RESUMO: O INRAPORC® é um sistema de modelos mecanicista, dinâmico e determinista. Seu uso em sistemas comerciais de produção de suínos é restrito, pois necessita de informações de desempenho de animais sob manejo alimentar à vontade (AV), uma vez que este manejo não é utilizado em todas as fases de produção. Por isso é interessante verificar se a calibração do INRAPORC® baseada em um pequeno grupo de animais AV em situação laboratorial é capaz de simular a cinética média de uma população comercial maior e de subsidiar equações de correção de dados preditos de peso vivo (PV) e espessura de toucinho (ET). As análises foram realizadas comparando os dados preditos e observados sob o teste da curva de calibração da predição (b0=0 e b1=1), as curvas obtidas apresentaram erro sistemático de efeito fixo para a ET de +2,37mm. Os valores preditos de PV e ET foram corrigidos utilizando os valores dos erros sistemáticos obtidos. Como resultado, 100% das médias observadas de PV, estavam contidas nos intervalos de confiança (IC) das médias preditas pelo INRAPORC®, sem necessidade de correções e 78,5% das médias reais de ET estavam contidas nos IC das médias preditas pelo sistema, após as correções. A calibração do INRAPORC® baseada em uma pequena população de animais em situação laboratorial pode ser aplicada para predições de um sistema comercial de criação de suínos, bem como a aplicação do procedimento de correção dos dados preditos de PV e ET nas populações suínas que apresentem erros sistemáticos nas validações preditivas do sistema.

ABSTRACT: INRAPORC® is a mechanistic, dynamic, and deterministic model system that is used in commercial pig production. However, its use is limited as it requires performance information for animals under ad libitum (AL) feed management, which is not provided at all stages of production. Verification of the INRAPORC® calibrations were conducted in this investigation using data from a small group of animals fed with AL in a laboratory situation, to simulate the mean kinetics of a larger commercial population and generate the correction equations for the predicted body weight (BW), and backfat thickness (BT). Analyses were performed by comparing the predicted and observed data, and by submitting them to prediction calibration curve tests (b0 = 0, and b1 = 1). The obtained curves presented a systematic, fixed effect error (+2.37 mm) for BT. The predicted BW and BT values were corrected using the values of the systematic errors obtained. As a result, 100% of the BW averages observed were contained in the confidence intervals (CI) of the INRAPORC® predicted averages, without the need for corrections, and 78.5% of the actual BT averages were contained in the CI of the averages predicted by the system, after corrections. The INRAPORC® calibrations, based on a small population of animals in laboratory conditions could thus be utilized to make predictions for commercial pig production systems and for value correction procedures for the BW and BT of pig populations that have systematic errors in their prediction validations.

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<–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.