoo J, Swain NC, Mishra HP, Mohapatra PC (2006) Oilseed production technology in Orissa. Agricultural Technology Information Centre, Directorate of Extension Education Orissa University of Agriculture and Technology Bhubaneshwar (Odisha) p 23 Trivedi SJ, Ahlawat RPS (1991) Effect of nitrogen and phosphorus on growth and yield on niger (Guizotia abyssinica Cass). Indian J Agron 36(3):432-433 Trivedi SJ, Ahlawat RPS (1993) Quality studies in niger (Guizotia abyssinica Cass) in relation to nitrogen and phosphorus. Gujrat Agric Univ Res J 18(2):92-93
(Manuscript Receivd : 20.7.12; Accepted : 11.12.13)
287 JNKVV Res J 47(3): 288-290 (2013)
Water productivity of early, medium and hybrid rice varieties under aerobic condition
R.K. Tiwari, B.S. Dwivedi*, I.M. Khan, S.K. Tripathi and Deepak Malviya All India Coordinated Rice Improvement Project College of Agriculture Rewa 486001 (MP) *Department of Soil Science and Agricultural Chemistry, College of Agriculture Jabalpur 482 004 (MP) Email : [email protected]
Abstract Material and methods
A field experiment was conducted in Kharif 2012 under A field experiment was conducted in Kharif 2012 under AICRIP-Rice at JNKVV College of Agriculture Farm, Rewa AICRIP-Rice at JNKVV, College of Agriculture Farm, MP in aerobic condition. Three dates of sowing i.e. D , D and 1 2 Rewa (M.P.) in aerobic condition. Three dates of sowing D as main treatment and six rice genotypes two in each group 3 i.e. D , D and D (20th June, 30th June and 10th July of early, (Danteshwari and Narendra-97), medium (Govinda 1 2 3 and Sahabhagi) and hybrid (PHB 71 and BH 21) as sub 2012 respectively) as main treatment and six rice treatment. Direct seeding method was used in rainfed aerobic genotypes two in each group of early, (Danteshwari and condition. It was found that D2 (30th June) seeding date was Narendra 97), medium (Govinda and Sahabhagi) and found suitable for rice direct seeding in upland aerobic hybrid (PHB 71 and BH 21) as sub treatment. Direct condition and among the different group of genotypes, seeding method was used in rainfed aerobic condition. Danteshwari in early, Sahabhagi in medium and BH-21 in Uniform dose of 100 kg N, 60 kg P2O5 and 40 kg K2O/ hybrid exhibited higher water productivity and grain yield. 2 ha along with 20 kg ZnSO4 was applied to all 25 m plots through urea, SSP and MOP. Application of Rice (Oryza sativa L.) is the main food crop in Asia where nitrogen was done in 3 split i.e. 50% as basal, 25% at more that 90% of the world's rice is produced and tillering and remaining 25% at PI stage of crop growth. consumed which provides on an average of 35% of total Soil of experimental field was silty clay loam having 6.7 calorie intake (Bauman 2001). The 40% of total pH, low in available nitrogen and medium in phosphorus cultivated area of rice is under fragile ecosystems which and high in potassium with 0.52% organic carbon. include the rain fed upland, lowland and deepwater rice Observations were recorded on yield attributing where yield are both low and extremely variable. In characters in all treatments and water productivity was upland ecosystem where sustainability is threatened by calculated on agronomic yield (g of grain)/unit of water fresh water scarcity, water pollution and competition for use (kg of water) by using the following formula (Grassi water use (Gleick 1993). It is difficult to have water for 2009). irrigated rice system which consumes two three times more water than other cereals therefore major Y challenges are to produce more rice in aerobic condition WP = with increase water productivity and reduce water input (I+R) (Postel 1997). Aerobic condition help in water saving in terms of water use efficiency. In the present scenario, Where, water productivity is more important and thus, need to find out suitable time and genotypes for efficient water WP = Water productivity use and productivity. Hence, the present study was Y = Yield design to find out the suitable time of seeding and I = Water irrigation applied genotypes of early, medium and hybrid rice for efficient water use and productivity. R = amount of rainfall
288 ) 2 0.05 0.12 0.46 2.379 2.580 2.948 3.061 3.166 3.048 2.930 2.799 3.092 3.149 3.179 3.225 2.917 2.785 3.136 3.105 3.150 3.136 Water (kg/m productivity 3022 3277 3744 3888 4022 3872 3722 3555 3927 4000 4038 4094 3705 3538 3983 3944 3988 3983 249.12 192.31 301.26 (kg/ha) Grain yield 0.85 1.71 2.48 27.27 26.46 28.67 26.87 27.34 27.27 27.60 26.60 28.14 26.67 27.87 27.07 26.50 27.00 26.77 27.50 27.47 26.34 Test weight Test panicle panicle (g) NS 2.44 1.97 2.64 2.84 2.74 2.85 2.94 2.34 2.90 2.84 3.27 3.31 2.61 2.14 2.84 2.62 3.20 3.17 0.22 0.46 Weight of panicle panicle (g) 2 303 389 313 315 321 330 320 307 326 328 330 335 320 323 322 317 330 338 5.95 9.76 14.12 no./m Panicle 94 92 95 96 95 98 NS 105 109 120 122 106 110 120 121 110 112 121 125 1.02 2.15 Day Day of Maturity Danteshawari N-97 Govendra Sahabhagi PHB-71 BH-21 Danteshawari N-97 Govendra Sahabhagi PHB-71 BH-21 Danteshawari N-97 Govendra Sahabhagi PHB-71 BH-21 Sub Sub plot (genotypes) Early Early medium medium Hybrid Hybrid Early Early medium medium Hybrid Hybrid Early Early medium medium Hybrid Hybrid Yield Yield attributing characters, yield and water productivity of early, medium and hybrid rice genotypes in aerobic condition July 2012 June 2012) June 2012 th th th (20 (30 (10 1 2 3 Table 1. Table plot main Treatment (Date of sowing) D D D LSD (D) LSD (G) (DXG)
289 th Results It is concluded from the study that D2 (30 June) seeding date was found suitable for rice direct seeding in upland aerobic condition and among the different Effect of date of seeding on maturity and crop group of genotypes, Danteshwari in early, Sahabhagi productivity in medium and BH-21 in hybrid exhibited higher water productivity and grain yield. The crop duration was increased by 1 to 6 days in early duration genotypes form D to D . Maturity of N-97 was 1 3 vf[ky Hkkjrh; vuqla/kku ifj;kstuk ds varxZr d`f'k egkfo|ky;] delayed by 6 days in D3. In medium duration genotypes maturity was delayed by 4-5 days from first date of jhok ds iz{ks= esa [kjhQ 2012 ds /kku dh lh/kh cqokbZ ds fy;s rhu seeding (D1) to 3rd date of sowing (D3) and maximum fofHkUUk cqokbZ fof/k;ks ds lkFk /kku dh N% iztkfr;ks dk v/;;u fd;k delayed was occurred in cv. Govinda while minimum x;kA ftlesa 2 iztkfr;k¡ ¼/kUrs"ojh] ujsUnz 97½ de vof/k esa idus delayed (1 to 3 days) in maturity was found in hybrid okyh] nks iztkfr;k¡ ¼xksfoUnk] lgHkkxh½ e/;e vo/kh esa idus okyh ,oa group from D1 to D3 dates of seeding. The mean rainfall received by all genotypes was 1269.6 mm during crop nks iztkfr;k¡ ¼ih-,p-ch- 71] ch-,p- 21½ "kadj iztkfr;k¡ FkhA v/ growth period. ;;u ls ;g irk pyk fd /kku dh lh/kh cqokbZ ds fy;s Mh&2 ¼30 Highest mean water productivity (3.06 kg/m3) was twu½ lcls mfpr Fkh] ftles /kku dh iztkfr;k¡ ds rhuks lewgks esa associated with D2 i.e. 30th June 2012 followed by D3 lkFkZd mit izkIr gqbZA
(3.03) and D1 (2.86). Genotypes Danteshwari in early group, Sahabhagi in medium and BH-21 in hybrid group Reference had mximum water productivity (Table 1) in D2 and among the different group of genotypes hybrids had higher water productivity followed by medium and early group. Bouman BAM (2001) Water efficient management strategies in rice production. IRRI Notes, 26 (2): 17-22 Gleick PH (1993) Water crisis: a guide to the world fresh water Effect of date of seeding on yield parameters and yield resources. PISDES, Stockholm Environment Institute, New York (USA) Oxford Univ Press 473 Significant variation was recorded for various yield Grassi C, Bouman BAM, Castaneda AR, Manzelli M, Vecchio parameters and yield among the different dates of V (2009) Aerobic rice: Crop performance and water use efficiency. J Agric & Environ Internat Develo 103 sowing and genotypes. The mean maximum panicles/ (40) : 259-270 m2, panicle weight and test weight (g) was found in D 2 Postel S (1997) Last oasis facing water scarcity, Norton and followed by D3 while, the minimum values of these yield company, New Yark (USA) 239p attributing characters was found in D1. Among the different group of genotypes, panicle No/m2, panicle (Manuscript Receivd : 5.9.13; Accepted : 30.12.13) weight, test weight and grain yield was superior in hybrids followed by medium and early group genotypes. In early duration group genotype Danteshwari had maximum panicles/m2, panicle weight and test weight, while in medium duration genotypes Sahabhagi exhibited superiority over Govinda. In the hybrids BH- 21 had maximum number of panicles, panicle weight and test weight. Significant variation was found in grain yield in different dates of sowing and genotypes. Mean maximum grain yield (3889.33 kg/ha) was found in D2 closely followed by D1 (3856.83 kg/ha) while, minimum grain yield was noted in D1 because there was no rains after dry seeding. Among the genotypes group, hybrid HB-21 yielded maximum (4094 kg/ha) followed by Sahabhagi (4000 kg/ha) in medium group and Danteshwari (3788 kg/ha) early groups.
290 JNKVV Res J 47(2): 291-297 (2013)
Wine production from over ripe guava fruits using Saccharomyces cerevisiae
Yogesh Kalyanrao Patil, L.P.S. Rajput, Yogendra Singh and Keerti Tantwai Biotechnology Centre Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract C in human health. Guava is consumed mainly as fresh fruit or processed juice products. Guava wine is the The present study was conducted with the objectives to product of anaerobic fermentation by yeast in which the analyse the chemical composition of guava fruits collected sugars are converted into alcohol and carbon dioxide. from different locations, optimization of the fermentation Despite that, several studies have been carried out to variables for maximum yield of alcohol using Saccharomyces know the suitability of other fruits as substrates for the cerevisiae MTCC 170 and evaluation of the sensory quality purpose of wine production (Okunowo et al. 2005). of fruit wine produced. Firstly, different chemical constituents Guava is easy to grow, possesses high nutritive value of guava fruit pulp were analysed which showed that the guava and its products like juices, beverages, nectars etc. are fruit pulp was found to contain a good amount of TSS required largely appreciated by the consumers. Guava juice for bioconversion into alcohol. Secondly , investigations were done to get maximum recovery of alcohol yield at standard requires 'chaptalization' so as to adjust its Brix and TSS of 20oBrix, incubation temperature of 30oC and pH of prepare a perfect wine out of it. The chaptalized juice 3.76 (original pH of guava fruit juice) with different ranges of ("must") is treated with pectinase or a combination of incubation periods viz. 24, 48, 72, 96, 120, 144, 168 and 192 enzymes and fermented with traditional yeasts at a hr. The higher yield (10.5%) of alcohol was recorded at temperature range of 22 to 30°C and inoculum size of incubation period of 168 hr and found the same at further 6 to 11% (v/v). The addition of N and P improves ethanol incubation period of 192 hr. The results of various experiments production and various consumer quality parameters revealed that the culture of yeast gave maximum yield of of guava wine. Racking and ageing of guava wine also alcohol (13.2%) at TSS level of 22oBrix, pH of 4.0 with improves the sensory and organoleptic characteristics maintaining the incubation temperature of 27°C and incubation period of 168 hr. Third investigation on the sensory quality of guava wine (Kocher and Pooja 2009). Moreover, the evaluation of guava fruit wine revealed that guava fruit wine seasonal availability and high cost of grapes in India sample with alcohol yield of 13.2% was found to be more has also necessitated the search for alternative fruit acceptable with respect to all the sensory attributes in sources viz. guava, bel, jamun etc. (Alobo and Offonry comparison to other samples of guava wine. 2009). High rate of wastage of these fruits especially at their peak of production season necessitates the need for alternative preservation and post harvest Kewwords: Guava fruit, Wine, Saccharomyces cerevisiae MTCC 170, TSS, Sensory attributes technologies towards their value addition that can reduce the level of post harvest losses besides increasing diversity of wine (Okoro 2007 Alobo and Offonry 2009). Guava (Psidium guajava L.) is one of the most important commercial fruit crops consumed locally in India. It is The guava fruit is available in plenty during the fourth most important fruit in our country after citrus, season of production causing glut in the market. In mango and banana. It is a good source of ascorbic acid, addition to this, fruits are highly perishable in nature pectin, sugars and certain minerals (Adree et al. 2010). and there is a lot of spoilage in production season due Guava is completely edible fruit and considered as to insects, pests, diseases in addition to losses during "apple of the poor" due to its low cost, easy availability transportation and storage. Not much work has been and high nutritive value. It plays an important role in done on preparation of wine from guava fruits. Hence reducing nutritive disorders due to deficiency of vitamin there is an urgent need to develop the production 291 technology for such type of products from over ripened different market locations of Jabalpur city and pooled guava fruits. Keeping in view the above fact this them to get pulp for research work .The wine producing research work was planned with the objectives to microorganism's culture viz. Saccharomyces cerevisiae analyse the chemical composition of guava fruits MTCC 170 was obtained from Institute of Microbial collected from different locations and optimize the Technology (IMTECH) Chandigarh, Punjab. The strain fermentation variables for maximum yield of alcohol was selected due to high yielding capacity with no using Saccharomyces cerevisiae MTCC 170 and there production of any unwanted substances. The culture of after to evaluate the sensory quality of fruit wine Saccharomyce cerevisiae was grown and maintained produced. on Yeast Extract Peptone Dextrose (YEPD) media. The homogenized pulp of guava was incubated at 45oC with pectinase 0.50mg/100g pulp for 6 hours to obtain juice Materials and methods from the pulp. The juice was separated by filtration. The clear juice was used for chemical analysis and The present study was conducted in the Fermentation preparation of wine.The fermentation process described Technology Laboratory, Biotechnology Centre, by Kocher and Pooja (2011) was used for production of Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur wine from over ripe guava fruits using Saccharomyces (M.P).Over ripe guava fruits were purchased from cerevisiae (Fig 1). The above mentioned fermentation method was Guava fruits also used for carrying out the experiments on optimization of different fermentation variables Washing (incubation period, TSS, pH and incubation temperature) for achieving the better recovery of wine. Pulping Different samples of guava fruit pulp and wine were analysed for TSS, pH, titrable acidity, total sugar and Pectinase treatment ascorbic acid also. Total soluble solids (TSS) in guava (0.50mg/100g pulp at 45° C for 6 hours) fruit pulp and wine were determined with the help of Erma Hand Refractometer. Acidity of guava fruit pulp Filtration and wine were determined by A.O.A.C (1990) method. The pH was measured by pH meter after Juice standardization. Total sugar was estimated by the method described by Rangana (1997). The yield of Adjustment of TSS and pH alcohol was determined by distillation and dehydration (TSS 22oBrix and pH 4.0) process adopted by O'Leary (2000). Various sensory quality parameters such as colour, flavor, taste and Addition of DAHP and KMS overall quality characteristics of wine were assessed in (DHAP 0.05 %and KMS 100ppm) order to know the consumers acceptability for further application on large scale. Wines were evaluated by a Pasteurization of juice panel of 8 Judges according to the method of Amerine (85°C for 30 minute) et al. (1965) on a 9 point hedonic scale. Addition of yeast culture Results and discussion (Saccharomyces cerevisiae) Fermentation for 168hr Chemical composition of guava fruit revealed that guava o (at 27oC) fruit pulp contained TSS 13.2 Brix, pH 3.76, titrable acidity 0.71%, Ascorbic acid 237.5 mg/100ml, total Pasteurized wine sugar 10.70 %, reducing sugar 7.53 % and non-reducing (85°C for 20 minute) sugar 3.17 %. Data presented in Table 1 on yield of alcohol using culture i.e. Scaccharomyces cerevisiae Addition of clearing agent Bentonite MTCC170 employing the process of fermentation (0.1g/100ml wine) showed that there was a gradual increase in alcohol yield up to incubation period of 168hr. At a incubation Guava wine period of 168hr, culture produced maximum yield
292 Table 1. Effect of incubation period on the yield of alcohol at incubation temperature of 30oC, pH 3.76 and TSS 20oBrix
Incubation Alcohol yield Incubation Alcohol yield Incubation Alcohol yield period (hr) % (v/v) period(hr) % (v/v) period(hr) % (v/v) 0 0 72 5.6 144 9.9 24 2.2 96 6.8 168 10.5 48 4.1 120 8.6 192 10.5 *Values are average of triplicates
Table 2. Effect of incubation period on TSS Content* at incubation temperature of 30oC, pH 3.76 and TSS 20oBrix
Incubation TSS Incubation TSS Incubation TSS period (hr) (oBrix) period (hr) (oBrix) period (hr) (oBrix) 0 20 72 11.5 144 5.2 24 17.1 96 8.2 168 4.1 48 14.3 120 6.9 192 4.1 *Values are average of triplicates
Effect of different pH and TSS levels on titrable Table 3. Effect of different pH and TSS levels on alco- Table 4. acidity* of guava wine at different incubation tempera- hol yield* at different incubation temperature with an 0 optimum incubation period of 168hr tures 24 C with an optimum incubation period of 168 hrs
S.No. Temp. TSS Alcohol yield (%) o (oBrix) pH S.No. Temp.TSS ( Brix) Titrable acidity (%) pH 3.0 3.5 4.0 4.5 3.0 3.5 4.0 4.5 o 1 24 C 18 7.8 7.8 9.3 8.6 1 24oC 18 1.73 1.64 1.44 1.42 2 20 7.3 8.6 6.4 10.5 2 20 1.69 1.60 1.46 1.39 3 22 7.8 9.3 11.8 9.9 3 22 1.74 1.62 1.40 1.37 4 24 8.6 9.9 11.3 11.8 4 24 1.70 1.69 1.37 1.33 o 5 27 C 18 7.8 8.6 9.3 7.3 5 27oC 18 1.60 1.58 1.40 1.37 6 20 6.4 6.4 10.5 11.3 6 20 1.78 1.64 1.56 1.42 7 22 8.6 10.5 13.2 12.6 7 22 1.63 1.60 1.47 1.46 8 24 8.6 7.8 11.3 12.3 8 24 1.71 1.58 1.55 1.42 o 9 30 C 18 7.3 8.6 9.3 9.9 9 30oC 18 1.58 1.44 1.39 1.32 10 20 8.6 9.3 9.9 10.5 10 20 1.67 1.46 1.41 1.36 11 22 8.6 9.9 11.5 11.3 11 22 1.72 1.69 1.59 1.44 12 24 5.8 7.8 9.3 11.8 12 24 1.69 1.68 1.52 1.38 o 13 33 C 18 7.3 9.3 9.9 8.6 13 33oC 18 1.64 1.60 1.57 1.46 14 20 8.6 9.9 10.5 5.9 14 20 1.69 1.56 1.42 1.36 15 22 8.6 10.5 11.3 9.3 15 22 1.74 1.69 1.58 1.49 16 24 7.3 7.8 9.3 9.9 16 24 1.79 1.68 1.59 1.44 * Values are average of triplicates * Values are average of triplicates 293 (10.5%) of alcohol whereas at a incubation period of incubation temperature of 27°C and incubation period 192 hr, it remained the same (10.5%). Data presented of 168 hr. The value of alcohol yield was found to be in Table 2 on the effect of incubation period on TSS lowest and recorded as 5.8% at a TSS level of 24oBrix, content showed that there was a gradual decrease in pH of 3.0 with maintaining the incubation temperature TSS content up to a incubation period of 168hr. At an of 30°C and incubation period of 168 hr. Several workers incubation period of 168hr, TSS was found to be 4.1oBrix have also reported the alcohol yield almost in the similar whereas at a incubation period of 192 hr, it was the range from bioconversion of TSS rich substrates using same (4.1oBrix). The Effect of different pH and TSS yeast (Shankar et al. 2006 Reddy and Reddy 2011). levels on alcohol yield at different incubation Jawahar (1999) reported that using strain temperatures with an optimum incubation period of Saccharomyces cerevisiae 3287, 22% sugar, 4.0 pH 168hr was also recorded. The findings in this and 0.05% DHAP were found to be optimum for the investigation revealed that alcohol yield varied to a great production of good quality wine from guava juice. Sevda extent employing yeast in the process of fermentation. and Rodrigues (2011) reported that the fermentation temperature of 25°C, pH 4.0, DAP 0.6% and 6% The observations depicted in Table 3 indicated inoculum level gave the better results. The findings that the culture of yeast (Saccharomyces cerevisiae obtained in this investigation showed that these results MTCC170) gave maximum yield of alcohol (13.2%) at o are in agreement with the reported observations by a TSS level of 22 Brix, pH of 4.0 with maintaining the earlier workers. Although some variations observed in
Table 5. Changes in TSS, pH, alcohol yield, titrable acidity, ascorbic acid and total sugar of guava wine during the fermentation period of 192 hr with an interval of 24 hr at incubation temperature of 27oC, TSS 22oBrix and pH 4.0
