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Abstract: The method of Boisen and Fernandez [Boisen, S., Fernandez, J.A., 1997. Prediction of total tract digestibility of energy in feedstuffs and pig diets by in vitro analyses, Anim. Feed Sci. Technol. 68, 277–286] for measuring in vitro fecal digestibility of organic matter (OMdv) or in vitro digestible organic matter content (DOMv, g/kg) was used on 113 compound feeds (79 as mash and 34 as pellets) and 66 ingredients (as mash) whose digestibility of organic matter (OMd) and energy (Ed) and digestible energy content (DE, MJ/kg) had been measured in 60kg growing pigs for all compound feeds and ingredients, and in adult sows for about 2/3 of the compound feeds (as mash); net energy (NE, MJ/kg) of these feeds were estimated from digestibility information. The repeatability and accuracy of the method were evaluated. Data obtained on compound feeds fed as mash were used to establish prediction equations of OMd, Ed, DE NE from OMdv or DOMv and chemical criteria. The levels of accuracy and repeatability of OMdv measurement were satisfactory and values for OMdv and OMd of mash compound feeds were very close and highly correlated (r =0.91). Apart from OMdv, the best prediction equations of OMd or Ed included ash content and a cell wall criterion (ADF or crude fiber); for prediction of DE, fat content had also to be considered. The coefficient of variation of all equations was below 0.02. The equations allow a satisfactory prediction of OMd, Ed or DE of the 66 ingredients fed as mash. However, the equations established on data obtained on mash feeds underestimate the in vivo nutritional value of pelleted feeds and are not applicable to prediction of energy value of feeds for adult pigs. [Copyright &y& Elsevier]

Mathematical models are increasingly used to predict the response of an animal to a changing nutrient supply. The objective of this experiment was to provide data that can be used in model development or evaluation and concerns the energetic efficiency with which nutrients are used for protein and lipid deposition. A basal diet (D1), limiting in lysine supply, was fed at 1.7 MJ metabolizable energy (ME)/(kg BW(0.60) x d1) to growing pigs that weighed approximately 60 kg. Four additional diets were formulated: the basal diet and a dietary supplement that consisted of starch (D2), starch and corn gluten meal (D3), starch and casein (D4) or starch and lipid (D5). The latter four diets were fed at 2.55 MJ ME/(kg BW(0.60) x d1) and ensured the same intake of the basal diet across treatments; the difference was supplied by the supplement. Metabolic utilization of the basal diet and supplements was determined using nitrogen and energy balances (indirect calorimetry). The N retention was similar in pigs fed diets D1, D2, D3 and D5 but considerably higher in those fed D4. A data analysis model was developed to account for differences in ME utilization between nutrients. The ME not deposited as protein entered a common pool of energy, which was used for adenosine triphosphate synthesis or lipid deposition. The energetic efficiencies of ME utilization were 0.842, 0.520 and 0.883 for starch, protein and lipid, respectively. Due to the energy cost of protein deposition (or protein turnover), the energetic efficiencies of depositing dietary protein as protein or lipid were similar. [ABSTRACT FROM AUTHOR]

Feed formulation using apparent metabolizable energy (AME) corrected to zero nitrogen retention (AMEn) is widely used by poultry nutritionists. Most available tabulated data are from experiments using adult cockerels or growing broilers. Specific values are rarely available for laying hens. A study was conducted to evaluate AME, AMEn, and AMEs (AME adjusted to 50% nitrogen retention) of corn, soybean meal (SBM) and wheat in laying hens using the reference diet substitution and regression methods. Forty eight 42-wk-old Hy-Line Brown hens were used, 2 birds per cage with six replicates per diet. Test diets contained 30% test ingredient (as is basis) and 65.7% reference diet (as is basis) with limestone, other minerals, vitamins, and amino acids held constant across the reference and test diets. Using the reference diet substitution method, AME values obtained for corn, SBM, and wheat were 3,791, 2,621, and 3,565 kcal/kg (DM), respectively. The corresponding AMEn values were 3,722, 2,496, and 3,479 kcal/kg (DM), and AMEs were 3,784, 2,835, and 3,562 kcal/kg (DM), respectively. Calculation of AME, AMEn, and AMEs of ingredients using regression based on the inclusion rate (DM) of dietary ingredients and reference diet gave identical values to those obtained by the reference diet substitution method. In addition, the measured AMEn values of ingredients using laying hens in this study were close to those calculated from proximate composition using the European Union prediction equation based on adult cockerels. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Net energy prediction and energy efficiency of feed for broiler chickens" which appeared in a previous issue.

