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Ruminants may contribute to global warming through the release of methane gas by enteric fermentation. Until now, methane emissions from ruminants were estimated using simple regression equations. The objective of this study was to compare the capacity of dynamic and mechanistic models to that of regression equations to predict methane production from dairy cows. The updated version of the model of Baldwin et al. and a modified version of the model of Dijkstra et al. and the regression equations of Blaxter and Clapperton and Moe and Tyrrell were challenged with 32 experimental diets selected from 13 publications. The predictive capacity of mechanistic models and regression equations was evaluated by comparing predicted and observed methane production using regression analysis. Results of regression showed better prediction of methane production with mechanistic models than with regression equations. The modified model of Dijkstra et al. predicted methane production with the higher R2 (.71) and the smaller error of prediction (19.87% of the observed mean). The model of Baldwin et al. predicted methane production with a similar R2 (.70) but a higher error of prediction (36.93%). However, a large proportion of this error can be eliminated by a correction factor. Predictions using the equations of Moe and Tyrrell and Blaxter and Clapperton were poor (R2 = .42 and .57; error of prediction = 33.72% and 22.93%, respectively). This study demonstrated that from a large variation in diet composition, mechanistic models allow the prediction of methane production more accurately than simple regression equations.

Considerable progress has been made in the nutritional modelling of growth. Most models typically predict (or analyse) the response of a single animal. However, the response to nutrients of a single, representative animal is likely to be different from the response of the herd. To address the variation in response between animals, a stochastic approach towards nutritional modelling is required. In the present study, an analysis method is presented to describe growth and feed intake curves of individual pigs within a population of 192 pigs. This method was developed to allow end-users of InraPorc (a nutritional model predicting and analysing growth in pigs) to easily characterise their animals based on observed data and then use the model to test different scenarios. First, growth and intake data were curve-fitted to characterise individual pigs in terms of BW (Gompertz function of age) and feed intake (power function of BW) by a set of five parameters, having a biological or technico-economical meaning. This information was then used to create a population of virtual pigs in InraPorc, having the same feed intake and growth characteristics as those observed in the population. After determination of the mean lysine (Lys) requirement curve of the population, simulations were carried out for each virtual pig using different feeding strategies (i.e. 1, 2, 3 or 10 diets) and Lys supply (ranging from 70% to 130% of the mean requirement of the population). Because of the phenotypic variation between pigs and the common feeding strategies that were applied to the population, the Lys requirement of each individual pig was not always met. The percentage of pigs for which the Lys requirement was met increased concomitantly with increasing Lys supply, but decreased with increasing number of diets used. Simulated daily gain increased and feed conversion ratio decreased with increasing Lys supply ( P , 0.001) according to a curvilinear-plateau relationship. Simulated performance was close to maximum when the Lys supply was 110% of the mean population requirement and did not depend on the number of diets used. At this level of Lys supply, the coefficient of variation of simulated daily gain was minimal and close to 10%, which appears to be a phenotypic characteristic of this population. At lower Lys supplies, simulated performance decreased and variability of daily gain increased with an increasing number of diets ( P , 0.001). Knowledge of nutrient requirements becomes more critical when a greater number of diets are used. This study shows the limitations of using a deterministic model to estimate the nutrient requirements of a population of pigs. A stochastic approach can be used provided that relationships between the most relevant model parameters are known.

The impact of moving from conventional to precision feeding systems in growing-finishing pig operations on animal performance, nutrient utilization, and body and carcass composition was studied. Fifteen animals per treatment for a total of 60 pigs of 41.2 (SE = 0.5) kg of BW were used in a performance trial (84 d) with 4 treatments: a 3-phase (3P) feeding program obtained by blending fixed proportions of feeds A (high nutrient density) and B (low nutrient density); a 3-phase commercial (COM) feeding program; and 2 daily-phase feeding programs in which the blended proportions of feeds A and B were adjusted daily to meet the estimated nutritional requirements of the group (multiphase-group feeding, MPG) or of each pig individually (multiphase-individual feeding, MPI). Daily feed intake was recorded each day and pigs were weighed weekly during the trial. Body composition was assessed at the beginning of the trial and every 28 d by dual-energy X-ray densitometry. Nitrogen and phosphorus excretion was estimated as the difference between retention and intake. Organ, carcass, and primal cut measurements were taken after slaughter. The COM feeding program reduced (P < 0.05) ADFI and improved G:F rate in relation to other treatments. The MPG and MPI programs showed values for ADFI, ADG, G:F, final BW, and nitrogen and phosphorus retention that were similar to those obtained for the 3P feeding program. However, compared with the 3P treatment, the MPI feeding program reduced the standardized ileal digestible lysine intake by 27%, the estimated nitrogen excretion by 22%, and the estimated phosphorus excretion by 27% (P < 0.05). Organs, carcass, and primal cut weights did not differ among treatments. Feeding growing-finishing pigs with daily tailored diets using precision feeding techniques is an effective approach to reduce nutrient excretion without compromising pig performance or carcass composition.

