A review of neonatal mortality in outdoor organic production and possibilities to increase piglet survival

Impacts of Farrowing Pen Design, Season, and Sow Parity on Litter Performance and Piglet Mortality

Piglet mortality during lactation is a significant concern in swine production, influenced by complex interactions involving sow, piglet, environmental, and management factors. While crushing by the sow may be the ultimate cause of piglet mortality, there are many factors influencing the outcome, including parity, thermal stress, and animal housing systems. New farrowing systems are continuously being developed; however, it is difficult for producers to make decisions without any scientific basis. This study aimed to assess the impact of different farrowing pen layouts on piglet performance, considering parity and season. A total of 546 sows and 9123 piglets were monitored across 36 lactation cycles. Sows were randomly assigned to three farrowing pen layouts (standard, diagonal, and offset) in three rooms (20 sows by room). All farrowing pens had the same space allocations (2.7 m by 1.8 m and 2.1 m by 0.6 m for the sow area). The three types of farrowing pens were blocked by position within the room. Piglet performance traits (percent of stillborns, percent of mortality, percent of overlays, and average daily weight gain: ADG) and sows traits (health and parity) were monitored following US Meat Animal Research Center (USMARC) procedures. Results indicated that treatment, parity, and season influenced some piglet performance traits. The offset farrowing pen had a lower percent of stillborns compared to the standard. No significant differences were observed between the diagonal crate and the other treatments. When evaluating high mortality sow (>two piglets), the offset and standard treatments had a lower percent of overlays. Piglets from first-parity sows had lower ADG than those from higher-parity sows. A higher percent of overlays were observed in Autumn and Summer compared to Spring and Winter, and Summer had lower average daily weight gain than other seasons. The results suggest that modifying the layout (offset), with sows placed further away from the heating source, can reduce the percent of overlays in sows with high mortality (>2 piglets). In addition, the influence of season on the piglet production traits demonstrated the importance of proper management of the environment, even in systems with a certain level of climatic control.

Genetic polymorphisms in ESR and FSHβ genes and their association with litter traits in Large White pigs

The estrogen receptor (ESR) gene and follicle-stimulating hormone β (FSHβ) gene are responsible for litter traits. The present study aimed to verify the polymorphisms of ESR and FSHβ and assess their effects on the litter traits in 201 Large White pigs. Four SNPs (g.C669T, g.A1296G, g.C1665T and g.A1755G) were found in ESR. The TT genotype at g.C1665T locus and AA genotype at g.A1755G locus could significantly increase the total litter size of the first litter of American Large White pigs (p < 0.05). Eight SNPs were found in exon 3 of FSHβ. The AA genotype at g.A511G locus, AA and AG genotypes at g.A617G locus, CC and CT genotypes at g.C630T locus, CT and TT genotypes at g.C652T locus, CT and TT genotypes at g.C735T locus, AA and AG genotypes at g.A746G, AA and AG genotypes at g.A921G and CT genotype at g.C678T could significantly increase the litter size of different strains of Large White pigs (p < 0.05). Our study revealed that the genetic variations of ESR and FSHβ were closely related to the litter trait of Large White pigs. Therefore, ESR and FSHβ genes could be used as molecular markers for the genetic selection of Large White pigs.

Statistical and machine learning approaches to describe factors affecting preweaning mortality of piglets

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the U.S. Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, litter, environment, and piglet parameters on PWM. Then, different models (beta-regression and machine learning model: a random forest [RF]) were evaluated. Finally, the RF model was used to predict PWM and overlays for all listed contributing factors. On average, the mean birth weight was 1.44 kg, and the mean mortality was 16.1% where 5.55% was for stillbirths and 6.20% was contributed by overlays. No significant effect was found for seasonal and location variations on PWM. Significant differences were observed in the effects of litter lines on PWM (P < 0.05). Landrace-sired litters had a PWM of 16.26% (±0.13), whereas Yorkshire-sired litters had 15.91% (±0.13). PWM increased with higher parity orders (P < 0.05) due to larger litter sizes. The RF model provided the best fit for PWM prediction with a root mean squared errors of 2.28 and a correlation coefficient (r) of 0.89 between observed and predicted values. Features' importance from the RF model indicated that, PWM increased with the increase of litter size (mean decrease accuracy (MDA) = 93.17), decrease in mean birth weight (MDA = 22.72), increase in health diagnosis (MDA = 15.34), longer gestation length (MDA = 11.77), and at older parity (MDA = 10.86). However, in this study, the location of the farrowing crate, seasonal differences, and litter line turned out to be the least important predictors for PWM. For overlays, parity order was the highest importance predictor (MDA = 7.68) followed by litter size and mean birth weight. Considering the challenges to reducing the PWM in the larger litters produced in modern swine industry and the limited studies exploring multiple major contributing factors, this study provides valuable insights for breeding and production management, as well as further investigations on postural transitions and behavior analysis of sows during the lactation period.

