Methodologies on estimating the energy requirements for maintenance and determining the net energy contents of feed ingredients in swine: a review of recent work

Correlation between reproductive performance and sow body weight change during gestation

This study investigated the correlation between piglet performance and sow body weight change (BWC) during two gestational periods: 35-70, 70-105, and 35-105 days. A cohort of 70 sows was evaluated for BWC, backfat thickness change (BFC), caliper score change (CALC), feed intake, and weaning-to-estrus interval (WEI). The collected data were then analyzed according to the two specified periods. Our findings highlighted that piglet birth weight, weaning weight, and average daily weight gain (ADG) correlated with sow body characteristics, including BFC and CALC. The strongest correlation was observed with BWC. Piglet mortality was intimately associated with BFC. Piglet birth weight, weaning weight, and ADG showed a positive correlation with sow BWC, particularly during the 35-70 day period. Furthermore, sows displaying a higher BWC during the 70-105 day period, and also exhibiting a higher BW gain from 35-70 days, registered greater piglet weight gains and higher weaning weights. These trends became more apparent as the sow's BWC increased during the 70-105 day period. Piglet mortality increased when the sow exhibited a lower BWC during both the 35-70 and 70-105 day periods. No significant observations were found concerning the number of stillborn piglets, live-born piglets, or weaned piglets, and no interaction effects were detected between these periods. In conclusion, our findings underscore the significance of sow BWC during the early stages of gestation (d 35-70) for enhancing piglet performance from birth to weaning.

Mitigating environmental impacts using net energy system in feed formulation in China's pig production

As the world's largest pork producer, China is facing substantial environmental pressures caused by pig production and the relevant feed production. The net energy (NE) system is promoted as a new evaluation method to evaluate energy content in feed and energy requirements of pigs, but its application lacks of comprehensive and comparative evaluation from the environmental perspective. To identify influence factors and to develop mitigation strategies, the carbon and nitrogen footprints and land use (LU) of pigs (25-120 kg) in China were explored through scenario analysis and cradle-to-farm gate life cycle assessment (LCA). Functional unit (FU) was defined as 1 kg of live weight increase in pig. Among all the procedures of pig production, feed crop production and manure management were the principal contributors to the greenhouse gas (GHG) and nitrogen emissions. As for the carbon footprint, the GHG emissions ranged from 2.37 to 2.55 kg CO₂-eq. FU^-1 for scenarios using the NE system, 2 % lower than that of the metabolizable energy (ME) system. Cottonseed meal-based scenario generated the lowest GHG emissions, and anaerobic digestion achieved the same effects as other manure management methods. As for the nitrogen footprint, reactive nitrogen (Nr) emissions ranged from 53.4 to 66.2 g Nr FU^-1 for scenarios using the NE system, 4 % lower than that of the ME system. Peanut-based scenario won the lowest Nr losses. Moreover, arable LU ranged from 4.63 to 5.85 m² FU^-1 for scenarios using the NE system, 4 % lower than that of the ME system, and economic advantage by using the NE system was also proved. Sensitivity analysis and data quality assessment were conducted to quantify the uncertainties of the above models. In conclusion, the application of the NE system in feed formulation was an effective strategy to improve the environmental sustainability of China's pig production.

Modeling net energy partition patterns of growing-finishing pigs using nonlinear regression and artificial neural networks

The objectives of this study were to evaluate the net energy (NE) partition patterns of growing-finishing pigs at different growing stages and to develop the corresponding prediction models using nonlinear regression (NLR) and artificial neural networks (ANN). Twenty-four pigs with an initial body weight (BW) of ~30 kg were kept in metabolic cages and fed ad libitum and were moved into six respiration chambers in turns until ~90 kg. The NE partition patterns, i.e., NE for maintenance (NEm), NE retained as protein (NEp), and NE retained as lipid (NEl), were calculated based on indirect calorimetry and nitrogen balance techniques. The energy balance data collected through the animal trial was then randomly split into a training data set containing 75% of the samples and a testing data set containing the remaining 25% of the samples. The NLR models and a series of ANN models were established on the training data set to predict the metabolizable energy intake, NE intake, NEm, NEp, and NEl of pigs. The best-fitted ANN models were selected by 5-fold cross-validation in the training data set. The prediction performance of the best-fitted NLR and ANN models were compared on the testing data set. The results showed that the average NE intakes of pigs were 17.71, 23.25, 24.56, and 28.96 MJ/d in 30 to 45 kg, 45 to 60 kg, 60 to 75 kg, and 75 to 90 kg, respectively. The NEm and NEl (MJ/d) kept increasing as BW increased from 30 kg to 90 kg, while the NEp increased to its maximum value and then kept in a certain range of 4.64 to 4.88 MJ/d. The proportion of NEm for pigs at 30 to 90 kg stayed within the range of 42.0% to 48.6%, while the proportion of NEl kept increasing. For the prediction models built based on the animal trial, ANN models exhibited better performance than NLR models for all the target outputs. In conclusion, NE partition patterns changed in different growth stages of pigs, and ANN models are more flexible and powerful than NLR models in predicting the NE partition patterns of growing-finishing pigs.

