Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Semina. Ciências Agrárias (Online) |
Texto Completo: | https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38089 |
Resumo: | Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state’s production chain. There were no significant differences in this frequency for SCC and SPC, neither between the microregions studied, nor between the dry and rainy season (p > 0.05). The analysis of variance considered the period of year and type of cooling tank and showed higher SPC and SCC in the rainy season (p < 0.05); SCC and SPC were higher in collective tanks used by more than 5 farmers (p < 0.05). Spatial dependence was weak for SCC (DD = 22.02) and moderate for SPC (DD = 25.93), indicating the Machadinho do Oeste region as a priority area for mastitis control, and the Ariquemes microregion and west of the Porto Velho microregion as areas of high SPC. The results demonstrated the feasibility of spatial analysis as a tool for evaluating of refrigerated raw milk quality indicators and may support the definition of public and private strategies and policies to improve the milk quality and legislation adequacy. |
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Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia stateCaracterização espacial dos indicadores higiênico-sanitários do leite cru refrigerado de três microrregiões do estado de RondôniaBacterial countKrigingMilk qualitySomatic cell count.Contagem bacterianaContagem de células somáticasKrigagemQualidade do leite.Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state’s production chain. There were no significant differences in this frequency for SCC and SPC, neither between the microregions studied, nor between the dry and rainy season (p > 0.05). The analysis of variance considered the period of year and type of cooling tank and showed higher SPC and SCC in the rainy season (p < 0.05); SCC and SPC were higher in collective tanks used by more than 5 farmers (p < 0.05). Spatial dependence was weak for SCC (DD = 22.02) and moderate for SPC (DD = 25.93), indicating the Machadinho do Oeste region as a priority area for mastitis control, and the Ariquemes microregion and west of the Porto Velho microregion as areas of high SPC. The results demonstrated the feasibility of spatial analysis as a tool for evaluating of refrigerated raw milk quality indicators and may support the definition of public and private strategies and policies to improve the milk quality and legislation adequacy.A contagem bacteriana (CPP) e contagem de células somáticas (CCS) são considerados indicadores universais da qualidade do leite. O objetivo deste trabalho foi identificar clusters de CPP e CCS em amostras de leite cru resfriado de três microrregiões do estado de Rondônia e avaliar a influência do período do ano e tipo de tanque nestes indicadores. Foram avaliados 566 tanques de resfriamento de leite localizados nas microrregiões de Ariquemes, Ji-Paraná e Porto Velho, vinculados a indústrias lácteas com Serviço de Inspeção Federal (SIF). Os resultados de CPP e CCS das amostras de tanques e as coordenadas geográficas foram obtidas do banco de dados de indústrias lácteas e consideraram os resultados de análises oficiais realizadas em laboratórios credenciados ao Ministério da Agricultura, Pecuária e Abastecimento (MAPA), referentes ao período seco e chuvoso do ano de 2015. Para elaboração dos mapas de distribuição espacial dos indicadores de qualidade foi utilizado o programa ArcView 3.1®. A dependência espacial foi avaliada por meio da geoestatística, utilizando o método de Krigagem ordinária para interpolação dos dados. Para a análise de variância foi realizada a transformação logarítmica (logaritmo na base 10) dos resultados de CCS (log10CCS) e CPP (log10CPP). Para as variáveis, tipo de tanque (individual e coletivo) e período do ano (seco e chuvoso), foi utilizada análise de variância (ANOVA) pelo procedimento GLM do SAS 9.0. Foram avaliados 6.792 dados de análise e 2.209 produtores vinculados. A frequência de adequação dos indicadores de qualidade do leite aos limites definidos na legislação demonstrou que a CPP constitui um grande desafio para a cadeia produtiva do estado. Não foram observadas diferenças das frequências de adequação aos limites vigentes para CCS e CPP entre as microrregiões estudadas para o período seco e chuvoso (p>0,05). A análise de variância considerou o período do ano e tipo de tanque de resfriamento e demonstraram maiores CPP e CCS no período chuvoso (p<0,05). Considerando os tipos de tanque, a CCS e CPP foram mais elevadas nos tanques coletivos com mais de 5 produtores (p<0,05). Houve dependência espacial fraca para CCS (GD=22,02) e moderada para CPP (GD=25,93), indicando a região de Machadinho do Oeste como área prioritária para o controle