Farm data analysis for lifetime performance components of sows and their predictors in breeding herds

Maternal supplementation of Lonicera flos and Scutellaria Baicalensis mixed extracts improve reproduction performance and metabolic health through modulating gut microbiota during pregnancy

BACKGROUND

This study aimed to evaluate the impacts of dietary supplementation with a combination of plant extracts on performance, metabolic health, and gut microbiota of sows. A total of 1003 crossbred pregnancy sows (DanBred Landrace × DanBred Yorkshire, mean parity 4.44 ± 1.84) were assigned to one of the two dietary treatments: a control group (CON, basal diet) and a Lonicera flos and Scutellaria baicalensis mixed extracts group (LSE, basal diet supplemented with 0.5 g/kg of mixed extracts).

RESULTS

Supplementation of LSE increased (P < 0.05) the numbers of total born, litter weight and average piglet weight on L21 d, average daily feed intake, and survival rate of piglets during lactation. Compared to CON, LSE group reduced (P < 0.05) interleukin-6 (IL-6) concentration in the feces and plasma on G109 d, while increased (P < 0.05) interleukin-10 (IL-10) concentration on G109 d and on L3 d. Supplementation of LSE had lower (P < 0.05) plasma reactive oxygen species levels on G30 d and on L3 d, and had a reducing tendency (P = 0.07) for thiobarbituric acid reactive substances concentrations and a trend toward increased (P = 0.08) value of homeostatic model assessment of insulin sensitivity of sow plasma on G109 d. In addition, supplementation of LSE increased (P < 0.05) the abundance of Firmicutes and Proteobacteria and decreased (P < 0.05) the abundance of Bacteroidetes and Spirochaetes on G109 d. The abundance of Christensenellaceae_R_7_group, UCG_002, Clostridium_sensu_stricto_1, Escherichia_Shigella, un_f__Christensenellaceae, Bacteroides, and Terrisporobacter were significantly increased (P < 0.05) in the LSE diet group. The abundance of Christensenellaceae_R_7_group, UCG_002 and un_f__Ruminococcaceae were positively correlated with plasma IL-10 (P < 0.01), and negatively correlated with plasma IL-6 and TBARS levels.

CONCLUSIONS

This study demonstrates that dietary supplementation with Lonicera flos and Scutellaria baicalensis mixed extracts (LSE) at 0.5 g/kg during gestation significantly improves reproductive performance and metabolic health in sows, likely through modulating gut microbiota composition.The observed improvements in performance and health parameters coincide with microbiota-driven inflammation attenuation and redox balance restoration, suggesting a gut-immune axis regulatory role of LSE.

Reproductive Failure in Smallholder Pig Farms in East and Southeast Asia: A Systematic Review

Reproductive failure has significant socioeconomic impacts on smallholder pig farms. This systematic review was conducted to compile the types of reproductive failures and their underlying causes reported in smallholder pig farms from East and Southeast Asia and to identify relevant knowledge gaps. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 26 peer-reviewed studies met the eligibility criteria and were included in our synthesis. These studies were conducted in 11 countries, with Vietnam, China, and Thailand representing the highest share (53.8%). Only six studies (23%) investigated reproductive failure as their primary objective. Stillbirth, mummification, late-term abortion, and weak-born piglets were the predominant reproductive failures reported from smallholder pig farms across the region. The most frequently cited viral pathogens associated with these failures were porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV-2). Common non-infectious risk factors included extreme climate conditions (e.g., heat stress), poor diet and housing, and suboptimal boar management. Our synthesis highlighted a dearth of research focused on reproductive failure in smallholder pig farms in the region and emphasised the need for more targeted studies to clarify the biological, environmental, and managerial risk factors contributing to reproductive failure. This will facilitate the development of targeted prevention and control measures that account for the unique farming conditions and challenges smallholder farms face in East and Southeast Asia.

Dietary Short-Chain Fatty Acids Supplementation Improves Reproductive Performance and Gut Microbiota in Gilts

BACKGROUND

Short-chain fatty acids (SCFAs) have emerged as critical modulators of female reproductive function and host gut microbiota.

OBJECTIVES

This study aimed to investigate the impact of dietary SCFAs supplementation on reproductive performance and gut microbiota in gilts, and to elucidate the underlying mechanisms.

METHODS

Eighty gilts (95 d old) were randomly assigned to either a control group (Ctrl, 40 gilts) receiving a basal diet, or a SCFAs treatment group (SCFAs, 40 gilts) receiving a basal diet supplemented with 0.13% sodium acetate, 0.11% sodium propionate, and 0.09% sodium butyrate. At third estrus, 13 gilts (6 from Ctrl and 7 from SCFAs) were killed for follicular development and gut microbiota analysis, whereas the remaining gilts completed gestation for reproductive performance assessment.

RESULTS

SCFAs group had higher total number born (11.97 compared with 9.44) and total number born alive (11.28 compared with 9.34) compared with Ctrl group (P < 0.05). SCFAs group had increased counts of secondary follicles (36.14 compared with 26.83), antral follicles (10.29 compared with 6.67), and corpus luteum (25.09 compared with 19.33), alongside had reduced atretic follicles (15.32 compared with 20.67) compared with Ctrl group (P < 0.05). Proteomic analysis revealed that SCFAs-induced differentially expressed proteins (DEPs) were significantly enriched in the follicular development-related pathways (P < 0.05). Apoptosis-related DEPs positively correlated with follicular development indices (P < 0.05), consistent with the reduced apoptosis observed in ovarian granulosa cells of the SCFAs group. Additionally, SCFAs supplementation improved both the composition and alpha-diversity (P < 0.05) of gilts' gut microbiota. Furthermore, both the SCFAs-enriched bacteria and plasma SCFAs concentrations showed positive associations with gilts' follicular development indices (P < 0.05).

