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Registro Completo |
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Biblioteca(s): |
Embrapa Caprinos e Ovinos. |
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Data corrente: |
13/02/2017 |
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Data da última atualização: |
13/02/2017 |
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Autoria: |
REDDY, R. R.; PRASAD, D. A. |
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Título: |
Performance nutrient utilization and nitrogen balance of growing and finishing lambs fed complete ensiled diets. |
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Ano de publicação: |
1983 |
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Fonte/Imprenta: |
The Indian Journal of Animal Sciences, v. 53, n. 4, p. 387-392, Apr. 1983. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: The enriched sugarcane tops (30% DPW [dried poultry waste], dry basis; 2% molasses and 0.5% salt) were ensiled with conventional (CD-1) or an unconventional (CD-2) mixture, and were compared with complete diets made by blending enriched sugarcane tops silage with conventional (CD-3) or unconventional (CD-4) mixture prior to feeding to lambs, in a ratio of 50:50 on DMB [dry matter basis]. In experiment 1, significantly higher (P < 0.01) ADG [average daily gain] was observed in lambs fed CD-4 than those fed CD-1 or CD-2. Complete ensiling with conventional mixture decreased feed efficiency (P < 0.01) and gain/protein intake (P < 0.05). Feed cost per kilogram gain was greater by Rs 7.07. In experiment 2, the ADG for lambs fed CD-3 or CD-4 was higher (P < 0.01) than for those fed the respective complete ensiled diets. In experiment 3, the ADG (P < 0.01), dry-matter [DM] intake (P < 0.05) and DM consumed per W0.75 kg (P < 0.01) were higher; feed/gain was superior (P < 0.05) and gain/protein intake higher (P < 0.01) for lambs fed CD-3 than for those fed CD-1. Nutrient digestibilities and N retention among treatments were not different. The retention of Ca (P < 0.10) and P (P < 0.05) was lower for lambs fed CD-1 than for those fed CD-3 or CD-4. Higher (P < 0.01) dressing percentage on empty body weight and separable lean and lower (P < 0.01) bone and fat were observed in treatment 3 than in treatment 1. Complete ensiling with unconventional mixture did not affect dressing percentage or percent separable bone but increased fat (P < 0.01) and decreased (P < 0.01) lean. Completely ensiled mono-diets were not superior to the ones blended prior to feeding. Mono-diet blended prior to feeding with unconventional mixture was as efficient as the one blended with conventional mixture. MenosAbstract: The enriched sugarcane tops (30% DPW [dried poultry waste], dry basis; 2% molasses and 0.5% salt) were ensiled with conventional (CD-1) or an unconventional (CD-2) mixture, and were compared with complete diets made by blending enriched sugarcane tops silage with conventional (CD-3) or unconventional (CD-4) mixture prior to feeding to lambs, in a ratio of 50:50 on DMB [dry matter basis]. In experiment 1, significantly higher (P < 0.01) ADG [average daily gain] was observed in lambs fed CD-4 than those fed CD-1 or CD-2. Complete ensiling with conventional mixture decreased feed efficiency (P < 0.01) and gain/protein intake (P < 0.05). Feed cost per kilogram gain was greater by Rs 7.07. In experiment 2, the ADG for lambs fed CD-3 or CD-4 was higher (P < 0.01) than for those fed the respective complete ensiled diets. In experiment 3, the ADG (P < 0.01), dry-matter [DM] intake (P < 0.05) and DM consumed per W0.75 kg (P < 0.01) were higher; feed/gain was superior (P < 0.05) and gain/protein intake higher (P < 0.01) for lambs fed CD-3 than for those fed CD-1. Nutrient digestibilities and N retention among treatments were not different. The retention of Ca (P < 0.10) and P (P < 0.05) was lower for lambs fed CD-1 than for those fed CD-3 or CD-4. Higher (P < 0.01) dressing percentage on empty body weight and separable lean and lower (P < 0.01) bone and fat were observed in treatment 3 than in treatment 1. Complete ensiling with unconventional mixture did not affect dressing... Mostrar Tudo |
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Palavras-Chave: |
Balanço de nitrogênio. |
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Thesagro: |
Alimento para animal; Cana de açúcar; Cordeiro; Crescimento; Eficiência nutricional; Ensilagem; Ganho de peso; Nutrição animal; Nutriente; Ovino; Silagem. |
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Thesaurus Nal: |
Animal feeding; Animal nutrition; Nitrogen balance; Sheep. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02761naa a2200325 a 4500
001 2063800
005 2017-02-13
008 1983 bl uuuu u00u1 u #d
100 1 $aREDDY, R. R.
245 $aPerformance nutrient utilization and nitrogen balance of growing and finishing lambs fed complete ensiled diets.
