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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
30/12/2019 |
Data da última atualização: |
06/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
ANDRADE, R. G.; HOTT, M. C.; MAGALHAES JUNIOR, W. C. P. de. |
Afiliação: |
RICARDO GUIMARAES ANDRADE, CNPGL; MARCOS CICARINI HOTT, CNPGL; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL. |
Título: |
Estimation of energy flux and biomass in pasture areas through remote sensing techniques. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
International Journal of Advanced Engineering Research and Science, v. 6, n. 4, p. 59-65, 2019. |
DOI: |
https://dx.doi.org/10.22161/ijaers.6.4.6 |
Idioma: |
Inglês |
Conteúdo: |
Pasture production is estimated through remote sensing techniques with the aid of models and algorithms. The application with no need for extensive field measurements is one of the advantages of the Surface Energy Balance Algorithm for Land (SEBAL). The objective of this work was to estimate energy fluxes and, subsequently, pasture biomass with the aid of remote sensing techniques. The study area is located on the Experimental Farm of Embrapa Beef Cattle, municipality of Campo Grande, State of Mato Grosso do Sul, Brazil. For the implementation of the SEBAL and estimation of energy fluxes and biomass of the pasture areas, meteorological data and Landsat 5 - TM image were used. It was found that the technique has the potential to be applied to indicate the forage availability and to support decision-making in the planning and management of the extensive production of beef and milk cattle, with economic and environmental sustainability of pasture areas. |
Palavras-Chave: |
Geotechnology; SEBAL. |
Thesaurus Nal: |
Environmental sustainability; Livestock; Rural planning. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/207931/1/IJAERS-RicardoG-Estimation.pdf
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Marc: |
LEADER 01686naa a2200217 a 4500 001 2117869 005 2024-02-06 008 2019 bl uuuu u00u1 u #d 024 7 $ahttps://dx.doi.org/10.22161/ijaers.6.4.6$2DOI 100 1 $aANDRADE, R. G. 245 $aEstimation of energy flux and biomass in pasture areas through remote sensing techniques.$h[electronic resource] 260 $c2019 520 $aPasture production is estimated through remote sensing techniques with the aid of models and algorithms. The application with no need for extensive field measurements is one of the advantages of the Surface Energy Balance Algorithm for Land (SEBAL). The objective of this work was to estimate energy fluxes and, subsequently, pasture biomass with the aid of remote sensing techniques. The study area is located on the Experimental Farm of Embrapa Beef Cattle, municipality of Campo Grande, State of Mato Grosso do Sul, Brazil. For the implementation of the SEBAL and estimation of energy fluxes and biomass of the pasture areas, meteorological data and Landsat 5 - TM image were used. It was found that the technique has the potential to be applied to indicate the forage availability and to support decision-making in the planning and management of the extensive production of beef and milk cattle, with economic and environmental sustainability of pasture areas. 650 $aEnvironmental sustainability 650 $aLivestock 650 $aRural planning 653 $aGeotechnology 653 $aSEBAL 700 1 $aHOTT, M. C. 700 1 $aMAGALHAES JUNIOR, W. C. P. de 773 $tInternational Journal of Advanced Engineering Research and Science$gv. 6, n. 4, p. 59-65, 2019.
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Embrapa Gado de Leite (CNPGL) |
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Registro Completo
Biblioteca(s): |
Embrapa Gado de Corte. |
Data corrente: |
22/12/2023 |
Data da última atualização: |
22/12/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
RAMOS, P. B. B.; MENEZES, G. R. de O.; SILVA, D. A. DA; LOURENCO, D.; SANTIAGO, G. G.; TORRES JUNIOR, R. A. de A.; SILVA, F. F. E; LOPES, P. S.; VERONEZA, R. |
Afiliação: |
PEDRO VITAL BRASIL RAMOS, UNIVERSIDADE FEDERAL DE VIÇOSA; GILBERTO ROMEIRO DE OLIVEIRA MENEZE, CNPGC; DELVAN ALVES DA SILVA, UNIVERSIDADE FEDERAL DE VIÇOSA; DANIELA LOURENCO, UNIVERSITY OF GEORGIA; GUSTAVO GARCIA SANTIAGO, GDM SEEDS; ROBERTO AUGUSTO DE A TORRES JUNIOR, CNPGC; FABYANO FONSECA E SILVA, UNIVERSIDADE FEDERAL DE VIÇOSA; PAULO SÁVIO LOPES, UNIVERSIDADE FEDERAL DE VIÇOSA; RENATA VERONEZE, UNIVERSIDADE FEDERAL DE VIÇOSA. |
Título: |
Genomic analysis of feed efficiency traits in beef cattle using random regression models. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Journal Animal Breeding and Genetics, 2023. |
DOI: |
10.1111/jbg.12840. |
Idioma: |
Inglês |
Notas: |
Online ahead of print. |
Conteúdo: |
ABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56days for DMI and RFI selection and 77days for BWG and RWG selection. MenosABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average... Mostrar Tudo |
Thesagro: |
Análise Estatística; Gado de Corte; Genótipo. |
Thesaurus NAL: |
Beef cattle; Feed intake; Genotype; Nellore. |
Categoria do assunto: |
-- |
Marc: |
LEADER 03961naa a2200325 a 4500 001 2160221 005 2023-12-22 008 2023 bl uuuu u00u1 u #d 024 7 $a10.1111/jbg.12840.$2DOI 100 1 $aRAMOS, P. B. B. 245 $aGenomic analysis of feed efficiency traits in beef cattle using random regression models.$h[electronic resource] 260 $c2023 500 $aOnline ahead of print. 520 $aABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56days for DMI and RFI selection and 77days for BWG and RWG selection. 650 $aBeef cattle 650 $aFeed intake 650 $aGenotype 650 $aNellore 650 $aAnálise Estatística 650 $aGado de Corte 650 $aGenótipo 700 1 $aMENEZES, G. R. de O. 700 1 $aSILVA, D. A. DA 700 1 $aLOURENCO, D. 700 1 $aSANTIAGO, G. G. 700 1 $aTORRES JUNIOR, R. A. de A. 700 1 $aSILVA, F. F. E 700 1 $aLOPES, P. S. 700 1 $aVERONEZA, R. 773 $tJournal Animal Breeding and Genetics, 2023.
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