CONCLUSIONS

Dietary SCFAs supplementation enhances reproductive performance in gilts by promoting ovarian follicular maturation and optimizing gut microbiota composition.

The Role of Nutrition Across Production Stages to Improve Sow Longevity

Modern hyperprolific sows are increasingly susceptible to health challenges. Their rapid growth rates predispose them to locomotor disorders, while high metabolic demands, reduced backfat thickness, and increased protein accretion heighten their vulnerability to heat stress and dystocia. Additionally, prolonged farrowing negatively affects the oxidative and inflammatory status of these females. Additionally, prevalent conditions such as gastric ulcers and cystitis raise ethical, welfare, and economic concerns. Despite the several studies related to sow nutrition, there are no studies which compile and extrapolate nutrition approaches from the rearing period and their impact on sows' health and longevity. Also, the aim of our review was to shed light on gaps that require further investigation. Controlling body condition scores is crucial for maximizing productivity in sows. During gestation, high-fiber diets help maintain optimal body condition and prevent constipation, particularly during the peripartum period. Antioxidants offer a range of beneficial effects during this critical phase. Additionally, probiotics and acidifiers can enhance gut health and lower the risk of genitourinary infections. On the day of farrowing, energy supplementation emerges as a promising strategy to reduce farrowing duration. Collectively, these strategies address major health challenges, enhancing welfare and promoting sow's longevity.

Evolution of Sow Productivity and Evaluation Parameters: Spanish Farms as a Benchmark

This study examines the global evolution of sow productivity, with a particular focus on Spain. The analysis is based on key performance metrics such as piglets weaned per sow per year (PWSY), prolificacy, and pre-weaning mortality, utilizing data from literature reviews, the InterPIG, and BDporc® databases. Globally, significant advancements in genetic selection and management practices have led to productivity increases across major pig-producing countries, with notable improvements in prolificacy. However, higher prolificacy has been accompanied by rising piglet mortality rates during lactation, posing sustainability challenges. In Spain, the average productivity of commercial sows increased from 23.78 PWSY in 2009 to 29.45 PWSY in 2023, while Iberian sows reached an average of 17.44 PWSY. Despite these gains, Spain's figures remain slightly below the European Union average. The study highlights the need for new benchmarks, such as non-productive days, piglet survival, and sow longevity, to more accurately assess farm efficiency. These indicators, combined with considerations for animal welfare and environmental sustainability, are crucial for addressing current challenges such as piglet mortality, sow culling, and the carbon footprint. The findings emphasize the importance of adopting comprehensive management strategies that balance productivity with growing social and environmental demands on the swine industry.

Risk factors associated with piglet pre-weaning mortality in a Midwestern U.S. swine production system from 2020 to 2022

Piglet pre-weaning mortality (PWM) is a significant issue in the U.S. swine industry, causing economic losses and raising sustainability and animal welfare concerns. This study conducted a multivariable analysis to identify factors associated with PWM in a Midwestern U.S. swine production system. Weekly data from 47 sow farms (7207 weaning weeks) were captured from January 2020 to December 2022. Initially, 29 variables regarding farm infrastructure, productivity parameters, health status, and interventions were selected for univariate analysis to assess their association with PWM. The initial multivariable analysis included the variables with P < 0.20 in the univariate analyses. A backward stepwise model selection was conducted by excluding variables with P > 0.05, and the final multivariable model consisted of 19 significant risk factors and 6 interaction terms. The overall average PWM for the study population was 14.02 %. Yearly variations in PWM were observed, with the highest recorded in 2020 (16.61 %) and the lowest in 2021 (15.78 %). Cohorts with a pond water source, lower farrowing rate (71.9 %), higher farrowing parity (5.1), shorter gestation length (116.2 days), and using oxytocin during farrowing had increased PWM. The higher productivity parameters such as mummies rate, stillborn rate, and average total born, the higher the PWM was. Additionally, health status and intervention-related factors were associated with PWM, where higher PWM rates were observed in herds facing porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks, porcine epidemic diarrhea virus (PEDV) positive, the weeks before and during feed medication, and weeks without using Rotavirus vaccine or Rotavirus feedback. Altogether, these results corroborate that PWM is a multifactorial problem, and a better understanding of the risk factors is essential in developing strategies to improve survival rates. Therefore, this study identified the major risk factors associated with PWM for groups of pigs raised under field conditions, and the results underscore the significance of data analysis in comprehending the unique challenges and opportunities inherent to each system.

Infectious Agents Associated with Abortion Outbreaks in Italian Pig Farms from 2011 to 2021

The present study retrospectively analyzed the infectious agents associated with 829 abortion outbreaks occurring from 2011 to 2021 in northern Italy. Foetuses were subjected to necropsies, and organ samples were analyzed by direct PCR to screen for six swine pathogens. In 42.0% of the examined outbreaks, at least one infectious agent was found. Porcine reproductive and respiratory syndrome virus (PRRSV) (24.9%) and porcine circovirus-2 (PCV2) (11.5%) were the most frequently detected among the known abortion-inducing pathogens. Chlamydia spp. (5.6%), porcine parvovirus (PPV) (4.0%), and Leptospira spp. (2.6%) were less common. Although its role in swine reproductive disorders is still unclear, PCV3 was detected in 19.6% of the cases. Coinfections were detected in 25.0% of positive outbreaks, and the most frequent coinfection was represented by PRRSV and PCV2 (32.2%), followed by PRRSV and PCV3 (23%). PCV2 prevalence showed a slight but consistent reduction during the study period, while PCV3 increased in frequency. Our data suggest an overall reduction in abortion outbreaks during the study period. PRRSV was confirmed as the main abortion agent detected in the examined area, while PCV2 prevalence showed a decline. Conversely, PCV3 detection has been increasing, supporting its potential role as an abortion agent. Our results highlight the importance of implementing a consistent and standardized sampling procedure, as well as a thorough diagnostic protocol, to reduce the incidence of inconclusive diagnoses.

