Loading…

Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil

The aim of the present study was to construct agroclimatic zoning for the conilon coffee crop in the state of Bahia, Brazil, using fuzzy logic. Historical data series on rainfall, mean air temperature, and relative air humidity were used. Analyses were carried out considering the mean values of the...

Full description

Saved in:
Bibliographic Details
Published in:International journal of fruit science 2021-01, Vol.21 (1), p.205-217
Main Authors: Medauar, Caique Carvalho, Silva, Samuel De Assis, Galvão, Ícaro Monteiro, Franco, Laís Barreto, Carvalho, Luis Carlos Cirilo
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3
cites cdi_FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3
container_end_page 217
container_issue 1
container_start_page 205
container_title International journal of fruit science
container_volume 21
creator Medauar, Caique Carvalho
Silva, Samuel De Assis
Galvão, Ícaro Monteiro
Franco, Laís Barreto
Carvalho, Luis Carlos Cirilo
description The aim of the present study was to construct agroclimatic zoning for the conilon coffee crop in the state of Bahia, Brazil, using fuzzy logic. Historical data series on rainfall, mean air temperature, and relative air humidity were used. Analyses were carried out considering the mean values of the accumulated variables for each month in the historical series. The data were subjected to geostatistical analysis to verify and quantify the existence of spatial dependence between the values of the studied variables. Subsequently, maps with representations of the monthly means of the variables were subjected to continual classification using fuzzy mapping to identify suitable areas and areas of climate favorability for the implantation of conilon coffee in the state of Bahia. Bahia presents great spatial variability in regard to suitability for conilon coffee cultivation, with highly favorable areas, but no totally unsuitable region. The south and extreme south of Bahia were the regions with the lowest temporal-spatial variability for climate favorability for the development of conilon coffee trees, these being the most suitable regions for this crop. The zoning through fuzzy logic assisted in decision-making on which regions of the state had the highest suitability for crop implantation.
doi_str_mv 10.1080/15538362.2020.1864698
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1080_15538362_2020_1864698</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2615376299</sourcerecordid><originalsourceid>FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3</originalsourceid><addsrcrecordid>eNp9kM1OwzAQhCMEEqXwCEiWuJLi2LXr3ICIAlIRB-BsbRKbunLj4jhF6dPj_l057Wj3m13tJMl1hkcZFvguY4wKysmIYBJbgo95Lk6SwbafCk6y06OO0Hly0bYLjKPkdJCYabfZ9OgNVivTfCOnUWHNEoJCU1g7D6WxJvRIO4_CXKGis8GsIRjX7FjXGBtl4bRWCplmB32ErT-OH2Fu4BY9etgYe5mcabCtujrUYfI1ffosXtLZ-_Nr8TBLKypYSAWpGCVlxVStgdBc6RLGE8hUTTgDXBI6nuh8UmscxwJKwfMxISXTNcMU04oOk5v93pV3P51qg1y4zjfxpCQ8Y3TCSZ5Hiu2pyru29UrLlY9_-15mWG5TlcdU5TZVeUg1-u73PtPETJbw67ytZYDeOq89NJVpJf1_xR82x35f</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2615376299</pqid></control><display><type>article</type><title>Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil</title><source>Taylor &amp; Francis (Open Access)</source><creator>Medauar, Caique Carvalho ; Silva, Samuel De Assis ; Galvão, Ícaro Monteiro ; Franco, Laís Barreto ; Carvalho, Luis Carlos Cirilo</creator><creatorcontrib>Medauar, Caique Carvalho ; Silva, Samuel De Assis ; Galvão, Ícaro Monteiro ; Franco, Laís Barreto ; Carvalho, Luis Carlos Cirilo</creatorcontrib><description>The aim of the present study was to construct agroclimatic zoning for the conilon coffee crop in the state of Bahia, Brazil, using fuzzy logic. Historical data series on rainfall, mean air temperature, and relative air humidity were used. Analyses were carried out considering the mean values of the accumulated variables for each month in the historical series. The data were subjected to geostatistical analysis to verify and quantify the existence of spatial dependence between the values of the studied variables. Subsequently, maps with representations of the monthly means of the variables were subjected to continual classification using fuzzy mapping to identify suitable areas and areas of climate favorability for the implantation of conilon coffee in the state of Bahia. Bahia presents great spatial variability in regard to suitability for conilon coffee cultivation, with highly favorable areas, but no totally unsuitable region. The south and extreme south of Bahia were the regions with the lowest temporal-spatial variability for climate favorability for the development of conilon coffee trees, these being the most suitable regions for this crop. The zoning through fuzzy logic assisted in decision-making on which regions of the state had the highest suitability for crop implantation.