Optimizing cereal yields in Morocco’s Favorable agro-ecological zone: Integrating dynamic vegetation modeling, machine learning, and climate projections for adaptive agricultural strategies

Climate change poses significant challenges to cereal crop productivity, highlighting the urgent need for effective adaptation strategies to ensure agricultural sustainability. This study investigates the impact of sowing dates on the yields of soft wheat, durum wheat, and barley in Morocco's Favorable agro-ecological zone, a region of critical national food security importance, under changing climate conditions from 2024 to 2099. Utilizing the CARAIB dynamic vegetation model, Random Forest machine learning, and high-resolution regional climate projections from the Euro-CORDEX initiative, this study provides a robust framework for evidence-based adaptation planning. December sowing dates were identified as the most favorable, producing consistent yield increases of up to 15% compared to the 30 October baseline, while late January and early September sowing dates resulted in significant yield reductions of up to 32%. The study also highlights a shift in optimum sowing dates from November to late December over the century, reflecting the need to align planting schedules with changing climatic conditions. Additionally, average growth cycles for wheat and barley are projected to shorten by 2099, suggesting accelerated phenological development driven by rising temperatures, thereby emphasizing the need for the development of heat- and drought-tolerant varieties with adapted growth durations. Despite this shortening, yield increases under optimal sowing dates result from improved synchronization of critical growth stages with periods of higher precipitation and lower thermal and water stress, particularly during grain filling. These findings provide a scientifically grounded basis for informing adaptation strategies and strengthening the resilience of cereal production systems under accelerating climate change. • Using CARAIB model, machine learning, and RCMs to assess the impact of sowing dates. • December emerges as the optimal sowing period for cereal crops. • Climate change shifts optimal sowing dates from November to December. • Precipitation and water stress are also major drivers of yield variability. • Length of growing periods will decrease, impacting productivity of current varieties.

Authors

Institutions

Publication Details

Journal
Next Sustainability
Published
2026-03-31
DOI
https://doi.org/10.1016/j.nxsust.2026.100298
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing cereal yields in Morocco’s Favorable agro-ecological zone: Integrating dynamic vegetation modeling, machine learning, and climate projections for adaptive agricultural strategies

Ingrid Jacquemin, Riad Balaghi, Mouanis Lahlou, Iliass Loudiyi et al.
Next Sustainability
Climate change impacts on agriculture
article

Optimizing cereal yields in Morocco’s Favorable agro-ecological zone: Integrating dynamic vegetation modeling, machine learning, and climate projections for adaptive agricultural strategies

Ingrid Jacquemin, Riad Balaghi, Mouanis Lahlou, Iliass Loudiyi, Louis François
article en

Abstract

Climate change poses significant challenges to cereal crop productivity, highlighting the urgent need for effective adaptation strategies to ensure agricultural sustainability. This study investigates the impact of sowing dates on the yields of soft wheat, durum wheat, and barley in Morocco's Favorable agro-ecological zone, a region of critical national food security importance, under changing climate conditions from 2024 to 2099. Utilizing the CARAIB dynamic vegetation model, Random Forest machine learning, and high-resolution regional climate projections from the Euro-CORDEX initiative, this study provides a robust framework for evidence-based adaptation planning. December sowing dates were identified as the most favorable, producing consistent yield increases of up to 15% compared to the 30 October baseline, while late January and early September sowing dates resulted in significant yield reductions of up to 32%. The study also highlights a shift in optimum sowing dates from November to late December over the century, reflecting the need to align planting schedules with changing climatic conditions. Additionally, average growth cycles for wheat and barley are projected to shorten by 2099, suggesting accelerated phenological development driven by rising temperatures, thereby emphasizing the need for the development of heat- and drought-tolerant varieties with adapted growth durations. Despite this shortening, yield increases under optimal sowing dates result from improved synchronization of critical growth stages with periods of higher precipitation and lower thermal and water stress, particularly during grain filling. These findings provide a scientifically grounded basis for informing adaptation strategies and strengthening the resilience of cereal production systems under accelerating climate change. • Using CARAIB model, machine learning, and RCMs to assess the impact of sowing dates. • December emerges as the optimal sowing period for cereal crops. • Climate change shifts optimal sowing dates from November to December. • Precipitation and water stress are also major drivers of yield variability. • Length of growing periods will decrease, impacting productivity of current varieties.

Next SustainabilityVol. 7
University of Liège (BE), Institut National de la Recherche Agronomique du Niger (NE), Institut Agronomique et Vétérinaire Hassan II (MA)
Wallonie-Bruxelles International
Climate action
Openalex Percentile: Top 25%
Climate change impacts on agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.