How do pig veterinarians view technology-assisted data utilisation for pig health and welfare management? A qualitative study in Spain, the Netherlands, and Ireland

BACKGROUND

Application of data-driven strategies may support veterinarians' decision-making, benefitting pig disease prevention and control. However, little is known about veterinarians' need for data utilisation to support their decision-making process. The current study used qualitative methods, specifically focus group discussions, to explore veterinarians' views on data utilisation and their need for data tools in relation to pig health and welfare management in Spain, the Netherlands, and Ireland.

RESULTS

Generally, veterinarians pointed out the potential benefits of using technology for pig health and welfare management, but data is not yet structurally available to support their decision-making. Veterinarians pointed out the challenge of collecting, recording, and accessing data in a consistent and timely manner. Besides, the reliability, standardisation, and the context of data were identified as important factors affecting the efficiency and effectiveness of data utilisation by veterinarians. A user-friendly, adaptable, and integrated data tool was regarded as potentially helpful for veterinarians' daily work and supporting their decision-making. Specifically, veterinarians, particularly independent veterinary practitioners, noted a need for easy access to pig information. Veterinarians such as those working for integrated companies, corporate veterinarians, and independent veterinary practitioners expressed their need for data tools that provide useful information to monitor pig health and welfare in real-time, to visualise the prevalence of endemic disease based on a shared report between farmers, veterinarians, and other professional parties, to support decision-making, and to receive early warnings for disease prevention and control.

CONCLUSIONS

It is concluded that the management of pig health and welfare may benefit from data utilisation if the quality of data can be assured, the data tools can meet veterinarians' needs for decision-making, and the collaboration of sharing data and using data between farmers, veterinarians, and other professional parties can be enhanced. Nevertheless, several notable technical and institutional barriers still exist, which need to be overcome.

Too late or too soon? The replacement gilt paradox

Due to high annual culling rates, pig farms require a constant income of replacement gilts. Gilts typically reach puberty at nearly six months of age. Puberty may be induced through early boar exposure, therapy with steroid hormones and chorionic gonadotropins, and optimized by identifying biological predictors and risk factors. Old age at the time of the first mating is associated with an increased risk of premature culling, often attributed to reproductive failures and locomotor problems. While female prolifacy has increased substantially during the last few decades, selecting for litter size to optimize lifetime productivity would be more efficient after two parities. Additionally, uterine capacity and the number of functional teats should be considered in selecting future dams. For each female, the cost-effective number of parities at removal is determined by the cumulative number of pigs born and weaned during the total herd days.

Swine fertility in a changing climate

Climate change has been linked to increasing temperatures and weather extremes. Certain regions around the world become more susceptible to environmental hazards that limit pig production and reproductive fertility. Environmental measures that link to pig fertility are needed to assess change, risk and develop solutions. Sub-populations of pigs display lower fertility in summer and are susceptible to heat stress. In the context of a warming climate, elevated temperatures and number of heat stress days increase body temperature and change the physiology, behavior, feed intake, and stress response of the pig. These changes could alter follicle development, oocyte quality, estrus expression, conception and litter size. In boars, sperm quality and production are reduced in response to summer heat stress. Nevertheless, while temperature increases have occurred over the years in some warmer locations, other regions have not shown those changes. Perhaps this involves the measures used for heat stress assessment or that climate is buffered in more temperate areas. Reductions in pig fertility are not always evident, and depend upon climate, year, genotype and management. This could also involve selection, as females more susceptible to heat stress and fertility failure, are subsequently culled. In the years from 1999 to 2020 when increases in global temperature from baseline occurred, measures of female fertility improved for farrowing rate and litter size. Progressive reduction in fertility may not be apparent in all geo-locations, but as temperatures increases become more widespread, these changes are likely to become more obvious and detectable.

Artificial insemination and optimization of the use of seminal doses in swine

The optimization of processes associated with artificial insemination (AI) is of great importance for the success of the pig industry. Over the last two decades, great reproductive performance has been achieved, making further significant progress limited. Optimizing the AI program, however, is essential to the pig industry's sustainability. Thus, the aim is not only to reduce the number of sperm cells used per estrous sow but also to improve some practical management in sow farms and boar studs to transform the high reproductive performance to a more efficient program. As productivity is mainly influenced by the number of inseminated sows, guaranteeing a constant breeding group and with healthy animals is paramount. In the AI studs, all management must ensure conditions to the health of the boars. Some strategies have been proposed and discussed to achieve these targets. A constant flow of high-quality and well-managed breeding groups, quality control of semen doses produced, more reliable technology in the laboratory routine, removal of less fertile boars, the use of intrauterine AI, the use of a single AI with control of estrus and ovulation (fixed-time AI), estrus detection based on artificial intelligence technologies, and optimization regarding the use of semen doses from high genetic-indexed boars are some strategies in which improvement is sought. In addition to these new approaches, we must revisit the processes used in boar studs, semen delivery network, and sow farm management for a more efficient AI program. This review discusses the challenges and opportunities in adopting some technologies to achieve satisfactory reproductive performance and efficiency.