</description><identifier>ISSN: 1553-8362</identifier><identifier>EISSN: 1553-8621</identifier><identifier>DOI: 10.1080/15538362.2020.1864698</identifier><language>eng</language><publisher>Abingdon: Taylor &amp; Francis</publisher><subject>Agricultural management ; agroclimatic zoning ; Air temperature ; Coffee ; Crops ; Cultivation ; Decision making ; Fuzzy logic ; geostatistics ; Historical account ; Implantation ; Mapping ; Rainfall ; Relative humidity ; thematic maps ; Variability ; Zoning</subject><ispartof>International journal of fruit science, 2021-01, Vol.21 (1), p.205-217</ispartof><rights>2021 The Author(s). Published with license by Taylor &amp; Francis Group, LLC. 2021</rights><rights>2021 The Author(s). Published with license by Taylor &amp; Francis Group, LLC. This work is licensed under the Creative Commons Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3</citedby><cites>FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3</cites><orcidid>0000-0002-2243-7401 ; 0000-0001-8339-5244 ; 0000-0002-0718-7328 ; 0000-0002-8498-4742 ; 0000-0002-2790-3723</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/15538362.2020.1864698$$EPDF$$P50$$Ginformaworld$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/15538362.2020.1864698$$EHTML$$P50$$Ginformaworld$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27500,27922,27923,59141,59142</link.rule.ids></links><search><creatorcontrib>Medauar, Caique Carvalho</creatorcontrib><creatorcontrib>Silva, Samuel De Assis</creatorcontrib><creatorcontrib>Galvão, Ícaro Monteiro</creatorcontrib><creatorcontrib>Franco, Laís Barreto</creatorcontrib><creatorcontrib>Carvalho, Luis Carlos Cirilo</creatorcontrib><title>Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil</title><title>International journal of fruit science</title><description>The aim of the present study was to construct agroclimatic zoning for the conilon coffee crop in the state of Bahia, Brazil, using fuzzy logic. Historical data series on rainfall, mean air temperature, and relative air humidity were used. Analyses were carried out considering the mean values of the accumulated variables for each month in the historical series. The data were subjected to geostatistical analysis to verify and quantify the existence of spatial dependence between the values of the studied variables. Subsequently, maps with representations of the monthly means of the variables were subjected to continual classification using fuzzy mapping to identify suitable areas and areas of climate favorability for the implantation of conilon coffee in the state of Bahia. Bahia presents great spatial variability in regard to suitability for conilon coffee cultivation, with highly favorable areas, but no totally unsuitable region. The south and extreme south of Bahia were the regions with the lowest temporal-spatial variability for climate favorability for the development of conilon coffee trees, these being the most suitable regions for this crop. The zoning through fuzzy logic assisted in decision-making on which regions of the state had the highest suitability for crop implantation.</description><subject>Agricultural management</subject><subject>agroclimatic zoning</subject><subject>Air temperature</subject><subject>Coffee</subject><subject>Crops</subject><subject>Cultivation</subject><subject>Decision making</subject><subject>Fuzzy logic</subject><subject>geostatistics</subject><subject>Historical account</subject><subject>Implantation</subject><subject>Mapping</subject><subject>Rainfall</subject><subject>Relative humidity</subject><subject>thematic maps</subject><subject>Variability</subject><subject>Zoning</subject><issn>1553-8362</issn><issn>1553-8621</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><recordid>eNp9kM1OwzAQhCMEEqXwCEiWuJLi2LXr3ICIAlIRB-BsbRKbunLj4jhF6dPj_l057Wj3m13tJMl1hkcZFvguY4wKysmIYBJbgo95Lk6SwbafCk6y06OO0Hly0bYLjKPkdJCYabfZ9OgNVivTfCOnUWHNEoJCU1g7D6WxJvRIO4_CXKGis8GsIRjX7FjXGBtl4bRWCplmB32ErT-OH2Fu4BY9etgYe5mcabCtujrUYfI1ffosXtLZ-_Nr8TBLKypYSAWpGCVlxVStgdBc6RLGE8hUTTgDXBI6nuh8UmscxwJKwfMxISXTNcMU04oOk5v93pV3P51qg1y4zjfxpCQ8Y3TCSZ5Hiu2pyru29UrLlY9_-15mWG5TlcdU5TZVeUg1-u73PtPETJbw67ytZYDeOq89NJVpJf1_xR82x35f</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Medauar, Caique Carvalho</creator><creator>Silva, Samuel De Assis</creator><creator>Galvão, Ícaro Monteiro</creator><creator>Franco, Laís Barreto</creator><creator>Carvalho, Luis Carlos Cirilo</creator><general>Taylor &amp; Francis</general><general>Taylor &amp; Francis Ltd</general><scope>0YH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QR</scope><scope>7SN</scope><scope>7T7</scope><scope>7TM</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0002-2243-7401</orcidid><orcidid>https://orcid.org/0000-0001-8339-5244</orcidid><orcidid>https://orcid.org/0000-0002-0718-7328</orcidid><orcidid>https://orcid.org/0000-0002-8498-4742</orcidid><orcidid>https://orcid.org/0000-0002-2790-3723</orcidid></search><sort><creationdate>20210101</creationdate><title>Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil</title><author>Medauar, Caique