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

• Autor(a) principal: Magagnin, Sebastião Ferreira
• Data de Publicação: 2020
• Outros Autores: Hauptli, Lucélia, Warpechowski, Marson Bruck
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: https://locus.ufv.br//handle/123456789/30356; https://doi.org/10.37496/rbz4920190177
• topic: backfat thickness; calibration procedures; lipid correction; nutritional modeling; swine

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<‒0.87) but positively correlated with the maintenance adjustment factor (MAINT) (r = 0.75). The inclusion of actual or default MP values in the ACM strongly influenced the estimation of other values, as well the predicted outcomes for BW and BT. The BTcor procedure and the input of actual or default MP values into the ACM of INRAPORC® is justified to reduce prediction errors, as it yields considerably greater accuracy in a pig nutritional adjustment system