An explainable Bi-LSTM model for winter wheat yield prediction

An explainable Bi-LSTM model for winter wheat yield prediction

Accurate, reliable and transparent crop yield prediction is crucial for informed decision-making by governments, farmers, and businesses regarding food security as well as agricultural business and management. Deep learning (DL) methods, particularly Long Short-Term Memory networks, have emerged as...

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Bibliographic Details
Main Authors: Abhasha Joshi, Biswajeet Pradhan, Subrata Chakraborty, Renuganth Varatharajoo, Abdullah Alamri, Shilpa Gite, Chang-Wook Lee
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Plant Science
Subjects:
crop yield
explainability
shap
lime
integrated gradients
bidirectional LSTM
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2024.1491493/full
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https://www.frontiersin.org/articles/10.3389/fpls.2024.1491493/full

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