A Research on Prediction of Crop Yield and Its Forecasting Methods - Dr. Geeta Kandpal (International Journal of Modern Agriculture, 2021)
Agriculture has the biggest share of our nation's GDP. Still farmers are most suffered people in India because they don't get a reasonable profit value of their crops. This happens because of inadequacy in irrigation level or crop selections or often the yield from crops is way lower than there expectations. It is possible to estimate the net crop yield by evaluating the soil and environment at maximum crop in a given area in order to provide more crop yield. This forecast would help farmers pick appropriate crops based on the type of soil, temperature, moisture, ranging depth, water level, season, fertilizer, soil pH, and the months. Crop production early Predictions is a technique for forecasting crop yields using various parameters such as precipitation, temperature, chemicals, insecticides, ph level, pesticides and different other environmental parameters and conditions . ANN (Artificial Neural Network) is a yield-predicting tool. To put it simply, crop yield is the quantity of crop produced per land area. It is usually used for rice, cereals, wheat, or legumes, and can be recorded in kilograms / hectare or metric tons / hectare. Agricultural production is also called crop yield. Technology, including the use of nitrogen, the production of better agricultural equipment, modern growing techniques and enhanced crop hybrids have increased yields. The higher the yield and the more productive use of the soil, the greater a farmer's productivity and profitability; this improves farming families' well-being.