Toward better estimates of the real-time individual amino acid requirements of growing-finishing pigs showing deviations from their typical feeding patterns

Author(s)

Hauschild, L. ^[1] ; Kristensen, A. R. ^[2] ; Andretta, I. ^[3] ; Remus, A. ^[4] ; Santos, L. S. ^[5] ; Pomar, C. ^[4]

Affiliation

^[1] Sao Paulo State Univ UNESP, Sch Agr & Vet Sci, Dept Anim Sci, BR-14883108 Jaboticabal - Brazil

^[2] Univ Copenhagen, Fac Hlth & Med Sci, Dept Vet & Anim Sci, Gronnegardsvej 2, DK-1870 Frederiksberg C - Denmark

^[3] Univ Fed Rio Grande do Sul, Fac Agron, BR-91540000 Porto Alegre, RS - Brazil

^[4] Agr & Agri Food Canada, Sherbrooke Res & Dev Ctr, 2000 Coll St, Lennoxville, PQ J1M 1Z3 - Canada

^[5] Univ Fed Rural Rio de Janeiro, Dept Anim Nutr & Pastures, BR-23897000 Seropedica, RJ - Brazil

• Document type: Journal article
• Source: ANIMAL; v. 14, n. 2, SI, p. S371-S381, AUG 2020.
• Web of Science Citations: 0

Abstract

Pigs exposed to stressors might change their daily typical feeding intake pattern. The objective of this study was to develop a method for the early identification of deviations from an individual pig's typical feeding patterns. In addition, a general approach was proposed to model feed intake and real-time individual nutrient requirements for pigs with atypical feeding patterns. First, a dynamic linear model (DLM) was proposed to model the typical daily feed intake (DFI) and daily gain (DG) patterns of pigs. Individual DFI and DG dynamics are described by a univariate DLM in conjunction with Kalman filtering. A standardized tabular cumulative sum (CUMSUM) control chart was applied to the forecast errors generated by DLM to activate an alarm when a pig showed deviations from its typical feeding patterns. The relative feed intake (RFI) during a challenge period was calculated. For that, the forecasted individual pig DFI is expressed as its highest DFI relative to the intake during pre-challenge period. Finally, the DLM and RFI approaches were integrated into the actual precision-feeding model (original model) to estimate real-time individual nutrient requirements for pigs with atypical feeding patterns. This general approach was evaluated with data from two studies (130 pigs, at 35.25 +/- 3.9 kg of initial BW) that investigated during 84 days the effect of precision-feeding systems for growing-finishing pigs. The proposed general approach to estimating real-time individual nutrient requirements (updated model) was evaluated by comparing its estimates with those generated by the original model. For 11 individuals out of 130, the DLM did not fit the observed data well in a specific period, resulting in an increase in the sum of standardized forecast errors and in the number of time steps that the model needed to adapt to the new patterns. This poor fit can be identified by the increase in the CUMSUM with a consequent alarm generated. The results of this study show that the updated model made it possible to reduce intra-individual variation for the estimated lysine requirements in comparison with the original model, especially for individuals with atypical feeding patterns. In conclusion, the DLM in conjunction with CUMSUM could be used as a tool for the online monitoring of DFI for growing-finishing pigs. Moreover, the proposed general approach allows the estimation of real-time amino acid requirements and accounts for the reduced feed intake and growth potential of pigs with atypical feeding patterns. (AU)

• FAPESP's process: 16/25157-8 - Modelling the feeding patterns of growing-finishing pigs reared under precision feeding strategies
• Grantee: Luciano Hauschild
• Support type: Scholarships abroad - Research
• FAPESP's process: 18/15559-7 - Precision nutrition for sanitary challenged pigs reared in hot climate areas
• Grantee: Luciano Hauschild
• Support type: Research Grants - Young Investigators Grants - Phase 2