Incubation TSS pH Alcohol yield Titrable acidity Ascorbic acid Total sugar period (hr.) (oBrix) (%) (%) (mg/100ml) (%) 0 22 4.0 0.0 0.79 237.5 19.17 24 17.8 3.93 2.7 0.89 217.2 17.3 48 13.10 3.89 4.4 0.97 179.1 13.2 72 11.6 3.81 6.8 1.06 154 10.7 96 8.6 3.74 8.6 1.19 127.6 7.8 120 7.2 3.71 10.5 1.28 112.7 6.1 144 5.7 3.66 11.8 1.36 102 4.2 168 4.3 3.61 13.2 1.47 94.3 3.42 192 4.3 3.60 13.2 1.48 94.0 3.40 * Values are average of triplicates
Table 6. Chemical composition* of guava fruit wine the values in this study might be due to the genetic variability of the strains used and fermentation conditions maintained. S.No. Constituents Amount In the present investigation, different 1. TSS (oBrix) 4.3 observations have been made on titrable acidity of 2. pH 3.61 guava wine at different TSS levels (18, 20, 22 and 24oBrix) under different pH conditions (3.0, 3.5, 4.0 and 3. Alcohol yield (%) 13.2 4.5) with different incubation temperatures (24, 27, 30 4. Titrable acidity (%) 1.47 and 33°C) at an optimum incubation period of 168 hr. The findings in the investigation revealed that titrable 5. Ascorbic acid (mg/100ml) 94.3 acidity varied to a great extent under different 6 Total sugar (%) 3.42 fermentation conditions. The observations (Table 4) * Values are average of triplicates indicated that the titrable acidity was found to be
294 maximum (1.79%) at a TSS level of 24oBrix, pH of 3.0 converted into alcohol and carbon dioxide. Similarly, with maintaining the incubation temperature of 33°C and pH of guava must got decreased due to increase in optimum incubation period of 168 hr. The value of titrable acidity as fermentation progressed. These titrable acidity was found to be lowest and recorded as observations also revealed that the total acidity and fixed 1.32% at a TSS level of 18oBrix, pH of 4.5 with acidity of wine increased as fermentation progressed maintaining incubation temperature of 30°C and due to the presence of organic acid formed as by- incubation period of 168 hr. Several workers have also product. Reddy and Reddy (2009) reported that upon reported the titrable acidity almost in the similar range guava must fermentation, sugar got decreased from (Divya and Kumari 2009; Reddy and Reddy 2009 ). 14.2 to 1.2%, acidity increased from 2.5 to 2.8% and Diwan and Shukla (2005) reported that guava wine ethanol increased up to 7.3%(w/v). Saveda and found to contain titrable acidity between 1.11 to 1.95%. Rodergues (2011) also reported that TSS level got Shankar et al. (2006) reported that total acidity and fixed decreased upon guava must fermentation. Kocher and acidity of wine increased as fermentation progressed Pooja (2011) reported that during the guava must due to the presence of organic acid formed as by- fermentation, pH and ascorbic acid got decreased up product. The findings obtained in this investigation to 3.6 and 83.6mg/100ml respectively and alcohol yield showed that these are in agreement with the reported increased up to 13.8%. Andri et al. (2012) observed observations made by earlier workers. Although some that with the increase in fermentation periods, sugar variations observed in the values in present concentration decreased and ethanol concentration got investigation might be due to the genetic variability of increased almost linearly when 0.5%(w/v) Baker yeast the strains used and culture condition maintained in the was used in the Jackfruit wine making procedure. The earlier studies. findings obtained in the present investigation showed that these are in agreement with the reported There was a gradual decrease in TSS level, pH, observations by earlier workers. Although some ascorbic acid and total sugar contents with a relative variations observed in the values in present increase in incubation period up to 192 hr. On the other investigation might be due to the genetic variability of hand, there was a gradual increase in alcohol yield and the strains used and culture condition maintained during titrable acidity with a relative increase in incubation the fermentation process. period upto 192 hr (Table 5). It was also observed that these changes became less pronounced after 168 hr Chemical composition of guava fruit wine was of fermentation. The similar observations have also also studied. The data presented in Table 6 on chemical been reported in the literature with some minor composition of guava fruit wine revealed that various variations in their values (Okoro et al. 2007; Alobo and important chemical constituents such as TSS, pH, Offonry 2009; Divya and Kumari 2009; Masyimi et al. alcohol yield, titrable acidity, ascorbic acid and total 2013). Shankar et al. (2006) reported that reducing sugar present in guava fruit wine were having the similar sugar and total sugar contents of guava must got composition as reported in the literature, although some decreased upon fermentation as sugars present are minor variation in the values were observed (Kocher
Table 7. Mean score values of sensory quality characteristics of guava fruit wine with maximum alcohol yield
Sample Code Sensory quality characteristics of guava fruit wine Colour Flavour Taste Overall acceptability A 8.4 8.1 8.0 8.2 B 7.8 7.6 7.7 7.8 C 7.1 7.0 7.4 7.3 SEm + 0.05 0.05 0.02 0.03 CD 5% 0.13 0.14 0.09 0.11
Sample A - with maximum alcohol yield (13.2%) Sample B - with second maximum alcohol yield (12.6%) Sample C - with third maximum alcohol yield (12.3%)
295 and Pooja 2011; Reddy and Reddy 2011). Kocher and desirable product (Swiegers et al. 2005). In modern Pooja (2011) reported that wine prepared from Panjab winemaking, specific yeast strains have been pink variety of guava contained 13.8% alcohol yield, preferentially used to guarantee the desired quality of 3.6 pH and 83.6mg/100ml ascorbic acid. Similarly, the product. Yeasts are the prominent organisms Reddy and Reddy (2011) also reported that guava wine involved in wine production and determine several contained 1.2% sugar, 4.5 pH, 2.8% acidity and 7.3% characteristics of the wine including the flavour by a alcohol yield. The findings obtained in the present range of mechanisms and activities (Fleet 2003). investigation showed that these are in agreement with the reported observations by earlier workers. In the References present investigation, the slight variation in the values of various chemical constituents observed in the guava fruit wine might be due to the genetic variability of the AOAC (1990) Official method of analysis, 23th Ed., Association strains used and culture condition maintained. In of official analytical chemists, Washington, DC addition to these, environmental conditions and other Adree M, Younis M, Farooq U, Hussain K (2010) Nutritional factors might have also played some role in influencing quality evaluation of different guava varieties. Pak J the composition of various constituents. Agri Sci 47(1) : 1-4 Alobo AP, Offonry SU (2009) Characteristics of coloured wine The sensory quality characteristics of guava fruit produced from Roselle Hibiscus sabdariffa) calyx wine (Table 7) revealed that guava fruit wine samples extract. J Inst Brew 115: 91-94 (A) were found to be more acceptable with respect to Amerine MA, Roessler EB (1965) Principles of sensory all the sensory attributes in comparison to samples 'B' evaluation of foods. Academic press, New York and 'C'. Guava wine (Sample A) was found to contain Andri CK, Sari DR, Pinandita APP, Retnowati DS, Budiyati 13.2% alcohol under optimum conditions of fermentation CS (2012) Preparation of wine from jackfruit viz. TSS 22oBrix, pH of 4.0, incubation temperature of (Artocarpus heterophyllus lam) juice using baker 27oC and incubation period of 168 hr. Many workers yeast: effect of yeast and initial concentrations. World have also reported the sensory quality characteristics Applied Sci J 16(9): 1262-1268 of fruit wine as the sensory quality analysis of wine is Attri BL (2009) Effect of initial concentration on the physico- an important parameter in determining its quality (Attri chemical characteristics and sensory qualities of cashew apple wine. Nat Prod Radiance 8: 374-379 2009). Pooja (2011) reported that guava wine prepared from three varieties (Panjab pink, Arka amuiya and Divya Kumari A (2009) Effect of different temperatures, timings and storage periods on the physico-chemical and Lacknow-49) had enhanced taste, aroma and flavor with nutritional characteristics of whey-guava beverage. aging of three month. The finding of earlier workers have World J Dairy & Food Sci 4(2): 118-122 shown that guava wine was acceptable by a panel of Diwan A, Shukla SS (2005) Process development for the judges indicating the possibility of using guava fruits production of clarified guava juice. J Food Sci Tech for commercial production for the growing market of wine 42: 245-249 in our country. Various reports have been published in Fleet H (2003) Yeast interactions and wine flavor. Int J Food the literature indicating the variation in the Microbiol 86: 11-22 physiochemical, processing and sensory quality Jain PK, Nema PK (2007) Processing of pulp of various characteristics of the guava fruit variety and processed cultivars of guava (Psidium guajava L.) for leather products (Jain and Nema 2007; Sharma et al. 2010 ). production. Agri Engg Int: the CIGR E J 9: 1-9 Jawahar A (1999) Studies on preparation of wine from guava Since the beginning of the 1980s, the use of juice. M.Sc. Thesis, MPKV, Rahuri (MH) Saccharomyces cerevisiae yeast starters has been Kocher GS, Pooja (2011) Status of wine production from guava extensively applied in the industrial and homemade (Psidium guajava L.): A traditional fruit of India. Afric beverage production processes. Currently, most of the J of Food Sci 5(16): 851-860 wine production processes rely on various strains of Musyimi SM, Sila DN, Akoth EM, OnyangoCM, Mathooko FM Saccharomyces cerevisiae that allow rapid and reliable (2013) The influence of process optimization on the fermentation, reduce the risk of sluggish or stuck fermentation profile of mango wine prepared from fermentation and prevent microbial contamination the apple mango variety. J Ani Plant Sci 17(3): 2600- (Romano et al. 2003). Yeast starter cultures that are 2607 specifically selected for the winemaking process on the OkoroCE (2007) Production of red wine from roselle (Hibiscuss basis of scientifically verified characteristics typically abdariffa) and pawpaw (Carica papaya) using palm- complement and optimise the raw material quality and wine yeast (Saccharomyces cerevisiae). Niger Food individual characteristics of the wine, creating a more J 25: 158-164
296 Okunowo WO, Okotore RO, Osuntoki AA (2005) The alcoholic Sevda SB, Rodriguess L (2011) Fermentative behavior of fermentative efficiency of indigenous yeast strains Saccharomyces strains using guava (Psidium of different origin on orange juice. Afr J Biotechnol guajava L.) must fermentation and optimization of 4:1290-1296 guava wine production. J Food Process and Technol Pooja (2011) Optimization of fermentation conditions for 2: 118-127 production of wine from guava (Psidium guajava L.). Shankar S, Dilip J, Narayana RY (2006) Fermentation of guava MSc Thesis Punjab Agricultural University Ludhiana pulp with grape grown yeast (S. cerevisae var. India ellipsoideus) for wine production. Ind J Hort 60: 171- Rangana S (1997) Hand book of analysis and quality control 173 for fruit and vegetable product Tata McGraw Hill Pub Sharma A, Sehrawat SK, Singhrot RS, Tele A (2010) Co Morphological and chemical characterization of Reddy LV, Reddy OS (2009) Production optimization and Psidium species. Pro Nat Bot Hor Agrobot Cluj 38: characterization of wine from mango (Mangifera 28-32 indica Linn.) Nat Prod Rad 8(4): 426-435 Swiegers JH, Bartowsky EJ, Henschke PA, Pretorius IS (2005) Reddy LVA, Reddy LPA (2011) Preliminary study on Yeast and bacterial modulation of wine aroma and preparation and evaluation of wine from guava flavour. Australian J Grape and Wine Res 11: 139- (Psidium guajava L.) fruit. Int J Food and Ferm 173 Technol 1(2): 261- 266 Romano PC, Fiore M, Paraggio M, Caruso M, Capece A (2003) Function of yeast species and strains in wine flavor. (Manuscript Receivd : 30.9.13; Accepted : 17.12.13) Int J Food Microbiol 86: 169-180
297 JNKVV Res J 47(3): 298-302 (2013)
Investigations on the nutritional characteristics of kodo millet based traditional fermented food by tribals of Madhya Pradesh, India
Deepali Agrawal, A. Upadhyay* and Preeti Sagar Nayak**
Krishi Vigyan Kendra Powarkheda (Hoshangabad) *Department of Food Science **Department of Plant Physiology Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482 004 (MP)
Abstract ischemic stroke, obesity, breast cancer, childhood asthma and premature death (Cade et al 2007). Minor Kodo (Paspalum scorbiculatum L.) is popular millet grown in millets are hardy and have a marvelous storability. The Madhya Pradesh. Tribals of Madhya Pradesh use kunaita (mud minor millets a group includes several food crops mill) for dehsking of kodo and get creamish white grain. In the namely finger millet, foxtail millet, proso millet, barnyard present study kodo based fermented food 'idli' was developed. millet and kodo millet. Kodo millet (Paspalum Idli was made with different proportion of kodo in place of rice scorbiculatum L.) generally used by Goand and Baiga (25, 50, 75 and 100%) and blackgram dhal and a control with tribe of Madhya Pradesh. They used kunaita (mud mill) rice and blackgram (100:50). Changes in pH and batter volume for dehusking of kodo and get creamish white grain they were note down before and after fermentation and also the feed their child with gruel of this kodo millet. Low content acceptability of 'idli' produced was ascertained and compared of protein and certain anti-nutritional factors of this food with the control. pH of the batter was found to decreased in all types of idli batter, whereas batter volume increased are causing malnutrition problem in children in tribal significantly after 16 hour fermentation at 300C. Sensory areas of MP. Consumption of cereals with legumes, age characteristics like appearance, colour, texture, flavor and old tested practice, take care of deficiencies of each overall acceptability were lower in kodo based 'idli', however other and make the dual more balanced. However, the product was found acceptable. Thus the neglected grain improvement in the quality of the diet can be realized can be utilized as value added product in terms of nutritional with simple inexpensive fermentation technology quality acceptability for all age group of people. (Agrawal et al. 2003). Hence the present study was conducted planned to find out the feasibility of the kodo: Keywords: Kodo, Idli, Fermentation, nutricereals black gram mixture for production of traditional fermented food 'idli'.
The Millets are a group of variable, small-seeded, annual grasses that are native to many parts of the Materials and method world. Millets provides a nutritious, staple source of millions of people in India. However, realizing the Rice, dehusked kodo and blackgram dhal purchased nutrient composition of the grains they are now locally, were washed and soaked separately in distilled considered as nutricereals. Millets helps to lower blood water. Idli was prepared by mixing of kodo with rice and glucose levels and improves insulin response (Lakshmi blackgram dhal in different ratio 100:00:50 (control), et al 2002). Whole grains like millet may have health 75:25:50, 50:50:50, 25:75:50 and 00:100:50 promoting effects equal to or even in higher amount respectively. Washed and soaked separately in water than fruits and vegetables and have a protective effect till they become soft according to different proportion. against insulin resistance, heart diseases, diabetes, The ingredients ground separately were mixed and
298 allowed to ferment for 16 hr at 370C. Rise in batter acceptability as per the hedonic rating mentioned (Table volume and change in pH was noted. The batter was 2). filled in idli pot and steam cooked. Total sugar and free sugar were estimated by Results and discussion Carrol et al. (1956) and Dubois et al. (1951) respectively, amino nitrogen by microkjeldhal digestion procedure as The chemical compositions of millet grains and their given in A.O.A.C. (1980) with the help of Pelican food products were found to be modified by Nitrogen Analyzer. Water soluble vitamin like vitamin fermentation. Therefore, millet grains are used to C was assayed by the methods given in Methods of produce different kinds of traditional fermented foods vitamin assay (1966). Calcium was estimated by using in developing countries in Africa and Asia. Fermentation systronic-128 flame photometer. Iron was determined is one of the processes that decrease the levels of by atomic absorption spectrophotometer. Sensory antinutrients in food grains and increase the protein evaluation test of 'Idli' was done by the procedure given availability, in vitro protein digestibility (IVPD), and by Amerine et al. (1965) using 9 point hedonic scale for nutritive value. Fermented foods like Dosa and Idli are like, dislike taking into account the various quality popular in many parts of India. These are very common attributes like colour and appearance, shape and size, as breakfast foods and even as the evening meals in texture, taste and overall acceptability. The panel was southern part of the country. Millet is widely used as supplied with the basic information about the product one of the ingredient for these kinds of fermented foods. and was asked to write down the result on score card. It not only improves the taste but at the same time The ratings were given on the sensory attributes like enriches the food value in terms of protein, calcium and appearance, colour, texture, taste, flavour and overall fibre. All the combination of fermented food items was found Table 1. Combination of rice, kodo and blackgram dhal to be acidic in nature and pH evaluated was found to for preparation of idlis be in between 4.3 to 4.6 (Table 3). The acidic nature of these products is probably due to the production of Treatment Rice De husked Black gram organic acids during fermentation by acid producing (%) kodo (%) dhal (%) microorganisms, as the fermentation is carried out under unhygienic and uncontrolled dominance of these genera T (control) 100 00 50 1 in other cereal based beverages has also been
T2 75 25 50 discussed earlier (Bassapa 2002; Muyanja et al. 2003). Among all the combination studied Rice: Kodo: Black T 50 50 50 3 gram dhal (00:100:50) was found to be most acidic having pH value 4.3 while Rice: Kodo: Black gram dhal T4 25 75 50 (100:00:50) was found to have higher pH value i.e. 4.6.
T5 00 100 50 Venkatasubbaiah et al. (1984) reported that lowering of pH (4.20 to 4.82) to be a common feature in idli batter after fermentation. According to Steinkraus et al. (1967) Table 2. Rating of Idli using nine point Hedonic scale
Like extremely : 9 Table 3. Physico-chemical characteristics of Idli Batter Like very much : 8 Ingredients pH Batter volume(ml) Like moderately : 7 (Rice: Kodo: Unfermented Fermented Unfermented Fermented Black gram dhal) Like slightly : 6 100:00:50 6.5 4.6 100 195 Neither like nor dislike : 5 75:25:50 6.3 4.5 100 189 Dislike slightly : 4 50:50:50 6.2 4.5 100 182 Dislike moderately : 3 Dislike very much : 2 25:75:50 6.3 4.4 100 182 Dislike extremely : 1 00:100:50 6.3 4.3 100 178
299 idlis prepared from batter in the pH range of 4.1-5.3 The mean acceptability scores obtained by the had a satisfactory flavour when steamed. The results sensory evaluation of millet idlis are in Table 5. Among showed that the pH of all combination of the batter was the different variations standard idli has got a highest within this ranges after 16 hours fermentation. scores of 9.0 followed by the variation mixed idli with a Nagarathamma and Siddappa (1965) suggested a pH score of 8.2 and the least score 6.5 is obtained by the of 5.0 to be most an optimum for obtaining satisfactory idli. Kodo idli for the colour attributes. The texture attributes was found to be maximum for the standard with the score The combination of Rice: Kodo: Black gram dhal of 9.0 followed by the mixed idli (7.9). Regarding the (00:100:50) was found to have maximum value for Total taste attributes the highest score of 8.8 is obtained by Sugar, Free sugar, Vitamin C, Iron and minimum for the standard which is followed by the mixed idli with the Amino nitrogen and Calcium as given in the Table 4. The calcium and iron contents of the millets were score of 7.5. The overall acceptability scores of standard analyzed as these two minerals are of nutritional were found to be slightly higher (8.8) than the mixed importance in the diets of population who consume millet idli with the score of 7.0 and the lowest was obtained as staple food. Fermentation of idli batter has a by Kodo idlis (6.3). Although, colour and appearance significant effect on the increase of vitamins B, C and of millet idli were rated as less attractive compared to essential amino acids and in the reduction of anti rice idli, the products were acceptable. The white colour nutrients (Phytate-50% hydrolyzed), enzyme inhibitors imparted on idli and any deviation from white colour and flatus sugars (Steinkraus 1983).