A review of swine heat production: 2003 to 2020

Swine heat production (HP) data are an essential element of numerous aspects affecting swine production sustainability, such as, housing environmental control design, energetics and thermoregulation modeling, as well as understanding of feed energy partitioning. Accurate HP values that reflect the continuous advances in growth, nutrition, health, and reproduction are needed to update outdated models and data; hence, this review of swine HP values is a critical contribution. This review updates the last previous review conducted in 2004, by reviewing literature from growing and breeding pigs from 2003 to 2020. In total, 33 references were identified that provided relevant HP data and from these references, 192 records were identified for pigs ranging in weight from 12.5 to 283 kg and exposed to temperatures between 12.0°C and 35.5°C. For growing pigs at thermoneutral conditions, a 4.7% average increase in HP was observed compared to HP data summarized from 1988 to 2004. Only five records were identified for gestating sows and the 43 records for lactating sows plus litter. This sow data shows high variability and inconsistent trends with temperature, most likely attributed to variation in experimental protocols, management, and limited reported information. There is still a lack of data on growing pigs greater than 105 kg, gilts and gestating sows housed in different systems (stall, pen, mixed, etc.), and latent HP values that reflect different housing systems. Further, there is a need to standardize reporting of HP values (with an example provided) across different disciplines to drive documentation of increased swine production efficiency, environmental control design, and energetics modeling.

Methodologies for energy evaluation of pig and poultry feeds: A review

The cost of feed represents an important part of the total cost in swine and poultry production (>60%) with energy accounting for at least 70% of feed cost. The energy value of ingredients or compound feeds can be estimated as digestible (DE), metabolisable (ME) and net energy (NE) in pigs and ME and NE in poultry. The current paper reviews the different methods for evaluating DE, ME and NE of feeds for monogastric animals and their difficulties and limits, with a focus on NE. In pigs and poultry, energy digestibility depends on the chemical characteristics of the feed, but also on technology (pelleting, for instance) and animal factors such as their health and body weight. The ME value includes the energy losses in urine that are directly dependent on the proportion of dietary N excreted in urine resulting in the concept of ME adjusted for a zero N balance (MEn) in poultry. For poultry, the concept of true ME (TME, TMEn), which excludes the endogenous fecal and urinary energy losses from the excreta energy, was also developed. The measurement of dietary NE is more complex, and NE values of a given feed depend on the animal and environmental factors and also measurement and calculation methods. The combination of NE values of diets obtained under standardised conditions allows calculating NE prediction equations that are applicable to both ingredients and compound feeds. The abundance of energy concepts, especially for poultry, and the numerous feed and animal factors of variation related to energy digestibility or ME utilisation for NE suggest that attention must be paid to the experimental conditions for evaluating DE, ME or NE content. This also suggests the necessity of standardisations, one of them being, as implemented in pigs, an adjustment of ME values in poultry for an N retention representative of modern production conditions (MEs). In conclusion, this review illustrates that, in addition to numerous technical difficulties for evaluating energy in pigs and poultry, the absolute energy values depend on feed and animal factors, the environment, and the methods and concepts. Finally, as implemented in pigs, the use of NE values should be the objective of a more reliable energy system for poultry feeds.