This study was developed to assess the impact on performance, nutrient balance, serum parameters and feeding costs resulting from the switching of conventional to precision-feeding programs for growing-finishing pigs. A total of 70 pigs (30.4 ± 2.2 kg BW) were used in a performance trial (84 days). The five treatments used in this experiment were a three-phase group-feeding program (control) obtained with fixed blending proportions of feeds A (high nutrient density) and B (low nutrient density); against four individual daily-phase feeding programs in which the blending proportions of feeds A and B were updated daily to meet 110%, 100%, 90% or 80% of the lysine requirements estimated using a mathematical model. Feed intake was recorded automatically by a computerized device in the feeders, and the pigs were weighed weekly during the project. Body composition traits were estimated by scanning with an ultrasound device and densitometer every 28 days. Nitrogen and phosphorus excretions were calculated by the difference between retention (obtained from densitometer measurements) and intake. Feeding costs were assessed using 2013 ingredient cost data. Feed intake, feed efficiency, back fat thickness, body fat mass and serum contents of total protein and phosphorus were similar among treatments. Feeding pigs in a daily-basis program providing 110%, 100% or 90% of the estimated individual lysine requirements also did not influence BW, body protein mass, weight gain and nitrogen retention in comparison with the animals in the group-feeding program. However, feeding pigs individually with diets tailored to match 100% of nutrient requirements made it possible to reduce ( P < 0.05) digestible lysine intake by 26%, estimated nitrogen excretion by 30% and feeding costs by US$7.60/pig (−10%) relative to group feeding. Precision feeding is an effective approach to make pig production more sustainable without compromising growth performance.Keywords: nutrition, nutrient requirements, precision feeding, protein, swine ImplicationsPresent study investigated the impact of using a mathematical model estimating real-time daily lysine requirements in a sustainable precision-feeding program for growing pigs. Results clearly indicate that this is an effective approach for reducing nutrient intake, nutrient excretion and feeding costs. Feeding pigs individually with daily tailored diets that provide 100% of estimated requirements can reduce lysine intake by 26% and nitrogen excretion by 30% without compromising the pig performance. The proposed precisionfeeding system represents a paradigm shift in pig production, as it takes into account between-animal differences in nutrient requirements within a population and their dynamic evolution over time.

The feeding behavior of growing-finishing pigs reared under precision feeding strategies was studied in 35 barrows and 35 females (average initial BW of 30.4 ± 2.2 kg) over 84 d. Five different feeding programs were evaluated, namely a conventional 3-phase program in which pigs were fed with a constant blend of diet A (high nutrient density) and diet B (low nutrient density) and 4 daily phase-feeding programs in which pigs were fed daily with a blend meeting 110, 100, 90, or 80% of the individual Lys requirements. Electronic feeder systems automatically recorded the visits to the feeder, the time of the meals, and the amount of feed consumed per meal. The trial lasted 84 d and the database contained 59,701 feeder visits. The recorded database was used to calculate the number of meals per day, feeding time per meal (min), intervals between meals (min), feed intake per meal (g), and feed consumption rate (feed intake divided by feeding time per meal, expressed in g/min) of each animal. The feeding pattern was predominantly diurnal (73% of the feeder visits). Number of meals, duration of meals, time between meals, feed consumed per meal, and feed consumption rate were not affected by the feeding programs. The females ingested 19% less feed per meal and had a 6% lower feed consumption rate in comparison with the barrows ( < 0.05). Pig feeding behavior was not correlated with diet composition. However, feed efficiency was negatively correlated with amount of feed consumed per meal ( = -0.38, < 0.05) and feed consumption rate ( = -0.44, < 0.05). Feed consumption rate was also negatively correlated with protein efficiency ( = -0.44, < 0.05). Multivariate analysis indicated that feed consumption rate and number of meals per day are the variables related most closely to pig production performance results. Current results indicate that using precision feeding as an approach to reduce Lys intake does not interfere with the feeding behavior of growing-finishing pigs.