Table 4. Nutrient composition of fermented idli batter made from different proportion
Ingredients Total sugar Free sugar Amino nitrogen Vitamin C Calcium Iron (Rice: Kodo: (mg/g) (mg/g) (g) (mg) (mg) (mg) Black gram dhal) 100:00:50 55.2 4.25 0.14 5.28 39.4 5.58 75:25:50 51.3 3.23 0.14 5.10 40.6 5.93 50:50:50 52.4 2.69 0.15 5.20 48.3 5.29 25:75:50 50.62 2.24 0.16 5.10 55.3 5.25 00:100:50 48.40 2.16 0.17 5.10 65.1 5.15 S.Ed 0.82 0.92 0.02 0.91 0.88 1.05 CD@ 5% 1.82 2.05 0.04 2.03 1.96 2.34
Table 5. Mean score of quality attributes of Idli
Ingredients Parameters (Rice: Kodo: Black gram dhal) Colour Texture Taste Over all acceptability 100:00:50 9.0 9.0 8.8 8.8 75:25:50 8.2 7.9 7.5 7.0 50:50:50 7.2 7.0 7.0 7.0 25:75:50 6.8 7.0 6.8 6.8 00:100:50 6.5 6.8 6.6 6.3 S.Ed 0.85 0.78 0.76 0.82 CD@ 5% 1.88 1.75 1.69 1.84
300 has been reason for low mean score for idli based on esa fofHkUu ek=k esa pkaoy ds LFkku ij dksnks dk ¼25, 50, 75 ,oa kodo millets (00:100:50) which was natural dull cream 100½ ek=k ,oa mjn nky yh xbZ gSA fu;a=.k ds fy, ¼Control colour however kodo base idli were acceptable as indicated by the mean score of overall acceptability. sample½ pkaoy ,oa mjn nky ¼100:50½ yh xbZA blesa ih-,p- ,oa Similar results were found by Veena et al. (2004). The dksnks dh ek=k ¼Value½ dks fHkUu & fHkUu eki esa Mkydj fd.ou ls idli batter comprises lactic acid bacteria and causes an iwoZ o ckn esa mldh fd.ou voLFkk dks ns[kk x;k ,oa mldh improvement in the nutritional, textural and flavour Lohdk;Zrk dks Hkh tkuk x;k fu;a=.k ds lkFk Hkh rqyuk dh xbZA 30 characteristics of the final product. The sensory 0 attributes of idli (final product) prepared from the Maize C ij 16 ?kaVs esa bMyh ds ?kksy ¼Batter½ dk PH tSls&tSls de and rice based batter related well to the determined gksrk x;k oSls&oSls mldh Qwyus dh ek=k c<+rh xbZA rS;kj ?kksy esa flavour profile (Agrawal et al. 2003). 30 0C ij 16 ?kaVs ds fd.ou ds ckn dkQh o`f) gqbZ] tcfd ?kksy ds ih,p] bMyh vkVk ds lHkh izdkjksa esa deh ikbZ xbZA mifLFkfr] jax] Conclusion cukoV] Lokn vkSj lexz Lohdk;Zrk laosnh fo'ks"krkvksa bMyh vk/kkfjr dksnks esa de Fks] ysfdu mRikn Lohdk;Z fd;k x;k FkkA lHkh vk;q lewg In the developed countries, due to large obesity problem and also for maintaining normal and sound health, ds fy;s iks"kd rRoksa dh xq.koRrk Lohdk;Zrk ds ekeys esa mRikn tksM+h different formulations and activities are coming up, ds :Ik esa bl izdkj ds misf{kr vukt dk mi;ksx fd;k tk ldrk gSA specially delivering soluble fibres to the consumers via different foods like cereals and cereal products References containing antioxidants. The ethnic small millets proved to have a good scope for enhancing nutrition security, Agrawal Deepali, Pandey Sheela, Gupta OP (2003) marketing and income generation of community Biochemical and organoleptic studies on the members, particularly rural women. The chemical feasibility of maize based fermented food. JNKVV changes during fermentation include an increase in free Res J 37(2):25-27 sugar indicating partial breakdown of carbohydrates. Amerine MA, Pangborn, RM Rosster, EB (1965) Principles of An increase in amino nitrogen indicates a similar sensory evaluation of foods. Academic Press New breakdown of proteins. It is likely that the intermediates York. 275 in these conversions such as simpler starches, dextrin, AOAC (1980) Official methods of analysis, 23rd Ed. maltose and peptides also increase. Increase in the Association of Official Analytical Chemists, number of bacteria also involved in increasing niacin, Washington, DC riboflavin and vitamin C. These changes serve to make Bassapa SC (2002) Investigations on Chhang from finger idli more nutritious, palatable and digestible which is millet (Eleucine Coracena Gaertn.) and its commercial prospects. Indian Food Ind 21(1) 46-53 beneficial for children. To combat the malnutrition in terms of protein, calorie and micro nutrient problems, Cade JE, Berley VJ, Greenwood DC (2007) Dietary fibre and risk of breast cancer in the UK womens's Cohort the use of kodo millets with pulse are effective choice study. Int J Epidemiol 36:431-438 in tribal areas in domestic preparation of fermented food Carrol MV, Lonely RN, Roe TJ (1956) Determination of total idli are effective choice in tribal areas. Formulation also sugar in cereals. J Biochem 220:580 showed to be a highly strategic intervention in the Dubois MK, Gilles MK, Hamilton PA, Robers F, Smith W (1951) popularization of nutritionally and technologically rich A colorometric method for the determination of sugar. local crops which are currently largely neglected and Nature 168:167 underutilized. Lakshmi KP, Sumathi S (2002) Effect of consumption of finger millet on hyperglycemia in non-insulin dependent diabetes mellitus (NIDDM) subjects. Food Nutr Bull Paspalum scorbiculatum L. dksnks ¼ ½ e/;izns'k esa mxkbZ tkus 23(3) 241-245 okyh yksdfiz; Qly gSA e/;izns'k ds vkfnoklh dksnks dks dquSrh Methods of Vitamin assay (1966) The association of vitamin ¼feV~Vh dh pDdh½ esa ihykiu fy;k gqvk lQsn vukt izkIr djrs gSA Chemists, Interscience Publishers, New York, 3rd orZeku v/;;u esa dksnks ls cuh fd.ou bMyh rS;kj dh xbZ gSA bMyh edn; 287
301 Muyanja BK, Naruhus JA, Langsrud T (2003) Isolation, characterization and identification of lactic acid bacteria from Bushera: A Ugandan traditional fermented beverage. Food Microbiology 80(3) 201- 210 Nagarathanamma K, Siddappa GS, (1965) Canning of idli. J Food Sci Tech 2(3)132 Steinkraus KH, Vanveen AG, Thiebean OB (1967) Studies on idli-An Indian fermented black gram rice food. Food Technol 21: 916-919 Steinkraus KH (1983) Handbook of Indigenous Fermented Foods. Marcel Dekker Inc, 304 New York. Veena B, Bharati V, Chimmad Rama, Naik K, Malagi Usha (2004) Development of Barnyard Millet Based Traditional Foods in barnyard millet based idli. Karnataka J Agri Sci 17 (3) 522-527 Venkatasubbaiah P, Dwarakanath ET, Murthy V (1984) Microbiological and Physico-chemical changes in idli batter during fermentation. J Food Sci Tech 21: 61
(Manuscript Receivd : 20.8.13; Accepted : 30.12.13)
302 JNKVV Res J 47(3): 303-307 (2013)
Effect of different micronutrients on the incidence of major sucking insect pests of tomato
A.S. Thakur, S. K. Barfa, Amit Kumar Sharma and R. Pachori Department of Entomology College of Agriculture Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP) Email : [email protected]
Abstract like leaf curl, mosaic etc. Nymphs and adults both cause the damage by sucking the sap from leaves and tender The study on effect of different micronutrients on the incidence parts of the plants. The severe infestation resulting in of sucking pests of tomato crop during the rabi 2006-07, premature curling of leaves and plant become unable revealed that mixture of all micronutrients was found most for flowering and fruiting. The losses caused by these effective treatment in reducing the population of white fly (0.83 insects and diseases varies from 50 to 92%. Various white fly/10cm twig/plant) which was at par with Manganese methods are used for controlling the insect pests in sulphate 100 ppm (1.11 white fly/10cm twig/plant) while tomato like chemicals, botanicals, use of resistance/ remaining treatments (T1, T2, T3, T4, T5 and T7) were found tolerance varieties etc., of which only the practical at par to each other but superior to untreated control in respect method to control the pests is by chemical insecticides. to white fly population. In case of aphid the treatments of However, it leaves a film of persistence insecticidal Manganese sulphate 100 ppm (1.05 aphid/10cm twig/plants) and mixture of all micronutrients (1.22 aphid/10cm twig/plants) poison over the foliage and fruits which is hazardous were found most effective in reducing the aphid population and uneconomical too. Therefore alternative methods and at par to each other. The next effective treatments in like application of micronutrients are cheap and order of effectiveness were Ferrous sulphate 100 ppm, affordable for small scale farmers compared to synthetic Commercial formulation-Multiplex 100 ppm, Zinc sulphate 100 pesticides. Micronutrients are safer to use and they ppm, and Copper sulphate 100 ppm indirectly affect different insect pests. Keeping these facts in view, the present study was under taken to Keywords: Micronutrients, sucking pests, evaluate the effect of different micronutrients on the management, tomato incidence of major sucking pests of tomato.
Tomato (Lycopersicone esculentum) is one of the most Materials and methods popular and widely grown vegetable in the world. It is grown in all seasons and is the second most important The field experiment was conducted during rabi season crop among vegetables. The total area under tomato in of the year 2006-07 in Randomized Block Design (RBD) country is assessed 4.66 million ha with a total yield of with three replications at the JNKVV research farm, about 8.272 million tones and an average yield of 16- Jabalpur. The tomato variety Jawahar Tomato 99 was 17 tones/ha In Madhya Pradesh, tomato is cultivated in grown. The micronutrients (Boric acid 100 ppm, Zinc an area of 23 thousand ha. with an average yield of sulphate 100 ppm, Ammonium molybdate 50 ppm, about 0.52 million tones. Tomato farming for profit cannot Copper sulphate 100 ppm, Ferrous sulphate 100 ppm, imagined without adequate protection from principle Manganese sulphate 100 ppm, commercial formulation enemies such as insects, fungus, weeds and mites. multiplex 100 ppm and Mixture of all micronutrients) Among the these enemies insect pests are major were applied three times as foliar application using Foot because all parts of the plant offer food, shelter and Sprayer. Total quantity of spray solution required for reproduction site for them. Whitefly and aphid are the uniform coverage of the crop on per plot basis was major sucking pests of tomato. Both these pests are worked out for each treatment separately. The polyphagous in nature and vector of many viral diseases treatments were prepared by mixing desired quantity 303 1.8 1.83 1.99 2.27 1.83 1.11 1.99 0.83 3.61 0.05 0.17 (1.52) (1.57) (1.66) (1.52) (1.52) (1.26) (1.57) (1.15) (4.11) Overall Overall mean 2.00 2.33 2.00 2.00 2.00 1.33 2.00 1.00 4.33 0.15 0.45 after (1.55) (1.55) (1.58) (1.58) (1.34) (1.55) (1.16) (2.19) ( 1.67) 7th 7th day Third spray 1.00 1.66 1.33 1.33 1.66 1.00 1.66 0.66 3.33 0.13 0.41 after (1.16) (1.46) (1.34) (1.34) (1.43) (1.16) (1.46) (1.04) (1.95) 3rd day 2.33 2.00 4.00 2.33 2.00 1.33 2.33 1.33 3.33 0.12 0.38 after (1.67) (1.55) (2.11) (1.67) (1.67) (1.34) (1.67) (1.34) (1.95) 7th 7th day Second Second Spray 1.66 2.66 3.66 1.66 2.66 1.33 2.33 0.66 4.33 0.10 0.31 after (1.46) (1.77) (1.85) (1.46) (1.77) (1.34) (1.67) (1.04) (2.19) 3rd day 2.33 1.33 2.00 2.33 1.33 0.66 1.66 0.66 3.33 0.13 0.41 after (1.67) (1.34) (1.55) (1.67) (1.34) (1.04) (1.46) (1.04) (1.95) 7th 7th day White fly population on 10 cm/ twig/ plant First Spray 2.00 2.00 1.66 1.33 1.33 1.00 2.00 0.66 3.66 0.15 0.45 after (1.55) (1.55) (1.46) (1.34) (1.34) (1.22) (1.58) (1.04) (2.03) 3rd day NS 2.66 2.33 3.00 2.33 2.66 3.00 2.66 3.33 3.00 0.97 (1.77) (1.67) (1.85) (1.67) (1.77) (1.85) (1.76) (1.94) (1.85) Pre Treatment Pre 50 100 100 100 100 100 100 100 ppm Dose in Effect of different micronutrient on the incidence of tomato fly white - Boric acid - Zinc sulphate Ammoniummolebdate - - Copper sulphate - Ferrous sulphate - Manganese sulphate - Commercial formulation (Multiplex) - Mixture of all micronutrients - Control 1 2 3 4 5 6 7 8 9 Table 1. Table Treatments T T T T T T T T T S.Em+ C.D. at 5% ()= Figures in parenthesis are arcsin transformed values
304 2.66 2.11 2.71 2.11 1.83 1.05 1.94 1.22 6.27 0.04 0.14 (1.77) (1.61) (1.79) (1.61) (1.52) (1.24) (1.56) (1.31) (2.60) Overall Overall mean 1.66 2.66 2.00 2.33 2.00 1.00 1.66 1.00 5.00 0.15 0.47 after (1.46) (1.77) (1.55) (1.67) (1.55) (1.22) (1.46) (1.22) (2.33) 7th 7th day Third spray 1.00 1.33 1.33 1.33 2.00 0.66 1.66 0.66 5.33 0.12 0.38 after (1.16) (1.34) (1.34) (1.34) (1.55) (1.04) (1.46) (1.04) (2.40) 3rd day 2.66 2.66 5.66 3.00 2.66 2.00 2.66 2.00 7.00 0.17 0.52 after (1.77) (1.73) (2.47) (1.85) (1.76) (1.67) (1.76) (1.67) (2.72) 7th 7th day Second Second Spray 1.33 2.00 3.00 2.00 2.00 1.33 2.33 1.00 6.00 0.16 0.50 after (1.34) (1.67) (1.85) (1.67) (1.67) (1.34) (1.67) (1.16) (2.53) 3rd day 4.00 1.66 1.66 1.33 1.00 0.66 1.33 1.00 8.00 0.17 0.53 after (2.11) (1.43) (1.46) (1.34) (1.16) (1.04) (1.34) (1.16) (2.90) Aphid Aphid population on 10 cm/ twig/ plant 7th 7th day First Spray 5.33 2.33 2.66 2.66 1.33 0.66 2.00 1.00 6.33 0.17 0.57 after (2.40) (1.64) (2.77) (1.76) (1.34) (1.04) (1.55) (1.16) (2.60) 3rd day NS 4.66 5.00 5.33 5.33 5.00 5.33 5.66 5.00 6.00 0.30 (2.26) (2.30) (2.37) (2.40) (2.33) (2.40) (2.44) (2.22) (2.48) Pre Treatment Pre 50 100 100 100 100 100 100 100 ppm Dose in Effect of different micronutrient on the incidence of tomato aphid - Boric acid - Zinc sulphate Ammoniummolebdate - - Copper sulphate - Ferrous sulphate - Manganese sulphate - Commercial formulation (Multiplex) - Mixture of all micronutrients - Control 1 2 3 4 5 6 7 8 9 Table 2. Table Treatments T T T T T T T T T S.Em+ C.D. at 5%) ()= Figures in parenthesis are arcsin transformed values
305 of water for each plot separately. The crop was sprayed oviposition and corn earworm larval growth rates were thrice with each of the micronutrient at an interval of 7 higher on the vigorous plants and lower on the punched. days on the appearance of the pests. The observations Berlinger and Wermelinger (2001) also reported that were recorded on the number of aphids and white flies the plant nutrient have their impact on insect growth a day before the spray and 3rd, and 7th day after and development. They studied life history parameters spraying. The observations on white flies were taken of white fly and reported that the longevity and fecundity on one selected twig of 10 cm in each 5 randomly increased with higher nitrogen level in the nutrient selected plants. These twigs were covered carefully with solution, whereas the developmental time decreased. transparent polythene bags. The number of nymph and Over all growth was faster on high nitrogen plants than adults were counted at each twig. The population of on low nitrogen plants. El Rafie (2000) also reported aphid was recorded at 10cm/twig on 5 randomly that the plants treated with high levels of nitrogen selected plants from each plot. (ammonium sulphate 21% nitrogen) had increased numbers of Bemisia tabaci and decreased yields. A mixture of moderate levels of nitrogen with potassium Result and discussion sulphate and phosphorous resulted in low population of B. tabaci and increased yield. Chatterjee et al. (2013) White fly reported that significant reduction in whitefly population was observed in treatments containing higher amount of FYM or vermicompost as compare to sole inorganic The pre-treatment observations indicated non- fertilizers significant differences among the experimental plot in respect to white fly population (ranged between 2.33 to 3.33 white fly/ 10 cm twig/ plant). All the micronutrients Aphid were found to be significantly superior over untreated control in reducing white fly population (Table1). The The pretreatment observations indicated non-significant mean white fly population in different treatments differences among the experimental plots. The aphid revealed that the treatment Mixture of all micronutrients population was in range of 4.66 to 6.00 aphid/10cm twig/ (0.83 white fly/10cm twig/plant) was found most effective plant (Table 2). All the micronutrients had their impact in reducing white fly population which was at par with on aphid population and they were found significantly Manganese sulphate @ 100ppm (1.11 white fly/10cm superior over untreated control in reducing the aphid twig/plant) while remaining treatments were found at population. Among the micro nutritional treatments the par to each other in respect to white fly population. The treatment of Manganese sulphate @100 ppm was found highest number of white fly population was recorded most effective in reducing the aphid population (1.05 from the untreated control plot (3.61 white fly) (Fig. aphid/10cm twig/plants) which was at par with Mixture 1).The result is conformity with the result of Inbar et al of all the micronutrient (1.22 aphid/10cm twig/plant). The (2001), they reported that leaf minor feeding &
4 7
3.5 6 3 5 2.5 4 2 1.5 3 cm twigs/plant cm 1 twigs/plant cm 2 0.5 1 No. of nymphs & adults/10 & nymphs of No. No. of nymphs & adults/10 & nymphs of No. 0 0 T1 T2 T2 T4 T5 T6 T7 T8 T9 T1 T2 T2 T4 T5 T6 T7 T8 T9 Treatments Treatments Fig 1. Effect of diffenet micronutrient on incidence of Fig 2. Effect of different micronutrient on incidence of tomato whitefly tomato aphid
306 Pic. 1 White fly infestation on tomato leaf Pic. 2 Aphid infestation on tomato leaf next effective treatments in order of effectiveness were References Ferrous sulphate 100 ppm, Commercial formulation Multiplex 100 ppm, Zinc sulphate 100ppm, and Copper sulphate 100 ppm, they were at par to each other. Berlinger M J, Wermelinger B (2001) N-nutrition of tomato plants affects life table parameters of the green Highest number of aphid population was recorded from house white fly. Mitteilungender- Schweizerishen- the untreated control plot (6.27 aphid/10cm twig/plant) Entomolgischen-Gesellschaft 74 (1-2): 69-75 (Fig. 2). Leite et al (1999) reported that there was a El Rafie (1999) Effect of different rates of (N, P and K) fertilizer direct relationship between mite infestation and the level on Bemisia tabaci Genn. Infestation on tomato and of phosphorous applied to the soil. Leite et al (1998) its effect on the yield. Egyptial J Agril Res 77 (3): recorded that increasing nitrogen and potash fertilization 1067-1073. increased the leaf miner oviposition rate on Inbar M, Doostdar H, Mayer RT (2001) Suitability of stressed Lycopersicon hirsutum. and vigorous plants to various insect hervivorus. Oikos 94 (2): 228-235 Leite GLD, Picano M, Zanuncio JC, Jham GN, Moura, MF o"kZ 2006&07 ds jch ekSle esa VekVj ds jlpwld dhVkas ¼lQsn (1999) Effect of the levels of fertilization on the eD[kh ,oa ekgq½ ds fu;a=.k gsrq lw{e iks"kd rRoksa ¼cksfjd ,flM 100 intensity of attack by Tuta absuluta in Lycopersicon esculentum. Manejo Integrado de plagas 53: 72-76 ih-ih-,e-] ftad lYQsV 100 ih-ih-,e-] veksfu;e ekWfyCMsV 50 Leite GLD, Picano M, Azevedo AA, Zurita Y, Marauini F (1998) ih-ih-,e-] dkWij lYQsV 100 ih-ih-,e-] Qsjl lYQsV 100 ih-ih- Oviposition and mortility of Tuta obsoluta on Lycopersicone esculentum. Menjo Integrado de ,e-] eSXuht+ lYQsV 100 ih-ih-,e-] O;kikfjd QkeZwys'ku eYVh plagas 49: 26-35 IYsDl 100 ih-ih-,e-] rFkk lw{e iks"kd rRoksa dk feJ.k½ dk Chatterjee Ranjit, Choudhuri Partha, Nripendra Laskar (2013) ewY;kadu fd;k x;k A mijksDr iz;kksx ls izkIr ifj.kkeksa ds vuqlkj Influence of nutrient management practices for minimizing whitefly (Bemisia tabaci Genn.) VekVj dh lQsn eD[kh ds fu;a=.k gsrq lw{e iks"kd rRoksa dk feJ.k population in tomato (Lycopersicon esculentum Mill.). Int J Sci Env Tech 2: 956 - 962 rFkk esXuht+ lYQsV 100 ih-ih-,e lokZf/kd izHkko'kkyh ik;k x;k A blh izdkj VekVj ds ekgq dhV ds fua;=.k gsrq eXuht lYQsV 100 (Manuscript Receivd : 30.8.13; Accepted : 19.12.13) ih-ih-,e & lw{e iks"kd rRoksa dk feJ.k lokZf/kd izHkko'kkyh fln~/k gq,A
307 JNKVV Res J 47(3): 308-311 (2013)
Efficacy of some new molecules against the infestation of bringal shoot and fruit borer (Leucinodes orbonalis Guenee)
R. Pachori, Sapna Tanve, Amit Kumar Sharma and A.S. Thakur Department of Entomology Colllege of Agriculture Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP) Email : [email protected]
Abstract The apparent loss of fruits has been reported to be varying from 20-90% in various parts of the country (Raju The study on the investigation of some newer insecticides for et al. 2007).Chemicals are widely used for managing managing brinjal shoot and fruit borer (Leucinodes orbonalis insect pests in brinjal but the use of inappropriate Guenee) was made during rabi 20011-12. Application of pesticides, incorrect timing of application and improper Emmamectin Benzoate 5 SG @ 200g/ha was significantly doses have resulted in high pesticides costs with little superior with the highest marketable fruit yield of 551.27q/ha, or no appreciable reduction of pest damage. Further it followed by Profenofos 50% EC @ 2000ml/ha (398.72q/ha) has been reported that due to indiscriminate use of which was at par with Rynaxypyr 20% EC @150ml/ha (394.56 insecticides, Leucinodes orbonalis has developed q/ha). The next in order of comparative effectiveness were resistance to the conventional toxic insecticides (Raju Pyriproxyfen 10% EC @ 500ml/ha (318.17 q/ha) and Difenthiuron 50% WP@ 600g/ha (316.66 q/ha). The least et al. 2007 Hegde et al. 2009). In addition, the residues effective insecticidal treatment was Pyriproxyfen 5% EC + of chemical pesticides on the edible parts are more than Fenpropathrin 15% EC @ 500ml/ha (243.28 Q/ha) and the the tolerable level (Jha et al. 2006). The present lowest yield 141.43 q/ha was recorded from the untreated investigation was made to test the efficacy of some control plots. newer insecticides for the effective management of bringal shoot and fruit borer. Keywords: Leucinodes orbonalis, Efficacy, insecticides, shoot and fruit borer, brinjal Materials and methods
