ANALYZING IRRIGARION QUALITY TO POTENTIALLY IMPROVE SUGARCANE YIELD USING AGRICULTURE DATA ANALYTICS

Abstract

Agriculture is the foundation of Indian economy. Sugarcane is one of the widely developed harvests in Tamilnadu. Big data are emerging précised and viable analytical tool in agricultural research field. This study paper facilitates the farmers to improve the crop yield. The object of the present study was to investigate the relationship between the chemical properties of water and sugarcane yield, by this means identifying the water parameters that determine the final productivity of the yield. The Sugarcane fields monitored during the cultivation for water samples and yield data collected annually. A random forest algorithm applied to investigate the influence of different water attributes on yield using by collected data, over the study period. The irrigation mainly depends on several parameters of water, which is termed as Electrical Conductivity (EC) node and Sodium Absorption Ratio (SAR) node under the Residual Sodium Carbonate (RSC) finalized. From the final report of the RSC that concluded with four types of Soil. The water irrigation prediction is important for farmers and it maintained with the help of previously available data. An irrigation influenced by salinity, alkalinity, sodicity and surface hardening of the soils. The results show that the amount of available water EC, PH, and Alkalinity. Sugarcane farmers are consistently in the expedition for higher harvest yields, higher expanded profit.