Artificial intelligence and porcine breeding

Livestock management is evolving into a new era, characterized by the analysis of vast quantities of data (Big Data) collected from both traditional breeding methods and new technologies such as sensors, automated monitoring system, and advanced analytics. Artificial intelligence (A-In), which refers to the capability of machines to mimic human intelligence, including subfields like machine learning and deep learning, is playing a pivotal role in this transformation. A wide array of A-In techniques, successfully employed in various industrial and scientific contexts, are now being integrated into mainstream livestock management practices. In the case of swine breeding, while traditional methods have yielded considerable success, the increasing amount of information requires the adoption of new technologies such as A-In to drive productivity, enhance animal welfare, and reduce environmental impact. Current findings suggest that these techniques have the potential to match or exceed the performance of traditional methods, often being more scalable in terms of efficiency and sustainability within the breeding industry. This review provides insights into the application of A-In in porcine breeding, from the perspectives of both sows (including welfare and reproductive management) and boars (including semen quality and health), and explores new approaches which are already being applied in other species.

Spermiogram, Kinetics, Flow Cytometric Characteristics and DNA Damage Degree in Boar Ejaculates: Summarization and Clustering

Boar semen analysis includes sperm motility, concentration, morphology and other more complex analyses such as membrane integrity, DNA damage and seminal plasma components. This study aims to summarize these numerous data by linear combinations of them, to classify ejaculates in several categories (clusters) and to investigate the potential differences among clusters on fertility and prolificacy. Young Pietrain boars (23 ± 3.6 months) were investigated: ten boars from the Nucléus genetic line (group 1: 90 ejaculates weekly) and five boars from the Batallé genetic line (group 2: 30 ejaculates weekly). Computer-assisted semen analysis (CASA) examined motility. Sperm viability, acrosome reaction, early apoptosis, mitochondrial activity and DNA damage were studied by flow cytometry analysis. SPSS v.26 software was used to perform principal component analysis (PCA) and clustering. Three principal components (PC1: speed; PC2: linear path; PC3: DNA damage) were detected and four clusters identified in both groups. Clusters also differed significantly in several variables not included in these PCs (group 1: beat cross frequency and poly (ADP-ribose) polymerase; group 2: cathepsin B, abnormal forms, mitochondrial activity and high DNA stainability). PCA and clustering achieved adequate description of these ejaculates, but no differences among clusters were found for fertility or prolificacy, probably because the minimum sperm requirements had been met.

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach

In an effort to enhance reproductive management and reduce non-productive periods in swine breeding, this study presents a novel, non-invasive metabolomics approach for the identification of early pregnancy biomarkers in sows. Utilizing an untargeted metabolomics approach with mass spectrometry analysis, we examined saliva samples from pregnant (n = 6) and non-pregnant control sows (n = 6, artificially inseminated with non-viable sperm). Our analysis revealed 286 differentially expressed metabolites, with 152 being up-regulated and 134 down-regulated in the pregnant group. Among these, three metabolites, namely Hyodeoxycholic acid, 2'-deoxyguanosine, and Thymidine, emerged as potential early pregnancy biomarkers. These biomarkers were further evaluated using targeted LC-MS/MS quantification and qualification, accompanied by ROC curve analysis. The study confirmed Hyodeoxycholic acid and 2'-deoxyguanosine as promising biomarkers for early pregnancy detection, offering potential for future implementation in swine production environments. This research establishes a robust theoretical foundation for the development of innovative molecular diagnostic techniques and explores new avenues for molecular genetic breeding and non-invasive diagnostics, ultimately enhancing fertility and productivity in sow herds.

Preweaning piglet survival on commercial farms

Preweaning piglet mortality (PWM), a trait highly related to litter size, is one of the main concerns associated with productive efficiency and animal welfare in commercial pig farms. The objectives of this work were to study piglet survival at the farm level, to establish a survival rate (SR) as a target indicator to be improved, and to model it based on other reproductive parameters. Analyzed data corresponded to 580 Spanish commercial farms with a total inventory of 809,768 sows. These farms showed a mean SR of 85.70% piglets born alive (BA), which decreased to 81.81% when total piglets born (TB) were considered. The SR was strongly associated with prolificacy (P < 0.01), the parities with the highest prolificacy being those that had the lowest SR. Thus, the highest correlations were for the SR of piglets BA in the third and fourth parities (r = -0.460 and r = -0.452, respectively, P < 0.01), and for the SR of piglets TB in the fourth parity (r = -0.546, P < 0.01), which was the one with the highest prolificacy. The values corresponding to the quartile of farms with the highest SR within the most productive farms were established as targets to be improved, which were ≥88.5% of piglets BA and 83.2% of piglets TB. Nevertheless, the direct associations shown between the piglet's survival and prolificacy and other productive factors, such as the age of piglets at weaning, the farrowings per sow and year and the farrowing interval, suggest the convenience of modeling the risk of PWM on farms to have its own target of survival index to be improved.