The brinjal shoot and fruit borer, Leucinodes orbonalis The experiment was conducted at experimental field of Guenée is a potential pest. Brinjal plants are very much the Department of Entomology, Live Stock Farm, susceptible to insect attack right from seedling to final Adhartal, JNKVV, Jabalpur (M.P.) during rabi 2011-12., harvesting stage. Brinjal is attacked by 53 species of using randomized block design. The plot size was 3.6 x insect pests of which 8 are considered as major pests 2.4 m. The bringal crop ( A. K. 123) was transplanted in causing enormous damage to the crop in every season the fourth week of November.The treatments consisted in every year (Biswas et al. 1992 and Nayer et al. 1995). of spraying the crop for four times with Pyriproxyfen Among the major insect pests, brinjal shoot and fruit 10% EC (500ml/ha), Pyriproxyfen 5% EC + borer is the most destructive pest of brinjal in fenpropathrin 15% EC (500ml/ha), Difenthiuron 50% Bangladesh and India (Tewari and Sandana 1990). The WP (600gm/ha), Emmamectin Benzoate (Proclaim) productivity of brinjal in Madhya Pradesh is 0.07 t/ha 5%SG (200gm/ha), Rynaxypyr 20%EC (150ml/ha), against that of the country (0.06 t/ha), and world's Profenofos 50% EC (2000ml/ha) and untreated control. (16.90t/ha). Infestation of insect pests and its poor Fruit infestation by shoot and fruit borer was assessed management is the major cause of the low production by counting the total number of damage and healthy of brinjal in Madhya Pradesh. White fly (Bemicia tabaci), shoot/ fruit at each picking per plot. The percentage leaf hopper (Amrasca biguttula biguttula) and shoot and data on damaged fruits and fruit yield loss data were fruit borer (Leucinodes orbonalis) infestation have a transformed to arcsin transformation and statistically major role in lowering the marketable yield of the brinjal. analyzed as per the method advocated by Snedecor 308 and Cochran (1967). Similarly, data on healthy marketable fruit yield were also subjected to statistical
4.77 9.35 8.09 0.70 1.94 analysis at 5% level of significance. 12.95 15.71 14.33 19.48 (22.52) (24.40) (23.60) (16.60) (20.02) (19.08) (26.86) Overall Overall mean of four sprays Results and discussion
7 Fruit damage percentage 0.28 7.75 6.36 0.15 0.47 11.31 13.96 12.21 18.10 (3.05) (19.65) (21.94) (20.45) (16.16) (14.61) (25.18)
All the insecticidal treatments were significantly superior
6 over untreated control (Table 1). Emmamectin benzoate 1.12 8.47 7.29 0.68 2.10 12.21 14.59 13.56 14.89 (6.08)
(20.45) (22.45) (21.60) (16.92) (15.67) (22.70) (4.77%) was superior followed by Profenofos (8.09%) which was at par with Rynaxypyr (9.35%). The next best treatment was Pyriproxyfen (12.95%) which was also
5 at par with Difenthiuron (14.33%). Other treatments were 3.41 8.66 7.45 0.11 0.33 12.11 14.98 13.71 18.23 (20.36) (22.77) (21.74) (10.65) (17.11) (15.84) (25.28) least effective but superior over control. Similarly Sharma (2010) reported that Emmamectin benzoate was highly effective in terms of reduction in fruit 4 5.70 9.52 8.22 0.27 0.84
13.33 15.82 14.67 19.86 infestation, Sarkar et al. (2011) also reported that fairly (21.41) (23.44) (22.52) (13.81) (17.97) (16.66) (26.46) Pickings good and healthy yields of bringal was produced by the application of new generation pesticide molecules like
3 Rynaxypyr and Emmamectin benzoate. 6.62 9.72 8.56 0.40 1.23 13.56 15.93 14.74 21.74 (Mean of three replication) (21.60) (23.53) (22.58) (14.91) (18.17) (17.01) (27.71)
Per Per cent fruit damage per picking Healthy fruit yield 2 7.52 9.12 0.38 1.17 14.03 16.96 15.63 10.57 20.32
(21.99) (24.32) (23.29) (15.99) (18.97) (17.58) (26.79) Different treatments were found to have an effect on the yield of marketable fruits of brinjal (Table 2). The marketable fruit yield ranged from 141.43 to 551.27 q/ 1 ha. The maximum fruit yield of 551.27 q/ha was recorded 8.72 9.62 0.14 0.43 14.11 17.45 15.81 10.73 23.49 (22.07) (24.69) (23.43) (17.18) (19.12) (18.07) (28.99) from the plot treated with Emmamectin benzoate was found significantly superior over other treatments. It was followed by Profenofos 50% EC (398.72q/ha) which was at par with Rynaxypyr 20 EC (394.56 q/ha). Similar NS Pre- 0.44 23.31 23.47 24.11 24.04 24.35 24.52 24.64 (28.87) (28.97) (29.41) (29.36) (29.57) (29.68) (29.76) treatment
Table 2. Mean marketable fruit yield in different insecti-
600g 200g cidal treatments 150ml 500 ml500 ml500 2000 2000 ml Dose/ha Treatments Dose/ha Av yield /ha (q)
T1 Pyriproxyfen 10% EC 500ml 318.17
T2 Pyriproxyfen 5% + Fenpropathrin 15% 500ml 243.28
T3 Difenthiuron 50% WP 600g 316.66
T4 Emmamectin Benzoate 5 SG 200g 551.27
T5 Rynaxypyr 20% EC 150ml 394.56
T6 Profenofos 50% EC 2000ml 398.72 Fruit infestation (%) in different insecticidal treatments T7 Control 141.43 SEm+ 2.19 CD at 5% 6.06 Table 1. Table Treatments 10% Pyriproxyfen EC Pyriproxyfen 5% +Fenpropathrin 15% Difenthiuron 50% WP %SG Emmamectin 5 Benzoate 20% Rynaxypyr EC Profenofos 50% EC Control SEm+ CD at 5% () Figure in parenthesis are arcsin transformed values
309 Healthy fruits Damage fruit
Fruit damage by shoot and fruit borer Larva of shoot and fruit borer
310 finding have been reported by Suganya Kanna et al. Hegde JN, Girish R, Chakravarthy AK (2009) Integated (2005), Dutta et al. (2007) and Sarkar et al. (2011).The management of brinjal shoot and fruit borer, next in order of comparative effectiveness were Leucinodes orbonalis (Guen.). Proceeding Pyriproxyfen 10% EC (318.17 q/ha) and Difenthiuron International Conference on Horticulture on "Horticulture for Livelihood Security and Economic (316.66 q/ha). The least effective insecticidal treatment Growth", November 9-12, 2009, Bangalore University was Pyriproxyfen 5% EC + Fenpropathrin 15% EC of Agricultural Science 1103-1107 (243.28 Q/ha) and the lowest yield 141.43 q/ha were Jha SK Jaikrishnan S, Gopal Madhuban (2006) Persistence recorded from the untreated control plots (Fig. 1). of chloropyrifos on egg plant for the management of shoot and fruit borer. Ann Pl Protec Sci 14:116-118 o"kZ 2011&12 dh joh ekSle esa cSaxu ds ruk ,oa Nsnd dhV ds Nayer KK Ananthakrishnan TN, David BV (1995) General and Applied Entomology. 11edn. Tata McGraw- Hill fu;s=.k gsrq ,ekdsfDvu csatk,V 5 ,l-th- izksQsuksQkl 50% bZ-lh- pub Co Ltd 4/12, New Delhi 557 p ] jkbusfDlikj 20% bZ-lh-] ikbjhizkDlhQsu 10% bZ-lh-] MkbQsuF;wjkWu Raju SVS Bar UK Shankar Uma, Kumar Sailendra (2007) Scenario of infestation and management of eggplant 50% MCyw ih- ,oa ikbjhizkDlhQsu 5 $ QsuizksisfFkzu 15% bZ-lh- shoot and fruit borer, Leucinodes orbonalis (Guen.) dk ewY;kadu fd;k x;k izkIr ifj.kkeksa ds vuqlkj ,ekesfDVu csatks,V in India. Resis Pest Manag. N Let 16(2):14 5 ,l-th- 200 xzke@gs- cSxu ds ruk ,oa Qy Nsnd dhV ds izdksi Sarkar Sudarshan, Chakraborti, Kanti P (2011) Management of Leucinodes orbonalis Guenee on eggplants during dks fu;af=r djus esa lokZf/kd izHkko'kkyh ik;k x;k rFkk blds mipkj the rainy season in India. J Pl Protec Res 51(4) : Lo:i cSxu dh 551-27 fdo-@gs- mit izkIr gqbZ A f}rh; izHkko'kkyh 325-328 dhVuk'kd ds :i esa izksQsuksQkl 50% bZ-lh- 2000 fe-yh-@gs- Sharma Anil (2010) Bioefficacy of insecticides against Leucinodes orbonalis on brinjal. J Env Bio 31(4) : ik;k x;k ftles mipkj }kjk 398-72 fdo-@gs- mit izkIr gqbZ A 399-402 U;wure mit 141-43 fDo-@gs- vumipkfjr fu;a=.k ls izkIr gqbZA Snedecor GW, Cochran WG (1967) Statistical Methods, Oxford and IBH Publishing Company, New Delhi 1- 292 Reference Suganya Kanna S, Chandra Sekaran S, Regupathy A, Stanly J (2005) Field efficacy of emamectin 5 SG against tomato fruit borer, Helicoverpa armigera Pestology Biswas GC, Sattar MA, Seba MC (1992) Survey and 4: 21-22 monitoring of insect pests of brinjal Khagrachari Hilly Region. pp: 40-42. Annual Report 1991-92, Entomol Tewari GC, Sandana HR (1990) An unusual heavy Div BARI Joydebpur Gazipur parasitization of brinjal shoot and fruit borer, Leucinodes orbonalis Guen by a new braconid Dutta NK, Alam Nasiruddin MS, Das M, Munmun AK (2007) parasite. Ind J Entomol 52(2): 338-341 Efficacy of new chemical insecticides against brinjal shoot and fruit borer L. orbonalis (Guen). J Subtrop Ag. Res and Dev 5(3) : 301-304. (Manuscript Receivd : 30.8.13; Accepted : 19.12.13)
311 JNKVV Res J 47(3): 312-314 (2013)
Insect pest complex on Acacia
H. Dayma and R. Bajpai Department of Forestry College of Agriculture Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract The investigation was laid out in Randomized Block Design with three replication. In a Randomized Block Design each replication was divided in 30 plots Acacia nilotica is an important species under agroforestry system. It contributes for railway slipper, heavy construction to the different provenance of Acacia nilotica. Seed were etc. It is attract by wide spectrum of insect pest. In the present collected on the basis of phenotypic characters/yield study 30 provenance were evaluated against insect pest under per tree. To note the pest complex and incidence of insect natural field conditions. The results revealed that nine insect pest on Acacia nilotica the observation were recorded pest were found associated. Maximum and minimum at weekly interval in the field conditions starting from infestation was recorded on treatment Mashra khurd Laitpur the first week of August at different stage of plant/crop & Chsistoor Bhaswara Road Warda i.e. 72.4 and 40.4 growth up to 4th week of November on the five randomly respectively. selected plants.
[Acacia nilotica, provenances, infestation] Key words: Results and discussion
The National Forest cover is about 78.29 m/ha or Prevalence of insect pest complex on Acacia approximately 23.81% of total land covers. Acacia nilotica is a tree species largely belonging to the plantation, Agroforestry system, and homestead Nine insect pests were recorded on thirty provenances, plantation, which are mostly artificial systems of four have been found major that includes Bag worm ecosystem therefore the tree is prone to damage by (Eumeta crameri) Westwood (Lepidoptera: Psychidae), insect pest and disease. It is therefore, it is necessary Green beetle, (Mimela junii). (Coleoptera : to determine all damaging agency and their control Scarabeidae), Webworm, (Ethmia hiramella) measure for obtaining maximum production from forest (Lepidoptera : Ethmiidae), Hairy caterpillar, (Callitera and plantation of babul. There is little information grotei) Moore (Lepidoptera: Tortricidae), However, Green available about insects and diseases impacting forests bug, Coreidae Leach. (Hemiptera : Coreidae), and the forest sector. Acacia nilotica is the most valuable Geomatrid caterpillar, Ascotis infixaria Bagnall timber-producing plant species. It contributes an (Thysanoptera: Thripidae), Black carpenter bee, estimated 40-50 percent to the total timber production. Xylocopa latipes. Drury Hymenoptera : Apidae ), Larvae The tree occurs in pure, even age stands which have of butterfly, Lymantria incerta. (Lepidoptera : been artificially regenerated by direct seeding in flood Lymantriidae), Tree hopper, Oxyrachis tarandus plains. (Homoptera: Membracida) Successional investigations revealed that Materials and methods bagworm was observed first, followed hairy caterpillar, web worm, green beetle, tree hopper and butterfly of limitaria, during the month of November. Pillai and Gopi The field investigation was conducted at Dusty Acre (1984) reported the web worm larvae as a pest of foliage Research Farm, Department of Forestry, Jawaharlal and tender bark. Singh et al (1989) listed 6 species of Nehru Krishi Vishwa Vidyalaya, Jabalpur (M.P.) during Scarabaeid beetle on Acacia nilotica viz; C.scabrater, Kharif 2011-12 under the AICRP Project. 312 Pteroma playgiophleps, Clyta succinata, Diapromorpho Seasonal Incidence and Population Dynamics turcia, Dereadus denticollis, Homoeoserus signatus, Cysocories purpureous, Acrida lugubris and Orthacris Maximum and Minimum infestation recorded during the ruficarnis as major pest. They reported Araecerus period of observation by the major insect was in the fascuculater as a major pest of seeds of Acacia nilotica. treatment Mashra khurd Laitpur & Chsistoor Bhaswara Maximum infestation was recorded during October. Road Warda that is 72.4 % and minimum 40.4 % Beeson (1941) recorded larvae of Selpa celtis feeding respectively the maximum average temperature and on saplings in and young plantation during rainy season. humidity recorded during the month of November was Pillai and Gopi (1989) reported Lepidoptera as a major 30.9 and 88% similar work has been by El- Atta and order causing infestation. Abdel nour (1995) at lambwa forest Sudan. The effect of larvae of (Heteroropsylla incisa) was assessed on the diameter at breast height tree height volume and Acacia nilotica provenances collected from five Table 1. on mean annual increment of acacia. Over 4 year period different states there was 30 % reduction in dbh 21 % decrease in height growth. 54 % decrease in volume and 60 % decrease PT1 Mashara Khurd Jakhara Lalitpur UP in mean annual increment under condition of Sudan. PT2 Ragoli After Ramoli station sagar MP Maxine F- Miller (1993) recorded damage by Bruchid PT3 Gadhakota after river Damoh MP beetle on seeds from 4-100 % germination percentage of the seed in the range of 1-6 %. Banga (1999) recorded PT4 Kumaria Parsoria Damoh MP 62 and 55 % damage by insect borer i.e. Cerconata PT5 Majoli to tihar Jabalpur MP anninella and Trigonaspini Rohanar et al (1999) PT6 Choubatia mandla MP recorded more than 95 % damage by Bruchid beetle PT7 Mangoli Cijara Mandla MP PT8 23 km before Nagpur MS Population dynamics PT9 Chsistoor Bhaswara Road Warda MS Maximum population was of web worm and Hairy PT10 Anandwadi Bhaswara Road Warda MS caterpillar, Webworm was recorded during month of May PT11 Agril. university pt. Buldhana MS and green beetle was recorded during July and August PT12 Kolarigram after akola buldhana MS month. The period of infestation, population deviation PT13 Rustampur Pandhana Khandwa MP was maximum temperature/humidity was 310c and 90%) respectively. Walter (1994) finding indicated that PT14 Dasooda Uniyalfarm Indore MP adaption and ecology must be considered in each PT15 Mangalia Devas Road Indore MP special species present which may vary with changing PT16 Abhaypur Shajapur MP environmental condition form area to area and from time to time. Jayanthi et al. (2006) concluded that pest PT17 Shantinagar Bhopal MP incidence was not influenced by plant phenology. PT18 Purvalia Bhopal MP PT19 Shyampur Sehore MP —f"k okfudh esa vdsf'k;k fuyksfVdk o`{k dk ,d egRoiw.kZ LFkku gSaA] PT20 Penchi Guna MP bldh ydM+h jsyos rFkk fuek.kZ ds mi;ksx esa ykbZ tkrh gSaA dhVksa dk PT21 Badarvas Shivpuri MP vkd'kZ.k bl o`{k cgqr vf/kd ik;k x;k gSaA 'kks/k dk;Z ds nkSjku PT22 Hal Colum Nasik MS vdsf'k;ka fuyksfVdk ds 30 izkfousUll esa dqy uks dhVksa ls uqdlku dk PT23 Zars Dindori MP izHkko ik;k x;k gSaA vf/kdrd rFkk U;wure uqdlku Mashra PT24 Rau Pusa Faizabad UP khurd Laitpur & Chsistoor Bhaswara Road Warda esa PT25 College Of Agriculture Nagpur MS dze'k% 72-4 rFkk 40-4 izfr'kr ik;k x;kA PT26 College Of Agriculture Raipur CG PT27 Firozpur (R1l9 P4)Firojpur Punjab References PT28 Bilaspur CG
PT29 Jhansi UP Beeson CFC (1941) The ecology and control of the forest PT30 College Of Agriculture Jabalpur MP insects of India and the neighboring countries Vasant
313 Press, Dehra Dun pp 1007 Braga Sobrinho Banderira CT Mosquita ALM (1999) Occurrence and disease of Indian forest trees Forest 21(2): 213-238 EI-Atta HA Abdel Nour HO (1995) Forest pests in Sudan: their economic importance and control. United Pub. of Tenzonia FAO, Rome Tenzania Forestry Res. Inst. Marogaro Tenzania pp 82-91 Jayanthi PD Kamala Verghese Abraham, Rani Haonnarrmma, Nugraju, DK (2006) Damage potential and seasonability of the sapodilla bad borer Anarsia achrasella (Lepidoptera: Gelechidae) in India International Tropical Insect Sci 26 (2): 86-91 F Miller Maxine (1993) Large African herbivores, bruchid beetles and their interactions with acasia. Springer- Verlag Oecologia 97: 265- 270 Pillai SRM Gopi KG(1989) Further record of insect and pests on Acacia nolotica ucid. ex Del in Nurseries and young plantation and the needs for control measure. in Seminar on Forest Protection, June 29-30 (1989) Dehra Dun India Singh MP, Satyvir, DR Parihar (1989) A note on the coleopterous pest of forest plants in the Indian desert Indian. J For 12(4): 330-331 Rohner Christoph Ward David (1999) Large mammalian herbivores and the conservation of arid Acacia stands in the middle east. Spa: memiferos Herribores grandesyla conservation des acacia enel medio oriente. Conservation Biology Walter GH (1994) Species concepts and the natural of ecological generalization about diversity in lamberts (eds), Specncer HG speciation and the recognition concept. Theory and Application Johns Hopkins University Press, Baltimore
(Manuscript Receivd : 1.10.13; Accepted : 10.12.13)
314 JNKVV Res J 47(3): 315-320 (2013)
Genetic resources of okra for the utilization in the management of Okra Yellow Vein Mosaic Virus disease under climatic conditions of Kymore plateau zone, Madhya Pradesh
Usha Bhale, Priyanka Dubey and S. P. Tiwari Department of Plant Pathology Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract Singh 1973; Capoor and Varma 1950).
The monopartite begomo virus ( Geminiviridae) Evaluation of 16 varieties, 15 exotic and 34 indigenous and a small satellite DNA- induces the typical collections of okra was made under natural high disease symptoms of yellow vein mosaic disease in okra pressure conditions of Kymore plateau zone of Madhya (Mansoor et al. 2001).The most destructive and wide Pradesh, India against Okra Yellow Vein Mosaic Virus disease. spread disease is transmitted through white fly (Bemisia Base upon the coefficient of infection 4 varieties (Parbhani tabaci).The size of the virus particle ranges 18X 30 nm. Kranti, Arka Anamika, Shrawan, JAE 9457003) and six Presence of small, spherical particles reveals in the indigenous (IC 99746, IC 112481, IC 111511, IC 90175, IC phloem sieve nuclei (Dahal et al. 1993; Faquet et al. 326083, IC 433686) collections were found resistant . 2005). Plants infected 50 and 60 day after germination suffers a loss of 84 and 48% respectively. Yield loses Keywords: Varietals evaluation, okra, yellow vein to the tune of 49.3 to 93.8 % coupled with reduction in mosaic virus, disease measuring scale number of fruits and seeds per plant have been reported (Sastry and Singh 1974; Gupta and Thind 2006). Okra (Abelmoschus esculentus (L.) Moench), a flowering plant in the mellow family is commercially Materials and methods valued for its edible green tender fruits. Seeds are a good source of oil (13-22%) and protein (22-24%) and Evaluation of genetic resources a rich source of iodine (Baloch et al.1990).The oil is also used in soap, cosmetic industry and as Vanaspati, while protein for fortified feed preparation. The okra fruit Under natural field conditions 16 varieties, 15 exotic and seed fiber is often utilized in jute, textile and paper and 34 indigenous collections were (obtained through industry (http://en.wikipfdia.org./wiki/okra). The Okra Dr AK Nigam) and tested against the high disease Yellow vein Mosaic Disease is the widest spread pressure conditions at Maharjpur farm, Department of destructive problem, infects at all the stages of crop Horticulture, JNKVV, Jabalpur, when the crop attained stage. Initially, diseases appear as diffuse and mottled the age of 45 day. The coefficient of the infection (CI) appearance of younger leaves that may turn into was measured (Prabhu et al. 2007; Singh and Singh irregular inter venial yellow islands in older leaves. 2000) and as per scale on 10 randomly selected plants. Homogeneous interwoven network of yellow veins enclosing islands of green tissues is a common Coefficient of the infection (CI) =% plant disease symptom. Infected plants remain stunted and bear very incidence X response value to each severity grade few deformed and small fruits (Singh 2004; Sastry and
315 Scale
Appearance of disease Symptoms Response value Coefficient of the Reaction symptoms infection Absent 0 0.00 0.0-4.0 HR < 25% leaves 1 0.25 4.1-9.0 R 25-50% leaves 2 0.50 9.0-19.0 MR 51-75%leaves 3 0.75 19.1-39.0 MS 76-90% leaves 4 1.00 39.1-69 S > 90% leaves 5 1.00 69.0-100 HS
Results and discussion Evaluation of varieties
Disease incidence was measured on 10 randomly The disease incidence was variable and ranged from selected plants of each entry. During the period (15 20 to 50% (Table 1) in 16 varieties. The coefficient of November) the average temperature was 22C with 69% infection value ranged from 5.0 to 37.5. least coefficient relative humidity. In the particular standard of infection was recorded in Parbhani Kranti, Arka meteorological week no rainfall was received. The Anamika, JAE 6, JAE 9457003, while it was maximum average population of the vector ranged from 3 to 8 per (37.5%) in A4, JAE 7, VRO6 under Jabalpur conditions. leaf.
