Predicting corn digestible and metabolizable energy content from its chemical composition in growing pigs

Background: The nutrient composition of corn is variable. To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the...

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Veröffentlicht in:畜牧与生物技术杂志:英文版 2014 (3), p.357-364
1. Verfasser: Quanfeng Li Jianjun Zang Dewen Liu Xiangshu Piao Changhua Lai Defa Li
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description Background: The nutrient composition of corn is variable. To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy (DE) and metabolisable energy (ME) content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China (Jilin, Hebei, Shandong, Liaoning, and Henan) to obtain a range of quality. Results: The DE and ME contents of the 100 corn samples were measured in 3.5.3 ±1.92 kg growing pigs (six pigs per corn sample). Sixty corn samples were used to build the prediction model; the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg (dry matter basis), respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows: DE, kcal/kg of DM = 1062.68 + (49.72 ×EE) + (0.54 × GE) + (9.1 ] x starch), with R^2 = 0.62, residual standard deviation (RSD) = 48 kcal/kg, and P 〈 0.01; ME, kcal/kg of dry matter basis (DM) = 671.54 + (0.89 ×DE) - (5.57 × NDF) - (191.39 ×ash), with R^2 = 0.87, RSD = 18 kcal/kg, and P〈 0.01. Conclusion: This experiment confirms the large variation in the energy content of corn, describes the factors that influence this variation, and presents equations based on chemical measurements that may be used to predict the DE and ME content of individual corn samples.
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To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy (DE) and metabolisable energy (ME) content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China (Jilin, Hebei, Shandong, Liaoning, and Henan) to obtain a range of quality. Results: The DE and ME contents of the 100 corn samples were measured in 3.5.3 ±1.92 kg growing pigs (six pigs per corn sample). Sixty corn samples were used to build the prediction model; the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg (dry matter basis), respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows: DE, kcal/kg of DM = 1062.68 + (49.72 ×EE) + (0.54 × GE) + (9.1 ] x starch), with R^2 = 0.62, residual standard deviation (RSD) = 48 kcal/kg, and P 〈 0.01; ME, kcal/kg of dry matter basis (DM) = 671.54 + (0.89 ×DE) - (5.57 × NDF) - (191.39 ×ash), with R^2 = 0.87, RSD = 18 kcal/kg, and P〈 0.01. Conclusion: This experiment confirms the large variation in the energy content of corn, describes the factors that influence this variation, and presents equations based on chemical measurements that may be used to predict the DE and ME content of individual corn samples.</description><identifier>ISSN: 1674-9782</identifier><identifier>EISSN: 2049-1891</identifier><language>eng</language><subject>代谢能 ; 化学成分 ; 化学特性 ; 消化能 ; 玉米 ; 生长猪 ; 能量含量 ; 预测模型</subject><ispartof>畜牧与生物技术杂志:英文版, 2014 (3), p.357-364</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/71160X/71160X.jpg</thumbnail><link.rule.ids>315,781,785,4025</link.rule.ids></links><search><creatorcontrib>Quanfeng Li Jianjun Zang Dewen Liu Xiangshu Piao Changhua Lai Defa Li</creatorcontrib><title>Predicting corn digestible and metabolizable energy content from its chemical composition in growing pigs</title><title>畜牧与生物技术杂志:英文版</title><addtitle>Journal of Animal Science and Biotechnology</addtitle><description>Background: The nutrient composition of corn is variable. To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy (DE) and metabolisable energy (ME) content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China (Jilin, Hebei, Shandong, Liaoning, and Henan) to obtain a range of quality. Results: The DE and ME contents of the 100 corn samples were measured in 3.5.3 ±1.92 kg growing pigs (six pigs per corn sample). Sixty corn samples were used to build the prediction model; the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg (dry matter basis), respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows: DE, kcal/kg of DM = 1062.68 + (49.72 ×EE) + (0.54 × GE) + (9.1 ] x starch), with R^2 = 0.62, residual standard deviation (RSD) = 48 kcal/kg, and P 〈 0.01; ME, kcal/kg of dry matter basis (DM) = 671.54 + (0.89 ×DE) - (5.57 × NDF) - (191.39 ×ash), with R^2 = 0.87, RSD = 18 kcal/kg, and P〈 0.01. 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To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy (DE) and metabolisable energy (ME) content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China (Jilin, Hebei, Shandong, Liaoning, and Henan) to obtain a range of quality. Results: The DE and ME contents of the 100 corn samples were measured in 3.5.3 ±1.92 kg growing pigs (six pigs per corn sample). Sixty corn samples were used to build the prediction model; the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg (dry matter basis), respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows: DE, kcal/kg of DM = 1062.68 + (49.72 ×EE) + (0.54 × GE) + (9.1 ] x starch), with R^2 = 0.62, residual standard deviation (RSD) = 48 kcal/kg, and P 〈 0.01; ME, kcal/kg of dry matter basis (DM) = 671.54 + (0.89 ×DE) - (5.57 × NDF) - (191.39 ×ash), with R^2 = 0.87, RSD = 18 kcal/kg, and P〈 0.01. Conclusion: This experiment confirms the large variation in the energy content of corn, describes the factors that influence this variation, and presents equations based on chemical measurements that may be used to predict the DE and ME content of individual corn samples.</abstract></addata></record>
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subjects 代谢能
化学成分
化学特性
消化能
玉米
生长猪
能量含量
预测模型
title Predicting corn digestible and metabolizable energy content from its chemical composition in growing pigs
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