Global consumption of chicken meat has increased at a faster rate than any other animal protein source, and thus refinements in energy formulation techniques for feed have continued to gain importance. Formulation of animal feed based on net energy (NE) has been implemented in ruminants and pigs but not in poultry. A closed-circuit respiratory calorimetry system was employed on 25- to 28-day-old broilers fed 19 diets formulated with varying nutrient composition to produce equations to predict NE and apparent metabolizable energy (AME) efficiency of feed for broiler chickens. Performance, energy and N balance, respiratory quotient, and energy utilization were measured in the birds. Linear regression analysis was performed to generate prediction equations for dietary energy content and AME efficiency. The NE content was positively related to AME and ether extract, but negatively to crude protein. The study generated equations that can accurately predict NE, and NE/AME using AME value and chemical composition of feeds. The NE prediction equations were further validated on a separate set of diets with high correlation (r = 0.99) and accuracy. The outcomes are an important step for the broiler industry to adapt to an NE system in place of AME systems for the formulation of broiler chicken feeds following robust validation experiments. [ABSTRACT FROM AUTHOR]

Pig production has increased in hot climate countries over recent years, but the effect of exposure to high temperatures on the health status of farm animals has not been investigated thoroughly. It is not clear how the ambient temperature (Ta) might influence responses to inflammatory challenge in pigs. The aim of the present study was to evaluate the effects of high Ta on performance and physiological parameters of growing pigs, subjected to repeated administration of Escherichia coli lipopolysaccharide (LPS). Thirty-seven pigs, each fitted with a jugular catheter, were assigned to one of two Ta conditions: thermo-neutral (TN, 24 °C) or high (HT, 30 °C). After a 14-day adaptation period, and a 7-day measurement period, pigs were administered five repeated injections of LPS at 48 h intervals. Irrespective of Ta, the LPS chal-lenge reduced feed consumption and increased plasma pro-inflammatory cytokines, haptoglobin and Cortisol. However, the extent of these responses was greater in pigs at TN than HT. In both groups, plasma thyroxine and triiodothyronine concentrations decreased, following the first LPS injection and thereafter returned to baseline, which occurred faster at HT than at TN. Moreover, the LPS challenge decreased growth and feed efficiency in pigs kept at TN, which was not observed in pigs kept at HT. The results suggest a greater capacity of pigs to limit the physiological and metabolic disturbances caused by inflammatory challenge, when kept at HT, compared to TN. [ABSTRACT FROM AUTHOR]

