Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

Soil salinity is a serious land degradation issue in agriculture. It major threat to agriculture productivity. Extra irrigation water applied leach down the salts from root zone of plants form Leaching fraction (LF) water. For leaching process be effective, LF needs adjusted according environmental conditions and soil level Evapotranspiration (ET) rate. The relationship between ET rate hard defined by linear data-driven Machine learning (ML) based decisions are required determine calibrated (ETc) ML-assisted ETc proposed adjust level. A regression model prevailing temperature, humidity, sunshine, which would used smart trained tested against Blaney Criddle method Reference evapotranspiration (ETo) determination. validation test dataset reveals accuracy ML terms Root mean squared errors (RMSE) 0.41, Mean absolute (MAE) 0.34, (MSE) 0.28 mm day−1. applications solution real-time environment show that more effective reducing as compared traditional leaching.