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| Registros recuperados : 86 | |
| 1. |  | RECH, Â. F.; FAVARO, V. R. AVALIAÇÃO BROMATOLÓGICA DE GENÓTIPOS DE AZEVÉM-ANUAL. In: SIMPÓSIO INTERNACIONAL, CIÊNCIA, SAÚDE E TERRITÓRIO, 7., 2023, Lages, SC. Resumos... Lages, SC : UNIPLAC, 2023. p. 64| Biblioteca(s): Epagri-Sede. |
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| 6. | | ZARDO, V. F.; PINTO, M. G. L.; FAVARO, V. R. MANIPULAÇÃO HORMONAL DO ANESTRO DE OVINOS VISANDO O AUMENTO DA PROLIFICIDADE. In: SIMPÓSIO INTERNACIONAL CIÊNCIA, SAÚDE E TERRITÓRIO, 7., 2023, Lages, SC. Resumos... Lages, SC: Uniplac, 2023. p. 79| Biblioteca(s): Epagri-Sede. |
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| 13. | | RECH, Â. F.; ROCHA, D. J. A.; FAVARO, V. R. PRODUÇÃO DE MATÉRIA SECA DE CULTIVARES DE AZEVÉM-ANUAL. In: SIMPÓSIO INTERNACIONAL CIÊNCIA, SAÚDE E TERRITÓRIO, 7., 2023, LAGES, SC. Resumos... LAGES, SC: UNIPLAC, 2023. p. 83| Biblioteca(s): Epagri-Sede. |
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| 16. | | PINTO, M. G. L.; ZARDO, V. F.; FAVARO, V. R.; COSTA, M. D. ESCORE DE CONDIÇÃO CORPORAL AO PARTO E O DESEMPENHO REPRODUTIVO DE VACAS JERSEY EM PASTAGEM. Revista Latino-americana Ambiente e Saúde, Lages, SC, v. 5, n. 3, p. 164-169, 2023.| Biblioteca(s): Epagri-Sede. |
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| 19. | | PINTO, M. G. L.; ZARDO, V. F.; FAVARO, V. R.; COSTA, M. D. BALANÇO ENERGÉTICO NO PÓS-PARTO E DESEMPENHO REPRODUTIVO DE VACAS JERSEY EM PASTAGEM. Revista Latino-americana Ambiente e Saúde, Lages, SC, v. 5, n. 3, p. 143-149, 2023.| Biblioteca(s): Epagri-Sede. |
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| 20. | | FAVARO, V. R.; PINTO, M. G. L.; CUCCO, D. C.; WERNER, S. S.; ROSSETTO, L. Desempenho, características da carcaça e da carne de bovinos meio/sangue da raça Flamenga, terminados em pastagem de azevém anual e suplementados com casca de soja. Agropecuária Catarinense, Florianópolis, v. 34, n. 1, p. 37-41, 2021.| Biblioteca(s): Epagri-Sede. |
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| Registros recuperados : 86 | |
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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
20/09/2021 |
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Data da última atualização: |
20/09/2021 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
RECH, Â. F.; WERNER, S. S.; FAVARO, V. R. |
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Título: |
Near infrared spectroscopy (NIRS) and multivariate calibration to determine the bromatological composition of annual ryegrass. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: REUNIÃO DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 56., 2021, Online. Resumos... Brasília: SBZ, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Ryegrass (Lolium multiflorum Lam) is very important annual forage for livestock in southern Brazil. Monitoring the quality of pastures during their development stage is important to provide support for forage planning, pasture management and feeding management of grazing animals. However, the analyzes necessary to evaluate the bromatological quality of forages are time consuming and require polluting chemical reagents. Near-infrared spectroscopy is used for analytical purposes with the advantage of being faster, less costly, requiring no chemical reagents and being less polluting. The aim of this study was to develop multivariate calibration models to predict the levels of crude protein (PB), neutral detergent fiber (NDF) and acid detergent fiber (FDA), in vitro digestibility of organic matter (IVDMO) for ryegrass. Between 300 and 360 samples were used, depending on the component analyzed. Bromatological analyzes were performed at the Animal Nutrition Laboratory-Epagri by reference methods and the results were used for calibrations. The reflectance spectra of each sample were collected in triplicate by the NIRFlex N-500 Solids spectrophotometer in the range between 4,000 to 10,000 cm-1 number of waves. The ranges of waves used were selected according to the functional groups of each component. The values of SEC (standard error of calibration), SEP (standard error of prediction), bias, number of latent variables (VL), coefficient of determination (R2) of calibration and internal validation were used to verify the models. For each component, more than one model was fitted using the NIRCal 5 BUCHI software, the PLS algorithm, and some mathematical pretreatments. Some points detected as ?leverage? outliers and high Student residuals were eliminated. The models were evaluated by external validation (VE), with samples not included in the adjustment, and the choice of calibrations with better predictive capacity was made after comparing the results of RMSEP (square root of the mean prediction error), RPD (ratio deviation prediction) and bias. The best results of VE were as follows: RMSEP: 0.9; 1.0; 1.1 and 2.6; RPD: 6.2; 5.7; 4.0 and 3.0; bias 0.09; 0.5; 0.08 and 0,19; respectively for the models of PB, FDN, FDA and IVDMO. The mathematical pretreatments used in these models were: 9-point first Savitzky-Golay derivative and 9-point Savitzky-Golay smoothing; 9-point first Savitzky- Golay derivative and 9-point Savitzky-Golay smoothing Gap2; 9-point first Savitzky-Golay derivative and 3-point smoothing; normalization 0-1, 3-point smoothing Gap2 and 9-point first SavitzkyGolay derivative, respectively for PB, FDN, FDA and IVDMO. The R2 of the best calibrations were: 0.97; 0.94; 0.95; 0.93; respectively for PB, FDN, FDA and IVDMO. The