Beef production and carcass evaluation in Brazil

Nunes, Cris Luana de Castro; Pflanzer, Sérgio Bertelli; Rezende-de-Souza, Jonatã Henrique; Chizzotti, Mario Luiz

doi:10.1093/af/vfad074

Animal Frontiers

2024

DOI: 10.1093/af/vfad074

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Beef production and carcass evaluation in Brazil

Cris Luana de Castro Nunes,

Sérgio Bertelli Pflanzer,

Jonatã Henrique Rezende-de-Souza

et al.

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Cited by 3 publications

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“…What is interesting to me as I review these articles is not only the commonalities of the regions but also some of the unique differences. For example, in the Uruguay, Brazil, and Chile articles ( Arias, 2024 ; Brito et al, 2024 ; Nunes et al, 2024 ), they all highlight the use of a standards type approach for determining a grade category and thus a value. While some of the systems are mandated by the government, others are not.…”

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confidence: 99%

Value assessment of animal protein can help feed the future

Gwartney

2024

Animal Frontiers

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mentioning

confidence: 99%

Value assessment of animal protein can help feed the future

Gwartney

2024

Animal Frontiers

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Recent technological developments and future trends in the evaluation and prediction of beef sensory quality in Brazil and France

Mendes,

Briceno,

Mársico

et al. 2024

Livestock Science

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Environmental factors and management practices associated with beef cattle carcass quality in the mid-west of Brazil

Amaral,

Le Cornec,

Rosa

2024

Translational Animal Science

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The "Precoce MS" program, established by the Brazilian government in Mato Grosso do Sul in 2017, aims to encourage beef producers to harvest animals at younger ages to enhance carcass quality. About 40% of the beef produced in the state now comes from this program, which offers tax refunds ranging from 49% to 67% based on carcass classification and production system. Despite the program success, with participants delivering younger animals (with a maximum of 4 incisors), there remains significant variability in carcass quality. This paper investigates management practices and environmental factors affecting farm performance regarding carcass quality. Data from all animals harvested between the beginning of 2017 and the end of 2018 were analyzed, totaling 1,107 million animals from 1,470 farms. Farm performance was assessed based on the percentage of animals achieving grades 'AAA' and 'AA'. Each batch of harvested cattle from each farm was categorized into two groups: High Farm Performance (HFP, with more than 50% of animals classified as 'AAA' or 'AA') and Low Farm Performance (LFP, with less than 50% classified as such). A predictive logistic model was developed to forecast Farm Performance (FP) using 14 continuous and 15 discrete pre-selected variables. The most effective model, obtained through backward stepwise variable selection, had an R² of 0.18, accuracy of 71.5%, and AUC of 0.715. Key predictors included animal category, production system type, carcass weight, individual identification, traceability system, presence of a feed plant, location, and the Normalized Difference Vegetation Index (NDVI) from the 12-month average before harvest. Developing predictive models of carcass quality by integrating data from commercial farms with other sources of information (animal, production system, environment) can improve our understanding of production systems, optimize resource allocation, and advance sustainable animal production. Additionally, they offer valuable insights for designing and implementing better sectorial, social, and environmental policies by public administrations, not only in Brazil but also in other tropical and subtropical regions worldwide.

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Beef production and carcass evaluation in Brazil

Cited by 3 publications

References 10 publications

Value assessment of animal protein can help feed the future

Value assessment of animal protein can help feed the future

Recent technological developments and future trends in the evaluation and prediction of beef sensory quality in Brazil and France

Environmental factors and management practices associated with beef cattle carcass quality in the mid-west of Brazil

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