Multi-Criteria Evaluation Model of Management for Weaned Piglets and Its Relations with Farm Performance and Veterinary Medicine Consumption

Weaned piglets, being immature, demand careful handling to mitigate post-weaning stress in order to avoid immunosuppression and the use of antimicrobials to palliate the effects of disease outbreaks due to poor management. The objective of this work is to design a quick scan calculator or multi-criteria evaluation model of management for weaned piglets, founded on 10 critical indices covering post-weaning management aspects based on hygienic measures and management of facilities and animals. These include pre-weaning handling, batch management, biosecurity, water management, feed management, health program, stockmen training, temperature, ventilation, and floor conditions and density to relate handling and hygiene practices with farm performance and the consumption of veterinary medication. Each index carries a maximum score of ten, with evaluations derived from different management factors that make up each index (from three to eight factors were evaluated per index). Their cumulative score reflects the degree of adequacy of on-farm management. Therefore, a perfectly managed farm would achieve 100 points. The calculator underwent testing on 23 intensive farms with a total population of close to 16,000 sows and more than 400,000 weaned piglets, revealing the highest mean scores in floor conditions and density (8.03 out of 10) and pre-weaning handling and health programs (6.87 and 6.28, respectively). Conversely, the lowest scores corresponded to temperature, ventilation, water management, and stockmen training (4.08, 4.32, 4.81, and 4.93, respectively). The assessed farms averaged a global score of 56.12 out of 100 (from 37.65 to 76.76). The calculator's global score correlated with key post-weaning productivity and piglet health indicators, such as the feed conversion ratio, mortality rate, and piglet production cost, with r values of -0.442, -0.437, and -0.435, respectively (p < 0.05). Additionally, it negatively correlated with medication costs per piglet (r = -0.414; p < 0.05) and positively with annual farm productivity (r = 0.592; p < 0.01). To enhance management, hygiene, and prevention, farms should prioritize addressing indices with the lowest scores, thereby reducing medication consumption and enhancing productivity and health outcomes. Additionally, this quick scan calculator can be used for benchmarking purposes.

Managing prolific sows in tropical environments

Litter size in modern sows has been dramatically improved in recent decades by genetic selection for highly prolific sows. In a tropical environment, the average total number of pigs born and number born alive are reported to be as high as 17.2 and 15.1 piglets per litter, respectively. Therefore, the new production target in many herds aims to achieve 30-40 pigs weaned per sow per year. Despite the improvements in litter size, the mean preweaning piglet mortality rate remains high, at between 10% and 20%, in major pig-producing countries. A sufficient daily feed intake by lactating sows is important for high milk production as sow milk yield is the limiting factor for piglet growth rate. Heat stress, which can occur when the ambient temperatures rise above 25°C, is one of the major problems that decreases daily feed intake and compromises milk yield. Therefore, it is necessary to encourage high feed intakes to achieve high milk yields. However, even with high nutrient intakes, productivity can be constrained by intestinal barrier function, limiting digestive ability, and allowing potential pathogens and/or toxins to become systemic. This is more likely greater under tropical conditions because of heat stress, exacerbating sow fertility problems. Underpinning sow herd performance, including responses to environmental challenges, is the selection of appropriate gilts, for example, selection and management for early puberty, thus presumably selecting the more fertile gilts and the correct management of lactation to improve the number of weaned piglets are some of the key factors for future reproductive efficiency of the farm under tropical conditions.

Effects of dietary coenzyme Q10 supplementation during gestation on the embryonic survival and reproductive performance of high-parity sows

BACKGROUND

Fertility declines in high-parity sows. This study investigated whether parity-dependent declines in embryonic survival and reproductive performance could be restored by dietary coenzyme Q10 (CoQ10) supplementation.

METHODS

Two experiments were performed. In Exp. 1, 30 young sows that had completed their 2^nd parity and 30 high-parity sows that had completed their 10^th parity, were fed either a control diet (CON) or a CON diet supplemented with 1 g/kg CoQ10 (+ CoQ10) from mating until slaughter at day 28 of gestation. In Exp. 2, a total of 314 post-weaning sows with two to nine parities were fed the CON or + CoQ10 diets from mating throughout gestation.

RESULTS

In Exp. 1, both young and high-parity sows had a similar number of corpora lutea, but high-parity sows had lower plasma CoQ10 concentrations, down-regulated genes involved with de novo CoQ10 synthesis in the endometrium tissues, and greater levels of oxidative stress markers in plasma and endometrium tissues. High-parity sows had fewer total embryos and alive embryos, lower embryonic survival, and greater embryo mortality than young sows. Dietary CoQ10 supplementation increased the number of live embryos and the embryonic survival rate to levels similar to those of young sows, as well as lowering the levels of oxidative stress markers. In Exp. 2, sows showed a parity-dependent decline in plasma CoQ10 levels, and sows with more than four parities showed a progressive decline in the number of total births, live births, and piglets born effective. Dietary supplementation with CoQ10 increased the number of total births, live births, and born effective, and decreased the intra-litter covariation coefficients and the percentage of sows requiring farrowing assistance during parturition.

CONCLUSIONS

Dietary CoQ10 supplementation can improve the embryonic survival and reproductive performance of gestating sows with high parity, probably by improving the development of uterine function.

Effect of Sow Body Weight at First Service on Body Status and Performance during First Parity and Lifetime

In this retrospective study, we aimed to assess the effect of body weight (BW) at first service on body status development and sow performance during first parity and lifetime efficiency. A total of 360 DanBred gilts were used, which we categorized into three groups according to their BW: (1) Small sows (<135 kg BW; n = 108); (2) Medium sows (135−150 kg BW; n = 155); (3) Large sows (>150 kg BW; n = 63). We studied the gilts from first insemination to first weaning, and then monitored until culling. Sow body status, litter size and weight, farrowing rate, weaning-to-conception interval, lifetime performance, and hormones linked to metabolism were recorded. Sows in the Small group had the lowest body weight, backfat thickness, and loin depth during gestation. Moreover, they had the smallest number of total piglets born and longest weaning-to-conception interval at first parity. The Small sows also had, on average, one less piglet born during their productive life, and they tended to have a higher culling rate over three parities. For immunoglobulins, insulin, cortisol, and IGF-I levels, no differences were found. In conclusion, achieving optimal body weight at first service is essential for maximizing the sow’s lifetime performance.