calibration models developed shows satisfactory results meet the purpose of the study and can be used to predict the composition of samples of annual ryegrass. However, with the introduction of new samples, they will be periodically updated, validated and improved. MenosRyegrass (Lolium multiflorum Lam) is very important annual forage for livestock in southern Brazil. Monitoring the quality of pastures during their development stage is important to provide support for forage planning, pasture management and feeding management of grazing animals. However, the analyzes necessary to evaluate the bromatological quality of forages are time consuming and require polluting chemical reagents. Near-infrared spectroscopy is used for analytical purposes with the advantage of being faster, less costly, requiring no chemical reagents and being less polluting. The aim of this study was to develop multivariate calibration models to predict the levels of crude protein (PB), neutral detergent fiber (NDF) and acid detergent fiber (FDA), in vitro digestibility of organic matter (IVDMO) for ryegrass. Between 300 and 360 samples were used, depending on the component analyzed. Bromatological analyzes were performed at the Animal Nutrition Laboratory-Epagri by reference methods and the results were used for calibrations. The reflectance spectra of each sample were collected in triplicate by the NIRFlex N-500 Solids spectrophotometer in the range between 4,000 to 10,000 cm-1 number of waves. The ranges of waves used were selected according to the functional groups of each component. The values of SEC (standard error of calibration), SEP (standard error of prediction), bias, number of latent variables (VL), coefficient of determination (R2) of calibration and inter... Mostrar Tudo |
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Palavras-Chave: |
animal nutrition; forage; Lolium multiflorum Lam; modeling; prediction. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 03723naa a2200205 a 4500
001 1131228
005 2021-09-20
008 2021 bl uuuu u00u1 u #d
100 1 $aRECH, Â. F.
245 $aNear infrared spectroscopy (NIRS) and multivariate calibration to determine the bromatological composition of annual ryegrass.$h[electronic resource]
260 $c2021
520 $aRyegrass (Lolium multiflorum Lam) is very important annual forage for livestock in southern Brazil. Monitoring the quality of pastures during their development stage is important to provide support for forage planning, pasture management and feeding management of grazing animals. However, the analyzes necessary to evaluate the bromatological quality of forages are time consuming and require polluting chemical reagents. Near-infrared spectroscopy is used for analytical purposes with the advantage of being faster, less costly, requiring no chemical reagents and being less polluting. The aim of this study was to develop multivariate calibration models to predict the levels of crude protein (PB), neutral detergent fiber (NDF) and acid detergent fiber (FDA), in vitro digestibility of organic matter (IVDMO) for ryegrass. Between 300 and 360 samples were used, depending on the component analyzed. Bromatological analyzes were performed at the Animal Nutrition Laboratory-Epagri by reference methods and the results were used for calibrations. The reflectance spectra of each sample were collected in triplicate by the NIRFlex N-500 Solids spectrophotometer in the range between 4,000 to 10,000 cm-1 number of waves. The ranges of waves used were selected according to the functional groups of each component. The values of SEC (standard error of calibration), SEP (standard error of prediction), bias, number of latent variables (VL), coefficient of determination (R2) of calibration and internal validation were used to verify the models. For each component, more than one model was fitted using the NIRCal 5 BUCHI software, the PLS algorithm, and some mathematical pretreatments. Some points detected as ?leverage? outliers and high Student residuals were eliminated. The models were evaluated by external validation (VE), with samples not included in the adjustment, and the choice of calibrations with better predictive capacity was made after comparing the results of RMSEP (square root of the mean prediction error), RPD (ratio deviation prediction) and bias. The best results of VE were as follows: RMSEP: 0.9; 1.0; 1.1 and 2.6; RPD: 6.2; 5.7; 4.0 and 3.0; bias 0.09; 0.5; 0.08 and 0,19; respectively for the models of PB, FDN, FDA and IVDMO. The mathematical pretreatments used in these models were: 9-point first Savitzky-Golay derivative and 9-point Savitzky-Golay smoothing; 9-point first Savitzky- Golay derivative and 9-point Savitzky-Golay smoothing Gap2; 9-point first Savitzky-Golay derivative and 3-point smoothing; normalization 0-1, 3-point smoothing Gap2 and 9-point first SavitzkyGolay derivative, respectively for PB, FDN, FDA and IVDMO. The R2 of the best calibrations were: 0.97; 0.94; 0.95; 0.93; respectively for PB, FDN, FDA and IVDMO. The calibration models developed shows satisfactory results meet the purpose of the study and can be used to predict the composition of samples of annual ryegrass. However, with the introduction of new samples, they will be periodically updated, validated and improved.
653 $aanimal nutrition
653 $aforage
653 $aLolium multiflorum Lam
653 $amodeling
653 $aprediction
700 1 $aWERNER, S. S.
700 1 $aFAVARO, V. R.
773 $tIn: REUNIÃO DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 56., 2021, Online. Resumos... Brasília: SBZ, 2021.
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