Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC®

ABSTRACT We evaluated whether the procedure for correcting backfat thickness (BT) equation coefficients and lipid mass (LM) initial values in animal profiles, as well as actual model parameter (MP) data and their interrelationships, could reduce errors in predicting body weight (BW) and BT in pigs reared in Southern Brazil. Because different combinations of actual and estimated MP values in advanced system calibration mode (ACM) give rise to distinct calibration procedures, their BT and BW prediction errors were compared with those obtained by INRAPORC® default mode calibration based on different parameter combinations. Correlations among MP were also verified. The BT prediction correction (BTcor) procedure reduced the BT standard deviation of the estimate (σ) from 3.25 to 2.42 mm, but the correction had no effect on BW. Actual BT and feed intake data at 50 kg BW (FI50), reported in ACM, reduced prediction errors of BW and BT, in which their σ values were reduced from 5.29 to <4.08 kg and 2.42 to <2.12 mm, respectively. Mean protein deposition (MeanPD), FI50, and feed intake at 100 kg BW (FI100) were strongly and positively correlated (r>0.98). In addition, initial BW (BWi) was strongly negatively correlated with these parameters (r

摘要 我们评估了校正动物档案中背膘厚度（backfat thickness, BT）方程系数与脂肪量（lipid mass, LM）初始值，以及实际模型参数（model parameter, MP）数据及其相互关系的流程，是否能够降低巴西南部养殖生猪的体重（body weight, BW）与BT预测误差。由于高级系统校准模式（advanced system calibration mode, ACM）下实际与估算MP值的不同组合会产生各异的校准流程，因此将其BT与BW预测误差与基于不同参数组合的INRAPORC®默认模式校准所得误差进行了对比，并验证了MP间的相关性。背膘厚度预测校正（BTcor）流程将BT估计标准差（σ）从3.25 mm降至2.42 mm，但该校正对BW预测无影响。在ACM模式下报告的50 kg体重时采食量（FI50）与实际BT数据，可降低BW与BT的预测误差，二者的估计标准差分别从5.29 kg降至4.08 kg以下，以及从2.42 mm降至2.12 mm以下。平均蛋白质沉积量（mean protein deposition, MeanPD）、FI50与100 kg体重时采食量（FI100）呈现极强的正相关关系（r>0.98）。此外，初始体重（initial BW, BWi）与上述参数呈现极强的负相关关系（r