Second litter syndrome in Iberian pig breed: factors influencing the performance

Second litter syndrome (SLS) consists of a loss of prolificacy in the second parity (P2), when a sow presents the same or lower results for litter size than in the first parity (P1). This syndrome has been reported for modern prolific breeds but has not been studied for rustic breeds. The objectives of this study are to determine how and to what degree Iberian sows (a low productivity breed recently raised on intensive farms) are affected by SLS; to establish a target and reference levels; and to assess the factors influencing the performance. Analysed data correspond to 66 Spanish farms with a total of 126 140 Iberian sows. The average Iberian sow prolificacy in P1 was 8.91 total born (TB) and 8.47 born alive (BA) piglets, whereas in P2, it decreased by -0.05 TB and -0.01 BA piglets, suggesting some general incidence of SLS. At the sow level, 56.63% did not improve prolificacy in terms of BA piglets in P2, and 16.98% had a clear decrease in prolificacy, losing ≥3 BA piglets in P2. Within herds, a mean of 57.75% of sows showed SLS, with an evident decrease in the number of BA piglets in P2. The plausible target for the Iberian farm's prolificacy comes from the quartile of farms with the lowest percentage of SLS sows within the farms with the highest prolificacy between P1 and P2 (mean of 8.77 BA). So, in this subset of farms (N = 17), 47.3% of sows improved their prolificacy in P2 (i.e. did not show SLS). Hence, half the sows could be expected to show SLS even on farms with a good performance. Finally, this study brings out the main factors reducing P2 prolificacy through SLS in the Iberian breed: later age at first farrowing, long first lactation length, medium weaning to conception interval and large litter size in P1. In conclusion, improving the reproductive performance of Iberian farms requires reducing the percentage of sows with SLS, paying special attention to those risk factors. The knowledge derived from this study can provide references for comparing and establishing objectives of performance on Iberian sow farms which can be used for other robust breeds.

Optimizing feeding regimen of replacement gilts to improve their reproductive performance and retention rate of their first 2 parities

The effects of age, body weight (BW), and backfat thickness (BF) of replacement gilts at first estrus and first mating on their subsequent reproductive performance and retention of their first 2 parities as sows was evaluated. A total of 3,025 Danish replacement gilts were categorized by farm (allocated to 4 farms), cross combination, age, BW and BF at first estrus and first mating, estrous cycle number at first mating, and flush feeding before first mating. The result shows that all the factors mentioned above were significantly associated with reproductive performance and retention rates of the first 2 parities. Farm 3 had more piglets born alive per litter (BA) (P < 0.05). Farms 3 and 4 had more healthy piglets per litter (HP) (P < 0.05). Farm 4 had the most piglets weaned per litter (PW) (P < 0.05). Landrace × Landrace × Yorkshire (L × L × Y) replacement gilts had the most total piglets born per litter (TB), BA, HP, PW and a higher retention rate of the 2 parities than Landrace × Yorkshire (L × Y) replacement gilts (P < 0.05). In addition, flush feeding before first mating had the most TB, BA, HP, PW, and a higher retention rate of the 2 parities than no flush feeding (P < 0.05). Because the effects of replacement gilts rearing parameters on reproductive performance traits differed, we used 100 replacement gilts as a unit and the total number of weaned piglets from the first 2 parities as a new index. Replacement gilts undergoing their first estrus between 180 and 210 d of age at 115 to 124.9 kg BW and 14 to 15 mm BF had significantly higher reproductive indexes for their first 2 parities per 100 replacement gilts. Replacement gilts that mated between 210 and 230 d of age at 140 to 149.9 kg BW and 15 to 16 mm BF had optimal reproductive indexes. These results provide a new insight into the complex relationships among these reproductive performance traits and may help guide successful management of replacement gilts as a pivotal starting point for future fertility and longevity of rearing herds.

Traits Defining Sow Lifetime Maternal Performance

Declining sow performance with increasing parity or an increase in the number of poor- quality pigs potentially impacts on farm productivity. This study investigated the phenotypic and genetic background of the sow's influence on (i) the number of pigs not meeting the industry standards (tail-enders) and (ii) changes in performance with parity. Data were available for 3592 sows and their litters (13,976 litters) from a pig production system in NSW, Australia. The mean, standard deviation (SD), and slope for trait values over time were estimated for the sow characteristic traits: number of born-alive (NBA) and stillborn (SB) piglets and body condition of sow recorded with a caliper (CAL), along with maternal effects on piglet performance, represented by: average piglet birth weight (APBW), number of weaned piglets (WEAN), and tail-enders (TEND). Traits were analyzed in ASReml 4.2, by using an animal model. The number of tail-enders produced by a sow is a heritable trait, with a heritability estimate of 0.14 ± 0.04. Sow characteristics and maternal effects on piglet performance expressed by mean and slope had similar heritability estimates, ranging from 0.10 ± 0.03 to 0.38 ± 0.05, whereas estimates for SD traits were generally not different from zero. The latter suggests individual variability in sow characteristics or maternal performance between parities is largely not genetic in origin. This study demonstrated that more attention is required to identify contributions to the problem of tail-enders, and that slope traits could potentially be useful in the breeding program to maximize lifetime performance.