Table 1. Incidence of okra yellow vein mosaic virus disease in different varieties grown under natural field condi- tions
Variety % disease Response Co-efficient Reaction incidence value of infection Pusa Green 40 0.5 20.0 Moderately Susceptible Parbhani Kranti 20 0.25 05.0 Resistant Arka Anamika 20 0.25 05.0 Resistant Varsha Uphar 30 0.50 15.0 Moderately Resistant Arka Abhay (JAE 1) 30 0.50 15.0 Moderately Resistant Sonal (JAE 2) 40 0.50 20.0 Moderately Susceptible Kanchan (JAE 8) 40 0.50 20.0 Moderately Susceptible Tulsi (JAE 7) 50 0.75 37.5 Moderately Susceptible Shrawan (JAE 6) 20 0.25 05.0 Resistant MAHYCO (JAE 9457003) 20 0.25 05.0 Resistant MAHYCO (JAE 511010) 40 0.50 20.0 Moderately Susceptible A 4 50 0.75 37.5 Moderately Susceptible VRO 6 50 0.75 37.5 Moderately Susceptible SB 2 30 0.50 15.0 Moderately Resistant SB 4 30 0.50 15.0 Moderately Resistant SB 6 40 0.50 20.0 Moderately Resistant
316 Evaluation of exotic collections prevailing set of environment at Jabalpur. Variety Parbhani Kranti, Arka Anamika, Shrawan and MAHYCO Among 15 exotic collections the coefficient of infection (JAE 9457003) exhibited the resistant reaction .Six entries IC 99746, IC 112 481, IC 111511, IC 9175, IC ranged from 15.0 to 56.25 and diseases incidence 366083 and IC 433686 were resistant. Among the ranged from 30.0 to 75.0% .Least disease incidence (30%) was recorded in EC 169341 and EC 169337 while varieties, Varsha Uphar, Arka Abhay, SB 2, SB4 have shown the moderately resistant reaction while 5 exotic maximum (75%) was in EC 169355 (Table 2). In EC collections and 11 indigenous collections have shown 169337, EC 169515, EC 169341, EC 169319 and EC 169366, the coefficient of infection was below 20. the reaction. Among the exotic and indigenous collections, 2 entries were highly susceptible (EC169456-A, IC 1117251) while 5 entries in each from Evaluation of indigenous collections EC and IC have shown the susceptible reaction. Throughout the world, search of host resistance Among 34 indigenous collections the disease incidence using genetic resources has been considered as the ranged from 20(in IC 112481) to maximum (60%)in IC cheapest and most effective method for the 433682, IC 433715, IC 433718, IC 433720 (Table3).The management of OYVMV disease (Abdul and Waqar coefficient of infection was less than 20 in IC 99693, IC 2002; Chandra et al. 2000; Batra et al. 2000; Panda 99746, IC 105544, IC 117223, IC 112481, IC 111511, and Singh 2003; Khan and Mukopadhyay 1986). IC 111484, IC 117229, IC 117216, IC90175, IC 282286 Evaluation of 97 genotypes was made by Dhankar et and IC 326083. al.(1989) and IC 9273, Baunia 3(1) and IC 23592 was identified as resistant while Bora et al. (1992) reported Based upon the reactions, okra genetic resources Arka Anamika and five other genotypes free from were categorized under different categories (Table 4). disease among 22 genotypes. Khan and Mukopadhyay
Among the varieties, 4 were found under resistant (1986) screened 5 varieties and S1-1 exhibited minimum category while from indigenous collections only 6 entries incidence. Genotypes No 6, LORMI, VRO3, hybrid DVR had shown the desired grade. None of the entry from 1, DVR2 were found free from disease while VRO4, exotic collections exhibited the resistant reaction under exhibited mild reactions (Batra et al. 2000). Raghupati
Table 2. Incidence of okra yellow vein mosaic virus disease in different exotic collections under natural field conditions
Exotic collection % disease Response Co-efficient of Reaction incidence value infection EC 169463 70.0 0.75 52.5 Susceptible EC 169536 50.0 0.50 25.0 Moderately Susceptible EC 169366 37.5 0.50 18.75 Moderately Resistant EC 169319 33.5 0.50 16.75 Moderately Resistant EC 169399 70.0 0.75 52.50 Susceptible EC 169341 30.0 0.50 15.00 Moderately resistant EC 169374 42.8 0.50 21.40 Moderately Susceptible EC 169357 66.6 0.75 49.95 Susceptible EC 169355 75.0 0.75 56.25 Susceptible EC 169515 37.5 0.50 18.75 Moderately Resistant EC 169496 50.0 0.50 25.00 Moderately Susceptible EC 169337 30.0 0.50 15.00 Moderately resistant EC 169456-A 90.0 1.00 90.00 Highly Susceptible EC 169334 50.0 0.50 25.00 Moderately Susceptible EC 169481 6.6 0.75 49.95 Susceptible
317 Table 3. Incidence of okra yellow vein mosaic virus disease in different indigenous collections under natural field conditions
Indigenous collections % disease Response Co-efficient of Reaction incidence value infection % IC 99693 37.5 0.50 18.75 Moderately Resistant IC 99729 50.0 0.50 25.0 Moderately Susceptible IC 99746 20.0 0.25 05.0 Resistant IC 105544 30.0 0.50 15.0 Moderately Resistant IC 117223 22.2 0.50 11.0 Moderately Resistant IC 112481 20.0 0.25 05.0 Resistant IC 113904 50.0 0.50 25.0 Moderately Susceptible IC 111511 22.2 0.25 05.0 Resistant IC 117229 44.4 0.50 22.2 Moderately Susceptible IC 111484 30.0 0.50 15.0 Moderately Resistant IC 117229 30.0 0.50 15.0 Moderately resistant IC 111484 40.0 0.50 20.0 Moderately Susceptible IC 111478 40.0 0.50 20.0 Moderately Susceptible IC 117222 44.4 0.50 22.2 Moderately Susceptible IC 117216 37.5 0.50 18.75 Moderately resistant IC 90175 22.2 0.25 5.5 Resistant IC 90134 33.3 0.50 16.65 Moderately resistant IC 90170 33.3 0.50 16.65 Moderately resistant IC 433660 50.0 0.50 25.0 Moderately Susceptible IC 433662 50.0 0.50 25.0 Moderately Susceptible IC 433682 66.6 0.75 49.9 Susceptible IC 433715 66.6 0.75 49.9 Susceptible IC 433686 25.0 0.25 6.25 Resistant IC 433370 40.0 0.50 20.0 Moderately susceptible IC 433671 60.0 0.75 45.0 Susceptible IC 433718 60.0 0.75 45.0 Susceptible IC 433720 60.0 0.75 45.0 Susceptible IC 111483 30.0 0.50 15.0 Moderately Resistant IC 117251 100.0 1.00 1.00 Highly Susceptible IC 111481 50.0 0.50 25.0 Moderately Susceptible IC 112456 50.0 0.50 25.0 Moderately Susceptible IC 282286 30.0 0.50 15.0 Moderately Resistant IC 282288 37.5 0.50 18.75 Moderately Resistant IC 326083 22.2 0.25 05.0 Resistant
318 Table 4. Reaction of genetic resources of okra to yellow vein mosaic virus disease
Reaction Variety / Collection Resistant Variety Parbhani Kranti, Arka Anamika, Shrawan, MAHYCO (JAE 9457003) Exotic collection Nil Indigenous collection IC 99746, IC 112481, IC 111511, IC 90175, IC 326083, IC 433686 Moderately resistant Variety Varsha Uphar, Arka Abhay, SB2, SB4 Exotic collection EC 169366, EC 169319, EC 169341, EC 169515, EC 169337 Indigenous collection IC 99693, IC 105544, IC 117223, IC 111484, IC 117229, IC 117216, IC 90134, IC 90170, IC 111483, IC 282286, IC 282288 Moderately Susceptible Variety Pusa Green , Sonal, Kanchan Tulsi, MAHYCO(JAE 511010), A4, VRO6, SB6 Exotic collection EC 169536, EC 169374, EC 169496, EC 169334 Indigenous collection IC 99729, IC 113904, IC 117229, IC 111484, IC 111478, IC 117222, IC 433660, IC433662, IC433670, IC111481, IC112456 Susceptible Variety Nil Exotic collection EC 169463, EC 169399, EC 169357, EC 169355, EC169481 Indigenous collection IC 433270, IC 433718, IC 433671, IC 433715, IC 433662, IC 433682 Highly susceptible Variety Nil Exotic collection EC169456-A Indigenous collection IC 1117251
et al.(2000) reported that disease was absent in Bo1, Acknowledgement
HRB 55, KS404, HRB 9-2, Hy 8, Parbhani Kranti , S10 and S4. Azad Bhendi 1 has been reported to be more Authors are thankful to Dr A K Nigam for providing the resistant than Pusa Sawani, and Parbhani Kranti (Yadav germplasm of okra for the purpose and Professor & et al. 2004). Safadar et al. (2005) observed that Surkh Head, Department of Horticulture, JNKVV, Jabalpur for Bhendi as highly resistant, Sabz Pari and Safal as facilities. moderately resistant and Pahuja as tolerant to okra yellow vein mosaic disease. References e/; izns'k jkT; ds dSeksj IysV;q esas [ksrks dh voLFkk esa fHkaMh dh 16 Abdul Rehman, Waqar Ahmed (2002) Screening of okra iztkfr;k¡] 15 ,XlksfVd rFkk 34 bafMftul ,d=hdj.k dh xbZ genotypes for resistance to yellow vein mosaic virus iztkfr;k¡ dks fHkaMh ifRr f'kjk jksx ds fo:/k ijh{k.k fd;k x;k A under field conditions. Pakistan J Phytopath 14(1):84- dksfQf'k;aV vkWQ baQs'ku ds vuqlkj ijHkuh Økafr] vjdk vukfedk] 87 Batra V K, Singh J, Singh J (2000) Screening of okra varieties Jo.k] th-,-bZ- 9457003 rFkk Ng bafMftful ¼vkbZ-lh- 99746] to yellow vein mosaic virus under field conditions. vkbZ-lh- 112481] vkbZ- lh- 111511] vkbZ- lh- 90175] vkbZ- Veg Sci 27(2): 192-193 Bora GC, Saikia AK, Shadeque A (1992) Screening of okra lh- 326083] vkbZ- lh- 433686½ jksx izfrjks/kd ikbZ xbZ A genotypes for resistance to yellow vein mosaic virus disease. Ind J Virol 8(1):55-57 Capoor SP, Varma PM (1950) ellow vein mosaic of Hibiscus esculentus (L.) Ind J Agric Sci 20: 217-230 Chandra Deo, Singh KP, Panda KP, DeoC (2000) Screening
319 of Okra parental lines and their FLS for resistance Raghupati N, Veeraghavthatham D, Thamburaj S (2000) against yellow vein mosaic virus. Veg Sci 27(1): 78 Reaction of okra (Abelmoschus esculentus (L.) Dhal G, Neupane FP, Baral DR (19920 Effect of planting and Moench) cultures of bhendi yellow vein mosaic virus insecticides on the incidence and spread of yellow disease south. Indian Hort 48 (1-6):103-104 vein mosaic of okra in Nepal. Int J Tropical Plant Dis Safadar A, Khan MA, Habib A, Rasheed S, Iftkhar Y (2005) 10(1): 109-124 Management of yellow vein mosaic disease of okra Dhankar BS, Chauhan MS, Kishore N (1989) Reaction of through pesticides / biopesticides and suitable different genotypes of okra (Abelmoschus esculentus cultivars. Int J Agric & Biol 7(1):145-147 (L.) Moench) to yellow vein mosaic virus .Ind J Virol Sastry KSM, Singh SJ (1973) Restriction of yellow vein mosaic 5(1-2):94-98 virus spread in okra through the control of vector Fauqet CM , Mayao MA, Moriloff J, Desselbeyar U, Ball LA white fly (Bemisia tabaci)Ind J Mycol & Pl Path 3(1): (eds) (2005) Virus taxonomy VIII Report of ICTV. 76-80 Elsevier Press London UK Sastry KSM, Singh SJ (1974) Effect of yellow vein mosaic Gupta S K, Thind TS (2006) Disease problem in vegetable virus infection on growth and yield of okra crop .Indian production. Scientific Publishers Jodhpur (India) Phytopath 27(3): 294-297 576p Singh AK, Singh KP (2000) Screening for diseases incidence Khan MA, Mukopadhyay S (1986) Screening of okra of YVMV in okra treated with Gamma rays and CMS. (Abelmoschus esculentus (L.) Moench) varieties Veg Sci 27(1): 72-75 tolerant to yellow vein mosaic virus (YVMV) .Res & Singh RS (2004) Plant diseases (VIII ed) Oxford & IBH Pub Dev Rept 3(1): 86-87 Co New Delhi Mansoor SP, Amin M, Hussain Y,Zafar S Bull , Briddar RW, Yadav JR, Shrivastava JP, Singh B, Kumar R (2004) Azad Markam PG (2001) Association of disease complex bhendi 1 (Azad Ganga ) a disease resistant variety involving a Begamo virus DNA 1 and distinct DNA-? of bhendi . Plant Achieves 4(1):205-207 with leaf curl disease of okra in Pakistan . Plant Dis 85 (8)922 Panda PK, Singh KP (2003) Resistance in okra genotypes to (Manuscript Receivd : 30.9.11; Accepted : 16.8.13) yellow vein mosaic virus Veg Sci 30(2):171-172 Prabhu T, Warde SD, Ghante PH (2007) Resistance of okra yellow vein mosaic virus in Maharashtra .Veg Sci 35(2): 119-122
320 JNKVV Res J 47(3): 321-324 (2013)
Effect of weather parameters on development of ber powdery mildew and its control by fungicides
P.K. Amrate, Amarjit Singh and Chander Mohan Department of Plant Pathology Punjab Agricultural University Ludhiana 141004 Email : [email protected]
Abstract during 2010-11 and 2011-12 in the new orchard, Punjab Agricultural University (PAU) Ludhiana. The The correlation studies indicated that air temperature observations on powdery mildew appearance on the (maximum, minimum and average) significant negatively ber fruit cv. Umran were recorded at weekly interval whereas morning relative humidity positively related with commencing from the 40 standard meteorological week progression of ber powdery mildew. The favourable weather condition for very rapid progress of disease included air (SMW) during each year and continued up to the 05 temperature (maximum and minimum) ranged from 24 to 28 SMW in to next year. Disease severity was recorded 0 0 C and 8 to 13 C, respectively and high morning relative on randomly selected five ber trees with three fruiting humidity coupled with less rainfall. Four fungicides namely, Bayleton 25 WP, Score 25 EC (difenconazole), Tilt 25EC twigs tagged per plant using 0-5 grade (0= no disease; (propiconazole) and tebuconazole 25 EC @ 0.05 and 0.10 1= 1-20; 2= 21-40; 3= 41-60; 4= 61-80 and 5= 81-100 per cent were also tested on cv. Umran and Bayleton 25 WP per cent fruit area covered with powdery mildew). The significantly checked the disease and increased the fruit yield. per cent disease severity was calculated. Data on weekly temperature (maximum, minimum and average), Keywords: Ber, powdery mildew, weather parameters, RH (morning, evening and average) and rainfall (mm) fungicides were obtained from Agro meteorological department observatory. Correlation and regression analysis were performed between development of disease and Powdery mildew of ber (Zizyphus mauritiana) caused by Oidium erysiphoides f. sp zizyphi Yen and Wang is weather parameters. an important disease and commercially grown varieties are highly susceptible leading to qualitative and For the control of the disease, four fungitoxicants, quantitive losses upto 35-45 % to the ber growers namely Bayleton 25 WP, Score 25 EC (difenconazole), (Rawal and Saxena 1996). The fungus produces white powdery mass of spores on all the aerial plant parts Tilt 25EC (propiconazole) and tebuconazole 25 EC @ resulting in pre-mature drop of flower buds and fruits 0.05 and 0.10 per cent were sprayed during flowering (Rawal 1988). Infected fruit show discolouration, (September), mid - October, mid - November and early cracking and become mummified and fail to develop. - December on 15-year-old ber cv. Umran for two fruiting The time of appearance and disease severity vary and seasons (2010-11 and 2011-12) in the New orchard of is affected by the prevailing climatic factors. P.A.U. , Ludhiana. Each treatment was replicated thrice Investigations were thus conducted on the seasonal by keeping single tree per replication. An equal number occurrence of disease, its correlation with weather parameters and an attempt was also made to find out of unsprayed plants were kept as control. The data on efficacy of some fungicides against the disease. the development of powdery mildew on ber fruits were recorded on the three marked fruiting twigs per plant at the end of December using 0-5 grade. The per cent Material and methods disease severity and per cent disease control were computed. The yield was recorded in March at the time The role of abiotic factors on the progress of ber of harvest. powdery mildew under field condition was studied in 321 Table 1. Correlation matrix showing relationship among disease severity with weather parameters during 2010-11
Severity Temperature (0C) Relative humidity (%) Maximum Minimum Average Morning Evening Average Max Tem -0.625** Min Tem -0.803** 0.890** Ave Tem -0.730** 0.974** 0.970** Mor Rh 0.478* -0.552* -0.545* -0.566* Eve Rh -0.012 -0.690** -0.330 -0.532* 0.389 Ave Rh 0.079 -0.725** -0.408* -0.589* 0.607** 0.961** Rainfall -0.015 -0.182 -0.141 -0.166 -0.063 0.179 0.148 *Significance at 5 per cent; **Significance at 1 per cent
Table 2. Correlation matrix showing relationship among disease severity with weather parameters during 2011-12
Severity Temperature (0C) Relative humidity (%) Maximum Minimum Average Morning Evening Average Max Tem -0.555* Min Tem -0.641** 0.903** Ave Tem -0.607** 0.978** 0.972** Mor Rh 0.733** -0.635** -0.770** -0.719** Eve Rh 0.106 -0.652** -0.292 -0.494* 0.246 Ave Rh 0.264 -0.740** -0.452 -0.620** 0.478* 0.965** Rainfall 0.019 -0.495* -0.160 -0.345 -0.048 0.822** 0.740** *Significance at 5 per cent; **Significance at 1 per cent
Table 3. Efficacy of different fungicides against powdery mildew disease of Ber during 2010-11 and 2011-12
Treatments Concentrations(%) Powdery mildew Per cent diseasel Fruit yield/ Per cent Per cent control trees (kg) incidence severity Bayleton 0.05 6.5 1.3 96.4 91.0 0.10 0.0 0.0 100.0 92.5 Tilt 0.05 18.6 6.7 81.7 87.0 0.10 9.0 2.0 94.5 90.0 Score 0.05 20.4 7.8 78.7 86.0 0.10 13.0 3.7 89.9 87.5 Folicur 0.05 29.0 11.4 68.9 82.0 0.10 21.4 9.0 75.4 85.5 Unsprayed - 74.0 36.6 0.0 58.5 CD (0.05) 1.87 1.68 - 1.88
322 Fig 1. Weather data and ber powdery mildew severity during 2010-11(A) and 2011-12 (B)
Results and discussion The regression analysis was performed after pooling the both years (2010-11 and 2011-12) data to The severity of powdery mildew was low during first find out the relationship between weather parameters 2 couple of week in October during both the seasons (Fig and powdery mildew severity. The R value (coefficient 1). During 2010-11, the severity increased sharply from of determination) indicated that 78.6 per cent variation 14.6 to 33.5 per cent between 44 and 47 SMW and in the disease severity could governed by temperature, reaching a peak of 37.8 per cent in the 48 SMW. The relative humidity and rainfall. The multiple regression max temp between 44 to 48 SMW was 29.0 to 24.2 0C gave linear equation for per cent disease severity (Y) while the min temp ranged from 13.6 to 8.2 0C. Morning with respect to weather parameters (X1 = max temp, Relative humidity during this period 92 to 94 per cent X2 = min temp, X3 = average temp, X4 = morning RH, whereas in the evening 37 to 44 per cent and no rainfall X5 = evening RH, X6 = average RH and X7 = rainfall). has appeared. During 2011-12, the severity of the disease increased rapidly between the 45 to 48 SMW Y= -155.10 -13.55 X1 -11.19 X2 + 23.92 X3 + 6.59 X4 and reached the highest of 40.6 per cent at 48 SMW. +2.80 X5 -7.69 X6 + 0.647 X7 .…(Eq.1) The max temp between 28.3 to 24.6 0C whereas the (R2 = 0.786; SE = 7.32) min temp during this period ranged from 14.0 to 9.8 0C. Morning RH remained between 91 to 98 per cent while All four fungicides were found to be effective in evening RH was varied from 38 to 55 per cent and no controlling the powdery mildew. The average disease rainfall has appeared. severity and fruit yield varied from 0 to 11.4 per cent Simple correlation: The simple correlation and 82.0 to 92.5 Kg/tree in different treatment as coefficient matrices calculated between dependent compared to 36.6 per cent and 58.5 Kg/tree in control. (powdery mildew severity) and independent variables A highest disease control (96.4 and 100.0 per cent) and viz. temperature (max, min and average), relative fruit yield (91.0 and 92.5 Kg/tree) were observed from humidity (morning, evening and average) and rainfall both the concentration (0.05 and 0.10 per cent) of of the time course under investigation are presented Bayleton, respectively whereas tebuconazole 25 EC (Table 1 and 2). The correlation between severity and was found to be least effective (Table 3). the variables viz. min and average temp were highly significant (0.01) and negatively correlated (-0.803, The significant and negative correlation with -0.641 and -0.730, -0.607) during both the year, temperature (minimum, maximum and average) and respectively max temp was also significant and positive with morning relative humidity are in agreement negatively correlated. Morning RH was significant with the finding of Rawal and Sexana (1996) and Thind positively (0.478 and 0.733) correlated during both the and Kaur (2005). The superiority of bayleton in year. The variables viz. RH (evening and average) and controlling powdery mildew is in fair accordance with rainfall exhibited a non-significant and very weak Jamadar and Desai (1998), Munshi and Bal (2004) and relationship with severity during both the year. Thind and Kaur (2006).