The conventional regression method for partitioning heat production (HP) in growing animals between HP associated with either maintenance or growth assumes maintenance HP to be independent of feeding level (FL). However, there are indications that this assumption is not correct and an alternative method is proposed in this study from a reanalysis of 3 trials. In trial 1, 73-, 152-, and 237-kg calves received one milk replacer at 77, 84, 92, and 100% of their ad libitum metabolizable energy (ME) intake. In trial 2, 70-kg barrows received one diet at 60, 80, and 100% of their ad libitum ME intake (2600 kJ ME/[kg body weight )BW)0.60. dl). In trial 3, 60-kg barrows received a basal diet 11700 kJ ME/(kg BW0.60.d)1 or 4 diets consisting of the basal diet plus 850 kJ ME/(kg BW0.60,d) of starch alone or starch with corn gluten, casein, or vegetable oil. In the 3 trials (n = 48, 18, and 28, respectively), HP and activity-related HP were measured on individuals pigs and calves in respiration chambers for 6 d (fed state) and fasting HP )FHP; at zero activity) was calculated as the asymptotic value of HP kinetics on d 7 (feed-deprived state). The FHP changed by 0.22 kJ in calves and 0.14 kJ in pigs/kJ ME intake change during the previous days. The efficiency of using ME for maintenance and growth [kmg; 1- (HP - FHP)/ME] was not affected by FL (calves: 84%, pigs in trial 2: 74%). In trial 3, kmgvaried between diets in connection with variations in efficiencies between nutrients (from 55% for corn gluten to 85% for lipid). This new method of representing partitioning of ME intake considers FHP as variable with FL, does not require estimates of maintenance ME requirements, includes efficiencies that depend on diet characteristics, and is not biased by metabolic adaptations of the animal to FL. [ABSTRACT FROM AUTHOR]

Four experiments were conducted to measure total tract metabolizability of gross energy (GE), the AME, and AMER or AME content corrected for a standardized N retention (AMES) of 10 European wheat dried distillers grains with solubles (DDGS) in roosters, broilers (3 wk old), layers (25 wk old), and growing turkeys (10 wk old). The wheat DDGS were obtained from 7 European ethanol plants and selected to get a large variability in chemical composition. The AME, AMER, or AMES of wheat DDGS was obtained according to the difference method. The highest AMEn:GE was obtained for roosters with an average (minimummaximum) value of 49% (43-55), the lowest in turkeys (43%; 34-50), and intermediate values (47%; 41-57 and 46%; 36-50) in broilers and layers, respectively. Corresponding AMER values were 10.3 (9.0-11.3), 9.9 (8.5-11.7), 9.6 (7.8-10.5), and 9.6 (7.8-10.5) MJ/kg of DM for roosters, broilers, layers, and turkeys, respectively. The AMES for N retention equal to 50% of N intake was about 0.6 MJ higher than the corresponding AMER value. Our data indicate that the AMER content of wheat DDGS can be predicted from either their acid detergent fiber content (R2 = 0.79) or the lightness score (L*; R2 = 0.77) with a common slope but different intercepts for the 4 poultry categories. If dark and overheated samples (L* <50; n = 3) with the lowest AME11:GE ratio and AMER values are excluded, the average AMEn:GE ratio becomes 51, 49, 48, and 45% in roosters, broilers, layers, and turkeys, respectively, with corresponding AMEII values of 10.7, 10.2, 10.0, and 9.5 MJ/kg of DM that are more representative of a well-controlled process for DDGS preparation. The negative effect of L* on energy value and energy metabolizability indicates that overheating while drying should be minimized to maximize the energy value of wheat DDGS for poultry. Finally, equations for predicting AME values in layers, broilers, or turkeys from the AME values in roosters are proposed. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, policies encouraging the production of ethanol from corn or wheat have stimulated an increased production of distillers dried grains with solubles (DDGS) whose nutritional value for pigs is little described. Seventeen wheat DDGS samples were obtained from 7 different plants in Europe from July to September 2007. Each sample was analyzed and 10 representative samples were measured for amino acids (AA) content and their standardized ileal digestibility (SID) in pigs. Lightness score (L) of each DDGS was also measured. Our results indicate a rather stable crude protein content (32.6 to 38.9% DM basis; average: 36.1% DM basis) whereas lysine was the most affected AA with contents ranging between 0.82 and 3.00% of crude protein (CP; N*6.25). In addition, lysine SID was also variable (9 to 82%) with the lowest values observed in DDGS with low lysine level in CP. In fact, samples with low lysine content in CP and low SID of lysine had low lightness values (L<50) and a subsequent high occurrence of Maillard reactions. Consequently, both lysine content (R=0.63) and lysine SID (R =0.68) values were positively correlated with lightness and DDGS samples that were lighter in colour had higher total and digestible AA levels. Our data indicate that lysine SID can be accurately predicted from lysine content in CP with a quadratic model (R²=0.87) or a linear-plateau model (R²=0.80 with a breakpoint for lysine content in CP of 1.9% and SID at plateau of 68%). This also suggests that wheat DDGS with lysine content in CP lower than 1.9% should be avoided in pig diets. [ABSTRACT FROM AUTHOR]