Machine learning based personalized promotion strategy of piglets weaned per sow per year in large-scale pig farms

Background

The purpose of this study was to analyze the relationship between different productive factors and piglets weaned per sow per year (PSY) in 291 large-scale pig farms and analyze the impact of the changes in different factors on PSY. We chose nine different algorithm models based on machine learning to calculate the influence of each variable on every farm according to its current situation, leading to personalize the improvement of the impact in the specific circumstances of each farm, proposing a production guidance plan of PSY improvement for every farm. According to the comparison of mean absolute error (MAE), 95% confidence interval (CI) and R², the optimal solution was conducted to calculate the influence of 17 production factors of each pig farm on PSY improvement, finding out the bottleneck corresponding to each pig farm. The level of PSY was further analyzed when the bottleneck factor of each pig farm changed by 0.5 standard deviation (SD).

Results

17 production factors were non-linearly related to PSY. The top five production factors with the highest correlation with PSY were the number of weaned piglets per litter (WPL) (0.6694), mating rate within 7 days after weaning (MR7DW) (0.6606), number of piglets born alive per litter (PBAL) (0.6517), the total number of piglets per litter (TPL) (0.5706) and non-productive days (NPD) (− 0.5308). Among nine algorithm models, the gradient boosting regressor model had the highest R², smallest MAE and 95% CI, applied for personalized analysis. When one of 17 production factors of 291 large-scale pig farms changed by 0.5 SD, 101 pig farms (34.7%) can increase 1.41 PSY (compared to its original value) on average by adding the production days, and 60 pig farms (20.6%) can increase 1.14 PSY on average by improving WPL, 45 pig farms (15.5%) can increase 1.63 PSY by lifting MR7DW.

Conclusions

The main productive factors related to PSY included WPL, MR7DW, PBAL, TPL and NPD. The gradient boosting regressor model was the optimal method to individually analyze productive factors that are non-linearly related to PSY.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40813-022-00280-z.

Evaluation of a Numerical, Real-Time Ultrasound Imaging Model for the Prediction of Litter Size in Pregnant Sows, with Machine Learning

Simple Summary

The use of a numeric model to quantify real-time ultrasonographic (RTU) imaging is a prominent methodfor predicting the expected litter size by training an artificial neural network (ANN) to minimize the error of the prediction measured by metrics, such as root square mean error and mean absolute error. Time of the RTU application is a critical factor for such a prediction. Rated scale values (RSV) obtained from the RTU images relate to the accurate diagnosis of pregnancy and of litter size, suggesting the potential of a generalized use of the model in various farm conditions. Ultimately, the employment of the model in machine learning for an automated prediction of litter size can be used as a routine on-farm procedure for the efficient management of gestating sows.

Abstract

The present study aimed to evaluate the accuracy of a numerical model, quantifying real-time ultrasonographic (RTU) images of pregnant sows, to predict litter size. The time of the test with the least error was also considered. A number of 4165 pregnancies in Farm 1 and 438 in Farm 2 were diagnosed twice, with the quality of the RTU images translated into rated-scale values (RSV1 and RSV2). When a deep neural network (DNN) was trained, the evaluation of the method showed that the prediction of litter size can be performed with little error. Root square mean error (RMSE) for training, validation with data from Farm 1, and testing on the data from Farm 2 were 0.91, 0.97, and 1.05, respectively. Corresponding mean absolute errors (MAE) were 2.27, 2.41, and 2.58. Time appeared to be a critical factor for the accuracy of the model. The smallest MAE was achieved when the RTU was performed at days 20–22. It is concluded that a numerical, RTU imaging model is a prominent predictor of litter size, when a DNN is used. Therefore, early routinely evaluated RTU images of pregnant sows can predict litter size, with machine learning, in an automated manner and provide a useful tool for the efficient management of pregnant sows.

Analysis of culling reasons during the breeding cycle and lifetime performance: The strategy to remove crossbred Landrace and Large White sows under tropical climate

Background and Aim:

Sow culling is an important practice in commercial swine production because it is directly associated with the economic efficiency of the breeding herd. This study was conducted to analyze the reasons for sow culling and quantify the factors affecting culling in crossbred Landrace and Large White sows under tropical climate.

Materials and Methods:

A total of 4887 culled sows from one parent stock farm located in Ratchaburi province, Western Thailand, were examined in this study. Culling reasons were grouped into the following eight categories according to farm management: (1) Reproductive disorders, (2) old age, (3) low performance, (4) diseases, (5) lameness, (6) udder problems, (7) body condition, and (8) other illnesses. Logistic regression analysis was used to explore the relationship between culling sows and environmental factors. Effects of parity and season of culling were considered as fixed effects in a statistical model.

Results:

Descriptive statistics indicated the following factors accounting for sow removals: Old age (34.93%, n=1707), reproductive disorders (29.32%, n=1433), low performance (12.62%, n=617), lameness (12.56%, n=614), diseases (4.8%, n=235), body condition (4.68%, n=229), udder problems (0.79%, n=39), and other illnesses (0.26%, n=13). Parity and season of culling were also found to have a significant effect on sow culling (p<0.05). The majority of culling sows in this population were of old age and high parity.

Conclusion:

This study indicated that the purposeful culling of sows on this farm was within the targeted range. However, the incidence of reproductive disorders was too high and required further investigations.

