Closed manikumarreddyu closed 1 month ago
Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions or additional information, feel free to add them here. Your contributions are highly appreciated! 😊
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I am interested in contributing to this issue and try to build a yield prediction model based on the requirements. Please assign it to me and add the appropriate labels. Thankyou for your time and consideration!
Hello @manikumarreddyu! Your issue #64 has been closed. Thank you for your contribution!
if you have any queries connect me here: https://www.linkedin.com/in/manikumarreddyu
hi @AYUSHI-SHA if you can create frontend and api.. i will put labels here..because without froontend there is no use of it..and causing problems in cloning for others..please let me know if you can create frontend part...as of now you are simply getting projects from somewhere in other repos and pasting them here...im sorry for removing labels..if you do fronend and api part i can relabel them ..i think you understand my point...simply having notebook files does nothing..until now..which are in notebooks..all of them have frontend and api.. thank you @AYUSHI-SHA
Hello @manikumarreddyu! Your issue #64 has been closed. Thank you for your contribution!
Is there an existing issue for this?
Feature Description
I propose the development of a Yield Prediction Model using machine learning that estimates crop yield based on:
Soil quality (nutrients, pH, organic matter, etc.). Weather patterns (rainfall, temperature, humidity, etc.). Farming practices (irrigation methods, fertilizer usage, crop rotation, etc.). The model will take these inputs and provide farmers with an estimate of their potential harvest, helping them make informed decisions about resource allocation, crop selection, and timing.
Use Case
This feature would help farmers and agricultural managers by:
Estimating potential crop yield based on real-time data from their farm and local weather patterns. Optimizing farm management: With predicted yields, farmers can make more efficient decisions about inputs like fertilizers, water, and labor. Planning for market demand: Yield predictions help farmers plan harvest times and quantities for better market pricing and sales strategies.
Benefits
Informed Decision-Making: Farmers can optimize their farming practices and resource use based on predicted yields. Reduced Waste: By knowing their expected yield, farmers can minimize unnecessary inputs, reducing costs and environmental impact. Risk Management: Predicting lower-than-expected yields allows farmers to take proactive steps (like adjusting crop management or seeking alternative crops) to mitigate losses.
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Priority
High
Record