260 $c1983
520 $aAbstract: The enriched sugarcane tops (30% DPW [dried poultry waste], dry basis; 2% molasses and 0.5% salt) were ensiled with conventional (CD-1) or an unconventional (CD-2) mixture, and were compared with complete diets made by blending enriched sugarcane tops silage with conventional (CD-3) or unconventional (CD-4) mixture prior to feeding to lambs, in a ratio of 50:50 on DMB [dry matter basis]. In experiment 1, significantly higher (P < 0.01) ADG [average daily gain] was observed in lambs fed CD-4 than those fed CD-1 or CD-2. Complete ensiling with conventional mixture decreased feed efficiency (P < 0.01) and gain/protein intake (P < 0.05). Feed cost per kilogram gain was greater by Rs 7.07. In experiment 2, the ADG for lambs fed CD-3 or CD-4 was higher (P < 0.01) than for those fed the respective complete ensiled diets. In experiment 3, the ADG (P < 0.01), dry-matter [DM] intake (P < 0.05) and DM consumed per W0.75 kg (P < 0.01) were higher; feed/gain was superior (P < 0.05) and gain/protein intake higher (P < 0.01) for lambs fed CD-3 than for those fed CD-1. Nutrient digestibilities and N retention among treatments were not different. The retention of Ca (P < 0.10) and P (P < 0.05) was lower for lambs fed CD-1 than for those fed CD-3 or CD-4. Higher (P < 0.01) dressing percentage on empty body weight and separable lean and lower (P < 0.01) bone and fat were observed in treatment 3 than in treatment 1. Complete ensiling with unconventional mixture did not affect dressing percentage or percent separable bone but increased fat (P < 0.01) and decreased (P < 0.01) lean. Completely ensiled mono-diets were not superior to the ones blended prior to feeding. Mono-diet blended prior to feeding with unconventional mixture was as efficient as the one blended with conventional mixture.
650 $aAnimal feeding
650 $aAnimal nutrition
650 $aNitrogen balance
650 $aSheep
650 $aAlimento para animal
650 $aCana de açúcar
650 $aCordeiro
650 $aCrescimento
650 $aEficiência nutricional
650 $aEnsilagem
650 $aGanho de peso
650 $aNutrição animal
650 $aNutriente
650 $aOvino
650 $aSilagem
653 $aBalanço de nitrogênio
700 1 $aPRASAD, D. A.
773 $tThe Indian Journal of Animal Sciences$gv. 53, n. 4, p. 387-392, Apr. 1983.
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Registro original: |
Embrapa Caprinos e Ovinos (CNPC) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
01/06/2018 |
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Data da última atualização: |
06/06/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
TAVARES, R. L. M.; OLIVEIRA, S. R. de M.; BARROS, F. M. M. de; FARHATE, C. V. V.; SOUZA, Z. M. de; LA SCALA JUNIOR, N. |
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Afiliação: |
ROSE LUIZA MORAES TAVARES, Rio Verde University; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; FLÁVIO MARGARITO MARTINS DE BARROS, Feagri/Unicamp; CAMILA VIANA VIEIRA FARHATE, Feagri/Unicamp; ZIGOMAR MENEZES DE SOUZA, Feagri/Unicamp; NEWTON LA SCALA JUNIOR, FCAV/Unesp. |
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Título: |
Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Scientia Agricola, Piracicaba, v. 74, n. 4, p. 281-287, July/Aug. 2018. |
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DOI: |
http://dx.doi.org/10.1590/1678-992X-2017-0095 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms) in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80) for predicted and observed values. |
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Palavras-Chave: |
Data mining; Green sugarcane; Mineração de dados; Random Forest algorithm. |
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Thesagro: |
Argila; Cana de Açúcar; Saccharum Officinarum. |
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Thesaurus NAL: |
Clay; Soil organic carbon; Soil respiration; Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1092118/1/APPredictionTavaresetal.pdf
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Marc: |
LEADER 02375naa a2200325 a 4500
001 2092118
005 2018-06-06
008 2018 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1590/1678-992X-2017-0095$2DOI
100 1 $aTAVARES, R. L. M.
245 $aPrediction of soil CO2 flux in sugarcane management systems using the Random Forest approach.$h[electronic resource]
260 $c2018
520 $aABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms) in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80) for predicted and observed values.
650 $aClay
650 $aSoil organic carbon
650 $aSoil respiration
650 $aSugarcane
650 $aArgila
650 $aCana de Açúcar
650 $aSaccharum Officinarum
653 $aData mining
653 $aGreen sugarcane
653 $aMineração de dados
653 $aRandom Forest algorithm
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aBARROS, F. M. M. de
700 1 $aFARHATE, C. V. V.
700 1 $aSOUZA, Z. M. de
700 1 $aLA SCALA JUNIOR, N.
773 $tScientia Agricola, Piracicaba$gv. 74, n. 4, p. 281-287, July/Aug. 2018.
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Embrapa Agricultura Digital (CNPTIA) |
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