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Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)

The Law of the Minimum is often implemented using t-norm or fuzzy intersection. We propose the use of t-conorm or fuzzy union for climate suitability assessment of a grass species using annual ryegrass (Lolium multiflorum Lam.) as an example and evaluate the performance for alfalfa (Medicago sativa...

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Autores principales: Kim, Hyunae, Hyun, Shin Woo, Hoogenboom, Gerrit, Porter, Cheryl H., Kim, Kwang Soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033868/
https://www.ncbi.nlm.nih.gov/pubmed/29977010
http://dx.doi.org/10.1038/s41598-018-28291-3
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author Kim, Hyunae
Hyun, Shin Woo
Hoogenboom, Gerrit
Porter, Cheryl H.
Kim, Kwang Soo
author_facet Kim, Hyunae
Hyun, Shin Woo
Hoogenboom, Gerrit
Porter, Cheryl H.
Kim, Kwang Soo
author_sort Kim, Hyunae
collection PubMed
description The Law of the Minimum is often implemented using t-norm or fuzzy intersection. We propose the use of t-conorm or fuzzy union for climate suitability assessment of a grass species using annual ryegrass (Lolium multiflorum Lam.) as an example and evaluate the performance for alfalfa (Medicago sativa L.) and sorghum (Sorghum bicolor L.). The OR(F) and AND(F) models, which are fuzzy logic systems based on t-conorm and t-norm between temperature and moisture conditions, respectively, were developed to assess the quality of climate conditions for crops. The parameter values for both models were obtained from existing knowledge, e.g., the EcoCrop database. These models were then compared with the EcoCrop model, which is based on the t-norm. The OR(F) model explained greater variation (54%) in the yield of annual ryegrass at 84 site-years than the AND(F) model (43%) and the EcoCrop model (5%). The climate suitability index of the OR(F) model had the greatest likelihood of occurrence of annual ryegrass compared to the other models. The OR(F) model also had similar results for alfalfa and sorghum. We emphasize that the fuzzy logic system for climate suitability assessment can be developed using knowledge rather than presence-only data, which can facilitate more complex approaches such as the incorporation of biotic interaction into species distribution modeling.
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spelling pubmed-60338682018-07-12 Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor) Kim, Hyunae Hyun, Shin Woo Hoogenboom, Gerrit Porter, Cheryl H. Kim, Kwang Soo Sci Rep Article The Law of the Minimum is often implemented using t-norm or fuzzy intersection. We propose the use of t-conorm or fuzzy union for climate suitability assessment of a grass species using annual ryegrass (Lolium multiflorum Lam.) as an example and evaluate the performance for alfalfa (Medicago sativa L.) and sorghum (Sorghum bicolor L.). The OR(F) and AND(F) models, which are fuzzy logic systems based on t-conorm and t-norm between temperature and moisture conditions, respectively, were developed to assess the quality of climate conditions for crops. The parameter values for both models were obtained from existing knowledge, e.g., the EcoCrop database. These models were then compared with the EcoCrop model, which is based on the t-norm. The OR(F) model explained greater variation (54%) in the yield of annual ryegrass at 84 site-years than the AND(F) model (43%) and the EcoCrop model (5%). The climate suitability index of the OR(F) model had the greatest likelihood of occurrence of annual ryegrass compared to the other models. The OR(F) model also had similar results for alfalfa and sorghum. We emphasize that the fuzzy logic system for climate suitability assessment can be developed using knowledge rather than presence-only data, which can facilitate more complex approaches such as the incorporation of biotic interaction into species distribution modeling. Nature Publishing Group UK 2018-07-05 /pmc/articles/PMC6033868/ /pubmed/29977010 http://dx.doi.org/10.1038/s41598-018-28291-3 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kim, Hyunae
Hyun, Shin Woo
Hoogenboom, Gerrit
Porter, Cheryl H.
Kim, Kwang Soo
Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title_full Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title_fullStr Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title_full_unstemmed Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title_short Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)
title_sort fuzzy union to assess climate suitability of annual ryegrass (lolium multiflorum), alfalfa (medicago sativa) and sorghum (sorghum bicolor)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033868/
https://www.ncbi.nlm.nih.gov/pubmed/29977010
http://dx.doi.org/10.1038/s41598-018-28291-3
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