Net energy value of canola meal, field pea, and wheat millrun fed to growing-finishing pigs

Two experiments were conducted to (1) determine net energy (NE) values of soybean meal (SBM), Napus canola meal (NCM), Juncea canola meal (JCM), field pea, and wheat millrun (WM) using indirect calorimetry, and (2) compare the determined NE values with the calculated NE values of the same feedstuffs based on a prediction equation. In experiment 1, six ileal-cannulated barrows (31 kg) were fed five diets in 5 × 6 Youden square to give six replicates per diet. Diets were cornstarch-based diets containing SBM, NCM, JCM, field pea, or WM. The SBM was included as a reference. In experiment 2, six ileal-cannulated barrows (70 kg) were fed a N-free diet for determining energy digestibility and NE values of test feedstuffs fed in experiment 1 by difference method. The NE values of test feedstuffs were also calculated from the digestible energy (DE) values and analyzed macronutrient content of the test feedstuffs. On dry matter (DM) basis, SBM, NCM, JCM, field pea, and WM contained 51%, 41%, 42%, 28%, and 18% crude protein; 1.52%, 2.95%, 2.36%, 1.33%, and 3.12% ether extract; 2.93%, 0.14%, 1.44%, 36.7%, and 28.7% starch; and 5.30%, 21.0%, 13.4%, 9.49%, and 16.1% acid detergent fiber, respectively. The determined NE value for SBM (2.29 Mcal/kg) did not differ from that of NCM (1.72 Mcal/kg DM) or JCM (2.14 Mcal/kg DM). The NCM and JCM did not differ in NE value. Also, the determined NE value did not differ between field pea (2.00 Mcal/kg) and WM (2.55 Mcal/kg). The calculated NE values for SBM (2.18 Mcal/kg DM), NCM (1.73 Mcal/kg DM), and JCM (1.86 Mcal/kg DM) did not differ from the corresponding determined NE values of the same feedstuffs. However, the calculated NE value for field pea (2.51 Mcal/kg DM) was greater (P = 0.004) than the determined NE value of field pea, whereas the calculated NE value for WM (2.27 Mcal/kg DM) tended to be lower (P = 0.054) than the determined NE value of WM. In conclusion, the NE value for SBM and canola meals can be predicted based on the DE value and the macronutrient composition of the same feedstuffs. However, the NE value for field pea and WM may not be predicted precisely based on the DE value and the macronutrient composition of the same feedstuffs.

Meta-analysis of energy intake of growing-finishing pigs in China

Data from 655 treatments of 116 studies were used in a meta-analysis to determine the daily digestible energy (DE), metabolizable energy (ME) and net energy (NE) intake of Chinese growing-finishing pigs, and to predict feed efficiency responses to change in dietary DE, ME and NE. Three alternative functions (i.e., polynomial, Bridges and asymptotic function) were employed for fitting daily DE, ME or NE intakes to mean body weight. The results showed that the three models from the current study provided reasonable fit (all R²  > 0.83) for the energy intake data. However, under the same energy system, the polynomial function had the smallest Akaike's information criteria (AIC) and residual standard deviation (RSD), followed by Bridges and asymptotic functions. The three model-generated energy intakes of growing pigs were significantly less than that of the Chinese Feeding Standard of Swine, but similar to that of the National Research Council (2012), while the values of finishing pigs were greater than both standards. Compared with those that predict feed efficiency based on DE or ME, the equation with NE as a predictor had the minimized AIC and RSD. It was also found that feed efficiency increased with increasing dietary energy density (DED), but this response varied with pig body weight, and the lighter pigs were more sensitive to DED than heavier pigs.

Measures Matter-Determining the True Nutri-Physiological Value of Feed Ingredients for Swine

Many types of feed ingredients are used to provide energy and nutrients to meet the nutritional requirements of swine. However, the analytical methods and measures used to determine the true nutritional and physiological ("nutri-physiological") value of feed ingredients affect the accuracy of predicting and achieving desired animal responses. Some chemical characteristics of feed ingredients are detrimental to pig health and performance, while functional components in other ingredients provide beneficial health effects beyond their nutritional value when included in complete swine diets. Traditional analytical procedures and measures are useful for determining energy and nutrient digestibility of feed ingredients, but do not adequately assess their true physiological or biological value. Prediction equations, along with ex vivo and in vitro methods, provide some benefits for assessing the nutri-physiological value of feed ingredients compared with in vivo determinations, but they also have some limitations. Determining the digestion kinetics of the different chemical components of feed ingredients, understanding how circadian rhythms affect feeding behavior and the gastrointestinal microbiome of pigs, and accounting for the functional properties of many feed ingredients in diet formulation are the emerging innovations that will facilitate improvements in precision swine nutrition and environmental sustainability in global pork-production systems.

