Predictive Modeling of Climate-Driven Crop Yield Variability Using DSSAT Towards Sustainable Agriculture

Predictive Modeling of Climate-Driven Crop Yield Variability Using DSSAT Towards Sustainable Agriculture

Climate change poses a significant threat to agricultural productivity, particularly in regions vulnerable to extreme temperatures and water scarcity, such as Irbid, Jordan. This study assesses the future impacts of projected shifts in precipitation and temperature on wheat yields, using the Decisio...

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Bibliographic Details
Main Authors: Safa E. El-Mahroug, Ayman A. Suleiman, Mutaz M. Zoubi, Saif Al-Omari, Qusay Y. Abu-Afifeh, Heba F. Al-Jawaldeh, Yazan A. Alta’any, Tariq M. F. Al-Nawaiseh, Nisreen Obeidat, Shahed H. Alsoud, Areen M. Alshoshan, Fayha M. Al-Shibli, Rakad Ta’any
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:AgriEngineering
Subjects:
climate scenarios
crop–climate interaction
data-driven agriculture
gradient boosting
heat and water stress
machine learning
Online Access:https://www.mdpi.com/2624-7402/7/5/156
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