Prediction of crop yield includes forecasting factors like temperature, humidity, rainfall, etc., and crop yield based on soil moisture includes few measures like NPK (Nitrogen, Phosphorous and ...

Input Data Collection: Allows users to input data such as soil parameters, climate information, and geographic location. Data Preprocessing: Handles missing values, normalizes/scales features, and ...

Agriculture is the pillar of the Indian economy and more than 50% of India's population are dependent on agriculture for their survival. Variations in weather, climate, and other such environmental ...

FAYETTEVILLE, Ark. — A new machine-learning model for predicting crop yield using environmental data and genetic information can be used to develop new, higher-performing crop varieties. Igor ...

Instead, Descartes relies on 4 petabytes of satellite imaging data and a machine learning algorithm to figure out how healthy the corn crop is from space. Corn yield prediction is big business in ...

"But instead of not using nanotechnology altogether, we would like farmers to reap the many benefits provided by this technology but avoid the potential food safety concerns." Reference: Wang X, Liu L ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

To implement a machine learning algorithm that gives better prediction of suitable crop for the corresponding region and crop season in our country. Multiple Linear Regression In the given regression ...