Integrative Analysis of Energy Partition Patterns and Plasma Metabolomics Profiles of Modern Growing Pigs Raised at Different Ambient Temperatures

Simple Summary

Most of the studies focusing on energy partition patterns of growing pigs and the related mechanisms raised at different ambient temperatures were carried out during the 1970s to the early 2000s. With the rapid developments in pig breeding, research updates on such topics concerning modern growing pigs have been absent in the last decade. Therefore, this study focused on the energy partition patterns of modern growing pigs with different bodyweights at gradient-ambient temperatures and investigated the underlying changes in plasma metabolites under such conditions. Modern growing pigs at heavier bodyweight were more sensitive to high temperatures on energy intake and partition. At high ambient temperatures, most of the identified metabolites altered are associated with decreased fatty acid oxidation, increased lipid formation, and increased protein degradation. The findings of this study will provide possible solutions to precisely formulate diets for modern growing pigs raised at different ambient temperatures, and can help to improve our knowledge on potential mechanisms of thermoregulation in modern pig breeds.

Abstract

This study explores the energy partition patterns of modern growing pigs at 25 kg and 65 kg raised at gradient-ambient temperatures. It also investigates the underlying changes in plasma under such conditions, based on the integrative analysis of indirect calorimetry and non-target metabolomics profiling. Thirty-six barrows with initial BW of 26.4 ± 1.9 kg and 24 barrows with initial BW of 64.2 ± 3.1 kg were successively allotted to six respiration chambers with ambient temperatures set as 18 °C, 21 °C, 23 °C, 27 °C, 30 °C, and 32 °C, and four respiration chambers with ambient temperatures set as 18 °C, 23 °C, 27 °C, and 32 °C, respectively. Each pig was kept in an individual metabolic crate and consumed feed ad libitum, then transferred into the respiration chamber after a 7-day adaptation period for 5-day indirect calorimetry assay and 1-day fasting. As the ambient temperature increased from 18 °C to 32 °C, the voluntary feed intake, metabolizable energy intake, nitrogen intake, and retention, total heat production, and energy retention as a protein of growing pigs at 25 kg and 65 kg all linearly decreased (p < 0.05), with greater coefficients of variation for pigs at 65 kg when temperatures changed from 18 °C to 32 °C. The cortisol and thyroid hormone levels in the plasma of 25 kg pigs linearly decreased as the ambient temperature increased from 18 °C to 32 °C (p < 0.05), and 13 compounds were identified through metabolomics analysis, including up-regulated metabolites involved in fatty acid metabolism, such as adrenic acid and down-regulated metabolites involved in amino acid metabolism, such as spermidine at 32 °C. These results suggested that modern growing pigs at heavier bodyweight were more sensitive to high temperatures on energy intake and partition. Most of the identified metabolites altered at high ambient temperatures are associated with suppressed fatty acid oxidation and elevated lipogenesis and protein degradation.

The In Vivo Net Energy Content of Resistant Starch and Its Effect on Macronutrient Oxidation in Healthy Adults

The in vivo net energy content of resistant starch (RS) has not been measured in humans so it has not been possible to account for the contribution of RS to dietary energy intake. We aimed to determine the in vivo net energy content of RS and examine its effect on macronutrient oxidation. This was a randomized, double-blind cross-over study. Eighteen healthy adults spent 24 h in a whole room indirect calorimeter to measure total energy expenditure (TEE), substrate oxidation, and postprandial metabolites in response to three diets: 1) digestible starch (DS), 2) RS (33% dietary fiber; RS), or 3) RS with high fiber (RSF, 56% fiber). The in vivo net energy content of RS and RSF are 2.74 ± 0.41 and 3.16 ± 0.27 kcal/g, respectively. There was no difference in TEE or protein oxidation between DS, RS, and RSF. However, RS and RSF consumption caused a 32% increase in fat oxidation (p = 0.04) with a concomitant 18% decrease in carbohydrate oxidation (p = 0.03) versus DS. Insulin responses were unaltered after breakfast but lower in RS and RSF after lunch, at equivalent glucose concentrations, indicating improved insulin sensitivity. The average in vivo net energy content of RS is 2.95 kcal/g, regardless of dietary fiber content. RS and RSF consumption increase fat and decrease carbohydrate oxidation with postprandial insulin responses lowered after lunch, suggesting improved insulin sensitivity at subsequent meals.