Management strategies to improve the performance of low birth weight pigs to weaning and their long-term consequences

Identifying factors contributing to slow growth in pigs

Pigs that grow slower than their contemporaries can cause complications for animal welfare and profitability. This study was conducted to investigate factors that may contribute to slow growth of pigs. Pigs ( = 440) farrowed by 65 sows were monitored from birth to market. Pigs were categorized as slow, average, and fast growers based on market weight adjusted to 170 d of age (slow growers were <105 kg, average growers were between 105 and 125 kg, and fast growers were >125 kg). Blood samples were collected from 48 focal pigs at 9 and 21 wk of age and analyzed for hormone and free AA concentrations. Data were analyzed using the Mixed and Logistic procedures of SAS. Slow-growing pigs accounted for 10% of pigs marketed, average growers accounted for 49% of pigs marketed, and fast growers accounted for 41% of pigs marketed. Compared with fast growers, slow growers were lighter at birth ( < 0.01), at weaning ( < 0.01), and at nursery exit ( < 0.01) and had less backfat ( < 0.01) and smaller loin muscle area ( < 0.01) at marketing at 21 wk of age. Slow growers had lower plasma concentrations of IGF-1 ( = 0.03) and insulin ( < 0.001) during the nursery period and lower concentrations of leptin ( < 0.001) and insulin ( < 0.001) during the finishing period compared with average and fast growers. Serum concentrations of several essential, nonessential, and total free AA were less for slow growers during both the nursery and finishing periods compared with average and fast growers. Gilts were more likely to become slow growers than barrows (odds ratio = 2.17, 95% confidence interval = 1.19 to 3.96, = 0.01). Litter size and parity of the pigs' dam were not associated with slow growth. These results suggest that low concentrations of IGF-1, insulin, leptin, and AA may contribute to or be associated with slow growth in pigs.

Are all piglets born lightweight alike? Morphological measurements as predictors of postnatal performance

Birth weight (BiW) of pigs is a commonly used predictor of postnatal performance; however, it has been suggested that morphological measurements may be more reflective of the intrauterine environment and thus better predictors of postnatal growth. The aim of this study was to determine 1) whether morphological measurements, including ponderal index (PI), body mass index (BMI), and abdominal circumference (AC), could be used as predictors of postnatal performance and 2) if so, would they be better predictors than BiW and 3) would the same predictors apply to pigs of different BiW at different stages of their growth? Morphological measurements, BiW, and BW at d 28 and 70 were available for 731 pigs from experiments conducted over a 2-yr period. A series of linear models was used to determine predictors that affected growth performance from birth to d 28 and from d 28 to 70. For both light (LBiW; ≤1.25 kg) and normal BiW pigs (NBiW; 1.60 to 2.00 kg), BiW was not the best predictor of performance ( > 0.05); different variables for the growth periods considered applied to pigs with different BiW. For LBiW pigs BMI ( < 0.001) and AC ( = 0.0202) were the best predictors for d 1 to 28, and AC ( = 0.0317) and PI ( = 0.0450) were the best predictors from d 28 to 70, with pigs with a larger AC and higher PI/BMI more likely to have higher ADG pre- or postweaning. In contrast, the best predictor variables for NBiW pigs were AC ( = 0.0482) for d 1 to 28 and crown-rump length (CRL; = 0.0138) for d 28 to 70. Focusing on LBiW pigs with low ADG, BMI was the best predictor ( < 0.05) of growth for pre and postweaning, whereas for LBiW pigs with high ADG the best predictors were AC ( = 0.00132) from d 1 to 28 and BiW ( = 0.00601) from d 28 to 70, with increasing BMI, AC, and BiW associated with greater ADG. For NBiW pigs with high preweaning ADG, the best predictor consisted solely of AC ( 0.0210), but no morphological predictor variables were significant for NBiW pigs with low preweaning ADG. For d 28 to 70, the best predictor for NBiW pigs with low ADG was CRL ( = 0.0171), but for high ADG no predictor variables were significant. The present study showed that the morphology of piglets is more important than BiW when predicting the postnatal growth of pigs; however, which measurement is the most important depends on both the BiW and stage of growth. For small-sized pigs, these morphological measures may be considered as a decision-making tool by farmers when trying to identify potential poor performers.

Factors for improving reproductive performance of sows and herd productivity in commercial breeding herds

We review critical factors associated with reproductive performance of female breeding pigs, their lifetime performance and herd productivity in commercial herds. The factors include both sow-level and herd-level factors. High risk sow-level groups for decreasing reproductive performance of female pigs are low or high parity, increased outdoor temperature, decreased lactation feed intake, single inseminations, increased lactation length, prolonged weaning-to-first-mating interval, low birth weight or low preweaning growth rate, a few pigs born alive at parity 1, an increased number of stillborn piglets, foster-in or nurse sow practices and low or high age at first-mating. Also, returned female pigs are at risk having a recurrence of returning to estrus, and female pigs around farrowing are more at risk of dying. Herd-level risk groups include female pigs being fed in low efficiency breeding herds, late insemination timing, high within-herd variability in pig flow, limited numbers of farrowing spaces and fluctuating age structure. To maximize the reproductive potential of female pigs, producers are recommended to closely monitor females in these high-risk groups and improve herd management. Additionally, herd management and performance measurements in high-performing herds should be targeted.

