PAUL, K.S.R.LAKSHMI MONIKA, ATCHUTUNI2019-02-142019-02-142018http://krishikosh.egranth.ac.in/handle/1/5810094961D5621An attempt has been made in this study to examine the economics of post harvest losses in Prakasam district of Andhra Pradesh. The specific objectives of the study were 1. to study the disposal pattern of chickpea in Prakasam district of Andhra Pradesh 2. to measure the extent and quantify post harvest losses in chickpea and to analyze the economic impact of post harvest losses on chickpea farmers 3. to analyze the factors affecting post harvest losses at different stages in supply chain 4. to identify the constraints in minimizing post harvest losses in chickpea Multi-stage sampling technique was employed for selection of final respondents. A sample of 80 farmers, 20 wholesalers and 20 retailers was selected from sixteen villages and four mandals of Prakasam district of Andhra Pradesh. Tabular analysis was carried out to study the disposal pattern of chickpea in the study area. Post harvest losses at district, mandal and village level were also estimated using tabular analysis. Multiple linear regression was carried to study the economic impact and to analyse the factors affecting post harvest losses at different stages in supply chain. To identify the constraints in minimizing post harvest losses, Likert scale technique was used. The primary data were collected from the major pulses producers - farmers, wholesalers and retailers through personal interview method with the help of well prepare schedule for year 2017-18. On an average 92.01 per cent and 91.66 per cent of total production was found to be marketable and marketed surplus respectively. About 46.25 per cent of the farmers sold to wholesalers because of immediate cash payment, 25.00 per cent of the farmers sold to millers because of advance loan borrowed, 17.50 per cent sold to unauthorised brokers because of well known to them and trust worthiness, 11.25 per cent sold to distant markets because of better price given by them. Wholesalers dispose 40.77 per cent of total quantity to distant markets as distant markets pay more. The postharvest losses at the farm level have been estimated to be 7.26 kg/q for chickpea. This leads to an economic loss of Rs.435.6/q. Total estimated quantity of post harvest losses in Prakasam district was 7.36 lakh quintals. The loss percentage obtained in Prakasam district was 7.35 per cent. Economic loss of post harvest losses in Prakasam district estimated to be Rs. 441.78 crore. Harvesting losses were maximum because of shattering of the grain caused by delay in the harvesting. Drying losses were because of unfavourable weather and animal attack in the field. Post harvest losses at intermediaries level were found maximum at transportation i.e. 66.95 per cent followed by storage loss i.e. 33.05 per cent of total post harvest losses. At intermediaries level transportation loss was more compared to storage loss as storage facilities were adequate in the study area. The analysis of economic impact of post harvest losses on chickpea farmers revealed that the explanatory power of the model R2 was 44.3 per cent. This implies that all explanatory variables together were explaining only 44.3 per cent of variation. Harvesting loss and threshing loss were negatively significant at 1 per cent level of significance. Marketing loss was negatively significant at 5 per cent level of significance. Drying loss and storage loss were negative but non–significant. With the increase in harvesting, threshing and marketing losses the per hectare farmers income decreases. The analysis of post harvest losses in chickpea at farm level revealed that the explanatory power of the model R2 was 44.6 per cent. This implies that all explanatory variables together were explaining 44.6 per cent of variation in post harvest losses at farm level. At farm level, weather, transportation and timely labour availability were negatively significant at 1 per cent level of significance. Age, threshing machine and storage were negative but non–significant. Cultivated area in ha, education and production in quintal per ha were positive but non- significant. The explanatory power of the model R2 at intermediaries’ level was 91.4 per cent. This implies that all explanatory variables together were explaining 91.4 per cent of variation in post harvest losses at intermediaries’ level. At intermediaries’ level, age, quantities handled were negatively significant at 5 per cent level of significance. Time of storage was positively significant at 1 per cent level of significance. Transportation was negatively significant at 1 per cent level of significance. Education, experience and storage were positive but non- significant. Late harvesting, unavailability of timely labour, improper machine condition, timely unavailability of machines,unfavourable weather at the time of drying and unavailability of right floor for drying are the major constraints faced by farmers in minimizing post harvest losses. Lack of own conveyance and defective packing at the time of transfer of material are the major constraints faced by the intermediaries in minimizing post harvest losses.en-USnullThesis