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In Zvimba District of Zimbabwe International Journal of Scientific Research in ___________________________ Research Paper. Multidisciplinary Studies E-ISSN: 2454-9312 Vol.6, Issue.9, pp.37-42, September (2020) P-ISSN: 2454-6143 Determinants of Production of Sorghum (Sorghum bicolor) and Millet (Eleusine coracana) in Zvimba District of Zimbabwe I. Kutyauripo1*, P. Mutombo2 1Directorate of Quality Assurance and Standards, Ministry of Higher and Tertiary Education, Science and Technology Development, Harare, Zimbabwe 2Kariba Redd+ Project, Carbon Green Africa (CGA), Harare, Zimbabwe *Corresponding Author: [email protected], Tel.: +263-0712576808 Available online at: www.isroset.org Received: 26/Aug/2020, Accepted: 15/Sept/2020, Online: 30/Sept/2020 Abstract— The adverse effects of climate change are hampering maize (Sub Saharan Africa’s major staple cereal crop) production. Small grains are resilient to high temperatures and low rainfall that result from climate change. Small grains can be produced as an alternative to maize in times of climate change induced drought. However, the proportion of households that are in sorghum and millet production remains relatively lower to maize-producing households. This study sought to investigate the determinants of choice of sorghum and millet production in Zvimba District of Zimbabwe. Farming households (120) were selected from 6 wards through multistage sampling. A structured questionnaire was distributed to household heads. Descriptive statistics was used to analyse data. Binary logistic regression was used to analyse factors affecting choice of production of sorghum and millet. Results from the survey indicated that 59.2% of the interviewed farmers are into sorghum and millet production with 47.5% producing millet whilst 11.7% produce sorghum. Results of binary logistic regression indicated that age and training in small grain production significantly affect (p ≤ 0.05) the choice of producing small grains. Labour intensiveness, lack of market information, lack of certified seeds and lack of technical support were identified as the major constraints to sorghum and millet production. It was concluded that farmer’s age, agriculture extension, market information, technical support, seeds and labour influence sorghum and millet production. The results of this finding will inform African farmers and stakeholders on the challenges that need to be addressed in small grain farming as a way of adapting to the changing climate. Keywords— climate change, millet production, sorghum production, Zvimba district I. INTRODUCTION [7; 8]. Sorghum can be utilised as an alternative to maize in cases of maize production failures [9]. Finger millet is Southern Africa food security is under threat from the nutritious being high in calcium, iron and magnesium [6]. effects of the changes in the climate. A decline in annual However, despite all the advantages of growing millet and rainfall amount and rising temperatures over decades have sorghum as a grain cereal in times of climate change been witnessed in Southern African countries to include induced drought there is low adoption of sorghum and Zimbabwe [1;2;3]. These changes in the climate negatively millet production in the country, as the majority of affect rain fed maize production resulting in a yield decline communal farmers prefer maize to traditional small grains of 20% to 40% [1]. This decline in maize yields is a great [4]. Most farmers prefer to grow maize rather than small challenge given the situation that for countries in the South grains despite the fact that maize production is resulting in African Development Community only 6.6% of area under lower yields [10]. crop production is being irrigated [3]. According to [11] 9% and 12% of the farming households Communal farmers are facing drought due to the effects of in Zimbabwe produced pearl millet during the 2013/2014 climate change. Unpredictable rainfall patterns have and 2014/2015 farming season respectively. A proportion resulted in lower maize yields over the years thus resulting of 6% and 10% of the farming households produced finger in food insecurity in some areas in Zimbabwe [4]. Millet millet during the 2014/2015 farming season and 2015/2016 and sorghum have a potential for higher yields even in farming seasons respectively [11]. A household proportion times of low rainfall. Finger millet can be produced in poor of 21% and 28 % produced sorghum in the 2013/2014 soils under inconsistent rainfall thereby improving food season and 2015/2016 season respectively. According to security at household level even during the periods of [11] Mashonaland West had the lowest (18% sorghum, 2% drought [5; 6]. Sorghum is a drought resistant crop which finger millet and 1% pearl millet) small grain