Multi-Criteria Analysis of Management Allowed Deficit Levels in Sugar Beet (Shokoufa Cultivar) Cultivation | ||
| پژوهش آب در کشاورزی | ||
| Articles in Press, Accepted Manuscript, Available Online from 05 May 2026 | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/jwra.2026.372163.1107 | ||
| Author | ||
| Reza Mohammadikia* | ||
| 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 (Beta vulgaris L.) cultivar. A field experiment was conducted in Karaj during two growing seasons (2017–2019) using a randomized complete block design with three irrigation treatments (MAD = 40%, MAD = 60%, and MAD = 80%) and four replications. Quantitative and qualitative traits, including evapotranspiration, root and sugar yield, pure sugar percentage, extraction coefficient, and alkalinity, were measured, and water productivity was calculated. Analysis of variance (ANOVA) indicated significant effects of the treatments and year on the measured traits. Multi-criteria decision analysis using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) 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 treatment T2 (MAD = 60%) retained the first rank in 87.99% 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 | ||
| Irrigation management; Multi-criteria decision making; Sensitivity analysis; Water productivity | ||
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