Fuzzy Data Envelopment Analysis for Performance Evaluation of an Irrigation System

Raju, K. Srinivasa; Kumar, D. Nagesh

doi:10.1002/ird.1721

Cited by 15 publications

(6 citation statements)

References 44 publications

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“…Fuzzy modeling applied to the evaluation of irrigation system performance has been verified and better responses reported compared to standard models [25][26][27][28], such as multiple polynomial regression analysis. Based on this, Giusti and Marsili-Libelli [29] have developed a support system based on fuzzy logic for irrigation and water conservation in agriculture.…”

Section: Introductionmentioning

confidence: 91%

Fuzzy Modeling Development for Lettuce Plants Irrigated with Magnetically Treated Water

Ferrari Putti,

Cremasco,

Neto

et al. 2023

Plants

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Due to the worldwide water supply crisis, sustainable strategies are required for a better use of this resource. The use of magnetic water has been shown to have potential for improving irrigation efficacy. However, a lack of modelling methods that correspond to the experimental results and minimize error is observed. This study aimed to estimate the replacement rates of magnetic water provided by irrigation for lettuce production using a mathematical model based on fuzzy logic and to compare multiple polynomial regression analysis and the fuzzy model. A greenhouse study was conducted with lettuce using two types of water, magnetic water (MW) and conventional water (CW), and five irrigation levels (25, 50, 75, 100 and 125%) of crop evapotranspiration. Plant samples for biometric lettuce were taken at 14, 21, 28 and 35 days after transplanting. The data were analyzed via multiple polynomial regression and fuzzy mathematical modeling, followed by an inference of the models and a comparison between the methods. The highest biometric values for lettuce were observed when irrigated with MW during the different phenological stage evaluated. The fuzzy model provided a more exact adjustment when compared to the multiple polynomial regressions.

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Section: Introductionmentioning

confidence: 91%

Fuzzy Modeling Development for Lettuce Plants Irrigated with Magnetically Treated Water

Ferrari Putti,

Cremasco,

Neto

et al. 2023

Plants

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show abstract

“…destroy the ecological environment, the measurement of agricultural output should consider the negative impact of agricultural production on the ecological environment at the same time. Second, in the ordinary SBM model, the DMU whose efficiency level is greater than or equal to 1 is assigned a value of 1, so the DMU whose efficiency value is greater than 1 cannot be distinguished from the DMU whose efficiency value is 1 (She et al, 2020;Srinivasa Raju & Nagesh Kumar, 2013). However, the super-efficiency SBM model including undesired output directly incorporates the slack variables into the objective function, thus avoiding the above problem (Xiang et al, 2019).…”

Section: Assessment Of Agriculture Eco-efficiency Based On Super-sbm ...mentioning

confidence: 99%

Impacts of the integral development of agriculture and tourism on agricultural eco-efficiency: a case study of two river basins in China

Wang

Zhou

Xie

et al. 2022

Environ Dev Sustain

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The integral development of agriculture and tourism heavily depends on natural resources, especially agricultural resources, and it also may contribute to the sustainability of agriculture. The sustainability of agriculture is usually measured by the agricultural eco-efficiency. The main objective of this paper is to demonstrate the impact of the agriculture and tourism integration on agricultural eco-efficiency, so as to reflect the role of the agriculture and tourism integration on promoting agricultural sustainability. Applying panel data of 19 provinces in Yangtze River Basin and Yellow River Basin in China from 2008 to 2019, this paper uses a PSTR model to demonstrate the impact of agriculture and tourism integration on agricultural eco-efficiency and its mechanisms. It is found that in the study area, the integration of agriculture and tourism can contribute to improvements in agricultural eco-efficiency, and when levels of integration are high, the promotional effect is enhanced. However, impacts vary among different regions to some extent. In terms of influencing mechanisms, inputs of agricultural labor, sown crop area, effective irrigation area and other factors decrease with continuous improvements of integration. The input of pesticides, fertilizers and other factors does not decrease in the initial stage of integration but undergoes a rapid decrease after crossing a threshold value. And it demonstrates that the integration of agriculture and tourism is beneficial for improving the agricultural eco-efficiency, so that it will contribute to agricultural sustainability. Meanwhile, this paper offers a new research perspective for discovering effects of agriculture and tourism integration, providing implications for formulating regional policies for the integration.

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“…In terms of other application areas, a fuzzy DEA is used for wide range areas in including sustainable supply chain management, irrigation, energy and resource management. Problem domains include sustainable supplier selection problem (Azadi et al, 2015), irrigation (Srinivasa Raju & Nagesh Kumar, 2013), sustainable agriculture (Houshyar et al, 2012).…”

Section: Fuzzy Deamentioning

confidence: 99%

A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input–output life cycle assessment models on eco-efficiency assessment

Eğilmez

Gümüş

Küçükvar

et al. 2016

Journal of Cleaner Production

103

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The uncertainty in the results of input-output-based life cycle assessment models makes the sustainability performance assessment and ranking a challenging task. Therefore, introducing a new approach, fuzzy data envelopment analysis, is critical; since such a method could make it possible to integrate the uncertainty in the results of the life cycle assessment models into the decision-making for sustainability benchmarking and ranking. In this paper, a fuzzy data envelopment analysis model was coupled with an input-output-based life cycle assessment approach to perform the sustainability performance assessment of the 33 food manufacturing sectors in the United States. Seven environmental impact categories were considered the inputs and the total production amounts were identified as the output category, where each food manufacturing sector was considered a decision-making unit. To apply the proposed approach, the life cycle assessment results were formulated as fuzzy crisp valued-intervals and integrated with fuzzy data envelopment analysis model, thus, sustainability performance indices were quantified. Results indicated that majority (31 out of 33) of the food manufacturing sectors were not found to be efficient, where the overall sustainability performance scores ranged between 0.21 and 1.00 (efficient), and the average sustainability performance was found to be 0.66. To validate the current study's findings, a comparative analysis with the results of a previous work was also performed. The major contribution of the proposed framework is that the effects of uncertainty associated with input-output-based life cycle assessment approaches can be successfully tackled with the proposed Fuzzy DEA framework which can have a great area of application in research and business organizations that use with eco-efficiency as a sustainability performance metric.

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Fuzzy Data Envelopment Analysis for Performance Evaluation of an Irrigation System

Cited by 15 publications

References 44 publications

Fuzzy Modeling Development for Lettuce Plants Irrigated with Magnetically Treated Water

Fuzzy Modeling Development for Lettuce Plants Irrigated with Magnetically Treated Water

Impacts of the integral development of agriculture and tourism on agricultural eco-efficiency: a case study of two river basins in China

A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input–output life cycle assessment models on eco-efficiency assessment

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