Gao Wenjun, Zeng Zhengcheng, Shi Huangwei, Wang Lu, Liu Shijie, Dong Xinwei, Wang Tenghao, Lai Changhua, Zhang Shuai
State Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Chongqing Sinopig High-Tech Group Co., Ltd., Chongqing 402460, China.
Animals (Basel). 2025 Aug 21;15(16):2464. doi: 10.3390/ani15162464.
This study aimed to determine the net energy (NE) values of common energy-supplying nutrients, including starch, protein, and fat, to investigate their influence on energetic efficiency and NE partition patterns in growing pigs, and to develop prediction equations for the protein deposition (PD) and lipid deposition (LD) based on nutrient characteristics of ingredients. Two experiments were conducted. In Experiment 1, 36 growing barrows (Duroc × Landrace × Yorkshire, initial body weight = 28.1 ± 0.8 kg) were randomly allotted to six treatments, with six replicated pigs per treatment. The diets were formulated as follows: a corn-soybean meal basal diet (T1), and five experimental diets containing of 27% corn starch (T2), 27% tapioca starch (T3), 27% pea starch (T4), 5% soybean oil (T5), and 11.8% casein (T6), respectively. In Experiment 2, PD and LD data of 47 ingredients were collected. Subsequently, the nutrient characteristics of ingredients were used as input variables, and PD and LD were used as output variables to establish the prediction equations. Results exhibited that pigs fed the T2, T3, and T4 diets showed increased digestibility of gross energy (GE) and organic matter (OM) compared to those fed the T1 diet ( < 0.01). For various kind of starches, a greater efficiency of using metabolizable energy (ME) for net energy not deposited as protein (PD-free NE, efficiency denoted as ) was observed when pigs were fed the T2 or T3 diets compared to the T4 diet. Moreover, the of soybean oil was 11% and 27% greater than that of starch and casein, respectively, while casein demonstrated 46% and 39% greater efficiency of using ME for PD (efficiency denoted as ) compared to starch and soybean oil, respectively. Finally, the best-fitted prediction equations for PD and LD were PD = 364.36 - 18.44 × GE + 29.10 × CP - 3.79 × EE - 21.37 × ADF (R = 0.96; RMSE = 105.15) and LD = -1503.50 + 21.58 × CP + 51.98 × EE + 26.30 × Starch + 26.81 × NDF - 23.87 × ADF (R = 0.98; RMSE = 172.85), respectively. In summary, there are considerable differences in energetic efficiency and NE partition patterns among various nutrients. In addition, PD and LD can be predicted through nutrient characteristics of ingredients, presenting an innovative approach and methodological framework for the precision nutrition of pigs.
本研究旨在确定常见能量供应营养素（包括淀粉、蛋白质和脂肪）的净能（NE）值，研究它们对生长猪能量效率和NE分配模式的影响，并基于饲料原料的营养特性建立蛋白质沉积（PD）和脂肪沉积（LD）的预测方程。进行了两项试验。在试验1中，36头生长公猪（杜洛克×长白×大白，初始体重 = 28.1 ± 0.8 kg）被随机分配到6种处理中，每个处理6头重复猪。日粮配方如下：玉米 - 豆粕基础日粮（T1），以及五种试验日粮，分别含有27%玉米淀粉（T2）、27%木薯淀粉（T3）、27%豌豆淀粉（T4）、5%大豆油（T5）和11.8%酪蛋白（T6）。在试验2中，收集了47种饲料原料的PD和LD数据。随后，将饲料原料的营养特性用作输入变量，将PD和LD用作输出变量来建立预测方程。结果表明，与饲喂T1日粮的猪相比，饲喂T2、T3和T4日粮的猪总能（GE）和有机物（OM）消化率提高（P < 0.01）。对于各种淀粉，与饲喂T4日粮的猪相比，饲喂T2或T3日粮的猪将代谢能（ME）用于非蛋白质沉积净能（无PD - NE，效率表示为）的效率更高。此外，大豆油的无PD - NE分别比淀粉和酪蛋白高11%和27%，而酪蛋白将ME用于PD的效率（效率表示为）分别比淀粉和大豆油高46%和39%。最后，PD和LD的最佳拟合预测方程分别为PD = 364.36 - 18.44×GE + 29.10×CP - 3.79×EE - 21.37×ADF（R = 0.96；RMSE = 105.15）和LD = -1503.50 + 21.58×CP + 51.98×EE + 26.30×淀粉 + 26.81×NDF - 23.87×ADF（R = 0.98；RMSE = 172.85）。总之，各种营养素在能量效率和NE分配模式上存在显著差异。此外，可通过饲料原料营养特性预测PD和LD，为猪的精准营养提供了一种创新方法和方法框架。
