💡[Feature]: Crop recommendation and production prediction using supervised and unsupervised learning #1493
Description
Is there an existing issue for this?
- I have searched the existing issues
Feature Description
❓Problem Statement:
The aim is to develop a predictive model that can forecast crop yields based on various factors such as district, state, season, and crop type. By leveraging supervised machine learning techniques, the model will provide farmers with valuable insights into expected crop yields in advance. This information enables farmers to make informed decisions regarding crop selection and planning, ultimately optimizing agricultural productivity and resource allocation.
Description of dataset 1, crop production: The dataset contains historical records of crop yields along with corresponding factors such as district, state, season, and crop type. Each record represents a specific instance of crop cultivation and its corresponding yield.
Sample Data:
District: XYZ State: ABC Season: Kharif Crop Type: Rice Yield (in tons/acre): 5.8
District: XYZ State: DEF Season: Rabi Crop Type: Wheat Yield (in tons/acre): 4.3
Description of dataset 2, crop recommendation: The dataset contains records of multiple attributes that determine what type of crop can be grown for the given weather, soil and nutrient availability conditions
Sample Data:
N: 94,
P: 50,
K: 37,
temperature: 25.66585205,
humidity: 80.66385045,
ph: 6.94801983,
rainfall: 209.5869708,
label: rice
Use Case
To be added as a prediction model
https://github.com/avogadroB/Crop-Predict-Rec
Benefits
No response
Add ScreenShots
No response
Priority
High
Record
- I have read the Contributing Guidelines
- I'm a GSSOC'24 contributor
- I want to work on this issue