da mastite, e a microrregião de Ariquemes e à oeste da microrregião de Porto Velho como áreas de alta CPP. Os resultados poderão subsidiar a definição de estratégias e de políticas públicas e privadas para melhoria da qualidade do leite do estado.UEL2020-08-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/3808910.5433/1679-0359.2020v41n5supl1p2195Semina: Ciências Agrárias; Vol. 41 No. 5supl1 (2020); 2195-2208Semina: Ciências Agrárias; v. 41 n. 5supl1 (2020); 2195-22081679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38089/27823Copyright (c) 2020 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessDias, Juliana AlvesPacheco, Ivanete FranceschiniGrego, Celia ReginaFaria, Guilherme VieiraCruz, Pedro Gomes2022-10-07T13:34:20Zoai:ojs.pkp.sfu.ca:article/38089Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-10-07T13:34:20Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false |
dc.title.none.fl_str_mv |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state Caracterização espacial dos indicadores higiênico-sanitários do leite cru refrigerado de três microrregiões do estado de Rondônia |
title |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
spellingShingle |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state Dias, Juliana Alves Bacterial count Kriging Milk quality Somatic cell count. Contagem bacteriana Contagem de células somáticas Krigagem Qualidade do leite. |
title_short |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
title_full |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
title_fullStr |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
title_full_unstemmed |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
title_sort |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state |
author |
Dias, Juliana Alves |
author_facet |
Dias, Juliana Alves Pacheco, Ivanete Franceschini Grego, Celia Regina Faria, Guilherme Vieira Cruz, Pedro Gomes |
author_role |
author |
author2 |
Pacheco, Ivanete Franceschini Grego, Celia Regina Faria, Guilherme Vieira Cruz, Pedro Gomes |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Dias, Juliana Alves Pacheco, Ivanete Franceschini Grego, Celia Regina Faria, Guilherme Vieira Cruz, Pedro Gomes |
dc.subject.por.fl_str_mv |
Bacterial count Kriging Milk quality Somatic cell count. Contagem bacteriana Contagem de células somáticas Krigagem Qualidade do leite. |
topic |
Bacterial count Kriging Milk quality Somatic cell count. Contagem bacteriana Contagem de células somáticas Krigagem Qualidade do leite. |
description |
Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state’s production chain. There were no significant differences in this frequency for SCC and SPC, neither between the microregions studied, nor between the dry and rainy season (p > 0.05). The analysis of variance considered the period of year and type of cooling tank and showed higher SPC and SCC in the rainy season (p < 0.05); SCC and SPC were higher in collective tanks used by more than 5 farmers (p < 0.05). Spatial dependence was weak for SCC (DD = 22.02) and moderate for SPC (DD = 25.93), indicating the Machadinho do Oeste region as a priority area for mastitis control, and the Ariquemes microregion and west of the Porto Velho microregion as areas of high SPC. The results demonstrated the feasibility of spatial analysis as a tool for evaluating of refrigerated raw milk quality indicators and may support the definition of public and private strategies and policies to improve the milk quality and legislation adequacy. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-07 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38089 10.5433/1679-0359.2020v41n5supl1p2195 |
url |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38089 |
identifier_str_mv |
10.5433/1679-0359.2020v41n5supl1p2195 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38089/27823 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2020 Semina: Ciências Agrárias http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2020 Semina: Ciências Agrárias http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UEL |
publisher.none.fl_str_mv |
UEL |
dc.source.none.fl_str_mv |
Semina: Ciências Agrárias; Vol. 41 No. 5supl1 (2020); 2195-2208 Semina: Ciências Agrárias; v. 41 n. 5supl1 (2020); 2195-2208 1679-0359 1676-546X reponame:Semina. Ciências Agrárias (Online) instname:Universidade Estadual de Londrina (UEL) instacron:UEL |
instname_str |
Universidade Estadual de Londrina (UEL) |
instacron_str |
UEL |
institution |
UEL |
reponame_str |
Semina. Ciências Agrárias (Online) |
collection |
Semina. Ciências Agrárias (Online) |
repository.name.fl_str_mv |
Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL) |
repository.mail.fl_str_mv |
semina.agrarias@uel.br |
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1799306082243313664 |