ndia holds major position in most of agricultural commodities but at the same time the post-harvest losses for agricultural commodities estimated to be high and only insignificant proportion of agricultural produce is being processed. Thus need to emphasize on processing and value addition, developing the skills of farmers in this area and linking them with market and other supporting institutions. Therefore, development and promotion of an efficient value chain is critical for the accelerated development of agriculture sector and for increasing producers’ shares in consumers’ price. Moreover, promoting value chain development and establishing an enterprise, require degree of some entrepreneurial behaviour among processors which is the result of continuous interaction of personal factor and entrepreneurial environment. Considering the above mentioned factors, the present study was carried out to analyse the entrepreneurial behaviour and entrepreneurial environment for promoting value chain, developing value chain map in selected agricultural commodities, identifying training needs of agripreneurs engaged in food processing and to formulate strategies for inducing entrepreneurial behaviour and environment for promoting value chain development. The present study adopted an ex-post facto research design. Based on post-harvest losses and/or potential for undergoing value chain development, nine agricultural commodities like food grains (Maize, Wheat and Soybean); vegetables (Potato, Tomato and Mushroom) and fruits (Mango, Guava and Aonla) were selected purposively. After the selection of agricultural commodities, the states and further districts were selected purposively for each identified agricultural commodities based on high production under crop and/or potential for value addition. Selected districts for the present study were Samastipur, Bihar (Maize), Meerut (Potato), Lucknow (Mango), Allahabad (Guava), Pratapgarh, Uttar Pradesh (Aonla), Sonepat, Haryana (Mushroom), Dhar (Tomato) and Indore, Madhya Pradesh (Wheat, Soybean). Data was collected from 15 processors, 25 fruit producers, 20 vegetable producers and 20 food grain producers in each agricultural commodity. Further, 45 other stakeholders (intermediaries i.e. wholesaler, retailer; five from each commodity) and 18 experts (for devising strategy) were also interviewed, thus, total sample size of the present study was 393. The entrepreneurial behaviour between average processor and average farmer was compared through semantic differential technique and there was a significant difference 208 between them. The existing entrepreneurial environment was most favourable for mushroom processor (rank I) followed by soybean (rank II) andaonla processor (rank III). The lowest existing entrepreneurial environment was found for potato processor (rank IX) and tomato processor (rank VIII). The profitability between production and processing unit was compared for selected agricultural commodities and it was found that in processing unit cost incurred and net return was higher than production unit. It was also noticed the rate of processed products was more than raw material thus net income of processor was higher. Both the production and processing units were found to economically feasible as per break-even point at yield and price except potatoproduction unit for break-even yield. The marketing channels were identified for selected agricultural commodities for both processor and producer. It was found that producers’/ processors’ share in consumers’ price and market efficiency increases with decrease in intermediaries. The value chain maps were developed for selected agricultural commodities indicating major activities, actors of value chain and entrepreneurial environment through venn diagram. There was significant agreement among nine types of processors that marketing (3.78) was the major dimension of training need followed by technical (3.22), information (2) and social responsibility (1) dimension of training need. The market was most important dimension of training due to their lack of exposure to online market, promotional strategies, distant selling of products, determine competition in market, need to diversify their value added products, identify potential customer as well as point and volume of sale etc. The force field analysis was used to identify the driving and restraining forces and it was found that in case of driving forces, average processors (39.10) possessed significantly higher mean rank than average producers (21.90) and for restraining forces, average producers (45.33) possessed significantly higher mean rank than average processors (15.67). For devising strategies the experts were interviewed and Alfares method (2009) was used to analyse the data.Information dimension (94.62) was found to be the as most important aspect for strategy devising followed by institutional support (86.86), market facility (83.28), infrastructure (67.16) and post-harvest management aspect (60.59). Keywords: Post-harvest losses; Value chain; Entrepreneurial environment; Ex-post facto; Processors; Producers; Marketing channels; Break-even point; Venn diagram; Force field analysis; Alfares method.