India Needs Price Forecasting System to Tackle Volatility in Agri Produce

During the era of globalization, an agricultural dominated country like India needs an efficient and reliable food price forecasting models. India needs an accurate forecasting system to tackle price volatility in agricultural produce. Accurate crop-level price information can help farmers assess the work ability of their farms. As a result, they become efficient in their day-to-day activity.

Price Volatility in Food and Agriculture

There is high price volatility in agricultural sector. This plight might be due to three major reasons. First, the highly variable productions from period to period. Secondly, the production influences the fluctuating supply of the crops in need. Finally, the increase in demand due to a shortage of supply.

The need for a Forecasting System

Farmers have faced several frustrating situations due to elusive price trends. The extremely unpredictable production, supply, and demand in the agricultural sector affect the livelihood of farmers. Further, the growing population and increase in income in the developing countries will increase the commotion in the following decades. Currently, the prices are determined by domestic and international market values that induce high-cost variability. Thereby, the need for an indicator is a must.

Price Prognosis System

Forecasts of food prices intended to be extremely useful to farmers, government and agri-companies. The quantitative prediction that is accurate with minimal errors must be the basis for any price forecasting system. One such preliminary models Artificial Neural Network (ANN) provides a potential price forecasting technique. ANN is feasible given the availability of data in developing countries.

AI and Machine Learning in Agriculture to Determine Price Trend

Price forecasting system to save tomato growers

Artificial intelligence (AI) and Machine learning (ML) all set to rescue high volatile price trend. To achieve this Karnataka Agricultural Prices Commission (KAPC) in collaboration with IBM is on the verge of developing an advanced price forecasting system. Further, AI and ML detect farm pest and disease infestation to better the yield. Primarily, this forecasting system set to launch in major tomato harvesting districts- Kolar, Chikkaballapur and Belgavi.

Thus, these systems provide a beforehand prediction, thereby increasing the profit attained by the farmers and in turn country’s economy.

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