Jdi et al. (2025) Optimizing irrigation for Dutch roses in Beni Mellal, Morocco: Predictive modeling based on reference evapotranspiration

Identification

• Journal: Foods and raw materials
• Year: 2025
• Date: 2025-12-22
• Authors: Hamza Jdi, Noureddine Falih
• DOI: 10.21603/2308-4057-2027-1-690

Research Groups

• Sultan Moulay Slimane University, Beni Mellal, Morocco

Short Summary

This study developed a comprehensive predictive model to optimize daily irrigation requirements for Dutch roses in the water-scarce Beni Mellal region of Morocco. The model integrates historical weather data and crop-specific factors across four growth stages to provide a systematic approach for proactive and efficient water management.

Objective

• To develop and introduce a comprehensive predictive model for optimizing the daily irrigation of Dutch roses in the Beni Mellal region of Morocco, addressing the need for precise water management across four distinct plant growth stages.

Study Configuration

• Spatial Scale: Beni Mellal region, Morocco.
• Temporal Scale: Daily irrigation requirements across the entire growth cycle of Dutch roses, utilizing historical weather data.

Methodology and Data

• Models used:
  • Penman-Monteith equation (for calculating reference evapotranspiration, ET₀).
  • A comprehensive predictive model integrating:
    • Weather prediction (temperature, net radiation, wind speed, dew point).
    • Reference evapotranspiration calculation.
    • Application of crop coefficients (Kc) specific to each growth stage.
    • Estimation of crop evapotranspiration (ETc) and daily water needs.
• Data sources:
  • Historical weather data (temperature, net radiation, wind speed, dew point).
  • Crop-specific factors (crop coefficients for Dutch roses across four growth stages).

Main Results

• The integrated predictive model successfully estimated daily irrigation requirements for Dutch roses based on historical weather data and crop-specific factors.
• The system provided a systematic approach for predicting daily water requirements across the entire growth cycle of Dutch roses.
• The model demonstrated high adaptability, generating forecasts based on weather trends and plant growth stages.
• The approach is expected to enable rose farmers in Beni Mellal to optimize their irrigation practices, potentially leading to more efficient water use compared to conventional methods.

Contributions

• Introduction of a comprehensive predictive model specifically designed for optimizing Dutch rose irrigation in a water-scarce region (Beni Mellal, Morocco).
• Integration of multiple components (weather prediction, Penman-Monteith equation, crop coefficients) into a single system for precise daily water requirement estimation across different growth stages.
• Development of a proactive irrigation management tool that leverages historical weather patterns and growth stage-specific crop coefficients.
• The proposed framework offers significant potential for enhancing water use efficiency in rose cultivation and other crops in arid environments.

Funding

• Not specified in the provided text.

Citation

@article{Jdi2025Optimizing,
  author = {Jdi, Hamza and Falih, Noureddine},
  title = {Optimizing irrigation for Dutch roses in Beni Mellal, Morocco: Predictive modeling based on reference evapotranspiration},
  journal = {Foods and raw materials},
  year = {2025},
  doi = {10.21603/2308-4057-2027-1-690},
  url = {https://doi.org/10.21603/2308-4057-2027-1-690}
}