The ideal protein profile for late-finishing pigs in precision feeding systems: Threonine

Insulin sensitivity is associated with the observed variation of de novo lipid synthesis and body composition in finishing pigs

Variations in body composition among pigs can be associated with insulin sensitivity given the insulin anabolic effect. The study objectives were to characterize this association and to compare de novo lipogenesis and the gene expression in the adipose tissue of pigs of the same genetic background. Thirty 30-95 kg of body weight (BW) pigs, catheterized in the jugular vein participated into an oral glucose tolerance test (OGTT; 1.75 g glucose/kg of BW) to calculate insulin-related indexes. The 8 fattest and the 8 leanest pigs were used to determine the relative mRNA abundance of studied genes. The rate of lipogenesis was assessed by incorporation of [U-¹³C]glucose into lipids. The QUICKI and Matsuda indexes negatively correlated with total body lipids (r =  - 0.67 and r =  - 0.59; P < 0.01) and de novo lipogenesis (r =  - 0.58; P < 0.01). Fat pigs had a higher expression level of lipogenic enzymes (ACACA, ACLY; P < 0.05) than lean pigs. The reduced insulin sensitivity in fat pigs was associated with a higher expression level of glucose-6-phosphate dehydrogenase (G6PD) and a lower expression of peroxisome proliferator-activated receptor-gamma (PPAR-γ). In conclusion, pigs with increased body lipids have lower insulin sensitivity which is associated with increased de novo lipogenesis.

Estimating Amino Acid Requirements in Real-Time for Precision-Fed Pigs: The Challenge of Variability among Individuals

Simple Summary

Precision feeding considers the difference in amino acid requirements among pigs and over time by providing daily tailored diets. This practice allows improving environmental and economic performances. Future systems should focus on maximizing nutrient use efficiency to move towards “green” pig production. This study explored a new method of providing amino acids to maximize their use, mainly focusing on understanding variations in the protein metabolism response among individuals to minimize variation in growth response. This study showed that even pigs fed the same amino acid level might use these nutrients differently, especially in protein deposition. Logically, pigs with the greatest protein deposition are the ones that use amino acids the most efficiently, thus exhibiting the lowest nitrogen excretion. This study helped identify some of the factors affecting the efficiency of nitrogen use in pigs. By improving the understanding of pigs’ nutrient response, pig production can become more resource-efficient.

Abstract

This study aimed to measure protein deposition (PD) in pigs fed with daily tailored diets where either dietary lysine (Lys) or threonine (Thr) were provided at independent levels (ignoring an ideal ratio). A total of 95 growing pigs (35 kg body weight (BW)) with electronic ear tags granting them access to automatic feeders were randomly assigned to treatments. The setup was an unbalanced 2 × 5 factorial arrangement with Lys and Thr provided at five levels (i.e., 60%, 80%, 100%, 120%, and 140% of the estimated individual requirements of Lys and Thr), resulting in 25 treatments for 21 days. The observed PD variation to Lys and Thr provisions was large, with Lys and Thr intake explaining only 11% of the variation. Cluster analysis discriminated pigs with low (167 g/d, n = 16), medium (191 g/d, n = 38), and high (213 g/d, n = 37) PD, but with a similar amino acid intake. Differences in PD were associated with differences in nutrient efficiency of utilization. Providing Lys and Thr in a factorial mode, ignoring an ideal ratio, did not decrease the variability in PD. Future research efforts should focus on identifying and investigating the sources of interindividual variability—a necessary step before final recommendations can be made for AA in precision-fed pigs.

Feeding Strategies to Reduce Nutrient Losses and Improve the Sustainability of Growing Pigs

The efficiency of pig production using nutrients has increased over the years. Still, better efficiency of nutrient utilization can be achieved by feeding pigs with diets adjusted to their estimated requirements. An increase in nutrient efficiency of utilization represents economic gains while maximizing environmental performance. The objective of this paper is to review the impact of different methods of diet formulation that provide farm animals with the amount of nutrients to satisfy their needs while minimizing nutrient excretion and greenhouse gas emissions. Diet formulation is one tool that can help to maximize nitrogen and energy utilization by decreasing crude protein content in diets. The use of local feedstuff and non-human-edible products (e.g., canola meal) associated with synthetic amino acid inclusion in the diet are valuable techniques to reduce carbon footprint. Precision feeding and nutrition is another powerful tool that allows not only daily tailoring of diets for maximal nutrient efficiency of utilization but also to reduce costs and improve nitrogen efficiency of utilization. In this review, we simulated through mathematical models the nitrogen and energy efficiency of utilization resulting from crude protein reduction in the diet. An 8% crude protein reduction in the diet can increase nitrogen efficiency of utilization by 54% while costing 11% less than a control diet without synthetic amino acids. The same reduction in crude protein represented a major improvement in available energy due to the decrease of energetic losses linked to protein deamination. Urinary and hindgut fermentation energy losses were 24% lower for pigs fed with low-protein diets when compared to control diets. In terms of modern feeding techniques and strategies, precision feeding and nutrition can decrease nitrogen excretion by 30% when compared to group phase feeding. The benefits of feeding pigs with low-protein diets and precision feeding techniques are additive and might result in a 61% nitrogen efficiency of utilization. There is room for improvement in the way nutrient requirements are estimated in pigs. Improving the understanding of the variation of nutrient utilization among pigs can contribute to further environmental gains.

