C. Pomar

Development of sustainable precision farming systems for swine: Estimating real-time individual amino acid requirements in growing-finishing pigs

The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal.

Formulating diets for growing pigs: economic and environmental considerations

We look at the environmental impact of formulating diets for an animal production system, namely the case of growing pigs. The classic approach in animal production is to use a growth model based on the least-cost diet formulation. This optimal diet is generally established by linear programming. Such an approach can lead to adverse environmental effects in the form of nitrogen and phosphorus excretions. Multi-criteria (two and three criteria) models are proposed with the aim of addressing both economic and environmental considerations. We apply the models to two real-life contexts: Québec (Canada) and France, and make some comparisons. We show that important reductions in nitrogen and phosphorus excretions can be achieved at relatively low costs in both contexts.

Feeding behavior of growing-finishing pigs reared under precision feeding strategies

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.

Precision feeding can significantly reduce lysine intake and nitrogen excretion without compromising the performance of growing pigs.

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

Repeatability and reproducibility of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses1

7.60/pig (-10%) relative to group feeding. Precision feeding is an effective approach to make pig production more sustainable without compromising growth performance.

Environmental impacts of precision feeding programs applied in pig production

The precision of a dual-energy X-ray absorptiometry (DXA) device in terms of repeatability and reproducibility was evaluated on nine left half-carcasses from pigs with large variability in body weight and fat content. Repeatability was assessed by scanning each carcass 10 times sequentially in the same position. Reproducibility was assessed by scanning each carcass in 10 different positions. Images were analyzed with DXA software using a custom region of interest (ROI) and the standard head, trunk, arm, and leg ROI. Predicted values from the DEXA for bone mineral content (BMC), bone area, bone mineral density (BMD), total weight, soft-tissue weight, fat-tissue weight, and lean-tissue weight were considered. Repeatability was associated with the variance between measurements on the same carcass in the same position (repeatability conditions). An average variance value was obtained with all the carcasses combined, and the SD was calculated as the square root of this combined variance. The CV was the ratio between the SD of the measurements and its average value. Reproducibility was calculated for each carcass as the difference between the variance obtained under the reproducibility conditions and that obtained under the repeatability conditions. The effects of the ROI and conditions were evaluated by ANOVA and Tukeys test. Means of BMC, bone area, BMD, fat tissue, and lean tissue differed among the ROI (P < 0.05) in both the repeatability and reproducibility conditions. The CV of DXA measurements under repeatability condition obtained in the head, arm, and leg ROI was lesser than 1%. Only the repeatability errors of fat tissue differed (P < 0.05) among the ROI, with the lowest precision found for the trunk ROI. The reproducibility errors of BMC, bone area, fat tissue, and lean tissue differed (P < 0.05) among the ROI. The custom ROI had reproducibility errors greater than 2% for fat tissue and greater than 3.5% for BMC and bone area. In addition, the trunk ROI had the highest reproducibility errors for fat tissue (20.7%) and lean tissue (6.2%) when compared to the other ROI. In conclusion, repeatability and reproducibility results obtained for most of the studied ROI indicate that DXA is a valuable tool for carcass evaluation. From a methodological viewpoint and considering the variations observed in this study, the ROI should be chosen based on the item to be evaluated or on the conditions in which the DXA measurements are to be taken.

Effect of a lysine depletion-repletion protocol on the compensatory growth of growing-finishing pigs

This study was undertaken to evaluate the effect that switching from conventional to precision feeding systems during the growing-finishing phase would have on the potential environmental impact of Brazilian pig production. Standard life-cycle assessment procedures were used, with a cradle-to-farm gate boundary. The inputs and outputs of each interface of the life cycle (production of feed ingredients, processing in the feed industry, transportation and animal rearing) were organized in a model. Grain production was independently characterized in the Central-West and South regions of Brazil, whereas the pigs were raised in the South region. Three feeding programs were applied for growing-finishing pigs: conventional phase feeding by group (CON); precision daily feeding by group (PFG) (whole herd fed the same daily adjusted diet); and precision daily feeding by individual (PFI) (diets adjusted daily to match individual nutrient requirements). Raising pigs (1 t pig BW at farm gate) in South Brazil under the CON feeding program using grain cultivated in the same region led to emissions of 1840 kg of CO2-eq, 13.1 kg of PO4-eq and 32.2 kg of SO2-eq. Simulations using grain from the Central-West region showed a greater climate change impact. Compared with the previous scenario, a 17% increase in climate change impact was found when simulating with soybeans produced in Central-West Brazil, whereas a 28% increase was observed when simulating with corn and soybeans from Central-West Brazil. Compared with the CON feeding program, the PFG and PFI programs reduced the potential environmental impact. Applying the PFG program mitigated the potential climate change impact and eutrophication by up to 4%, and acidification impact by up to 3% compared with the CON program. Making a further adjustment by feeding pigs according to their individual nutrient requirements mitigated the potential climate change impact by up to 6% and the potential eutrophication and acidification impact by up to 5% compared with the CON program. The greatest environmental gains associated with the adoption of precision feeding were observed when the diet combined soybeans from Central-West Brazil with corn produced in Southern Brazil. The results clearly show that precision feeding is an effective approach for improving the environmental sustainability of Brazilian pig production.

A dynamic model of protein digestion in the small intestine of pigs.

The effect of Lys restriction followed by a repletion period on the performance of growing pigs was studied during 3 feeding phases, each lasting 28 d. A total of 47 castrated male pigs (G Performer 8.0 × Fertilis 25 pigs; Genetiporc Inc., Saint-Bernard, QC, Canada; initial BW of 26.7 ± 2.7 kg) were given each d 70% or 100% of their Lys requirements according to 1 of the following 5 sequences: 70-70-70, 70-70-100, 70-100-70, 70-100-100, or 100-100-100 (for each sequence, numbers indicate the Lys supply percentage in phase 1, 2, and 3, respectively). Individual Lys requirements were estimated daily on the basis of each pigs actual BW and feed intake and BW gain patterns obtained by regression using each pigs historical data. At the end of phase 1, the pigs given 100% of their Lys requirements had higher ADFI ( = 0.01), ADG ( < 0.01), and average daily protein deposition ( < 0.01) than did the pigs given 70% of their requirements. Similar results were observed during phases 2 and 3. At the end of phase 2, the pigs in the 70-100 sequence did not display any compensatory response, given that their ADFI, ADG, and average daily protein deposition did not differ from those of the pigs in the 100-100 sequence. Similar results were observed during phase 3. Although no compensatory growth was observed during the growing phases, the fact that the pigs in the 70-100-100 treatment were able to catch up in terms of BW and body protein mass to the pigs in the 100-100-100 sequence could indicate that a small degree of compensation did occur; these research results cannot ascertain that any compensatory growth occurred.