323 References
Jamadar M M, Desai S A (1998): Chemical control of powdery mildew of ber Karnataka. J Agric Sci 11: 415-18 Munshi GD, Bal JS (2004) Spray schedules for the control of powdery mildew of ber with fungicides. Pl Dis Res 19: 97 Rawal RD (1988) Assessment of yield losses in ber fruit due to powdery mildew. Pl Dis Res 3:138 Rawal RD, Saxena AK (1996) Diseases of dryland horticulture and their management. In: Proc Silver Jubilee Nat Symp Arid Hort, HAU Hisar Dec 5-6 127-39 Thind SK, Nirmaljit Kaur (2005) Correlation matrix of ber powdery mildew with weather parameters and its prediction model. Pl Dis Res 20(2): 192-193 Thind SK, Nirmaljit Kaur (2006) Management of ber powdery mildew with fungicides. Indian J Hort 63(3): 267-269
(Manuscript Receivd : 15.9.13; Accepted : 16.12.13 )
324 JNKVV Res J 47(2): 325-329 (2013)
Population dynamics and management of lesion nematode (Pratylenchus thornei) in chickpea
Jayant Bhatt, Arvind Jaware and S.P. Tiwari Department of Plant Pathology Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract Materials and methods
The population of lesion nematode fluctuates several times Seasonal fluctuation: during the season. There was a gradual increase in soil and root population from seedling to flowering stage and declined for a short period of time at pod formation stage was noted. The experiment was conducted under field conditions The population again increased and reached to its maximum naturally infested with lesion nematode (P. thornei). The at harvesting and declined as there was no crop in the field there after. Neem cake @ 10g /m2 as soil amendment and soil samples were collected at an interval of 15 days Trichoderma harzianum ( 5g/Kg) as seed treating agent were starting from fallow to sowing of chickpea to harvest. found most effective. The population of lesion nematode was extracted following the Cobb's sieving and decanting method. Keywords: population dynamics, soil amendments, Nematode population was assessed by suspending the seed treatment, Pratylenchus thornei nematodes in 100ml water and population was counted, by taking five aliquents of one ml. using stereoscopic binocular microscope. Later nematode population was The lesion nematode Pratylenchus thornei is described calculated taking average of five aliquants. as a major limiting factor in chickpea production which reduces the yield to the tune of 26 per cent(Anon 2000). Evaluation of different plant bi-products:The The nematode has gained an alarming situation in the experiment was conducted under field conditions in plots state due to monocropping of chickpea and posed a measuring 2.75m×3.50m naturally infested with P. threat to chickpea cultivation. thornei. The initial population ranged from 270-345N/ The application pattern of chemical pesticides to 200cm3. The oil cekes viz., Neem, Jatropha, NSKP and manage the nematode has increased particularly where mustard were individually mixed with the plot soil @ production methods were intensified to increase 10g/m2 and pulverized. Chickpea seeds (ver. JG74) agricultural output. Use of chemicals is costly, harmful were sown in each plot with row to row distance 40 cm. for the microflora and fauna with long residual effects. and plant to plant distance 30 cm along with a standard Amendment of soil with decomposable organic matter check of carbofuran (@ 1kg ai./ha) and one untreated and bio-control agents is recognized as the most control. The experiment was designed under effective methods of changing soil and rhizosphere Randomized Block Design (RBD) with five treatments environments there by adversely affecting the life cycle and four replications. Adequate plant protection of pathogens and enabling the plant to resist attack of measures were adopted to grow healthy crop. pathogens through better vigour and/or altered root physiology. Experiment was allowed to run till harvest and observations on final nematode population in soil/200 Keeping this in view an attempt has been made cm3 and roots/5g, nodulation/plant, plant height (at 30 to delineate the population dynamics of P. thornei and days), yield (q/ha) and final population of nematode to develope economically feasible and viable technology were recorded at the end of experiment. to manage P. thornei under field conditions 325 Evaluation of bio-agents as seed treatment Table 1. Seasonal fluctuation in the population of mi- gratory nematode in chickpea The experiment was conducted under field conditions, Month Date Nematode population Crop stage in plots measuring 2.75m×3.50m naturally infested with Soil/200cm3 Root/5gm lesion nematode. The initial population ranged from 260- 315N/200cm3 soil. The experiment was designed Nov. 30 280 Germination following RBD with five treatments viz., Trichoderma Dec. 15 200 90 Seedling harzianum, T. viride, Pochonia chlamydosporia , Paecilomyces lilacinus and an untreated control. 30 150 96 Growth Jan. 15 290 110 Pre- flowering Seeds of chickpea were treated with the talc formulation of bio-agents @ 5g/kg seeds (2×108 spores/ 30 410 122 Flowering g talc). The plots were sown with chickpea seeds (var. Feb. 15 360 105 Pod-formation JG-74) and irrigated. The experiment was allowed to 30 400 91 Maturity run till harvest and observations on final nematode population (soil/200 cm3 and root/5g), nodulation/plant, March 15 620 75 Harvesting plant height (at 30 days) and yield (q/ha) were recorded 30 740 at the time of harvest. April 15 345 30 255 Results and discussion
Seasonal fluctuation population of lesion nematode (280N) declines at seedling stage however penetration started and the roots showed presence of (90N) nematodes within 15 The experiment was conducted in naturally infested field days after germination. where the crop is being grow continuously. The data presented in the Table 1 revealed that the initial There was a gradual increase in the soil population during growth and pre-flowering (150 and
Table 2. Evaluation of different plant bi-products against Pratylenchus thornei in chickpea
Treatment Initial nematode Final nematode population Nodulation/ Plant height Yield population plant (cm) (q/ha) (Soil/200cm3) Soil/200cm3 Root/5g Neem cake @ 10g/m2 315* 345.75 86.05 88.05 9.98 13.1 (17.76)** (18.61) (9.30) Jatropha cake @ 10g/m2 280 387.55 105.25 84.75 9.95 11.97 (17.75) (19.70) (10.28) NSKP @ 10g/m2 290 359.57 92.83 86.39 9.18 36.25 (17.04) (18.98) (9.66) Mustered @10g/m2 270 410.15 110.25 83.15 9.25 12.36 (16.45) (20.26) (10.52) Carbofuran @ 1 kg ai./ha. 310 185.35 50.15 90.89 9.65 14.55 (17.62) (13.63) (7.12) Control 345 550.25 156.26 57.25 8.28 11.25 (18.59) (23.47) (12.52) S.Em.(±) (0.36) (0.54) (0.34) 5.08 0.83 1.01 CD(P=0.05) (1.10) (1.06) (1.06) 15.60 2.56 1.43 * Mean of four replications ** Figures in parenthesis are square root transformed values
326 290N) stage and a sudden increase (410N) was noted is presented ( Table 2 ). Treatment with carbofuran (1kg at flowering stage. Maximum (122N) nematode ai./ha) resulted with minimum population of lesion population was recorded in roots during this period. nematode in soil (185.35) and in roots (50.15) followed by neem cake where the nematode population was The nematode population in soil declined both recorded to be 345.75 in soil and 86.05 in roots. These in soil (360N) and in roots (105N) at pod formation and results are in accord with the findings of Tiyagi and again increased in soil (400N) but declined in root (91) Shamim (2004) on chickpea. The antinemic properties during pod formation and maturity. Root population of neem ascribed to the presence of oleic acid, sulphur showed drastic decline at harvest period but maximum and flavonoides as well as extra cellular enzyme toxin, (620 and 740N) population of P. thornei in soil was siderophore and phytochrome compounds of the recorded at the time of harvesting (March 15). potential bio control agents may be exploited in Thereafter, the soil population declined and biological control leading to an ecofriendly, low cost reached to its minimum (255N) when there was no crop technology for developing an appropriate integrated in the field. The data revealed the population in soil management system (Bandopadhyay 2002) gradually increased up to pre-flowering with a slight Jatropha and mustard recorded significantly decrease during seedling and growth stages and attains reduced nematode population in soil and root when a high level at flowering stage and reaches to its peak compared with control (550.25 and 156.26). Reduced during harvesting. Sebastian and Gupta (1995) reported soil (359.57) and root (92.83) population was also the population of P. thornei in soil to increase recorded with NSKP but was inferior in its efficacy when corresponding to the presence of crop and a gradual compared to neem cake. reduction in following months. The observations recorded during the investigations confirm the above The plant height in all the treatments was findings. The highest population at the time of harvest recorded to be non significant among themselves but may be due to decortications of roots leading to release significantly superior over control. Maximum (90.89) of nematodes. number of rhizobial nodules were noted with carbofuran followed by neem cake (88.05), NSKP (86.39), jatropha (84.75) and mustard (83.15). Minimum nodulation Evaluation of different plant bi-products (57.25) was recorded with control. Significant increase in yield (14.55 q/ha) was recorded in carbofuran (1kg The influence of various oil cakes and bi-products of ai./ha) followed by neem cake (13.10 q/ha), NSKP plant on nematode multiplication and growth of chickpea (12.43 q/ha) and mustard cake (12.36 q/ha) minimum
Table 3. Effect of bio-agents on the multiplication of Pratylenchus thornei in chickpea
Treatment Initial nematode Final nematode population Nodulation/ Plant height Yield population plant (cm) (q/ha) (Soil/200cm3) Soil/200cm3 Root/5g Trichoderma harzianum 310* 150.55 57.43 86.81 9.61 22.12 @ 5g/kg seed (17.63)** (12.29) (7.61) Trichoderma viride 275 206.61 72.32 83.69 9.32 20.85 @ 5g/kg seed (16.60) (14.39) (8.53) Pochonia chlamydosporia 285 310.25 118.65 79.95 9.57 19.66 @ 5g/ kg seed (16.90) (17.63) (10.92) Paceilomyces lilacinus 315 194.11 59.26 85.50 9.29 21.16 @ 5g/kg seed (17.76) (13.95) (7.73) Control 260 437.82 137.25 60.38 8.08 18.12 (16.14) (20.60) (11.74) S.Em. (±) (0.54) (0.80) (0.65) 6.38 0.83 1.69 CD(P=0.05) (1.66) (2.24) (1.99) 19.58 2.57 5.20 *Mean of four replications **Figures in parentheses are square root transformed values
327 (11.25 q/ha) yield was recorded with untreated control. yield. Similar results have also been reported by Mishra Jatropha stood next in order of efficacy in reducing the et al. (2003) who observed reduction in nematode nematode population and increasing the yield along with population in chickpea when seeds were treated with plant growth condition. Efficacy of Jatropha was also P. lilacinus. reported by Patel and Patel (2007) on tomato and Verma and Nandal (2007) on bottle gourd against root knot The effectivity of P. lilacinus against reproduction nematode. of nematode and improvement in plant growth was reported by Khan and Goswami (2000) on tomato Mustard cake however, reduced the nematode infected with Meloidogyne incognita. Further, the population and increased yield along with nodulation microscopic examination revealed empty eggs in the but it was inferior over neem and Jatropha. Sebastian roots of plants grown in P. lilacinus treated plots. Similar and Gupta (1996) reported the efficacy of mustard cake results have also been reported by Sharma and Trivedi and demonstrated that root population of P. thornei (1997) . The fungus penetrated the eggs and fed upon declined at 120 days after sowing. their contents leaving empty shels. The efficacy of T. viride against P. thornei was Effect of bio-agents also noted in terms of reduction in nematode population and increase n plant growth parameters. Similar findings Minimum soil (150.55) and root population (57.43) was have also been reported by Sankarnarayan et al. (1999) recorded with Trichoderma harzianum followed by P. who observed increase in plant growth parameters and lilacinus which recorded 194.11 nematodes in soil and reduction in nematode multiplication in sunflower treated 59.26 in roots. Trichoderma viride stood next in order with T. viride against Meloidogyne incognita. The results of efficacy where 206.61 nematode in soil and 72.32 are also in accord with the finding of Pandey et al. (2003) nematodes in roots were recorded (Table 3). The soil on chickpea against M. incognita. (310.25N) and root (118.65) population of P. thornei Pochonia chlamydosporia @ 10 g/kg seed also was recorded higher than other treatments but the works well in reducing the chickpea. The effect of P. significant effect of the fungus was noted when chlamydosporia was observed to be inferior than T. compared with control which recorded maximum harzianum, T. viride and P. lilacinus but superior over population of nematode in soil (437.82) and in roots control. The results are in conformation with the findings (137.25). of Dhawan et al. (2007) on okra. Kerry and Diaz (2004) Maximum 86.81 nodulation was recorded with reported that P. chlamydosporia significantly reduced Trichoderma harzianum followed by P. lilacinus (85.50) nematode infestation in vegetables. and P. chlamydosporia (79.95). Minimum (60.38) root nodules were recorded in control. The effect of pus ds ekSle esa ewy fo{kr lw=d`fe dh la[;k esa vusd ckj ?kV c<++ treatments on the formation of root nodules was recorded to be non significant but they are significantly ns[kh x;h bl la[;k esa tM+ ,oa e`nk esa ikS/k ls iq"i mRiUu gksus rd superior over control d`eksRrj o`f) gqbZ tcfd ?ksaVh cUkus dh voLFkk esa la[;k esa fxjkoV Maximum plant height (9.61cm) was noted in T. ikbZ xbZA dVkbZ mijkar e`nk esa lw=d`fe dh la[;k vf/kdre ikbZ xbZ harzianum which was observed to be statistically at par ftlesa Qly dh vuqifLFkfr esa fujarj fxjkoV ns[kh xbZ A uhe dh with P. chlamydosporia (9.57 cm) followed by T. viride [kyh dks nl xzke izfr oxZ ehVj dh nj ls e`nk esa feykus ,oa (9.32 cm) and P. lilacinus (9.29cm) against minimum VªkbdksMjek fojMh ikap xzke izfr fdyks xzke dh nj ls chtksipkj (60.38) in control. djuk lw=d`fe izca/ku esa mi;ksxh fl) gq,A Increased yield was noted in T. harzianum (22.12 q/ha) followed by P. lilacinus (21.16) and T. viride (20.85) against minimum (18.12 q/ha) in control. All the References treatments were superior over control. These results are in accord with the findings of Ali MS, Nath P, Gogoi KK (2004) Botanical management of sheath blight disease of winter rice in Assam. Hari Chand and Singh (2005) and Khan et al. (2004) Bioprospecting of commercially important plant on chickpea Paecilomyces lilacinus stood next in the proceeding of the national symposium on order of efficacy where the soil and root population of Biochechemical approaches for utilization and P. thornei declined drastically over control along with Exploitation of commercially important plants. Johat significant improvement on nodulation, plant height and India 12-14 Nov 2003, 2004: 207-212
328 Anon (2000) Quiquiennial Report. All India Co-ordinated Pandey Gopal RK, Hemlata Pant (2003) Efficacy of different Research Project on Nematode, Center JNKVV, levels of Trichoderma viride against root-knot Jabalpur nematode in chickpea (Cicer arietinum L.). Annals Bandopadhyay A K (2002) A current approach to the Plant Protec Sci 11(1) : 101-103 management of root disease in bast fibre plant with Patel BA, Patel SK (2007) Efficacy of Jatropha formulation conservation of natural and microbial agents. J against root knot nematodes in tomato nursery and Mycopathol Res 40(1): 57-62 field condition, National Symposium on Nematology Dhawan SC, Babu NP, Singh S (2007) Bio-management of in 21st Century: Emerging Paradigms (22-23) : 33 root knot nematodes (Meloidogyne incognita) on okra Sebastian S, Gupta P (1996) Evaluation of oil cakes against by egg parasitic fungus Pochonia chlamydosporia, Pratylenchus thornei on chickpea. Intn chickpea National. Symposium. on Nematology in 21st Century Pigeonpea Newsl (3): 40-41 Emerging Paradigms, Assam. Agricultural University Sebastian S, Gupta P (1995) Population dynamics of Jorhat 22-23 Nov pp 102 Pratylenchus thornei in infested fields at Allahabad. Govindachari TR, Suresh G, Masilamani S (1996) Antifungal Indian J Mycol Pl Path 25 (3): 270-271 activity of Azadirachta indica leaf hexane extract. Sharma W, Trivedi PC (1997) Concomitant effect of Fitoterapia 70 (4): 417-420 Paecilomyces lilacinus and Vesicular Arbuscular Hari Chand, Surender Singh (2005) Control of chickpea wilt Mycorrhizal fungi on root-knot nematode infected (Fusarium oxysporium f. sp. ciceri) using bioagents okra. Annals Plant Protec Sci 5:70-74 and plant extracts. Indian J Agril Sci 75(2) : 115-116 Tiyagi SA, Ajaz Shamim (2004) Biological control of plant Kerry B, Hidalgo-Diaz L (2004) Application of Pochonia parasitic nematodes associated with chickpea using chlamydosporia in the integrated control of root knot oil cakes and Paecilomyces lilacinus. Indian J nematode on organically grown vegetable crops in Nematol 34(1) : 44-48 cuba. Bulletin-OILB/SROP 27:123-126 Verma KK, Nandal SN (2007) Efficacy of organic cakes in the Khan MR, Goswami BK (2000) Effect of different doses of management of root knot nematode (Meloidogyne Paecilomyces lilacinus isolate 6 on Meloidogyne javanica) in bottlegourd, National. Symposium. on incognita infecting tomato. Indian J Nematol 30:5-7 Nematology. in 21st Century: Emerging Paradigm Mishra SD, Dhawan SC, Tripathi MN, Saswati Nayak (2003) 22-23 Nov p 58 Field evaluation of bio-pesticides, chemicals and bio- agents on plant parasitic nematodes infesting chickpea. Curr Nematol 14(1/2) : 89-91 (Manuscript Receivd : 22.9.13; Accepted : 20.12.13)
329 JNKVV Res J 47(3): 330-336 (2013)
Modelling and forecasting of area, production and yield of soybean in India
P.Mishra, H.L.Sharma*, R.B. Singh* and Siddarth Nayak* *Bidhan Chanda Krishi Vishwavidyalaya Nadia 741252 (WB) *Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP) Email : [email protected]
Abstract oilseeds. (Chauhan and Singh, 2004). Madhya Pradesh state contributes about 67% and 56% in total area and production of soybean and is called as 'Soya state'. Soybean is an important crop in India. This study focuses on Madhya Pradesh, Maharashtra and Rajasthan together forecasting the cultivated area and production of soybean in contribute about 97% to total area and 96% production India using Autoregressive Integrated Moving Average (ARIMA) model. Time Series data covering the period of 1970- of soybean in the country. The soybean seeds, oil and 2010 was used for the Study. The data were obtained from oil cake are economically useful in various ways. Agriculture at Glance 2010. The result shows soybean Soybean oil is used as cooking medium and for production forecast for the year 2020 to be about 12.29 millions manufacturing several industrial products, such as tonns. The model also shows that the soybean area would vanaspati ghee, paints, linoleum oilcloth, printing inks, be 11.70 million hectares in 2020. In case of yield model shown soaps, insecticides, disinfectants etc. Soybean seeds that the yield of soybean would be 1237 Kg/ha in 2020. This are used for preparation of soytofu (Paneer), soya milk, projection is important as it helps inform good policies with soya sprouts, immature pods, soya nuts, etc. Soybean respect to relative production, price structure as well as oil cake is used for preparation of biscuits, protein rich consumption of soybean in the country. The conclusion from bread and other confectionary, bakery, high protein the study is that, total cropped area can be increased in future, livestock feed etc. Iqbal et al. (2005) attempted to if land reclamation and conservation measures are adopted. forecast the area and production of wheat in Pakistan The projection shown that soybean will play vital role to solve food security problem in India in future. up to 2022 using last thirty years data of area and production of wheat for modeling purpose. Auto Regressive Integrated Moving Average (ARIMA) is the Keywords: ARIMA, forecasting, production, soybean most general class of models for forecasting a time series. Appearance of lags of the forecast errors in the model is called "moving average". (ARIMA) model was India is one among the largest vegetable oil economies introduced by Box and Jenkins in 1976 for forecasting in the world. Soybean (Glycine max) is an important variables. Badmus and Ariyo (2011) forecasted the vegetable oilseed crop. It is considered to be a cash cultivated area, production and yield for year 2020 of crop. It is a major source of edible vegetable oils and maize in Nigeria using ARIMA model taking time series proteins which contains about 40% protein and 20% data for 1970-2005. In the present study, an effort has oil. Soybean plays a major role in the world food trade. been made to study the production scenarios of total It constitutes about 42% and 56% of area and production soybean in India. Mishra et al. (2012) made tea respectively of total oilseeds. The current global production in India forecasts for 1918-2010 using production of soybean is around 176.64 million MT with ARIMA model USA being the largest producer (Satyawathi 2005) India ranks 5th in the area and production of soybean in the world after USA, Brazil, Argentina and China. In recent Material and methods years, soybean has assumed important position in the country, as it is one of the most stable kharif crops yielding cost effective production under varied agro Data related to area, production and yield of soybean climatic conditions unlike other kharif pulses and in India since 1970 to 2010 were collected from
330 Agriculture at Glance, 2010. Statistical tools used to After the evaluation of trend of each and every describe the above series are minimum, maximum, series, our next task is to forecast the series for the average, standard error, skewness, kurtosis; Box- year to come. For the purpose the study adopted the Jenkins (1976) ARIMA modelling has been used to Box -Jenkins methodology. Data for the period 1970- forecast series under consideration. 2006 have been used for the model building, while data for years 2007-10 are taken for model validation. Models Descriptive statistics are again compared according to the minimum values of Root Mean Square Error (RMSE), Mean Absolute To examine the nature of each series these have been Error (MAE), Mean Square Error (MSE) and maximum subjected to get various statistics. Descriptive statistics value of Coefficient of determination (R2). are used to describe the basic features of the data in a study. They provide simple summaries about the sample Autoregressive model and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data. Descriptive statistics are ARIMA models which stands for Autoregressive typically distinguished from inferential statistics. With Integrated Moving Average models. Integrated means descriptive statistics we are simply describing what is the trends have been removed; if the series has no or what the data shows. With inferential statistics, you significant trend, the models are known as ARMA are trying to reach conclusions that extend beyond the models. immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. Or, we use inferential statistics The notation AR (p) refers to the autoregressive to make judgments of the probability that an observed model of order p. The AR (p) model is written difference between groups is a dependable one or one that might have happened by chance in this study. Thus, P we use inferential statistics to make inferences from X c X our data to more general conditions; we use descriptive t i t t i 1 statistics simply to describe what's going on in our data.
Parametric Trends Models where p are the parameters of the model, c is
a constant and t is white noise. Sometimes the constant To get an overall movement of the time series data, trend term is omitted for simplicity. equations are fitted. In this exercise different idea about the models like, polynomial, exponential, linear, Moving Average model compound etc are used for the purpose.