. 2004. Distribution of intramuscular fat content and marbling within the longissimus muscle of pigs. Can. J. Anim. Sci. 84: 57-61. A better knowledge of intramuscular fat (IMF) content distribution would allow the identification of a predictive site on the longissimus muscle to assess the total IMF content. For this purpose, 50 commercial crossbred pigs of both genders were selected live with ultrasound equipment at the 3rd/4th last rib in order to provide backfat differences varying from 10 to 34.7 mm. Left longissimus muscles were deboned and sliced every 2 cm from the posterior (3rd last lumbar vertebra) to the anterior (5th thoracic rib) end. In all, 14 locations on the longissimus muscle were established and labeled as T5-T14 (thoracic region) and L1-L4 (lumbar region). The slices were used for subjective marbling evaluation and for intramuscular fat content (IMF) measurement. The results showed that total IMF content and marbling scores were correlated (r = 0.86) and followed a similar pattern, with highest values being obtained in the middle section of the thoracic region and in the middle-caudal section of the lumbar area. In addition, both IMF content and marbling scores were anatomical location dependant. Gender did not affect IMF content, but influenced marbling score, castrates being more marbled (score: 2.77 vs. 2.35) than females. The IMF content (R 2 : 0.94-0.95) and marbling score (R 2 : 0.73-0.81) were the best predictors of mean IMF when measured at or near the grading site (3rd/4th last rib).Key words: Pork, intramuscular fat, marbling score, longissimus muscle, within muscle variation Faucitano, L., Rivest, J., Daigle, J. P., Lévesque, J. et Gariepy, C. 2004. Variation de la teneur en gras intramusculaire et du persillage dans le muscle longissimus dorsi de porc. Can. J. Anim. Sci. 84: 57-61. Une meilleure connaissance de la distribution du gras intramusculaire permettrait de déterminer une zone précise sur le muscle longissimus à partir de laquelle on pourrait évaluer la teneur totale en gras intramusculaire. Pour vérifier cette hypothèse, nous avons choisi 50 porcs commerciaux croisés, des deux sexes, avant l'abattage dont nous avons mesuré l'épaisseur de gras dorsal au niveau de la 3 e /4 e côte à l'aide d'un appareil à ultrasons. Les animaux retenus présentaient des différences d'épaisseur de gras dorsal variant de 10 à 34.7 mm. Après l'abattage, le muscle longissimus du côté gauche des carcasses a été désossé et coupé en tranches de 2 cm, à partir de l'extrémité postérieure (3 e dernière vertèbre lombaire) jusqu'à l'extrémité antérieure (5 e côte thoracique). En tout, 14 zones du longissimus ont été déterminées et numérotées comme suit : T5 à T14 (région thoracique) et L1 à L4 (région lombaire). Nous avons utilisé les tranches pour évaluer le persillage et mesurer la teneur en gras intramusculaire. Les résultats ont révélé une correspondance entre la teneur totale en gras intramusculaire et la cote de persillage (r = 0,86). Nous avons également constaté que ces paramètres suivent des pr...

A dynamic mathematical model of the digestion of proteins in the small intestine of pigs was developed. The model integrates current knowledge on the transit of digesta along the small intestine, endogenous secretions, digestion of proteins, and absorption of amino acids into a mechanistic representation of digestion. The main characteristics of the model are the following: the small intestine is divided into several segments of variable length but with equal digesta retention time; the rate of transfer of digesta between segments is based on the progression of myoelectric migration complexes; pancreatic and biliary secretions are poured into the first segment, whereas intestinal secretions enter all intestinal segments; protein hydrolysis is described by first-order equations; and an intestinal absorption capacity is used to estimate absorption of hydrolyzed protein. Simulation results are consistent with observed data, although more information is needed to represent reality more closely. The sensitivity analysis shows that parameters for protein hydrolysis largely determine protein digestibility. The absorption capacity of the small intestine limits the absorption of amino acids at the beginning of a meal and modulates the appearance of amino nitrogen in the portal vein. It also shows that amino acid absorption can be limiting to protein digestibility when large amounts of protein are eaten in a single daily meal. The model is useful in evaluating the dynamics of protein digestion and absorption of feedstuffs. The model can be used in evaluating protein digestion of different feedstuffs and feeding strategies.