Machine Learning- and Feature Selection-Enabled Framework for Accurate Crop Yield Prediction
Agriculture is crucial for the existence of humankind. Agriculture provides a significant portion of the income for many people all around the world. Additionally, it provides a large number of work possibilities for the general public. Numerous farmers desire for a return to the old-fashioned techn...
Saved in:
Main Authors: | Sandeep Gupta, Angelina Geetha, K. Sakthidasan Sankaran, Abu Sarwar Zamani, Mahyudin Ritonga, Roop Raj, Samrat Ray, Hussien Sobahi Mohammed |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Journal of Food Quality |
Online Access: | http://dx.doi.org/10.1155/2022/6293985 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An IoT and Machine Learning-Based Model to Monitor Perishable Food towards Improving Food Safety and Quality
by: Amina Batool, et al.
Published: (2022-01-01) -
Random forest model that incorporates solar-induced chlorophyll fluorescence data can accurately track crop yield variations under drought conditions
by: Guangpo Geng, et al.
Published: (2025-03-01) -
Improved Support Vector Machine and Image Processing Enabled Methodology for Detection and Classification of Grape Leaf Disease
by: Arshiya S. Ansari, et al.
Published: (2022-01-01) -
YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation
by: Bellout Abdelaaziz, et al.
Published: (2024-01-01) -
Toward Accurate Physics‐Based Specifications of Neutral Density Using GNSS‐Enabled Small Satellites
by: Eric K. Sutton, et al.
Published: (2021-06-01)