Zhang et al. (2025) A Fuzzy Credibility-Constrained Fuzzy Multi-Objective Programming Model for Optimizing Irrigation Strategies to Balance Citrus Yield and Quality Under Uncertainty

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Agronomy
• Year: 2025
• Date: 2025-11-27
• Authors: Fan Zhang, Xinyu Zhang, Zihan Wu, Shanshan Guo, Sufen Wang
• DOI: 10.3390/agronomy15122739

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study develops a novel fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model to optimize irrigation strategies, demonstrating its effectiveness in simultaneously enhancing crop yield and fruit quality under water scarcity in a citrus-producing region of Southwest China.

Objective

• To develop and apply a novel fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model for optimizing irrigation strategies under uncertainty.
• To simultaneously enhance crop yield and fruit quality while adapting to stochastic hydrologic factors and decision-maker preferences in water-limited environments.

Study Configuration

• Spatial Scale: A citrus-producing region in Southwest China.
• Temporal Scale: Seasonal (addressing seasonal drought conditions).

Methodology and Data

• Models used: Fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model; IVIF-TOPSIS analysis; Performance evaluation using Synthetic Degree (SD), Sustainability Index (SI), and Approximation Degree (AD).
• Data sources: Not explicitly detailed, but implies hydrological data (for stochastic factors) and agricultural data (for crop yield, fruit quality attributes, and market dynamics).

Main Results

• IVIF-TOPSIS analysis quantitatively revealed that crop yield was the paramount objective for decision-makers in the study region, followed by single fruit weight.
• The FCC-FMOP model effectively balances yield and quality objectives while adapting to real-world fuzzy constraints, proving to be both robust and practical.
• Compared with conventional practices, the proposed irrigation strategy, calibrated under varying credibility levels (β = 0.55, 0.75, and 0.95), significantly improved crop yield, fruit weight, hue angle, water content, and soluble sugar content.
• Performance evaluation using SD, SI, and AD confirmed the FCC-FMOP model’s superiority over single-objective models and conventional practices.

Contributions

• Development of a novel fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model for irrigation planning that integrates stochastic hydrologic factors, decision-maker preferences, and complex interrelationships among fruit quality attributes.
• Provides a scalable and decision-maker-oriented tool for sustainable irrigation management in water-limited environments.
• Demonstrates a robust and practical approach to reconcile multiple, often conflicting, objectives (crop yield and fruit quality) under fuzzy constraints in real-world agricultural settings.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Zhang2025Fuzzy,
  author = {Zhang, Fan and Zhang, Xinyu and Wu, Zihan and Guo, Shanshan and Wang, Sufen},
  title = {A Fuzzy Credibility-Constrained Fuzzy Multi-Objective Programming Model for Optimizing Irrigation Strategies to Balance Citrus Yield and Quality Under Uncertainty},
  journal = {Agronomy},
  year = {2025},
  doi = {10.3390/agronomy15122739},
  url = {https://doi.org/10.3390/agronomy15122739}
}