Animal Health and Productivity of Organic Greek Pig Farms: The Current Situation and Prospects for Sustainability

A review of organic pig production in Greece was carried out. The aim was to present updated information on the production, development and health status of organic pig farming in Greece and potential prospects for sustainability and future development. The indigenous Greek Black Pig is the main breed reared in Greek organic pig farms. All the reasons why Greek Black Pig breeding is ideal for organic farming are mentioned. Furthermore, respiratory and parasitic infections are the most common health problems, while high piglet mortality rates are the main welfare issue in Greek organic pig farming. Concerns about how farmers and authorities should utilize the demands of modern consumers are discussed.

Relative Impact of Birth Weight and Early Growth on Neonatal Mortality in Puppies

Puppy survival during their first weeks of life can be improved, and early detection of puppies with increased mortality risk is one of the keys to success. In the canine species, the few studies on this subject focused on birth weight, which reflects intrauterine growth. The present work aimed to explore the interconnections between birth weight, early growth and survival until two months of life in the canine species. In total, data from 8550 puppies born in 127 French breeding kennels were analysed. Five different growth rates were calculated to reflect the growth of puppies during their first week of life. Low-birth-weight puppies had lower growth than normal-birth-weight puppies over the first two days of life but higher growth rates thereafter. Growth-rate thresholds allowing the identification of puppies at higher risk of mortality during their first two months of life were lower for low-birth-weight puppies. These thresholds will help breeders and veterinarians to identify puppies at risk with particular needs for monitoring and nursing to improve their chances of survival.

Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs

Knowledge remains limited on genetic variation and genetic correlations for traits in sows and piglets that are reared in an organic or outdoor setting. Here, we estimated genetic variance components for individual piglet weight, litter weight, litter size traits, and number of functional teats in a pig population raised under outdoor organic conditions. Data were collected from the largest organic multiplier farm in Denmark. Individual piglet weight was recorded at birth and on day 10. Number of live and dead piglets were recorded at birth, day 4, and day 11. Mean and total litter weight were calculated based on the individual weight of living piglets at birth and on day 10. The estimated heritability was highest for the number of functional teats (0.49), mean weight of a litter at birth (0.33) and on day 10 (0.25). In contrast, heritability was lowest for litter size traits (0.04-0.08) and piglet weight (0.06-0.07). Maternal heritability was much higher for individual piglet weight than direct heritability. The results showed that selection for higher mean weight results in smaller litters. Also, selection for individual birth weight of piglets results in heavier piglets at 10 days. In conclusion, this study confirmed that there is genetic variation in individual piglet weight, litter traits, and number of functional teats in organically and outdoor-reared pigs.

Changes in piglet and litter characteristics across parities in two highly prolific sow hybrids in an outdoor organic herd

High piglet mortality constitutes a welfare challenge in organic pig production. Litter characteristics were investigated from parities 1-5 of two hyper-prolific hybrids with different selection traits in an organic commercial herd (DanBred vs. Topigs Norsvin [TN70]). TN70 sows had more functional teats than DanBred sows, and their offspring had higher birth weights. Several interactions between hybrid and parity were found. The total born increased with higher parity and was more pronounced for DanBred sows. Litter weight at weaning was higher in parities 1-4 for TN70 compared with DanBred, and within DanBred parities 4 and 5 had higher litter weight at weaning than parity 1. The survival rate was higher for TN70 in parities 1 and 2 compared with DanBred, and for both hybrids, the survival rate was higher in parities 1 and 2 compared with parities 4 and 5. The number of weaned piglets was stable across parities 1-4 but lower in parity 5 for both hybrids. Thus, despite a lower number of total born piglets in TN70, TN70 sows weaned the same number of piglets as DanBred, with a lower mortality rate and a heavier litter at weaning.

Improving young pig welfare on-farm: The Five Domains Model

Considering welfare through the "neonatal and nursery pig perspective" is an exciting approach, and one that resonates with consumers. Overlaying this with the Five Domains Model, as we suggest in this review, points to practical on-farm improvements that provide each pig the opportunity to experience positive mental states. The Five Domains Model is broken into physical and functional states, that includes Domain 1 Nutrition, Domain 2 Physical Environment, Domain 3 Health and, Domain 4 Behavioral Interaction, and Domain 5 Mental State. The Five Domains Model can build on the breadth and depth of swine welfare science to highlight opportunities to improve welfare on-farm. In Domain 1 management of increasingly large litters is considered, with examples of sow vs. artificial rearing, colostrum quality and quantity, and creep feed management strategies. Efforts can result in positive mental states such as feeling full and content and the ability to experience pleasure of drinking and food tastes/smells. Domain 2 considers space complexity and access to key resources, along with thermal and physical amenities, to promote feelings of physical comfort. Domain 3 considers pig health in three broad, yet inter-linking categories, (a) congenital and hereditary health, (b) environmental pathogen load and, (c) colostrum quality and quantity, and its effect on the microbiome. Improvements can result in a pig that displays vitality and feels healthy. Domain 4 provides the pig opportunities to express its rich behavioral repertoire, specifically positive social interactions, play, and exploration. These efforts can result in pigs feeling calm, safe, comfortable, having companionship, engaged, interested and rewarded. In conclusion, using the Five Domains Model can highlight numerous opportunities to improve current and future housing and management through the "neonatal and nursery pig perspective" with a focus on inducing positive mental states that can result in improved quality of life and welfare state.