Carvalho ; Silva, Samuel De Assis ; Galvão, Ícaro Monteiro ; Franco, Laís Barreto ; Carvalho, Luis Carlos Cirilo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agricultural management</topic><topic>agroclimatic zoning</topic><topic>Air temperature</topic><topic>Coffee</topic><topic>Crops</topic><topic>Cultivation</topic><topic>Decision making</topic><topic>Fuzzy logic</topic><topic>geostatistics</topic><topic>Historical account</topic><topic>Implantation</topic><topic>Mapping</topic><topic>Rainfall</topic><topic>Relative humidity</topic><topic>thematic maps</topic><topic>Variability</topic><topic>Zoning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Medauar, Caique Carvalho</creatorcontrib><creatorcontrib>Silva, Samuel De Assis</creatorcontrib><creatorcontrib>Galvão, Ícaro Monteiro</creatorcontrib><creatorcontrib>Franco, Laís Barreto</creatorcontrib><creatorcontrib>Carvalho, Luis Carlos Cirilo</creatorcontrib><collection>Taylor &amp; Francis (Open Access)</collection><collection>CrossRef</collection><collection>Chemoreception Abstracts</collection><collection>Ecology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>International journal of fruit science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Medauar, Caique Carvalho</au><au>Silva, Samuel De Assis</au><au>Galvão, Ícaro Monteiro</au><au>Franco, Laís Barreto</au><au>Carvalho, Luis Carlos Cirilo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil</atitle><jtitle>International journal of fruit science</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>21</volume><issue>1</issue><spage>205</spage><epage>217</epage><pages>205-217</pages><issn>1553-8362</issn><eissn>1553-8621</eissn><abstract>The aim of the present study was to construct agroclimatic zoning for the conilon coffee crop in the state of Bahia, Brazil, using fuzzy logic. Historical data series on rainfall, mean air temperature, and relative air humidity were used. Analyses were carried out considering the mean values of the accumulated variables for each month in the historical series. The data were subjected to geostatistical analysis to verify and quantify the existence of spatial dependence between the values of the studied variables. Subsequently, maps with representations of the monthly means of the variables were subjected to continual classification using fuzzy mapping to identify suitable areas and areas of climate favorability for the implantation of conilon coffee in the state of Bahia. Bahia presents great spatial variability in regard to suitability for conilon coffee cultivation, with highly favorable areas, but no totally unsuitable region. The south and extreme south of Bahia were the regions with the lowest temporal-spatial variability for climate favorability for the development of conilon coffee trees, these being the most suitable regions for this crop. The zoning through fuzzy logic assisted in decision-making on which regions of the state had the highest suitability for crop implantation.</abstract><cop>Abingdon</cop><pub>Taylor &amp; Francis</pub><doi>10.1080/15538362.2020.1864698</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-2243-7401</orcidid><orcidid>https://orcid.org/0000-0001-8339-5244</orcidid><orcidid>https://orcid.org/0000-0002-0718-7328</orcidid><orcidid>https://orcid.org/0000-0002-8498-4742</orcidid><orcidid>https://orcid.org/0000-0002-2790-3723</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1553-8362
ispartof International journal of fruit science, 2021-01, Vol.21 (1), p.205-217
issn 1553-8362
1553-8621
language eng
recordid cdi_crossref_primary_10_1080_15538362_2020_1864698
source Taylor & Francis (Open Access)
subjects Agricultural management
agroclimatic zoning
Air temperature
Coffee
Crops
Cultivation
Decision making
Fuzzy logic
geostatistics
Historical account
Implantation
Mapping
Rainfall
Relative humidity
thematic maps
Variability
Zoning
title Fuzzy Mapping of Climate Favorability for the Cultivation of Conilon Coffee in the State of Bahia, Brazil
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T11%3A48%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fuzzy%20Mapping%20of%20Climate%20Favorability%20for%20the%20Cultivation%20of%20Conilon%20Coffee%20in%20the%20State%20of%20Bahia,%20Brazil&rft.jtitle=International%20journal%20of%20fruit%20science&rft.au=Medauar,%20Caique%20Carvalho&rft.date=2021-01-01&rft.volume=21&rft.issue=1&rft.spage=205&rft.epage=217&rft.pages=205-217&rft.issn=1553-8362&rft.eissn=1553-8621&rft_id=info:doi/10.1080/15538362.2020.1864698&rft_dat=%3Cproquest_cross%3E2615376299%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c385t-82c532bc5edfa239efba47a1ed265a0b2347f97df0fa28ab869422b5fd50303c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2615376299&rft_id=info:pmid/&rfr_iscdi=true