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Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model

Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-cri...

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Autores principales: Nedeljković, Miroslav, Puška, Adis, Doljanica, Suzana, Virijević Jovanović, Saša, Brzaković, Pavle, Stević, Željko, Marinkovic, Dragan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906314/
https://www.ncbi.nlm.nih.gov/pubmed/33630837
http://dx.doi.org/10.1371/journal.pone.0246857
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author Nedeljković, Miroslav
Puška, Adis
Doljanica, Suzana
Virijević Jovanović, Saša
Brzaković, Pavle
Stević, Željko
Marinkovic, Dragan
author_facet Nedeljković, Miroslav
Puška, Adis
Doljanica, Suzana
Virijević Jovanović, Saša
Brzaković, Pavle
Stević, Željko
Marinkovic, Dragan
author_sort Nedeljković, Miroslav
collection PubMed
description Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-criteria decision-making of available varieties, which is, in this paper, done on the example of hybrid varieties of rapeseed that were created by selection at the Institute of Field and Vegetable Crops in Novi Sad. By applying fuzzy logic, a novel integrated Multi-Criteria Decision-Making (MCDM) model is developed and rapeseed varieties were evaluated. For determining four main and 20 subcriteria, fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been applied based on fuzzy Bonferroni operator, while for ranking alternatives fuzzy MABAC (Multi-Attributive Border Approximation area Comparison) method has been used. The results obtained using the novel integrated fuzzy MCDM model showed that the variety A2 – Zorica has the best results, followed by A1 - NS Ras, while the worst results were seen by the variety A5 - Zlatna. These results were confirmed using other five fuzzy MCDM methods. Sensitivity analysis—changing criteria weights showed the worst results in the variety A6 - Jovana, which took last place in the application of 18 scenarios. The presented model and the results of this research will help farmers to solve this decision problem.
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spelling pubmed-79063142021-03-03 Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model Nedeljković, Miroslav Puška, Adis Doljanica, Suzana Virijević Jovanović, Saša Brzaković, Pavle Stević, Željko Marinkovic, Dragan PLoS One Research Article Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-criteria decision-making of available varieties, which is, in this paper, done on the example of hybrid varieties of rapeseed that were created by selection at the Institute of Field and Vegetable Crops in Novi Sad. By applying fuzzy logic, a novel integrated Multi-Criteria Decision-Making (MCDM) model is developed and rapeseed varieties were evaluated. For determining four main and 20 subcriteria, fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been applied based on fuzzy Bonferroni operator, while for ranking alternatives fuzzy MABAC (Multi-Attributive Border Approximation area Comparison) method has been used. The results obtained using the novel integrated fuzzy MCDM model showed that the variety A2 – Zorica has the best results, followed by A1 - NS Ras, while the worst results were seen by the variety A5 - Zlatna. These results were confirmed using other five fuzzy MCDM methods. Sensitivity analysis—changing criteria weights showed the worst results in the variety A6 - Jovana, which took last place in the application of 18 scenarios. The presented model and the results of this research will help farmers to solve this decision problem. Public Library of Science 2021-02-25 /pmc/articles/PMC7906314/ /pubmed/33630837 http://dx.doi.org/10.1371/journal.pone.0246857 Text en © 2021 Nedeljković et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nedeljković, Miroslav
Puška, Adis
Doljanica, Suzana
Virijević Jovanović, Saša
Brzaković, Pavle
Stević, Željko
Marinkovic, Dragan
Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title_full Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title_fullStr Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title_full_unstemmed Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title_short Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model
title_sort evaluation of rapeseed varieties using novel integrated fuzzy piprecia – fuzzy mabac model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906314/
https://www.ncbi.nlm.nih.gov/pubmed/33630837
http://dx.doi.org/10.1371/journal.pone.0246857
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