The notation MA (q) refers to the moving average model of order q: Different trend models used q
X t i t i t 2 3 k i 1 Polynomial Yt= b0+ b1 t + b2t + b2t +……+ bkt Linear Y = b +b t t 0 1 The Box-Jenkins type ARIMA process (Box and Quadratic Y = b +b t+b t2 t 0 1 2 Jenkins, 1976) can be defined as (B)( d y - ) = (B) , 2 3 t t Cubic Model Yt= b0+ b1t + b2t + b3t Here, yt denotes soybean area and production in mil- b1t Compound Yt= b0e lion hectares and million tons respectively, is the mean Exponential Y = b e(b1t) d p t 0 of yt , (B) = 1 - 1B - …….… pB , (B) = 1 - 1B - ... q th Logarithmic Yt = b0 + b1ln(t) - q B , i denotes the i moving average parameter, i denotes the ith autoregressive parameter and B denote b b In(t) Growth Yt e 0 1 the difference and back-shift operators respectively.
331 Model selection and diagnostic check n 2 ˆ XXi i RMSE i 1 Among the competitive models, best models are n selected based on minimum value of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean n ˆ Square Error (MSE) and maximum value of Coefficient XXi i of Determination (R2) and of course the significance of i 1 X i the coefficients of the models. Best fitted models are MAPE x 1 0 0 n put under diagnostic checks through auto correlation function (ACF) and partial autocorrelation function (PACF) of the residuals. n ˆ 2 XXi 2 i 1 R n R-squared 2 XXi i 1 An estimate of the proportion of the total variation in the series that is explained by the model. This measure is most useful when the series is stationary.R-squared With the help of SPSS 16 computer package ARIMA can be negative with a range of negative infinity to 1. models was found to be estimated for tea in India. Negative values mean that the model under consideration is worse than the baseline model. Positive values mean that the model under consideration is Model Formulation better than the baseline model. The whole period under consideration (1970-2010) has Root Mean Square Error (RMSE) been divided into two parts. (a) The model formulation period (1970-2006) The square root of mean square error is called RMSE. A measure of how much a dependent series varies from (b) Model validation period (2007-2010) its model-predicted level, expressed in the same units On the basis of best fitted model forecasting has been as the dependent series. made up to 2020.
Mean Absolute Percentage Error (MAPE) Results and discussion
A measure of how much a dependent series varies from Since 1970 the area under soybean has increased from its model-predicted level. It is independent of the units 0.03million ha to 9.79 million ha registering a growth of used and can therefore be used to compare series with almost 746%.The average area under soybean being different units. 3.60 million ha. In fact the effect of green revolution is being reflected. The effect of expansion of area is clearly Mean Absolute Error (MAE) visible in the production scenario of soybean. With a mere 0.01 million tonnes of production it has reached Measures how much the series varies from its model- to 10.97million tonnes during the year 2010. Platykurtic predicted level, MAE is reported in the original series nature of production indicates that there has been units. continuous force on enhancing production of these crops during the period. Increased production of n soybean would not been possible without a substantial ˆ XXi i increasing per ha yield of the crop. Starting with only i 1 MAE 426kg of Soybean per ha, it has reached to 1235kg/ha n during the year 2010. Thus the joint effect of expansion area and yield has resulted in a brighter picture of soybean production scenario in India.
332 Table 1. Descriptive Statistics competitive models. The best model was selected on the basis of the maximum R2 value, significance of the Area Production Yield model and its coefficient. In the following few sections (MH) (MT) (Kg/ha) we shall present (Table-2) the result of these exercises. Mean 3.60 3.58 879.95 Box-Jenkins modelling and forecasting Standard Error 0.51 0.55 30.70 Kurtosis -1.25 -1.01 -0.18 After the evaluation of trend of each and every series, Skewness 0.44 0.62 -0.50 our next task is to forecast the series for the year to Minimum 0.03 0.01 426 come. For the purpose we adoptated the Box -Jenkins Maximum 9.79 10.97 1235 methodology and forecasting has discuss in the material SGR (%) 746.34 2450 3.75 and method section. Data for the period 1970-2006 has CGR (%) 1.56 1.72 1.01 been used for the model building, while data for years 2007-10 are taken from model validation. (as describe Area and production are in respectively in million the material and method section ) Best fitted models hectare and million tonnes and yield in kg/ha. are used to forecast the series for the years to come. Though different series has been fitted with different ARIMA models but one thing is clear that none of the Trends in production behaviour of soybean series is stationary in nature and first order differencing is required for all the series. The selected models are To workout the trends in area, production and yield of ARIMA (0,1,0), ARIMA (0,1,3) ARIMA (0,1,4) and soybean in India different parameter model like Linear, ARIMA (0,1,5). These four models are again compared Logarithmic, Quadratic, Cubic, Compound growth and according to the minimum values of RMSE, MAE, MSE Exponential model where attempted to among the and MAPPE and maximum value of R2 which are given
Table 2. Model Summary and Parameter Estimates of parametric trend models
Equation R2 F Sig. Constant b1 b2 Area Cubic 0.987 918.918 0 0.396 -0.174 0.019 Production Cubic 0.955 259.528 0 0.51 -0.21 0.02 Yield Linear 0.419 28.1 0 656.938 10.62
Fig 1. Line graph showing the observed and expected Fig 2. Line graph showing the observed and expected value of area under soybean value of production of soybean 333 soybean has been modelled with the help of Box- Jenkins's ARIMA modelling technique. This justified that the selection of ARIMA (0, 1, 3) is the best model to represent the data generating process very precisely.
Area and production are in respectively in million hectare and million tonnes and yield in kg/ha.
Conclusions
ARIMA model offers a good method for predicting the Fig 3. Line graph showing the observed and expected magnitude of any variable. Its strength lies in the fact value of yield of soybean that the method is suitable for any time series with any pattern of change and it does not require the forecaster to choose a prior value of any parameter. In our study in Table 3. Hence, it can be concluded that ARIMA (0, ARIMA (0, 1, 5) model is best suited for estimation of 1,5) is the best fitted model for forecasting the Area of soybean area data. From the forecast values obtained soybean in India. Production behaviour of soybean has the regression model, it can be said that forecasted area been modelled with the help of Box- Jenkins's ARIMA will increases to some extent in future i.e. In 2010-11 modelling technique. This justified that the selection of ARIMA (1, 1, 3) is the best model to represent the data area of soybean was 10.97 million ha. Up to the year generating process very precisely. Yield behaviour of 2020-21 it will be 11.70 million ha.In case of production of soybean the ARIMA (1, 1, 3) model is best fitted. , it can be said that forecasted production will increases to some extent in future i.e. In 2010-11 production of Table 3. Model selection criteria for area, production and yield of soybean in India soybean was 9.81 million tonnes. Up to the year 2020- 21 it will be 12.29 million tonnes. In case of yield of 2 Best R RMSE MAPE MAE soybean the ARIMA (0, 1, 3) model is best fitted. , it ARIMA can be said that forecasted yield will increases to some model extent in future i.e. In 2010-11 production of soybean Area (0,1,5) 0.994 0.246 20.59 0.17 was 1065kg/ha. Up to the year 2020-21 it will be 1237 Production (1,1,3) 0.958 0.65 23.39 0.40 kg/ha.The projection of area, production and yield shown that soybean will play vital role to solve food Yield (0,1,3) 0.269 163.06 14.55 118.75 security problem in India in future.
Table 4. Forecasting of area, production and yield of soybean of India
Area Production Yield Year Observed Predicated Observed Predicated Observed Predicated 2007 8.88 8.83 10.97 10.62 1235 1211 2008 9.51 9.06 9.91 9.32 1041 1097 2009 9.79 9.25 10.05 9.59 1026 1061 2010 9.21 9.46 9.81 9.84 1065 1120 2015 10.57 11.06 1179 2020 11.70 12.29 1237
334 Fig 4. ACF and PACF graphs of residuals for the best Fig 5. Observed and Predicated / Forecasted area un- fitted (ARIMA 0, 1,5) of area under soybean der soybean
Fig 6. ACF and PACF graphs of residuals for the best Fig 7. Observed and predicated / forecasted produc- fitted (ARIMA 1, 1,3) of production of soybean tion of soybean
Fig 8. ACF and PACF graphs of residuals for the best Fig 9. Observed and Predicated / Forecasted Yield of fitted (ARIMA 0,1,3) of yield of soybean soybean
335 lks;kchu Hkkjr esa ,d egRoiw.kZ Qly gS A ;g v/;;u LolekJ;h ,dh—r xfreku vkSlr ds izk:i dk iz;ksx djrs gq, Hkkjr esa lks;kchu ds —"V {ks= ,oa mRiknu ds Hkfo";ok.kh ij izdk'k Mkyrk gS A bl v/;;u ds fy, 1970&2010 ds dky Js.kh ds vk¡dM+ksa dks iz;ksx fd;k x;k Fkk A vk¡dM+s 2010 ds —f"k ,d utj ls izkIr fd;k x;k A o"kZ 2020 ds fy, lks;kchu mRiknu vuqeku ds ckjs esa 12- 29 n'kyk[k gksus dk irk pyrk gS A ekWMy Hkh lks;kchu {ks= 2020 esa 11-70 yk[k gsDV;j gksxk] irk pyrk gS A lks;kchu dh iSnkokj 2020 esa 1237 fdyksxzke@gsDVs;j gksxk irk pyk gS fd mit ekWMy ds ekeys esa ;g lkis{k mRiknu] fdey lajpuk ds lkFk gh ns'k esa lks;kchu dh [kir ds fy, lEeku ds lkFk esa vPNh uhfr;ksa dks lwfpr ,oa enn~ gS ds :i esa ;g iz{ksi.k egRoiw.kZ gS A v/;;u ls fu"d"kZ] Hkwhe lq/kkj vkSj laj{k.k ds mik;ksa dks viuk;k tkrk gS A dqy Qly {ks=] Hkfo"; esa c<+k;k tk ldrk gS] lks;kchu iz{ksi.k dh Hkfo"; esa Hkkjr esa [kk| lqj{kk dh leL;k dks gy djus ds fy, egRoiw.kZ Hkwfedk gS A
References
Agricultural Statistics at a Glance (2010) Directorate of Economics and Statistics, Department of Agriculture and Cooperation, Ministry of Agriculture, Govt. of India Box GEP, Jenkins GM (1976) Time Series Analysis: Forecasting and Control, Holden-Day San Fransisco Badmus MA, Ariyo OS (2011) Forecasting Cultivated Areas and Production of Maize in Nigerian using ARIMA Model. Asian J Agric Sci 3(3): 171-176 Chauhan, GS, Singh NB (2004) Present status of soybean productionk and uses in India, Proceedings of soybean production and improvement in India, Indore : NRCS p 1-9 Iqbal NBK, Maqbool Asif, Shohab Abid Ahmad (2005) Use of the ARIMA Model for Forecasting Wheat Area and Production in Pakistan. J Agric Social Sci 1(2): 120- 122 Mishra P, Sahu PK, Bajpai P, Nirnjan HK (2012) Past Trends and Future Prospects in Production, and Export Scenario of Tea in India. International Review of Business and Finance 4(1):25-33 Satyawathi TC (2005) Improved soybean varieties of India, Indore National Research Centre for Soybean p 1- 30
(Manuscript Receivd : 20.8.13; Accepted : 17.12.13)
336 JNKVV Res J 47(3): 337-340 (2013)
SWOT analysis for lac cultivation in Madhya Pradesh
Arvind Dangi Thakur, S. C. Meena and Ashutosh Shrivastava Agro-Economic Research Centre for MP & CG Jawaharlal Nehru Krishi Vishwavidyalaya Jabalpur 482 004 (MP)
Abstract illicit felling and related desperate measures to obtain cash to overcome household food insecurity and other Madhya Pradesh (14.48%) is the third largest state of lac contingencies (repairing roofs, marriage, preparation production, and Balaghat, Mandla, Chhindwara, Seoni, for Kharif cropping etc,). The main Lac crop during the Narsinghpur, Dindori, Anuppur, Shahdol, Hoshangabad, months of May/ June months assist households to Khargone and Dewas are the major lac producing districts in overcome these difficulties and can also be a significant the state. It is assumed that 80 to 95 percent of the potential contributor to reducing migration. of lac host trees is not being utilized., Low cash and labour input activity with high returns which is generates rural There are 56,069 villages in the state; these employment and income are the strength of lac cultivation in villages are the primary production centers of food, M.P. Lac has significant climatic risks and up to 50 percent of fodder, fiber and fuel. Although these villages are also the potential crop is commonly lost in poor seasons. A the owners of natural resources in the state, about 37 favorable export market scope exists for greater value added activity within the State. Shortage of supply and high lac export percent of the people in the rural sector continue to live prices over years have reduced market uptake in some below poverty level. Most of the poor in the state live markets and encouraged substitutes. The effective cultivation either in the fringes of forest or near the forest. Farmers of lac production, Technical training, monitoring, assistance to in these rain-fed areas over recent years have faced a unify producers for brood lac distribution and marketing, a decline in their farm income. Their main option has been market information system and a strong state level planning to divert effort towards off-farm income. Off farm income and monitoring organization are required for lac cultivation has become a necessity among the resource poor and development. section in the rural sector to meet their household food security. Keywords : SWOT, cultivation, lac, Madhya Pradesh Lac production is a complimentary or supplementary form of income to the existing livelihood In Madhya Pradesh, forestry is the second major land activities of households. The harvesting periods of lac use after agriculture. About 83 percent of the 33 million (October and May/ June for rangeeni Lac, and June people engaged in agriculture practice rain-fed farming. and December for kusumi lac) coincides with the stress Rain-fed farming is always associated with risk and low period of the majority in the rain-fed parts of Madhya productivity. Erratic and uneven distribution of rain Pradesh. Lac is relatively low cash and labour input affects the crop growth and its productivity. The climate crop with high returns. It is generally compatible with in rain fed areas is semi arid and soils are usually existing rural livelihood activities in terms of its labour deficient in nutrients as well as moisture. Such requirement. Lac cultivation also encourages conditions are not conducive to improving crop conservation of host trees and leads to a re-greening performance. Under such rain-fed agriculture, where of the land. Kharif (wet season -July to October) is the main cultivation season for agricultural crops, followed by a Lac are scale insects (Laccifer Lacca) which live fallow or less productive season under crops in Rabi on trees called lac host trees where they secrete the (winter season-November to June), the cropping system lac resin which is scraped off and manufactured into leads to a prolonged lean period from November to shellac. To produce just 1 kilogram of lac resin around June. This lean period is characterized by migration, 300,000 insects lose their tiny lives. A scale insect is a
337 common name for any of about 2000 insect species 13.5 percent of India's total lac production. Experts say found all over the worlds that attach themselves in great that the state is poised to emerge as Agri-business hub numbers to plants and trees. Scale insects range from and this would help poor lac farmers share handsome an almost microscopic size to more than 2.5 cm. They profits. The home of richest biodiversity of economically can be very destructive to important lac insects. Lac of commerce is derived from trees - stunting or killing a few species belonging to the genus Kerria. Lac yields twigs and branches by three basic components of economical value, i.e., resin, draining the sap. wax and dye. In India, lac cultivation is widely practiced in the states of Jharkhand (50.6%), West Bengal (6.5%), Chhattisgarh (20%), Madhya Pradesh (13.5%), Orissa India is the foremost lac (1.9%), Maharashtra (4.1%) and parts of Uttar Pradesh producing country of the (2.3%), Andhra Pradesh (0.2%) and Gujarat (0.4%). world with an annual production of about 21,300 The principal districts that are currently producing tones and it is worth lac in MP are: Balaghat, Mandla, Chhindwara, Seoni, noticing here that Madhya Narsinghpur, Dindori, Anuppur, Shahdol, Hoshangabad, Pradesh stands third Khargone, Dewas. These districts are in the south and largest producer of lac in east of the State. the country. It produced approximately 2,870 tones of scrapped lac coming about Considering lac cultivation is an employment and
Pic. B: Host plant of Lac Pic. C: Different uses of lac
Fig. Lac Production Scenario in M.P. (2010-11) Pic. D: Lac Cultivation 338 income generation activity, the SWOT analysis of this not rain dependent and provides income at critical times enterprise has been done to drawn conclusions. of the year in rain-fed dependent agricultural areas. SWOT Analysis Export markets appear strong an unlikely to be seriously affected by an increase in production from MP of say 3000 to 5000 MT and It reduces migration SWOT is for Strengths, Weaknesses, Opportunities, and Threats. Using the SWOT Analysis would be outside the State during the lean income months of the evaluating these areas. A project or enterprises needs year and over the past four years 13,000 households to have an objective and they need to identify the areas have already commenced lac production with a doubling of enterprises. of lac production from MP. In many cases surveyed, lac is providing around 50 percent of rural household The usefulness of SWOT analysis is not limited cash expenditure needs. to profit-seeking organizations. SWOT analysis may be used in any decision-making situation when a desired It is compatible with existing land based activities end-state (objective) has been defined. Examples - minor shading does not appear to affect paddy include: non-profit organizations, governmental units, production or any other crop production. It provides an and individuals. SWOT analysis may also be used in important livelihood activity for women who in many pre-crisis planning and preventive crisis management. cases insist on their share of income for their input. SWOT analysis may also be used in creating a Rural youth are more attracted to lac than other group. recommendation during a viability study/survey.
Weaknesses Strengths
Lac has significant climatic risks from heat, rain, hail Lac production has a long tradition in MP and the activity and prolonged fog and up to 50 percent of the potential avoids many of the risks associated with "new" income crop is commonly lost in poor seasons., slow and earning activities., it is assumed that 80 to 95 percent requires technical training and follow-up technical of the potential of lac host trees are not being utilized., assistance one year lead-time before significant income Low cash and labour input activity with high returns and and brood lac has often been in short supply and needs generates rural employment and income are the careful co-ordination and organized transport as timing strength of lac cultivation in M.P., It encourages re- greening and forest conservation and the State of MP is critical and more than 80 percent of the lac produced has a generally favorable climate for production. It is in MP receives its primary processing through outside
Table 1. Production scenario of Lac in Madhya Pradesh (in tons)
Name of Districts Total Production % to State Total Production % to State in 2009-10 in 2009-10 Anuppur & Shahdol 28 1.17 15 2.19 Balaghat 547 22.89 217 31.68 Chhindwara 65 2.72 15 2.19 Dindori 27 1.13 20 2.92 Hoshangabad 120 5.02 95 13.87 Mandla 105 4.39 50 7.30 Narsinghpur 18 0.75 13 1.90 Seoni 1375 57.53 225 32.85 Others 105 4.39 35 5.11 Madhya Pradesh 2390 100.00 685 100.00
339 the State. Prices fluctuate up to +/-40 percent in a year A shortage of supply and high lac export prices because of price manipulation by export traders. over the past 4 years are stated by exporters to have reduced market uptake in some markets and The shelf life of scraped lac is short (maximum encouraged substitutes. Global warming and more of two months without cold storage conditions) so variable climates could increase climatic risk. producers cannot easily hold back selling during low price periods. Trading practices work unfairly against producers with under weighing, unfair grading and e/;izns'k ¼14.48%½ yk[k mRiknu es rhljk c³k jkT; gS! e-iz- esa opportunist pricing in many instances and Theft is a orZeku le; esa eq[; yk[k mRiknu dj jgs feyksa esa eq[;r% problem in most producing areas. It is perceived to be a crop of backward tribal communities and sometimes ckyk?kkV] e.Myk] flouh] ujflgaiqj] fMaMksjh] vuwiiqj] 'kgMksy] difficult to attract other new producers. gks'kaxkckn] [kjxksu o nsokl gS A
Taxes (VAT and mandi tax) on lac in MP reduce ;g ekuk tkrk gS fd yxHkx 80 ls 90 izfr'kr yk[k ds grower returns compared with neighboring states. vkfJr isMksaa dh {kerk dk mi;ksx ugha gks ikrk] e/; izns'k esa de Chhattisgarh has removed both Vat and CESS on lac. Maharashtra has removed VAT. Unfortunately lac is uxnh ,oa FkksMs etnwj vkxrksa ds lkFk vf/kdre ykHk ds lkFk jkstxkj treated as both a NTFP and agricultural crop under ,oa vk; mRikfnr djuk gh xzkeh.k {ks=ksa es yk[k dh [skrh dh 'kfDr taxation (and other) laws. Inoculation for the katki crop gS A in July comes at a time when labour is short in some intensive agricultural cropping areas. No minimum price yk[k ekSleh vfuf'prrk] ls lh/ks :Ik ls izHkkfor gksrk gS ,oa support or crop insurance schemes operate for lac. and No crop credit facilities exist for lac producer input 50 izfr'kr izHkkoh Qly lk/kkj.kr% [kjkc ekSle ls u'V gks tkrh requirements. gS A jkT; esa yk[k gsrq ewY; ls loa/kZu ,oa fu;kZr cktkj dh Hkjiwj Opportunities laHkouk,a O;kIr gS A vkiwfrZ dh deh ,oa mPp fu;kZr ykxr ds dkj.k foxr 4 o'kksZa ls fu;kZrd dqN cktkjksa ls [kjhnh de djrh gS rFkk The doubling of lac production that has taken place in the past four years could relatively easily be doubled ;gka ij fodYiksa dks izksRlkgu nsuk vko';d gS A e/; izns'k esa yk[k again and there is a favorable export market outlook mRiknu] rduhd izf'k{k.k ,oa fuxjkuh yk[k dhV forj.k ¼Brood with increasing interest in natural and sustainable lack½ vkSj foi.ku] cktkj lwpuk iz.kkyh vkSj ,d etcwr jkT; products. Scope exists for greater value added activity within the State - including possibly a special export Lrjh; fu;kstu vkSj fuxjkuh laxBu] yk[k dh [ksrh ds fodkl ds zone for lac industries and Opportunity for some fy, vko';d gS A producers/districts to specialize on brood lac production. The opportunity to unify produce through support Reference to encourage increased production, collective marketing and possibly processing., The opportunity to use lac in MP Forest Department: www.forest.mp.gov.in conjunction with Joint Forest Management (JFM) as a MP Minor forest Produce Federation: www.mfpfederation.com major forest conservation tool. Indian Lac Research Institute Ranchi: www.icar.org.in/ilri/ default.htm Threats www.kvkjabalpur.org www.pradan.org.in Other States in India could also quickly increase www.zeezivisa.nic.in production and possibly threaten export market stability. Little is known about the lac end uses and risks of (Manuscript Receivd : 16.12.12; Accepted : 8.10.13) substitution in export markets and the similarly little is known about the plans of other producing countries.
