Du Zhongyuan, Wang Yuming, Song Mingqiang, Zeng Shuli, Gao Lixiang, Zhao Jiangtao, Zhao Feng
State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Wen's Food Group Co. Ltd., Guangdong, 527439, China.
Anim Nutr. 2022 Apr 26;10:178-187. doi: 10.1016/j.aninu.2022.02.004. eCollection 2022 Sep.
The objective of this experiment was to develop a new computer-controlled simulated digestion system to predict the digestible energy (DE) and metabolizable energy (ME) of unconventional plant protein meals for growing pigs. Nine meals tested included 1 source of rapeseed meal, 4 sources of cottonseed meal, 2 sources of sunflower meal, and 2 sources of peanut meal. Twenty growing pigs (Duroc × [Landrace × Large White]) with an initial body weight (BW) of 41.7 ± 2.6 kg were allotted to a replicated 10 × 3 incomplete Latin square design to determine the DE and ME of 1 basal diet and 9 experimental diets formulated with 9 unconventional plant protein meals. The DE and ME values of unconventional plant protein meals were calculated by the difference method. The in vitro digestible energy (IVDE) of 1 basal diet, 9 experimental diets, and 9 unconventional plant protein meals were determined with 5 replicates of each sample in a complete randomized arrangement. The IVDE/DE or IVDE/ME ranged from 0.96 to 0.98 or 1.00 to 1.01, and the correlation coefficient between IVDE and DE or ME was 0.97 or 0.98 in 10 experimental diets. Accordingly, the IVDE/DE or IVDE/ME ranged from 0.86 to 1.05 or 0.96 to 1.20, and the correlation coefficient between IVDE and DE or ME was 0.92 or 0.91 in 9 unconventional plant protein meals. The coefficient of variation (CV) of IVDE was less than that of DE and ME in the experimental diets (0.43%, 0.80%, and 0.97% for CV of IVDE, DE and ME, respectively) and unconventional plant protein meals (0.92%, 4.84%, and 6.33% for CV of IVDE, DE and ME, respectively). The regression equations to predict DE from IVDE in 10 experimental diets and 9 unconventional plant protein meals were DE = 0.8851 × IVDE +539 ( = 0.9411, residual standard deviation [RSD] = 23 kcal/kg DM, < 0.01) and DE = 0.9880 × IVDE + 166 ( = 0.8428, RSD = 182 kcal/kg DM, < 0.01), respectively. There was no statistical difference in the slopes ( = 0.82) or intercepts ( = 1.00) of these 2 equations. Thus, 10 diets and 9 unconventional plant protein meals were pooled to establish the regression equation of DE on IVDE as: DE = 0.9813 × IVDE +187 ( = 0.9120, RSD = 118 kcal/kg DM, < 0.01). The regression equations to predict ME from IVDE in 10 experimental diets and 9 unconventional plant protein meals were ME = 0.9559 × IVDE +146 ( = 0.9697, RSD = 18 kcal/kg DM, < 0.01) and ME = 0.9388 × IVDE + 3 ( = 0.8282, RSD = 182 kcal/kg DM, < 0.01), respectively. There was no statistical difference in slopes ( = 0.97) but significant difference between the intercepts ( = 0.02) of these 2 equations. Our results indicate IVDE has similar response to the DE but different response to the ME in 10 experimental diets and 9 unconventional plant protein meals. Therefore, IVDE is more suitable to predict DE than ME of diets and unconventional plant protein meals for growing pigs.
本试验旨在开发一种新型计算机控制的模拟消化系统,以预测生长猪非常规植物蛋白饲料的消化能(DE)和代谢能(ME)。所测试的9种饲料包括1种菜籽粕、4种棉籽粕、2种向日葵粕和2种花生粕。将20头初始体重(BW)为41.7±2.6 kg的生长猪(杜洛克×[长白×大白])分配到重复的10×3不完全拉丁方设计中,以测定1种基础日粮和用9种非常规植物蛋白饲料配制的9种试验日粮的DE和ME。非常规植物蛋白饲料的DE和ME值采用差值法计算。对1种基础日粮、9种试验日粮和9种非常规植物蛋白饲料的体外消化能(IVDE)进行测定,每个样品进行5次重复,采用完全随机排列。在10种试验日粮中,IVDE/DE或IVDE/ME范围为0.96至0.98或1.00至1.01,IVDE与DE或ME之间的相关系数为0.97或0.98。因此,在9种非常规植物蛋白饲料中,IVDE/DE或IVDE/ME范围为0.86至1.05或0.96至1.20,IVDE与DE或ME之间的相关系数为0.92或0.91。试验日粮(IVDE、DE和ME的变异系数分别为0.43%、0.80%和0.97%)和非常规植物蛋白饲料(IVDE、DE和ME的变异系数分别为0.92%、4.84%和6.33%)中,IVDE的变异系数小于DE和ME。在10种试验日粮和9种非常规植物蛋白饲料中,由IVDE预测DE的回归方程分别为DE = 0.8851×IVDE + 539(r = 0.9411,剩余标准差[RSD]=23 kcal/kg DM,P < 0.01)和DE = 0.9880×IVDE + 166(r = 0.8428,RSD = 182 kcal/kg DM,P < 0.01)。这两个方程的斜率(P = 0.82)或截距(P = 1.00)无统计学差异。因此,将10种日粮和9种非常规植物蛋白饲料合并,建立DE对IVDE的回归方程为:DE = 0.9813×IVDE + 187(r = 0.9120,RSD = 118 kcal/kg DM,P < 0.01)。在10种试验日粮和9种非常规植物蛋白饲料中,由IVDE预测ME的回归方程分别为ME = 0.9559×IVDE + 146(r = 0.9697,RSD = 18 kcal/kg DM,P < 0.01)和ME = 0.9388×IVDE + 3(r = 0.8282,RSD = 182 kcal/kg DM,P < 0.01)。这两个方程的斜率(P = 0.97)无统计学差异,但截距(P = 0.02)有显著差异。我们的结果表明,在10种试验日粮和9种非常规植物蛋白饲料中IVDE对DE的反应相似,但对ME的反应不同。因此,IVDE比ME更适合预测生长猪日粮和非常规植物蛋白饲料的DE。