Empirical models to predict feed intake of growing-finishing pigs reared under high environmental temperatures

Abstract

Several empirical models were proposed to predict feed intake (FI) of growingfinishing pigs reared under high environmental temperatures. However, these models have not been evaluated under conditions different from those in which they were developed. Twelve empirical models were evaluated using a database built after systematic literature review (observed data: 28 studies in which the FI was evaluated in pigs under high environmental temperatures). Model accuracy was assessed using the mean squared of prediction error (MSPE). Analyses were performed considering two scenarios: (1) general population, where all observed data were used in the simulation; (2) reference population, where data were filtered in order to simulate only scenarios with environment (temperature range) and animals (body weight and sex) similar to that used in the model development. Six models estimated FI values similar (p > 0.05) to those observed in the general population, while four models produced estimates similar to the observed values in the reference populations. Most models were more accurate when they were simulated using the reference population than when the simulation considered the general database. Moving the simulation from the general database to the reference population reduced up to 98 % of the MSPE, depending on the equation. Empirical models allow to accurately predict FI of growing-finishing pigs exposed to high environmental temperatures, especially in scenarios similar to the ones used for model development. Thus, population characteristics (body weight and sex) and environment (temperature range) must be considered in the model assessment.

Modeling the performance of broilers under heat stress

“…For FI after 21 d, the accuracy of the model (Equation 5) was limited by the ER, however, this error is systematic and can be corrected by further modeling procedures. However, the accuracy observed for body weight gain estimation after 21 d (Equation 11) was limited by ED, which is a random error, difficult to correct ( Perondi et al., 2018 ). The diversity in the studies that composed the databases may contribute to this higher ED.…”

“…The MSPE was then broken down into error of central tendency ( ECT ) and error of regression ( ER ), which together with ECT indicated the lack of trueness, and error due to disturbances ( ED ) which indicated the lack of precision, following the proposition described by Theil (1966) . Afterward, the interpretation was performed according to Perondi et al. (2018) .…”

Spatial layout planning of intensive pig farms in the suburb: a case study of Nanyu, China

“…Compared with many studies (Zhao et al, 2006;Yan et al, 2010;Peng et al, 2014;Yan et al, 2016;Yan et al, 2017;Qiu et al, 2017;Liu et al, 2018), the current research determined the optimum potential intensive pig farms considering the suitability evaluation result of the spatial layout of intensive pig farms average surface temperature and area index results of cultivated land spatial matched with intensive pig farm. Furthermore, the existing research results had shown that the high temperature environment had a profound impact on the pig industry (Xia et al, 2016;Perondi et al, 2018;Morales et al, 2019;Oliveira et al, 2019). Therefore, selecting the region with relatively low temperature in summer as the potential location for spatial layout planning of intensive pig farms is highly valuable.…”

“…In addition, the results showed that the high temperature environment had a strong influence on the pig industry (Oliveira et al,2019). With the increase in the environment temperature, the thermoregulation indices of pig such as food intake, evaporation and heat dissipation, respiratory rate, and so on, have changed dramatically (Xia et al, 2016;Perondi et al, 2018;Morales et al,2019;Oliveira et al,2019). However, few studies examined the spatial layout of intensive pig farms considering the current regional environment temperature.…”