India is a predominantly agriculture based economy country. Annual population growth rate of the country is nearly % and if per capita consumption of rice is expected to be 400 gm of rice per day then the demand for rice in 2025 will be 130 m. tones. For obtaining the high yield with seed planting equipment or planter, it is very essential to drop the paddy seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on forward speed of the planting equipment, peripheral speed of metering plate and area of cells on the plate. The relationship between these factors and the performance parameters viz. seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and may pose to difficulty in the determination of inputs for a set of desired outputs (reverse mapping). | Neural network prediction of performance parameters of an inclined plate seed metering mechanism and its reverse mapping for rice
