Open AccessCrop Yield Prediction
Author(s) -
Pallavi Shankarrao Mahore,
Aashish A. Bardekar
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2173168
Subject(s) - yield (engineering) , crop , environmental science , soil fertility , crop yield , agricultural engineering , soil type , agronomy , mathematics , soil water , soil science , engineering , materials science , biology , metallurgy
Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance for crop yield is compared with Random forest, Support Vector Machine, Weather, K Nearest neighbor. , which shows better performance results for each selected weather parameters. Crop yield rate depends upon various parameters such as the geography of area, soil type, soil nutrients, soil alkaline, weather condition, etc. The combination of these parameters can be used for selection of suitable crops for a farm or land to gain maximum yield. In this manuscript, soil and weather parameters such as soil type, soil fertility, maximum temperature, minimum temperature, rainfall are used to identify suitable crops for specified farm or land.