proportion of can also thrive high temperatures. It highly adapts to low households for 2015/2016 season for all the farming fertile soils, and soils with poor water holding capacities provinces in Zimbabwe. According to [12] during the © 2020, IJSRMS All Rights Reserved 37 Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.9, Sept 2020 2016/17 agricultural seasons Mashonaland West had the production of sorghum and millet. The natural logarithm lowest proportion of small grain farming households (9% of the odds is the dependent variable and it is calculated as for sorghum,1% for pearl millet and 2% finger millet) in follows [16; 17]: Zimbabwe. The above information reflects that over the years Mashonaland West is one of the regions with the In [Ps/1-Ps] = β0 + β1X1s + β2X2s + β3X3s + …………+ lowest proportion of households that are into small grain βnXns. (1) production in Zimbabwe. This study investigated the factors influencing choice of sorghum and millet Where Ps is the probability of producing small grains, 1-Ps production in Zvimba District that lies in Mashonaland is the probability of not producing small grains, the West province of Zimbabwe. There is limited literature on subscript s denotes observation in the sample, β0 denotes a the constraints to traditional small grain production in the constant, β1…. βn denote regression coefficients and X1, Province of study. Section I of this paper is the …. Xn denote explanatory variables. introduction, Section II is the methodology, Section III contains the results and discussion of the study, Section IV Table 1. Binary logistic regression model explanatory variables concludes the research findings and recommends future Variable Description actions. Sex 0 if female 1 if male Age 0 if above 30 years, 1 if below II. METHODOLOGY 30 years Marital status 0 if not married, 1 if married Training in small grains 0 if not trained, 1 if trained Study Area Crop preference in terms of 0 if maize, 1 if small grains Zvimba District is located in Mashonaland West Province consumption of Zimbabwe. Zvimba district coordinates are 17° 42’ Religion 0 if Christian, 1 if African 0.00”S, 30° 12’ 0.00”E [13].The district is bordered by religion Guruve district, Mazowe district, Chegutu district, Education level 0 if formally educated,1 if not Makonde district, Kadoma district and City of Harare [14]. formally educated According to the 2012 census Zvimba district has 132 165 males and 130 855 females giving a total population of 163 III. RESULTS AND DISCUSSION 020. The livelihood of Zvimba district is mainly based on mining and agriculture with maize as one of the crops Demographic Information mainly grown in the district [13; 15]. Table 2. Demographic information of respondents Data Collection and Analysis Variable Percentage A quantitative research survey was carried out. Multistage Sex Male 52.5 sampling was used. Random sampling of 20 farming Female 47.5 households followed purposive sampling of six communal Age farming wards (wards 6, 7,10,11,12 and 29) of Zvimba 18-30 10.0 district. A questionnaire was designed in the structured 31-45 35.8 format to collect demographic information, small grain 46-60 31.7 (specifically millet and sorghum) production, annual Above 60 22.5 yields, farm area allocated to small grain production, Marital status reasons for not choosing small grains, major purpose for Single 6.7 small grain production and agriculture extension on small Married 66.7 grains. A pilot test of the questionnaire was conducted. Divorced 5.8 Widowed 20.8 Informed consent was sought from all the participants. The Farming experience questionnaire was distributed to household heads. 5 years and less 10.0 Frequencies and percentages were used in the descriptive More than 5 years 90.0 analysis of data. Binary logistic regression analysis using Level of education Statistical Packages for Social Scientists (SPSS) Version No formal education 12.5 20 determined factors influencing choice of small grain Primary level 26.7 farming. Binary logistic regression model was suitable for Secondary level 55.0 analysis of determinants of small grain production because Tertiary level 5.8 it is used when the dependent variable is dichotomous [16; Religion Christianity 97.5 17]. The dependent variable was small grain production African religion 2.5 and it had two options; producers of small grains represented by 1 and non-producers of small grains In this study majority of the respondents were males. represented by 0. The dependent variable (Y) denotes Majority of the farmers who participated in the study were small grain production. The independent variable (X) aged between 31 and 45. Married farmers constituted denotes explanatory variables that are listed in Table 1. majority of the respondents. Most of the
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