Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/42835 |
Resumo: | This study aimed to investigate factors associated with grain feeding and determine the typology of dairy farms that use high-grain diets. Twenty-two farm operators were interviewed in three municipalities located in the central-western region of Paraná state, Brazil. Information on reproductive and nutritional management practices, sociodemographic characteristics, and farm performance was collected. Data were analyzed using exploratory factor analysis, hierarchical cluster analysis, and multiple linear regression. Three factors (F1, F2, and F3) were extracted, which together explained 82.61% of the total variance. F1 comprised diet quality, technology, and breeding composition. F2 comprised labor and size. F3 comprised feed quality and schooling. Farms were classified into four groups and compared in terms of factor scores and performance parameters. Group 1 had the highest mean score on F1 (0.715), group 4 on F2 (1.642), and group 2 on F3 (1.116). Groups 4 and 1 had the highest milk productivity (2043.50 and 399.52 L day-1, respectively) and labor efficiency (418.16 and 148.63 L worker-1 day-1, respectively). Group 4 also had the highest mean number of cows per worker (25.52 cows worker-1). Regression analysis revealed that diet quality, technology, and breeding composition (F1) explained the variance in cow productivity. Labor and size, (F2) explained the variance in number of cows per worker. Daily productivity and labor efficiency were explained by both F1 and F2. Feed quality and farm operator’s level of schooling did not explain the variation in any of the variables. We found that roughage quality, breeding technology, and herd breed composition are the major factors associated with grain feeding. Farmers who feed cows high-quality roughage throughout the year and invest in genetic improvement and selective breeding strategies are more likely to adopt high-grain feeding and have high milk productivity. |
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Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, BrazilFatores associados ao uso de grãos em fazendas leiteiras localizadas na região centro-oeste do Estado do Paraná, BrasilAnimal feedConcentrateFarm typologyMultivariate approach.Alimentação animalConcentradoTipologiaAbordagem multivariada.This study aimed to investigate factors associated with grain feeding and determine the typology of dairy farms that use high-grain diets. Twenty-two farm operators were interviewed in three municipalities located in the central-western region of Paraná state, Brazil. Information on reproductive and nutritional management practices, sociodemographic characteristics, and farm performance was collected. Data were analyzed using exploratory factor analysis, hierarchical cluster analysis, and multiple linear regression. Three factors (F1, F2, and F3) were extracted, which together explained 82.61% of the total variance. F1 comprised diet quality, technology, and breeding composition. F2 comprised labor and size. F3 comprised feed quality and schooling. Farms were classified into four groups and compared in terms of factor scores and performance parameters. Group 1 had the highest mean score on F1 (0.715), group 4 on F2 (1.642), and group 2 on F3 (1.116). Groups 4 and 1 had the highest milk productivity (2043.50 and 399.52 L day-1, respectively) and labor efficiency (418.16 and 148.63 L worker-1 day-1, respectively). Group 4 also had the highest mean number of cows per worker (25.52 cows worker-1). Regression analysis revealed that diet quality, technology, and breeding composition (F1) explained the variance in cow productivity. Labor and size, (F2) explained the variance in number of cows per worker. Daily productivity and labor efficiency were explained by both F1 and F2. Feed quality and farm operator’s level of schooling did not explain the variation in any of the variables. We found that roughage quality, breeding technology, and herd breed composition are the major factors associated with grain feeding. Farmers who feed cows high-quality roughage throughout the year and invest in genetic improvement and selective breeding strategies are more likely to adopt high-grain feeding and have high milk productivity.Este estudo teve como objetivo investigar os fatores associados ao uso de grãos e determinar a tipologia de fazendas leiteiras que utilizam dietas ricas em grãos. Foram entrevistados 22 produtores rurais em três municípios localizados na região centro-oeste do estado do Paraná, Brasil. As informações foram coletadas sobre práticas de manejo reprodutivo e nutricional, características sociodemográficas e desempenho da fazenda. Os dados foram analisados por meio de análise fatorial exploratória, análise de agrupamento hierárquico e regressão linear múltipla. Foram extraídos três fatores (F1, F2 e F3), que juntos explicaram 82,61% da variância total. F1 compreendeu uso de grãos, qualidade da dieta, estratégia de melhoramento genético e composição racial do rebanho. F2 compreendeu as características da força de trabalho, tamanho do rebanho e tamanho da fazenda. F3 compreendeu o nível de escolaridade e a qualidade da alimentação. As fazendas foram classificadas em quatro grupos e comparadas em termos de escores dos fatores e variáveis de desempenho. O grupo 1 teve a maior escore médio em F1 (0,715), o grupo 4 em F2 (1,642) e o grupo 2 em F3 (1,116). Os grupos 4 e 1 tiveram a maior produtividade de leite (2043,50 e 399,52 L dia -1, respectivamente) e eficiência de trabalho (418,16 e 148,63 L trabalhador -1 dia -1, respectivamente). O Grupo 4 também teve o maior número médio de vacas por trabalhador (25,52 vacas trabalhador -1). A análise de regressão revelou que a qualidade da dieta, estratégia de criação e composição do rebanho (F1) explicaram a variação