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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]

The aim of this study was to evaluate the associated effects of ambient temperature and inflammation caused by repeated administration of Escherichia coli lipopolysaccharide (LPS) on insulin, energy, and AA metabolism. Twenty-eight pigs were assigned to one of the two thermal conditions: thermoneutral (24 °C) or high ambient temperature (30 °C). The experimental period lasted 17 d, which was divided into a 7-d period without LPS (days −7 to −1), and a subsequent 10-d LPS period (days 1 to 10) in which pigs were administered 5 repeated injections of LPS at 2-d intervals. Postprandial profiles of plasma insulin and nutrients were evaluated through serial blood samples taken on days −4 (P0), 4 (P1), and 8 (P2). Before the LPS-challenge (P0), postprandial concentrations of glucose, lactate, Gln, Ile, Leu, Phe, Tyr, and Val were greater in pigs kept at 24 °C than at 30 °C (P < 0.05). In contrast, Arg, Asp, Gly, His, and Met postprandial concentrations at P0 were lower at 24 °C than at 30 °C (P < 0.05). At both 24 and 30 °C conditions, pigs had greater postprandial concentrations of insulin (P < 0.01) and lower concentrations of NEFA (P < 0.01) and α-amino nitrogen (P < 0.05) at P1 and P2 than at P0. Compared with P0, postprandial concentrations of glucose were greater (P < 0.05) at P1 in pigs kept at 24 °C, and at P1 and P2 in pigs kept at 30 °C. At both ambient temperatures, pigs had lower (P < 0.05) postprandial concentrations of Ala, Gly, His, Ile, Leu, Pro, Ser, Thr, Trp, and Val at P1 and P2 than at P0. Arginine postprandial concentration at P1 was lower than at P0 in pigs kept at 24 °C (P < 0.05), whereas no difference was observed in pigs at 30 °C. Relative to P0, Gln and Tyr concentrations were lower at P1 and P2 in pigs kept at 24 °C (P < 0.01), whereas lower Gln concentration was observed only at P2 (P < 0.01) and lower Tyr only at P1 (P < 0.01) in pigs kept at 30 °C. Our study shows a hyperglycemic and hyperinsulinemic state in LPS-challenged pigs and a greater magnitude of this response in pigs kept at 30 °C. Furthermore, LPS caused important changes in BCAA, His, Thr, and Trp profiles, suggesting the role these AA in supporting the inflammatory response. Finally, our results suggest that LPS-induced effects on postprandial profiles of specific AA (Arg, Gln, Phe, and Tyr) may be modulated by ambient temperature. [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]