Preseason Promotional and Extension Activities being Conducted by Research Seed Selling Seed Companies for the Hybrid Maize Crop
S. S. Lalage, H. R. Surnar, Y. S. Ekhande, H. B. Patil
Asian Journal of Agricultural Extension, Economics & Sociology · pp. 896–899 · Published 14 Aug 2023
10.9734/ajaees/2023/v41i92118Abstract
One of the most popular commercial seeds, maize generated Rs. 14.91 billion in income in 2016. The rise in ethanol production and increased usage of maize as animal feed are responsible for the increase in the crop. Currently, only around 25% of maize is used as food grain, with the remaining 75% being used for non-food purposes such as biofuels, animal feed, poultry feed, alcohol brewing, starch-based wet milling, and other industrial uses. However, the enhanced investment in maize by global seed companies would flow into India through technology transfer and Public-Private Partnerships in the next fifty years. The Exploratory research design was used for the present study. The study was conducted in Solapur district. Five tehsil were selected to conduct market research in Solapur district. In each tehsil 10 farmers and 5 Dealers were selected. The sample size was 5 leading markets of the district, 5 dealers per big markets and 10 farmers per big market i.e 50 farmers and 25 dealers. The research instrument used in this project was well defined structured questionnaire for Dealer and Farmer. The main objective of this study was to learn the preseason promotional and extension activities being conducted by research seed selling seed companies for the hybrid maize crop. It is revealed from that, the promotional and extension activities taken by the hybrid maize seed companies for the hybrid maize seed for encouragement of farmers as well as dealers for purchase that seed. At that time 23 farmers responded to the demonstration plot, 10 farmers responded to the advertising, 13 farmers’ response were to the campaigning and remaining 4 farmers response were to other activities taken by the companies. To make data analysis simple, simple statistical techniques like shares (percent), pie charts, and graphs were chosen once the data was systematically classified in accordance with the objectives.
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