na produtividade das vacas. As características da força de trabalho, tamanho do rebanho e tamanho da fazenda (F2) explicaram a variação no número de vacas por trabalhador. A produtividade diária e a eficiência do trabalho foram explicadas por F1 e F2. A qualidade da alimentação e o nível de escolaridade do produtor rural não explicaram a variação em nenhuma das variáveis. Descobrimos que a qualidade do volumoso, a tecnologia de melhoramento genético dos animais e a composição do rebanho são os principais fatores associados à alimentação a base de grãos. Os produtores que alimentam as vacas com volumoso de alta qualidade ao longo do ano e investem em melhoramento genético e estratégias reprodutivas têm maior probabilidade de adotar alto teor de grãos na dieta das vacas e ter alta produtividade.UEL2021-08-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa de campoapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/4283510.5433/1679-0359.2021v42n6p3431Semina: Ciências Agrárias; Vol. 42 No. 6 (2021); 3431-3448Semina: Ciências Agrárias; v. 42 n. 6 (2021); 3431-34481679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/42835/30067Copyright (c) 2021 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessLima, Pedro Gustavo LoesiaDamasceno, Julio CesarBorges, João Augusto RossiBánkuti, Ferenc IstvanMartinelli, Raiane Real2022-09-30T12:25:33Zoai:ojs.pkp.sfu.ca:article/42835Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-09-30T12:25:33Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false |
dc.title.none.fl_str_mv |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil Fatores associados ao uso de grãos em fazendas leiteiras localizadas na região centro-oeste do Estado do Paraná, Brasil |
title |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
spellingShingle |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil Lima, Pedro Gustavo Loesia Animal feed Concentrate Farm typology Multivariate approach. Alimentação animal Concentrado Tipologia Abordagem multivariada. |
title_short |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
title_full |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
title_fullStr |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
title_full_unstemmed |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
title_sort |
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil |
author |
Lima, Pedro Gustavo Loesia |
author_facet |
Lima, Pedro Gustavo Loesia Damasceno, Julio Cesar Borges, João Augusto Rossi Bánkuti, Ferenc Istvan Martinelli, Raiane Real |
author_role |
author |
author2 |
Damasceno, Julio Cesar Borges, João Augusto Rossi Bánkuti, Ferenc Istvan Martinelli, Raiane Real |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Lima, Pedro Gustavo Loesia Damasceno, Julio Cesar Borges, João Augusto Rossi Bánkuti, Ferenc Istvan Martinelli, Raiane Real |
dc.subject.por.fl_str_mv |
Animal feed Concentrate Farm typology Multivariate approach. Alimentação animal Concentrado Tipologia Abordagem multivariada. |
topic |
Animal feed Concentrate Farm typology Multivariate approach. Alimentação animal Concentrado Tipologia Abordagem multivariada. |
description |
This study aimed to investigate factors associated with grain feeding and determine the typology of dairy farms that use high-grain diets. Twenty-two farm operators were interviewed in three municipalities located in the central-western region of Paraná state, Brazil. Information on reproductive and nutritional management practices, sociodemographic characteristics, and farm performance was collected. Data were analyzed using exploratory factor analysis, hierarchical cluster analysis, and multiple linear regression. Three factors (F1, F2, and F3) were extracted, which together explained 82.61% of the total variance. F1 comprised diet quality, technology, and breeding composition. F2 comprised labor and size. F3 comprised feed quality and schooling. Farms were classified into four groups and compared in terms of factor scores and performance parameters. Group 1 had the highest mean score on F1 (0.715), group 4 on F2 (1.642), and group 2 on F3 (1.116). Groups 4 and 1 had the highest milk productivity (2043.50 and 399.52 L day-1, respectively) and labor efficiency (418.16 and 148.63 L worker-1 day-1, respectively). Group 4 also had the highest mean number of cows per worker (25.52 cows worker-1). Regression analysis revealed that diet quality, technology, and breeding composition (F1) explained the variance in cow productivity. Labor and size, (F2) explained the variance in number of cows per worker. Daily productivity and labor efficiency were explained by both F1 and F2. Feed quality and farm operator’s level of schooling did not explain the variation in any of the variables. We found that roughage quality, breeding technology, and herd breed composition are the major factors associated with grain feeding. Farmers who feed cows high-quality roughage throughout the year and invest in genetic improvement and selective breeding strategies are more likely to adopt high-grain feeding and have high milk productivity. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-12 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Pesquisa de campo |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/42835 10.5433/1679-0359.2021v42n6p3431 |
url |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/42835 |
identifier_str_mv |
10.5433/1679-0359.2021v42n6p3431 |
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/42835/30067 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Semina: Ciências Agrárias http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 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. 42 No. 6 (2021); 3431-3448 Semina: Ciências Agrárias; v. 42 n. 6 (2021); 3431-3448 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 |
_version_ |
1799306084890968064 |