340 JNKVV Res J 47(3): 341-345 (2013)
Performance of National Agricultural Insurance Scheme in Raisen District of Madhya Pradesh- An economic evaluation
Govind Prasad Namdev, P. K. Awasthi and N. K. Raghuwansi Department of Agricultural Economics and Farm Management Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 MP Email : [email protected]
Abstract present study to evaluate progress and performance of NAIS in Raisen district of Madhya Pradesh. Agricultural production in Madhya Pradesh involve several risks partly due to uncertain weather. NAIS is vital mechanism Material and method for providing insurance coverage to farmers and safeguardes against production risk. Against this backdrop the present study has examined are performance of NAIS operating in The study was confined to Raisen District of Madhya Raisen district of Madhya Pradesh and some suggestable Pradesh. The objective function of the study was to suggestion are given to make it more effective. evaluate the coverage and performance of the NAIS, in the study area. The relevant macro level parameters Keywords: Crop Insurance, Agriculture, NAIS, Madhya viz. number of farmers benefited area covered, sum- Pradesh insured and premium and claim compensated etc were collected from Annual Progress Report of the implementing agency covering a period from 2006 to Risk and uncertainty are twin dangers, which hamper 2011. Absolute change, Relative Change (%) and agricultural production and bring about instability in rural tabular analysis statistical techniques were used to economy of the state. Inadequate and uneven rainfall, analysed the collected data. hail-storm, incidence of insect pest and diseases etc. are important factors, which cause considerable losses Performance of NAIS in agriculture. Farmer and nature are the opposite players in crop production. Raisen district of Madhya The insured farmers increased every year except 2008 Pradesh is an agricultural important district of Narmada from 2006 up to 2011(105.75%). The lowest and highest valley. Rice, Wheat, Chickpea, soybean and pigeon number of farmers were insured during 2006 (19987) pea. their production level fluctuated widely due to these and 2011 (41125) respectively. climatic changes, thus, farmer loose considerable amount of farm income. The area insured was maximum in the year 2011(166018.78 ha) followed by 2010 (155943.4 ha). In order to mitigate these risk arising due to Whereas, it was minimum in the year 2008 (78959.31 various factors, Government of India introduced new ha) followed by 2006 (96478.14 ha). It is also inferred insurance scheme called "National Agricultural from the table that maximum sum insured was recorded Insurance Scheme from rabi 1999- 2000 season in place for the year 2011 (Rs 17057.45 lakh) followed by 2010 of the old Comprehensive Crop Insurance Scheme (Rs 12979.56 lakh) and 2009 (Rs 10969.69 lakh). On (CCIS) which was implemented in rabi since 1985. It the other hand the lowest sum insured of Rs 4443.63 lakh was noted for the year 2006 followed by 2008 (Rs provides coverage to all food crops, oilseed, 4471.74 lakh) and 2007 (Rs 6112.67 lakh). The premium horticultural/ commercial crops (banana, cotton) and collected was the highest in the year 2011 (Rs 697.01 livestock. Keeping in this view an attempt was made in lakh) while, it was lowest during 2008 (Rs 1.56 lakh).
341 During rest of the period of study it ranged from Rs 155.52 lakh to 454.28 lakh. The subsidy given was Rs sum
1.43 lakh in 2006 which increased up to Rs 5.19 lakh in 2.82 1.32 0.29 0.75 6.56 46.93
2011. The highest claim of Rs 8005.79 lakh was paid in Claims / 2011 which was much higher than rest of the years. A assured(%) lowest claim of Rs 13.05 lakh has been paid in 2008 followed by 2007(Rs 80.42 lakh). Similarly; 0.81 0.38 8.34 0.21 1.87 11.49
36204farmers were benefited in 2011 which is the Claims/ premium highest. The number of farmers benefited during rest of the period of study ranged from 396 to 6465 being lowest in 2008 (Table 1). 0.92 0.97 0.97 1.03 0.74 130.78 of subsidy Subsidy to premium under NAIS Percentage
In the year 2008 percentage of subsidy to premium was highest (130.78%) which is much higher than it is 396 709 2293 1418 6465 (5.12) (2.14) (2.21) 36204 (11.47) (16.44) (88.03) recorded for other years. The lowest value was farmers observed in 2011(0.74%) followed by 2006 (0.92%). Benefited Percentage of subsidy to premium was 0.97 in 2007 & 2009 and 1.03 in 2010, that claim to premium ratio ranged between 0.21 to 11.49 being lowest in 2009 and highest in 2011 respectively. This ratio was 8.34 in 2008 80.4 13.0 82.1 125.4 851.6 which was lower than noted in 2011 but, much greater 8005.8 (Rs in lakh) than recorded for rest of the years. Maximum percentage Claims paid of claim to sum assured was noticed for 2011 (46.93%) which was much higher than rest of the years followed by 2010 (6.56%).on the other hand it was the lowest for 2008 (0.29%) followed by 2009 (0.75) (Table1). 1.43 2.08 2.04 3.74 4.65 5.19 Subsidy (Rs in lakh) Category wise farmers are benefitted
Category wise farmers covered in 2006 were 50740 1.56 which increased by 104.9% up to 2011 (103970).This 155.5 213.9 383.9 454.3 697.0 Premium increase was noticed 22.55% and 164.82% for small/ (Rs in lakh) marginal and other categories of farmers respectively. It is also observed that farmers covered under small/ marginal farmers were much less from 2006 to 2011 than farmers of other category. Regarding the total area Sum
covered it increased from 209510 ha (2006) to 371510 4443.6 6112.7 4471.7 incured 10969.7 12979.6 17057.4 ha (2011), but it decreased for farmers under small/ (Rs in lakh) marginal categories by 61.2% (from 101100 ha to 39160 ha). Thus increase in total area is due to more coverage
of the farmers of other category (from 108400 ha to (ha) Area 96478 78959 incured 332350 ha). The sum insured of Rs 800987570 was 129116 142320 155943 166019 recorded for the year 2006 which increased up to Rs 3849508040 in the year 2011. Similar to area covered sum insured also decreased by 25.1% from 2006 (Rs 19987 27714 18535 32105 39316 41125 Farmer 464189910) to 2011 (Rs 347643300) for small/marginal incured farmers while, it increased from Rs 336797650 to 3501860730 for farmers of other category. Similar results were obtained for premium collected, it also Table 1. Performance of NAIS of Performance 1. Table Year 2006 2007 2008 2009 2010 2011 Source: Agriculture Insurance Company of India Limite
342 decreased for small/marginal farmers from Rs 16048380 It could be noted from the table that farmers covered (2006) to 8710410 (2011). Increase in total premium were slightly higher in rabi season as compared to kharif collected from 2006 to 2011 (from Rs 21269100 to in each year except 2003 where more farmers were 98282800) is due to increase in premium collected from covered in kharif (17580) as compared to rabi (4300). farmers of other category (Rs 5220720 to 89572390 A gradual increase in number of farmers was observed respectively for 2006 and 2011). in both the season from 2001 to 2011 with the exception Both absolute and relative changes were higher of kharif 2008, rabi 2008 and rabi 2011 where it declined for farmers of other category than small/marginal. The slightly than preceding year. During kharif season area covered was declined for small/marginal farmers number of farmers covered under NAIS ranged between and the absolute and relative changes were declined 17580 (2003) to 51440 (2011) whereas during rabi 61.94 and 61.26% respectively. But the area covered season they ranged between 4300 (2003) to 60680 increased for farmers of other category which in turn (2010). The range of area covered was 84.44 thousand increased the total area covered. Negative changes ha to 202.32 thousand ha and 15.24 thousand ha to were observed for sum insured and premium collected 213.00 thousand ha during kharif and rabi season too for the farmers of small/marginal category. On the respectively. Area per farmer ranged between 3.93 ha other hand positive changes were observed for the (2011) to 4.92 ha (2001) during kharif season and 2.94 farmers of other category (Table 2). ha (2004) to 4.18 ha (2001) during rabi season. Maximum sum insured was noted during kharif Claim disbursement of NAIS 2011(Rs 21137.79 lakh) followed by rabi 2011 (Rs17358.63 lakh) while minimum was recorded during rabi 2001 (Rs159.12 lakh). Similarly maximum sum Performance and claim disbursement of NAIS in both insured per hectare was also recorded during kharif the seasons was studied and data has been presented.
Table 2. Category wise farmers are benefited No. of Farmers: (000) Area: - (000 ha) Sum Insured & Premium: (000) Year Particular Small/marginal Others Total 2006 Farmers covered 21.37 29.37 50.74 Area covered 101.10 108.40 209.51 Sum insured 464189.91 336797.65 800987.57 Premium 16048.38 5220.72 21269.10 2011 Farmers covered 26.19 77.78 103.97 Area covered 39.16 332.35 371.51 Sum insured 347647.30 3501860.73 3849508.04 Premium 8710.41 89572.39 98282.80 Change Farmers covered A.C. 4.81 48.41 53.22 R.C. % 22.51 164.83 104.88 Area covered A.C. -61.94 223.94 161.99 R.C. % -61.26 206.57 77.32 Sum insured A.C. -116542.61 3165063.08 3048520.47 R.C. % -25.10 939.75 380.59 Premium A.C. -7337.97 84351.66 77013.69 R.C. % -45.72 1615.70 362.09 A.C. : Absolute Change , R.C.: Relative Change * Source: Agriculture Insurance Company Of India Limited
343 0 0 76 51 3.7 414 417 2.85 0.40 0.89 9.82 12.3 2.19 0.99 7.55 -410 9543 1466 2308 3808 1414 1125 1953 1922 2117 -99.5 -98.2 37.94 16.22 17.93 Farmers benefitted Area: Area: - (000 ha) 0 0 943 447 118 104 233 761 -2.6 1017 1333 8358 7194 4302 1717 8373 2079 1625 5796 Claim 19622 12556 17728 56386 28673 44843 44082 131687 810109 316718 104231 No. No. of Farmers : - (000) 66 93 91 28 38 33 57 60 48 33 113 155 179 159 733 810 314 266 314 430 540 428 395 1131 1104 1359 1198 1217 1195 -1.91 Per Per ha Sum Insured Premium & : - (Rs 000) premium 509 872 5996 7893 9661 7850 2445 4098 4767 5968 5220 7151 2351 -0.33 614.4 14953 18075 16048 24036 17397 46264 52088 69902 56085 12898 14036 26124 28381 22847 20496 Premium ) ` 12 182 1949 2736 3297 4415 5107 4591 2661 1262 2398 1666 3662 3913 3107 1415 1738 21858 24059 34501 33156 41092 36250 19509 15947 19199 25783 33051 26011 24595 Change insured ( Per ha sumha Per Rabi Kharif Change 639 Sum 1282 13854 15913 25396 insured 176328 231057 281636 427242 516446 464190 716935 517018 229674 259593 308186 388310 336798 800249 429133 857440 100301 1411780 1564324 2113779 1696628 1564508 1735863 1385937 1285636 4.92 4.38 4.86 3.64 3.83 4.73 4.61 4.25 4.36 3.95 3.93 4.72 4.08 4.18 3.75 3.54 2.94 3.22 3.69 3.75 3.38 3.27 3.51 3.22 3.82 3.33 -0.49 12970 -13.56 -12.82 area (ha) Per farmer Per 87.4 Area 90.46 84.44 85.41 96.76 101.1 91.39 86.77 15.24 84.16 99.24 108.4 90.91 70.30 101.13 151.18 178.30 186.52 202.32 189.05 117.87 108.27 153.69 146.02 213.00 169.18 176.07 105.76 150.44 497026 covered 4.3 26.4 30.8 18.39 19.26 17.58 26.56 21.38 32.80 21.49 40.92 47.18 51.44 18.41 46.51 24.38 20.92 28.88 28.61 29.37 41.02 26.91 44.66 60.68 52.52 18.03 52.62 34.59 152.65 191.79 covered Farmers Claim disbursement of NAIS disbursementof Claim Table 3. Table Year 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2001 2011 A.C. R.C.% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2001 2011 A.C. R.C.%
344 2011 (Rs 41092.13) followed by kharif 2009 (Rs References 34500.97) while minimum was noted during rabi 2001 (Rs 182.07). It is observed that maximum premium of Abbaspour (1996) Bayesian risk methodology for insurance Rs 699.01 lakh was collected in kharif 2011 while decisions. World Agril. Economics and Rural Soc minimum was noted for rabi 2003 (5.09 lakh). Per Abst 38 (8):486 hectare premium ranged between 66.28 to 1358.90 Ahsan SM (1983) Crop insurance in Bangladesh: An during kharif seasons of study and Rs 27.98 to Rs assessment of the pilot programme. Internat Agric 22 (3): 251-262 540.38 during rabi seasons. As regards the claim it was Bruce J (2009) Factors Affecting Farmers Utilization of noted maximum for kharif 2011(Rs 8101.09 lakh). Agricultural Risk Management Tools: The Case of Number of farmers benefited were highest in kharif 2002 Crop Insurance, Forward Contracting, and Spreading (9543) followed by kharif 2006 (Rs 2308) (Table 3). Sales: Agril and Applied Econo 41(1) 107-123 Chaubey P, Chesneau Doosti (2011) On Linear Wavelet Density Estimation : Some Recent Developments Conclusion Institute South Asian Studies 65(2):169-179
The study leads to concluded that the NAIS coverage in terms of area covered, Premium collected, Claim (Manuscript Receivd : 30.3.13; Accepted : 1.8.13) settlement etc. is small, and thus the present level of coverage will have to be improved for agricultural risk management. Efforts by the government be requires in terms of designing appropriate mechanism and also providing financial support to the insurance agencies. e/;izns'k esa vfuf'pr ekSle ds dkj.k d`f"k mRiknu rFkk iz{ks= vk; esa tksf[ke cuk jgrk gS jkf"V; d`f"k chek ;kstuk ftldk fdz;kUo;u o"kZ 1999&2000 ls Hkkjr ljdkj }kjk fd;k x;k gSaA ;g ;kstuk d`"kdks dks Qly chek lqfo/kk iznku djrh gSa vkSj fdluks dks mRiknu tksf[ke lss lqj{kk iznku djrh gSa A izLrqr v/;;u e/;izns'k ds jk;lsu ftys esa jkf"V; d`f"k chek ;kstuk dh izxfr dk eqY;kadu fd;k x;k gSaA rFkk ;kstuk ds laHkkfor fdz;kUo;u gsrq vko';d lq>koks dks Hkh fn;k x;k gSa A
345 JNKVV Res J 47(3): 346-349 (2013)
Growing degree days (GDD) measurement system to predict plant stages
Bharati Dass and A. K. Rai Instrument Development and Service Centre Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur 482004 (MP)
Abstract of heat. A certain amount of heat is required to provide enough energy for the plants to move to the next Crops grown in winter season such as wheat, garden peas, development stage. The amount of heat required chick peas etc requires specific amount of energy in calories remains constant from year to year, but depending on for attending maturity. The longer the period for acquiring weather conditions, the amount of actual time can vary. required energy greater will be the biomass leading to higher Each plant has a minimum base temperature or productivity. The above said varies from variety. Weak winter threshold below which development does not occur. season with intermittent high temperature days leads to early flowering and maturity, results in loss in yields. There are Plants require physical and chemical certain ways to take corrective steps to prevent early maturity environment/inputs for growth. Equipments are available by the said reasons. Presently there is no equipment to for estimating chemical parameters such as Nitrogen, calculate amount of energy absorbed day-to-day wise in crops, phosphorus, Potassium etc from soil and plants. preventing farmers to take appropriate steps. People often Similarly equipments are available for soil moisture use a calendar to predict plant development for management estimation and photo radiations in visible and IR regions. decisions. However, calendar days can be misleading, However in addition to above certain crops grown in especially for early crop growth stages. Measuring the heat winter season such as wheat, garden peas, chick peas, accumulated over time provides a more accurate physiological estimate than counting calendar days. The ability to predict a mustard etc requires specific amount of heat energy in specific crop stage, relative to insect and weed cycles, permits calories for attending maturity. The amount of heat better management. This is especially important when more required remains constant from year to year, but than two crops are being grown on same field, each with a depending on weather conditions, the period for different management schedule for pesticide application, acquired energy may vary and is not constant in terms fertility management, irrigation scheduling and harvest. of days. Each organism has a minimum base Growing degree days (GDD)_ sometimes called heat units temperature or threshold below which development are used to relate plant growth, development and maturity to does not occur. The longer the period for acquiring air temperature. GDD is based on the idea that development required energy greater will be the biomass leading to of a plant will occur only when the temperature exceeds a specific base temperature for certain number of days. Each higher productivity. This may vary from crop to crop and type of plant is adapted to grow best over its own specific variety to variety. Weak winter season with intermittent base temperature, called Tbase. Keeping above in view the high temperature days leads to early flowering and authors are proposing to develop a suitable system which maturity, results in loss in yields. will predict plant stages based on GDD. Growing Degree Day Keywords: Heat energy, growing degree days, plant growth, base temperature. The heat units accumulated over the growing season for a particular crop is defined as Growing degree Day. Plant development depends on temperature. Its GDD is based on the idea that development of a plant development is closely related to the daily accumulation
346 will occur only when the temperature exceeds a specific Need of the Equipment base temperature for certain number of days. Each type of plant is adapted to grow best over its own specific Presently there is no equipment to calculate amount of base temperature, called Tbase. energy absorbed day-to-day wise in crops, preventing farmers to take appropriate steps.
Daily GDD=((Tmax+Tmin)/2)-Tbase Importance where, Accurate prediction of crop stages can determine the Tmax = the daily maximum air temperature. growth progress of crops in relation to temperature and Tmin = the daily minimum air temperature. moisture.
Tbase = the GDD base temperature for the plant being Predicts and defines the time when herbicides monitored. or insecticides can be applied for optimum activity, If daily GDD calculates to a negative number it is made efficacy and control. equal to zero. Permits accurate comparisons of crop development in different years at widely separated Present Status locations. Predicts and determines when nutrient and People often use a calendar to predict plant irrigation scheduling can correspond to crop development for management decisions. However, deficiencies. Fertilizers can be added during early calendar days can be misleading, especially for early growth stages to correct deficiencies and increase crop growth stages. yields.
Use of Degree Day Methodology proposed
Measuring the heat accumulated over time provides a Basically to calculate GDD information needed are: more accurate physiological estimate than counting • T calendar days. The ability to predict a specific crop max stage, relative to insect and weed cycles, permits better • Tmin management. This is especially important when more • T than two crops are being grown on same field, each base with a different management schedule for pesticide application, fertility management, irrigation scheduling For measuring temperature electronically following and harvest. sensors are commonly used: • Platinum Resistance • Thermisters • IC based sensors • IR sensors
Some of them are having non-linear response. In addition to above Solid State Sensors are available such as analog (LM-35) and digital (LM-95234). Sensor will be selected after testing their Fig 1. Thresholds and degree days accuracy and power requirement. Electronic interface of sensors will be designed keeping in view the 347 Display P anel Clock Digital code
T1
T2 Microcontroller + T3 A MUX Memory D 16 C channel Digital data
T8
Start conversion
Fig 2. Hardware schematic block diagram
environmental conditions of the field such as humidity, mRikndrk c<+rh gSA mijksDr ÅtkZ fofHkUu fdLekss ds fy, vyx & temperature etc. The digital interface will be in terms of 12 bit ADC and 8051 microcontroller or any other low vyx gksrh gSA power microcontroller. 8051 consists of four-8bit parallel ports with a total of 32 I/O lines, 8bit data bus, 16 bit lfnZ;ksa de lnhZ iM+uk rkieku T;knk gksus ij Qlyksa es le; address bus, 4KB on chip program memory, 128 bytes on chip data memory, 32 general purpose register each ls igys Qwy ,oa ifjidork vk tkrs gS]ftlls iSnkokj esa uqdlku of 8 bits, two 16 bit timers, five interrupts, one 16 bit gksrk gS A tYnh ifjiDork dks jksdus ds dqN mik; gSA orZeku esa program counter and one 16 bit data pointer register, one 8 bit stack pointer, 12MHz crystal, one full duplex Qlyksa eas gj fnu vo"kksf'kr gksus okyh ÅtkZ dh ek+=k dh x.kuk djus serial communication port. ds fy, dksbZ midj.k ugh gaS A fdlku Qly izca?ku ds fy, ikS/kksa ds fodkl&nj izkIr djus dSysaMj fnuksa dk mi;ksx djrs gSaA dSysaMj fnu Conclusion Qly ds izkjfHHkd fodkl ds le; Hkzked gks ldrk gSA le; ds lkFk GDD measurement system will be very useful for vo"kks'kr ÅtkZ ekiu vf/kd lVhd vuqeku iznku djrh gSA predicting the plant stages and maturity of crops during winter season. References
'khrdky esa mxkbZ tkus okyh Qlykssa tSls xsagq eVj] puk bR;kfn dh Pal SK, Verma VN, Singh MK, Thakur R (1996) Heat unit ifjiDrk esa ÅtkZ dh fo"ks'k ek=k dh vko";drk gksrh gSA bl ÅtkZ requirement for phonological development of wheat (Triticum aestivum L.) under different levels of dks izkIr djus dh vo/kh T;knk gksus ij ck;aksekl T;knk gksxk ftlls irrigation, seeding date and fertilizer. Indian J Agric Sci 66: 397-400
348 Peterson RF (1965) Wheat Crop Series, Ed Polunin N, Inter Science Publication Inc. New York 422 Phadnawis NB, Saini AD (1992) Yield models in wheat based on sowing time and phonological development. Annal P Physiolo 6: 52-59. Tewari SK, Singh M (1993) Yielding ability of wheat at different dates of sowing: a temperature development performance. Indian J Agric Sci 38: 204-209 Wilsie CP (1962) Crop Adoptation and Distribution. Freeman W H and Co., London pp.52-59 Miller P, Lanier W, Brandt S (2001) Using Growing Degree Days to Predict plant stages, Montana State University, Mont Guide MT200103 AG 7/2001
A S t a r t
S e le c t a D i s p la y c r o p
H = 0 B I s H B A t t a in e d M a t u r i t y R e a d T m a x , v a l u e ? T m i n , T b a s e
C a l c u la t e G DD S t o p
I s GDD – v e ? G D D = 0
H = H + G D D
S t o r e H
A
Fig 3. Flow diagram
(Manuscript Receivd : 3.10.13; Accepted : 26.12.13)
349