Multi-Criteria Analysis of Management Allowed Moisture Deficit in Sugar Beet (Shokoufa Variety)

Document Type : Research Paper

Author

Researcher, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO)

Abstract

The objective of this study was to investigate the effects of different irrigation treatments based on the Management Allowable Depletion (MAD) of soil moisture on the yield, quality, and water productivity of sugar beet. A field experiment was conducted in Karaj, Iran, during two growing seasons (2017–2019) using a randomized complete block design with three irrigation treatments (MAD=40%, 60%, and 80%) and four replications. Quantitative and qualitative traits, including evapotranspiration, root and sugar yield, pure sugar percentage, extraction and alkalinity coefficient, were measured, and water productivity was calculated. Analysis of variance indicated significant effects of the treatments and year on the measured traits. Multi-criteria decision analysis using the TOPSIS method, coupled with sensitivity analysis of criterion weights and Monte Carlo simulation, was employed to evaluate the ranking and stability of the treatments. According to the TOPSIS results, the treatment with a MAD of 60% achieved the highest rank with a closeness coefficient of 0.577, and was identified as the optimal option. The treatment with MAD=40% ranked second with a closeness coefficient of 0.479. Conversely, the treatment with MAD=80% obtained the lowest rank with a closeness coefficient of 0.373, indicating a greater distance from the ideal conditions in the simultaneous evaluation of the considered criteria. Monte Carlo simulation results, incorporating a ±10% fluctuation in criterion weights, revealed that MAD= 60% retained the first rank in 99.87% of the simulations. This demonstrates high stability in the ranking and robustness of the decision against weight uncertainty, providing strong confidence that the selection of this treatment, under various management conditions and criterion weighting scenarios, represents the best option for optimizing both yield and water productivity of sugar beet.

Keywords

References

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Journal of Water Research in Agriculture
Volume 39, Issue 4
March 2026
Pages 341-357

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