Effect of Season and Parity on Reproduction Performance of Iberian Sows Bred with Duroc Semen

The Iberian pig is an autochthonous breed from the Iberian Peninsula highly valued for its meat. The sows are often bred as Iberian × Duroc crossings for increased efficiency. Since sow parity and season affect the reproductive performance, we evaluated two-year records from a commercial farrow-to-finish farm (live, stillborn, and mummified piglets after artificial insemination, AI). A total of 1293 Iberian sows were inseminated with semen from 57 boars (3024 AI). The effects of parity (gilts, 1, 2-4, 5-10, and >10 farrowings) and season were analyzed by linear mixed-effects models (LME). The data were fitted to cosinor models to investigate seasonal effects within parity groups. The effects of maximum daily temperature (MDT) and day length change (DLC) during spermatogenesis, pre-AI, and post-AI periods were analyzed with LME. The 2-4 group was the optimal one for parity. A seasonal effect was evident between spring-summer (lower fertility/prolificacy) and autumn-winter (higher). Cosinor showed that the seasonal drop in reproductive performance occurs earlier in Iberian sows than in other breeds, more evident in gilts. MDT negatively affected performance in all periods and DLC in spermatogenesis and pre-AI. These results are relevant for the improvement of Iberian sows' intensive farming.

Five risk factors and their interactions of probability for a sow in breeding herds having a piglet death during days 0-1, 2-8 and 9-28 days of lactation

Background

Increasing preweaning piglet mortality is a concern for veterinarians and producers in relation to sow performance and piglet welfare. Our objectives were (1) to characterize pre-weaning piglet mortality risk for sows (PWM) during early (0–1 days), mid- (2–8 days) and late (9–28 days) lactation and (2) to quantify the following five factors and their interactions, parity, number of piglets born alive (PBA), number of stillborn piglets (SB), gestation length (GL) and season for PWM during the three lactation phases.

Methods

Data obtained from 264,333 parity records of 55,635 sows farrowed in 2015 and 2016 from 74 Spanish herds. Three multi-level mixed-effects logistic regression models were separately applied for PWM during three lactation phases, which was analyzed as whether or not a sow had a piglet death (i.e. probability of a sow having a piglet death) in each phase.

Results

PWM during early, mid- and late lactation were 36.9, 27.0 and 15.4%, respectively. As PBA increased from 11 or less to 16 or more pigs, PWM during early and mid-lactation increased by 15.8 and 6.0%, respectively, but there was no increase during late lactation. Also, as GL decreased from 117–120 to 110–113 days, PWM during early, mid- and late lactation increased by 7.5, 6.8 and 1.5%, respectively. Additionally, PWM during the respective lactation phases increased by 8.3, 5.2 and 1.0%, as SB increased from 0 to 3 or more pigs. During early lactation, parity 1 sows had 2.1% lower PWM than parity 5 or higher sows, but during mid- and late lactation they had 4.2% higher PWM (P < 0.05). However, there was no difference between summer and winter for PWM during early lactation (P = 0.26).

Conclusion

Management practices to reduce PWM need to take account of these factors, and be modified for different phases. For example, during early lactation special care should be given to piglets born to parity 5 or higher sows farrowing 16 or more PBA, having 3 or more SB or GL 110–113 days, whereas during mid- and late lactation more care should be given to piglets born to parity 1 sows with the same PBA, GL and SB conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40813-021-00231-0.

A 10-year trend in piglet pre-weaning mortality in breeding herds associated with sow herd size and number of piglets born alive

BACKGROUND

Piglet pre-weaning mortality (PWM) is one of the biggest problems regarding sow performance and piglet welfare. Recently, PWM has increased in some countries, but it is not known if there are similar increases in other countries, nor whether increased PWM is related to either increased numbers of piglets born alive (PBA) or to sow herd size. So, the objectives of the present study were 1) to explore the trend in PWM in Spanish sow herds over a recent 10-year period, along with related measurements such as PBA, stillborn piglets, herd productivity and herd size; and 2) to examine the relationships between PWM and the related measurements.

METHODS

Herd-level annual data from 2007 to 2016 for 91 herds in Spain were abstracted from a sow database compiled by a veterinary consultancy firm that asked client producers to mail data files on a regular basis. The database software automatically calculated herd-level PWM (%) as follows: the total number of piglets born alive to a sow completely weaned during a year (TPBA) minus the total number of piglets weaned by the completely weaned sow during the year divided by TPBA × 100. All the statistical analyses were performed by using SAS University Edition. A growth curve model was applied to incorporate correlations for all of the observations arising from the same farm.

RESULTS

Over the 10 years, herd means of PWM (standard deviation) increased from 11.9 (4.1) % to 14.4 (3.2) %, and mean PBA increased by 1.9 pigs. Mean age of piglet death during lactation increased by 3.8 days, and later years were significantly associated with herd size and the number of piglets weaned per sow per year (PSY; P <  0.05). Higher PWM was associated with more PBA, more stillborn piglets and small-to-mid herds (lower than the median size: < 570 sows; P <  0.05). Also, there was a significant interaction between the herd size groups and PBA for PWM (P <  0.05): as PBA increased from 9 to 14 pigs, PWM increased by 9.6% in small-to-mid herds, compared with an increase of only 6.6% in large herds (> 570 sows). Furthermore, as PWM decreased from 18 to 8%, herd productivity measured as PSY increased by 2.2 pigs in large herds, compared with only 0.6 pigs in small-to-mid herds.

CONCLUSION

Large herds were better than small-to-mid herds at alleviating the association between increased PBA and increased PWM. Also, the relationship between decreased PWM and increased herd productivity was improved more in large herds than in small-to-mid herds.