A principal component analysis required in technical assistance guidance for chilled raw milk producers

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dc.creatorDyhogo Henrique Veloso Leal
dc.creatorAlcinei Místico Azevedo
dc.creatorAnna Christina de Almeida
dc.creatorOtaviano de Sousa Pires Neto
dc.creatorEduardo Robson Duarte
dc.creatorFernanda Santos Silva Raidan
dc.date.accessioned2023-10-20T15:28:15Z
dc.date.accessioned2025-09-09T00:41:03Z
dc.date.available2023-10-20T15:28:15Z
dc.date.issued2022
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.doihttps://doi.org/10.4025/actascianimsci.v44i1.55570
dc.identifier.issn1807-8672
dc.identifier.urihttps://hdl.handle.net/1843/59795
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofActa Scientiarum. Animal Sciences
dc.rightsAcesso Aberto
dc.subjectBovino de leite
dc.subjectLeite -- Qualidade
dc.subjectAnálise multivariada
dc.titleA principal component analysis required in technical assistance guidance for chilled raw milk producers
dc.typeArtigo de periódico
local.citation.epage10
local.citation.spage1
local.citation.volume44
local.description.resumoThe purpose of the present study was to evaluate the principal component analysis (PCA) to guide technical assistance regarding several dairy farms’ issues, which includes improving microbiological quality and physical-chemical composition of raw refrigerated milk. Data of monthly analysis of fat, protein, lactose, dry defatted stratum, somatic cell count, total bacterial count, milk temperature of 8,101 samples of milk from expansion tanks and production of 78 farms located in the northern region of Minas Gerais, Brazil were processed. Descriptive statistical measures and Pearson correlation coefficient were estimated involving all evaluated traits during the dry and rainy seasons. In addition, multivariate analyses were performed using PCA. The results showed that two farm sites were negatively related to milk quality in both seasons. One farm stood out positively, being able to be used as a herd management model to drive technical assistance actions. Thus, PCA is efficient in simplifying large amounts of data, allowing simpler and faster technical herd management interpretation.
local.identifier.orcidhttps://orcid.org/0000-0001-5196-0851
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.scielo.br/j/asas/a/3BNFFsDR4vYwCNGMZgbPDcz/?format=pdf&lang=en

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