Farmers are advised to store maize up to November 2012 Kharif grown Maize is steadily entering into markets of north Karnataka. Uncertain prices at harvest have made the farmers to think about the time and place of selling the produce. Under such a fix, to help the farmers to take right decision regarding place and time of sale of the commodity, the prices of Maize that would prevail in major market of north Karnataka have been predicted by the Domestic and Export Market Intelligence Cell (DEMIC) established in the Department of Agribusiness Management, University of Agricultural Sciences, Dharwad. Monthly modal prices of Maize were collected from Ranebennur regulated market for the past 15 years and were analyzed by using rigorous time series analytical models and reliable forecast prices that would prevail in these markets during the months of September, October and November were established. The output prices were cross verified with the opinions of traders, agricultural scientists and progressive farmers to fine tune the forecast prices. The prices from other major markets and the future prices being announced by the National Commodities and Derivates Exchange of India (NCDEX) were also considered to come up with accurate price forecast.
According to price forecasts and opinions of traders and suggestions of the experienced persons, the prices of Maize would be around Rs. 1100 to 1200/- in the month September and October and Rs.1200 to 1300 in the month of November per quintal in Ranebennur market. However, the prices are likely to improve in November month. Therefore, it is advised to store maize till coming November and sell afterwards. Storage cost in the government godowns is Rs. 3 per quintal per month. Good quality, bold seeded, clean grains free from pests and diseases are going to fetch better prices in the markets. Farmers need to keep these things in mind while storing the produce.
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Time Series Analysis
Your price forecasting service/method is highly appreciated by all and will help not only the farmers but the entire value chain. Time Series Analysis is generally used widely in industrial processes as well as in business metrics and aids for making forecasts in production, marketing as well as quality control. It will be very kind of you to explain the mechanism in slight detail