State Key Laboratory of Animal Nutrition, Ministry of Agriculture Feed Industry Centre, China Agricultural University, Beijing 100193, China.
J Anim Sci Biotechnol. 2014 Feb 13;5(1):11. doi: 10.1186/2049-1891-5-11.
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.
The DE and ME contents of the 100 corn samples were measured in 35.3 ± 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) + (9.11 × starch), with R2 = 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 R2 = 0.87, RSD = 18 kcal/kg, and P < 0.01.
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.
玉米的营养成分是可变的。为了防止生长性能的不可预见的下降,分级和分析方法被用来最小化计算值和分析值之间的营养变异性。本实验旨在确定玉米能量含量变化的来源,并开发一种实用的方法,以准确估计生长猪单个玉米样品的可消化能(DE)和代谢能(ME)含量。从中国五个省份(吉林、河北、山东、辽宁和河南)的每个省份中抽取 20 个样本,以获得一系列质量。
在 35.3±1.92kg 生长猪(每个玉米样本 6 头猪)中测量了 100 个玉米样本的 DE 和 ME 含量。60 个玉米样本用于建立预测模型;其余 40 个样本用于测试这些模型的适用性。确定了每个玉米样本的化学成分,并利用这些结果建立了从化学特性预测 DE 或 ME 含量的预测方程。100 个样本的平均 DE 和 ME 含量分别为 4053 和 3923kcal/kg(干物质基础)。还确定了物理特性,结果表明,容积重量和千粒重与能量含量无关。DE 和 ME 值可以从化学特性准确预测。最佳拟合方程如下:DE,kcal/kg DM=1062.68+(49.72×EE)+(0.54×GE)+(9.11×starch),R2=0.62,残差标准差(RSD)=48kcal/kg,P<0.01;ME,kcal/kg 干物质基础(DM)=671.54+(0.89×DE)-(5.57×NDF)-(191.39×ash),R2=0.87,RSD=18kcal/kg,P<0.01。
本实验证实了玉米能量含量的巨大变化,描述了影响这种变化的因素,并提出了基于化学测量的方程,可用于预测单个玉米样品的 DE 和 ME 含量。