(untitled) (International Journal of Food and Nutritional Sciences, 2024)
This work represent sa machine learning model.Weusedpythonlanguage andensembled learning techniques in order to predict the disease in paddy. The proposed system will integrate the data obtained from a dataset where images are clicked and set up to dataset. By usingmachinelearningalgorithms,wecanidentifythediseasesand classify theminto different types that gives farmer a better idea about the crop. This provides farmer informationabouttheircropandwhatdiseasehiscrophas,suchthathecanuseappropriate fertilizerorpesticidetogetridofthatdisease.Thediseasesinplantareduetomanyreasons like soil, excess rains, weather and climate change. Paddy is the most grown crop in our country and agriculture is a leading sector in our country. So, it would be definitely for farmers in real time. The loss of agricultural economy and losses in the community are there foresignificantly influencedbydiseasesin thepaddyplant.Itisverydifficultforthe farmerstodetectandrecognizethevarioussymptomsanddiseasesinpaddy.So,themajor