Feeding behavior of growing and finishing pigs fed different dietary threonine levels in a group-phase feeding and individual precision feeding system

Feeding behavior is an important aspect of pig husbandry as it can affect protein deposition (PD) in pigs. A decrease in plasma threonine (Thr) levels may influence feed intake (FI) due to amino acid imbalance. We set out to study whether different Thr inclusion rates of 70%, 85%, 100%, 115%, and 130% of the ideal Thr:lysine (Lys) ratio of 0.65 in two different feeding programs (individual precision feeding and group-phase feeding could affect pig feeding behavior and consequently PD. Two 21-d trials were performed in a 2 × 5 factorial setup (feeding systems × Thr levels) with 110 pigs in the growing phase [25.0 ± 0.8 kg of body weight (BW)] and 110 pigs in the finishing phase (110.0 ± 7.0 kg BW), which correspond to 11 pigs per treatment in each trial. Pigs were housed in the same room and fed using computerized feeding stations. The total lean content was estimated by dual x-ray absorptiometry at the beginning (day 1) and the end (day 21) of the trial. Multivariate exploratory factor analysis was performed to identify related variables. Confirmatory analysis was performed by orthogonal contrasts and Pearson correlation analysis. Graphical analysis showed no difference in feeding patterns between feeding systems during the growing or finishing phase. Pigs exhibited a predominant diurnal feeding, with most meals (73% on average) consumed between 0600 and 1800 h. Exploratory factor analysis indicated that feeding behavior was not related to growth performance or PD in growing or finishing pigs. Changes in feeding behavior were observed during the growing phase, where increasing dietary Thr resulted in a linear increase in the FI rate (P < 0.05). During the finishing phase, the duration of the meal and FI rate increased linearly as dietary Thr increased in the diet (P < 0.05). These changes in feeding behavior are, however, correlated to BW. In conclusion, the exploratory factor analysis indicated that feeding behavior had no correlation with growth performance or protein and lipid deposition in growing or finishing pigs. Dietary Thr levels and feeding systems had no direct effect on FI.

Precision livestock farming: real-time estimation of daily protein deposition in growing-finishing pigs

Precision feeding using real-time models to estimate daily tailored diets can potentially increase nutrient utilization efficiency. However, to improve the estimation of amino acid requirements for growing-finishing pigs, it is necessary to accurately estimate the real-time body protein (BP) mass. The aim of this study was to predict individual BP over time in order to obtain individual daily protein content of the gain (i.e., protein deposition/daily gain, PD/DG) to be integrated into a real-time model used for precision feeding. Two databases were used in this study: one for the development of the equations for the model and the other for model evaluation. For the equations, data from 79 barrows (25 to 144 kg BW) were used to estimate the parameters for a Gompertz function and a mixed linear-quadratic regression. Individual BP predictions obtained by dual X-ray absorptiometry were regressed as a function of BW. Individual pig BP estimates were obtained by linear-quadratic regression using the MIXED procedure of SAS, considering pig measurements repeated in time. Individual Gompertz curves were obtained using the NLMIXED procedure of SAS. Both procedures generate an average or a general model, which was assessed for accuracy with the database used to generate the equations. Coefficients of concordance and determination were both 0.99, and the RMSE was 0.21 kg for the linear-quadratic regression. The Gompertz curve coefficients of concordance and determination were both 0.99, and the RMSE was 0.36 kg. In sequence, the linear-quadratic regression and Gompertz curve were evaluated in an independent data set (488 observations; 21 to 126 kg BW). The linear-quadratic regression to predict BP mass was accurate (mean absolute percentage error (MAPE) = 2.5%; bias = 0.03); the Gompertz model performed worse (MAPE = 3.9%; bias = 0.04) than the linear-quadratic regression. When using the derivative of these equations to predict PD/DG, the linear-quadratic regression was more accurate (MAPE = 4.8%, bias = 0.17%) compared to the Gompertz (MAPE = 10.6%, bias = -0.99%) mainly due to the linear decrease in PD/DG in the observed data. Further analysis using individual pig data showed that the goodness of fit of PD/DG curve depends on the individual shape of the growth curve, with either the Gompertz or the linear-quadratic regression being more accurate for specific individuals. Therefore, both approaches are provided to allow end users to select the model that best fits their needs. The proposed update of the empirical component of the original model, using either linear-quadratic regression or the Gompertz function, is able to predict BP in real-time with good accuracy.