ESTIMATION OF QUANTITATIVE LOSSES OF RICE (ORYZAE SATIVA L.) DURING HARVESTING, THRESHING AND CLEANING IN THE UPPER EAST REGION: A CASE STUDY AT TONO IRRIGATION PROJECT

ABSTRACT

Loss assessment helps to identify constraints affecting the production and therefore the productivity of food crops. Information on loss assessment will thus assist in possible interventions needed to improve productivity. Quantitative losses associated with the production of rice (var. Jasmine 85) in the Kassena Nankana West District of the Upper East Region, one of the major rice producing areas in Ghana has not been adequately documented. A semi structured questionnaire was used to collect data from 84 rice farmers who were selected through a combination of multi-stage, purposive, and simple random sampling techniques. A multiple regression analysis was conducted to estimate quantitative losses and the factors that influenced the losses of rough rice. Kendall’s Coefficient of Concordance (WC) was used to determine the degree of agreement in the challenges farmers face at farm level. A technology-verification experiment was conducted on 12 farmer fields to estimate the yields and quantitative losses that do occur during harvesting and threshing at two (2) different harvesting times: improved harvesting time (35 days after heading) and farmer time of harvest (42 days after heading). A methodology adopted by Anwar (2010) was used to determine farmers’ harvest moisture content of rough rice. Rice cultivation on the Tono Irrigation Project was found to be dominated by males; only 38% were females. Therefore, males have purposefully made rice farming as a livelihood. Averagely, 0.68 ha field was under rice cultivation. Still, the average rough rice was produced at 2.73 mt/ha. The output saved for household consumption (0.7 mt/ha) was not significantly different (P>0.05) from the output (0.65 mt/ha) lost to the soil. Besides, the amount of rough rice that could have been saved for domestic consumption was equally lost at a percentage loss of 24%. From the perspective of the farmers, the losses were attributed to inappropriate time of harvesting. From the regression analysis, acreage (β=0.952 mt, P