Genetic variation in piglet mortality in outdoor organic production systems

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0-3 days of age, 4-11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0-3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0-11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.

The Effect of Using Organic or Conventional Sires on Genetic Gain in Organic Pigs: A Simulation Study

Simple Summary

Breeding programs are used for the selection and breeding of animals that maximize a breeding objective in a specific production environment. Currently, breeders use pigs from conventional populations to breed organic pigs. This could be problematic, because pigs that perform best in an indoor and controlled conventional environment may not perform as well in the outdoor and less-controlled organic environment. To test this theory, we simulated different breeding programs for organic pigs. We used our knowledge on the genetics of the Danish pig population to make the simulations as realistic as possible. The first simulated breeding program used conventional boars to breed organic pigs. The second simulated breeding program used only organic pigs to breed for organic pigs. The results of the current study illustrate the importance of using pigs from an organic breeding population to breed organic pigs. If conventional pigs are used instead, the organic pigs will be adapted to suit a conventional production system.

Abstract

Current organic pig-breeding programs use pigs from conventional breeding populations. However, there are considerable differences between conventional and organic production systems. This simulation study aims to evaluate how the organic pig sector could benefit from having an independent breeding program. Two organic pig-breeding programs were simulated: one used sires from a conventional breeding population (conventional sires), and the other used sires from an organic breeding population (organic sires). For maintaining the breeding population, the conventional population used a conventional breeding goal, whereas the organic population used an organic breeding goal. Four breeding goals were simulated: one conventional breeding goal, and three organic breeding goals. When conventional sires were used, genetic gain in the organic population followed the conventional breeding goal, even when an organic breeding goal was used to select conventional sires. When organic sires were used, genetic gain followed the organic breeding goal. From an economic point of view, using conventional sires for breeding organic pigs is best, but only if there are no genotype-by-environment interactions. However, these results show that from a biological standpoint, using conventional sires biologically adapts organic pigs for a conventional production system.

Selection for litter size and litter birthweight in Large White pigs: Maximum, mean and variability of reproduction traits

Gradually increasing trend of litter size poses a challenge to pig farmers in terms of managing larger litters. Therefore, it seems that a balanced approach that optimises litter size, litter birthweight, and uniformity of those traits is needed in order to address animal welfare and farm management concerns. This study aimed to investigate this issue by defining several traits for total number born (TNB), number born alive (NBA) and litter birthweight (LW). First, the highest value from at least five records per sow was selected as maximum (max) value for each reproduction trait. Second, a mean (mean) for each reproduction trait was calculated per sow. Last, the variability of reproduction traits between parities of the sow was calculated as log-transformed variance of residuals of all observations per sow for each reproduction trait (LnVar). In total, 23 193 Large White sows from Topigs Norsvin with 152 282 litter records were used for analysis in ASReml 4.1. Also, a simulation of breeding schemes was performed with the use of SelAction 2.1 and estimates from genetic analysis. Maximum value of reproductive traits had a much higher heritability than repeated observations or mean of reproduction traits, e.g., 0.31 for maxTNB vs. 0.12 for TNB and 0.07 for meanTNB, which allows for a faster response under selection. The maximum value traits, however, were found to carry more risks, i.e. higher ratio of stillborn (not for maxNBA) and increased variability of traits. Thus, using them in breeding programme should be carefully considered. The genetic coefficient of variation on SD level estimated to indicate the genetic magnitude for variability phenotypes indicated a maximum change of 6-9% in genetic SD of TNB, NBA and LW. The genetic correlations between mean and corresponding variability traits varied from 0.66 to 0.74, whereas the correlation between other mean and variability traits ranged from 0.33 to 0.99. The simulation indicated that even with selection targeted against the variability of reproduction traits, a very limited change should be expected due to a complex genetic and phenotypic relationship between the traits. In the scenarios with selection against LnVarTNB and LnVarLW, this was a decrease of 0.1-0.6% per year, whereas in scenario with selection against LnVarNBA, the range was 0.6-1.1% per year. It is still possible to increase litter size and birthweight further, however, a balance between mean and variability of reproduction traits is required, which can be obtained only by a very well designed breeding programme.