Reducing variation in pork production systems through maternal and pre- and post-weaning nutrition strategies

Variation is inherent in any biological system and is a challenge to manage in modern pork-production businesses. In the case of the growing and finishing herd, inherent variation within a population of pigs represents a significant cost as a result of the need to select on farm to meet market specifications, poor matching of diet specifications to nutrient requirements, grading losses, higher pre-weaning mortality, and challenges associated with health management. As a consequence, any management practice that can be applied to reduce variation at the point of sale has the potential to improve the profitability and overall efficiency of a pig enterprise. The present paper considers nutritional interventions of sows during gestation, lactation and the weaning to oestrus interval to minimise inherent variation in the progeny and then pre- and post-weaning nutrition of piglets to limit further variation. Prior to birth, there are many factors that can influence variation in the birthweight and growth potential of the progeny. In gestating sows, dietary energy will not influence variation in birthweight, but supplementation with free arginine and glutamine will reduce variation in birthweight of piglets born and piglets born alive. In lactating sows, maintenance of feed intake to optimise milk production and minimise weight loss of the sow during lactation not only minimises variation in progeny weight at weaning, but enhances subsequent birthweight heterogeneity due to the influence of the sow’s metabolic status on follicle and oocyte quality. Supplementation with dextrose during the weaning to oestrus interval can also reduce variation in birthweight due to a pronounced effect on plasma glucose and insulin concentrations. Prior to weaning, light weight piglets appear to have an enhanced capacity for growth compared with their larger counterparts. To this end, split suckling has been shown to reduce weaning-weight variation, despite no effect on average growth rate or weaning weight for litters with nine piglets or more born alive. Supplemental milk before weaning has reduced variation in weaning weights, but creep feeding has proved equivocal in this regard. Post-weaning, it appears that remedial feeding strategies will do little to improve the growth potential of light-weight pigs, and while high specification diets may contribute to a slight reduction in variation at slaughter, this strategy is unlikely to be economically viable. As with many aspects of commercial pork production, it would seem that the greatest potential to reduce variation in the slaughter weight of market pigs vests with careful management of gestating and lactating sows, with some potential for dietary interventions to further reduce variation in birth and weaning weights.

The consequences of introducing stochasticity in nutrient utilisation models: the case of phosphorus utilisation by pigs

Simulation models of nutrient utilisation ignore that variation in pig system components can influence the predicted mean and variance of the performance of a group of pigs. The objective of this study was to develop a methodology to investigate how variation in feed composition would (a) affect the outputs of a nutrient utilisation model and (b) interact with variation that arises from the traits of individual pigs. We used a P intake and utilisation model to address these characteristics. Introduction of stochasticity gave rise to a number of methodological challenges--for example, how to generate variation in both feed composition and pigs and account for correlations between ingredients when modelling variation associated with feed mixing efficiency. Introducing variation in feed composition and pig phenotype resulted in moderate decreases in mean digested, retained and excreted P predicted for a population of pigs and an increase in their associated CV. A lower percentage of pigs in the population were predicted to meet their requirements during the feeding period considered, by comparison with the no-variation scenario. Variation in feed ingredient composition contributed more to performance variation than variation due to mixing efficiency. When variations in both feed composition and pig traits were considered, it was the former rather than the latter that had the dominant influence on variability in pig performance. The developed framework emphasises the consequences of random variability on the predictions of nutrient utilisation models. Such consequences will have a significant impact on decisions about management strategies such as feeding that are subject to variation.

High specification starter diets improve the performance of low birth weight pigs to 10 weeks of age

Piglets born with low birth weights (LBiW) are likely to be lighter at weaning. Starter regimes tailored for pigs of average BW therefore may not be optimal for LBiW nursery performance. The objective was to determine if LBiW pigs benefit from a high specification starter regime and the provision of extra feed (additional allowance of last phase diet of the starter regime) in comparison to a standard commercial regime. Additionally, the effect of starter regime on performance of normal birth weight (NBiW) pigs at weaning was determined and compared to that of LBiW pigs. Finally, the cost effectiveness of the treatments was determined. The experiment was therefore an incomplete 2 × 2 × 2 factorial design, as the provision of extra feed was given only to LBiW pigs (n = 6 replicates per treatment; 5 pigs per replicate). Treatments comprised birth weight (LBiW or NBiW), starter regime (high specification [HS] or standard starter [SS]), and extra feed 3 quantity (yes [YF] or no [NF], for LBiW pigs only; feed 3 corresponded to the last phase diet of the starter regime). At weaning (d 28), pigs were randomly assigned within each birth weight category to treatment groups. Nutritional treatments were fed ad libitum on a kilogram/head basis for approximately 3 wk followed by a common weaner diet fed ad libitum until d 70. Starter regime (P = 0.019), feed 3 amount (P = 0.010), and their interaction (P = 0.029) had an effect on ADG of LBiW pigs from d 28 to 49, with pigs on HS followed by YF (HY) performing best. An improvement in feed conversion ratio (FCR) was noted between d 28 and 49 for pigs fed the additional feed 3 (P = 0.030); between d 49 and 70, the only residual effect seen was of starter regime (P = 0.017) on ADG. In contrast, there was no significant effect of starter regime from d 28 to 70 on ADG, ADFI, or FCR of NBiW pigs. By d 49 and 70, LBiW pigs on regime HY weighed the same as NBiW pigs (d 70 BW; 30.0 vs. 30.6 kg; P = 0.413), with similar growth rates from d 28 to 70 (0.570 vs. 0.533 kg/d; P = 0.137). Despite highest feed cost for regime HY at US$12.30 per pig, its margin over feed was greatest ($23.40). Conversely, regime SS gave the best margin over feed for NBiW pigs at $22.70 per pig. In conclusion, a postweaning feeding regime formulated for LBiW pigs improved the ADG and FCR to the end of the nursery phase enabling them to achieve the same weight as NBiW. Targeting the provision of the high quality expensive regime only to light pigs will ensure maximum growth and increased profitability.