Cotton Yield Prediction: A Machine Learning Approach With Field and Synthetic Data-Reference-Cited by-同舟云学术

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Cotton Yield Prediction: A Machine Learning Approach With Field and Synthetic Data

Published:2024 Issue: Volume:12 Page:101273-101288
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mitra Alakananda¹^ORCID,Beegum Sahila¹^ORCID,Fleisher David¹^ORCID,Reddy Vangimalla R.¹^ORCID,Sun Wenguang²^ORCID,Ray Chittaranjan³^ORCID,Timlin Dennis¹^ORCID,Malakar Arindam³^ORCID

Affiliation:

1. Adaptive Cropping Systems Laboratory, USDA-ARS, Beltsville, MD, USA

2. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, USA

3. Nebraska Water Center, Daugherty Water for Food Global Institute, University of Nebraska-Lincoln, Lincoln, NE, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10568958.pdf?arnumber=10568958

Reference86 articles.

1. Random Forests for Global and Regional Crop Yield Predictions

2. An interaction regression model for crop yield prediction

3. Machine learning for large-scale crop yield forecasting

4. Definitions and determination of crop yield, yield gaps, and of rates of change

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