Abstract: Animal production is facing new challenges that call for a more integrative approach towards nutrition. Although considerable research progress has been made by the development of mathematical models of nutrient utilisation in farm animals, practical application of these models has been rather limited. The objective of the InraPorc® project is to integrate the current state of knowledge in a nutritional model for growing pigs and sows, and make it available as a decision support tool to end-users. The objective for the growing pig (15–150kg BW) model is to analyse nutrient utilisation for characterised pig types and to evaluate the effects of using different nutritional strategies in terms of nutrient utilisation, performance and carcass characteristics. As model parameters related to feed intake and growth potential are adjusted by the model user, growth (in an absolute sense) is not predicted. The model is based on the transformation of dietary nutrients to body protein and lipid, which are then used to predict body weight, lean body mass and backfat thickness. The representation of nutrient utilisation is mostly based on concepts used in net energy and ideal protein systems. Driving forces of the model include feed intake, the partitioning of energy between protein and lipid deposition, and availability of dietary protein and amino acids. Using literature data, the model appeared reasonably well capable of predicting the consequence of a nutrient intake restriction. The decision support tool is available at http://www.rennes.inra.fr/inraporc/. Through a user-friendly interface, the tool can be used to visualise different aspects of nutrient utilisation and excretion. [Copyright &y& Elsevier]

Abstract: From results obtained over the last 20 years on energy and amino acid utilisation in reproductive sows, it has become possible to improve the determination of nutrient requirements (factorial approach) and the prediction of an animal''s response to nutrient supplies (modelling). The objective of this project was to integrate the current state of knowledge in a nutritional model for growing pigs and for sows and make it available as a software tool to end-users, mainly nutritionists involved in the pig industry and students in animal nutrition. The aim of this paper is to describe the basis of the sow model. The sow is represented as different compartments that change over the reproductive cycle. Nutrient flows considered are those of energy and digestible amino acids. Nutrients are used with the highest priority for maintenance and uterine growth or milk production. Subsequently, deposition and/or mobilisation of body proteins and lipids are determined and used for estimating the changes in body weight and backfat thickness of the sow. A decision support tool was built from the set of equations given, with additional modules to describe animal''s characteristics and adjust some model parameters to account for variations in genotypes and performance. This tool can be used to determine energy and amino acids requirements of sows according to production objectives, or to predict body composition changes according to a given feeding strategy. The use of the decision support tool is illustrated through some examples. [Copyright &y& Elsevier]

A dynamic model was developed to study the effects of diet composition on lipid deposition and fatty acid (FA) composition in pigs. A basic model of protein and lipid deposition was used. Deposited lipids originate from dietary FA and de novo synthesized FA. It is hypothesised that 0.85 of absorbed FA are deposited as-is, and that the composition of de novo synthesized FA was constant throughout growth. Sensitivity analysis indicated that feed intake, efficacy of dietary FA storage and partitioning of de novo synthesized FA had a major impact on FA composition. Evaluation of the model indicated that predictions of protein, lipid, and backfat mass were insufficient, mainly due to the assumption of a constant ratio of lipid to protein mass in the basic growth model. Nevertheless, predictions of the FA composition of backfat and perinephric tissue were reasonable. Differences in FA composition between different tissues could only partly be explained by differences in tissue development. Development of this conceptually simple model was hampered by the limited availability of experimental data on the contribution of dietary lipids to purposes other than lipid deposition, the composition of de novo synthesized FA and the partitioning of FA between different depot sites. [Copyright &y& Elsevier]