Description of on-farm treatment compliance and risk factors for culling in sows

Background In commercial pig farming, sick or injured sows are often treated by producers or hired staff. To date, limited quantitative data exists on treatment compliance and the possible effect on sow longevity post-treatment. The objective of the study was to quantify on-farm compliance of treatment selection, frequency, and dosage, as well as to investigate the association between body condition scores (BCS) and other sow-level factors on post-treatment cull risk. Results On-farm treatment records, including culling reason or reason of death up to 6 months post-treatment, production records and sow characteristics were obtained for 134 sows over an 8-week period. Treatment compliance was based on the accuracy of recorded treatments compared to the herd veterinarian’s established treatment guidelines. Univariable and multivariable logistic regression models including treatment reason, treatment compliance, BCS, parity, production stage and production metrics, were constructed to investigate associations between those variables and sow culling or death. This study found low compliance for on-farm sow treatment protocols, with only 22.4% (30/134) of the sows receiving correct and complete treatment during the duration of the study. No effect of individual treatment components (drug, dosage, or frequency) on sow culling was observed. A trend for an interaction between treatment compliance and BCS was found, and parity and number of piglets born alive were identified as predictors for sow maintenance in the herd. Conclusions On-farm sow treatment compliance was low, resulting in that approximately 80% of the enrolled sows were not treated according to existing guidelines. Non-compliance of treatment guidelines did not seem to affect the risk of culling in treated sows but may have prolonged any associated pain, recovery time and negatively impacted the sow welfare during that time period.

130 Utilization of Nutrack to Assess Variance Components and Heritability of Activity Traits

Overall activity and behavior are integral components of sows remaining productive in the herd. This investigation studied overall activity of group housed replacement gilts and the heritability of various activity traits. Beginning around 20 wk of age, video recorded data of approximately 75 gilts/group for a total of 2,378 gilts over 32 groups was collected for 7 consecutive d using the NUtrack System, which tracks distance travelled (m), avg speed (m/s), angle rotated (degrees), and time standing (s), sitting (s), eating (s), and laying (s). The recorded phenotypes were standardized to the distribution observed within a pen for each group. The final values used for analysis were the average daily standardized values. Data were analyzed using mixed models (RStudio V 1.2.5033) including effects of sire, dam, dam’s sire and dam, dam’s grandsire and granddam, farrowing group, barn, pen, and on-test date. Sire had an effect on every activity trait P < 0.001), and dam had an effect on average speed (P < 0.001). The dam’s sire had an effect on all activity traits (P < 0.001) and the dam’s grandsire had an effect on average speed (P < 0.001). Heritabilities and variance components of activity traits were estimated in ASReml 4 using an animal model with a two-generation pedigree. Genetic variances are 0.17 +/- 0.029, 0.19 +/- 0.034, and 0.11 +/- 0.024, residual variances are 0.37 +/- 0.023, 0.41 +/- 0.027, and 0.41 +/- 0.022, phenotypic variances are 0.54 +/- 0.018, 0.60 +/- 0.020, and 0.52 +/- 0.016, and heritabilities are 0.32 +/- 0.048, 0.32 +/- 0.049, and 0.21 +/- 0.044 for average speed, distance, and lie respectively. NUtrack offers potential to aid in selection decisions. Given the results presented herein, continued investigation into these activity traits and their association with sow longevity is warranted.

11 Metal Amino Acid Chelates/complexes with Emphasis on Molecule Absorption and Efficacy Differences in Swine

The objective of this presentation will be to discuss differences in the molecular structures between various organic trace minerals (OTM) and inorganic trace minerals (ITM) and discuss how these properties impact stability, absorption, bioavailability and retention. The Association of American Feed Control Officials (AAFCO) lists several different categories of OTM including chelates, complexes and proteinates. Typical ligands include organic acids, amino acids, peptides and polysaccharides. It is widely known that bioavailability of ITM is low, primarily due to the presence of antagonisms such as phytate and/or fiber or excesses of other minerals. For this reason, inclusions of trace minerals (e.g. Zn, Cu, Mn, Fe) are often added in commercial livestock diets at 2–3-fold higher concentrations than recommended by NRC. Feeding highly bioavailable trace minerals is important. These minerals are required components of thousands of the proteins, enzymes and transcription factors that support a wide variety of biochemical processes in the cells and tissues of animals. These functions include gene regulation, cell growth and division, immune development and function, tissue development and integrity, reproduction and oxidative stress management. Low bioavailability of these trace minerals can reduce animal performance, immune function, reproductive performance and increase lameness. Numerous in vitro and in vivo methodologies have been used to compare bioavailability and demonstrate higher stability, tissue retention and digestibility of OTM vs ITM. Sow longevity is a key factor in commercial swine herd profitability. Reproductive problems and lameness are the most common reasons for premature sow culling from breeding herds. Compared to ITM, OTM reduced gilt and sow mortality 9–17% (P < 0.10), culling rate 20–35% (P < 0.01) and increased sow retention (through parity 3) 5–10%; (P < 0.01). Greater bioavailability translates to biological benefits to the producer, however, our findings demonstrate that not all OTM perform better than ITM.

Identifying early indicator traits for sow longevity using a linear-threshold model in Thai Large White and Landrace females

Objective: The objective of the study was to investigate the possibility of utilizing an early litter size trait as an indirect selection trait for longevity and to estimate genetic parameters between sow stayability and litter size at different parities using a linear-threshold model for longevity in Thai Large White (LW) and Landrace (LR) populations.Methods: The data included litter size at first, second, and third parities (NBA1, NBA2, and NBA3) and sow stayability from first to fourth farrowings (STAY14). The data was obtained from 10,794 LR and 9,475 LW sows. Genetic parameters were estimated using the multipletrait animal model. A linear-threshold model was used in which NBA1, NBA2, and NBA3 were continuous traits, while STAY14 was considered a binary trait.Results: Heritabilities for litter size were low and ranged from 0.01 to 0.06 for both LR and LW breeds. Similarly, heritabilities for stayability were low for both breeds. Genetic associations between litter size and stayability ranged from 0.43 to 0.65 for LR populations and 0.12 to 0.55 for LW populations. The genetic correlation between NBA1 and STAY14 was moderate and in a favorable direction for both LR and LW breeds (0.65 and 0.55, respectively).Conclusion: A linear-threshold model could be utilized to analyze litter size and sow stayability traits. Furthermore, selection for litter size at first parity, which was the genetic trait correlated with longevity, is possible when one attempts to improve lifetime productivity in Thai swine populations.

296 Awardee Talk: The Genetics of Sow Longevity

Sow longevity is a key productivity indicator trait that has real economic and welfare importance for commercial swine farms globally. The average parity at culling is 3.8 parities. Reports indicate that it takes 3 to 4 parities before a sow “pays for herself.” Research groups around the world have reported heritabilities estimates for sow longevity traits ranging from 0.05 to 0.35. Estimate differences result from the animal population under evaluation, the trait being evaluated, and the methodology employed to obtain the genetic parameter estimate. Because sow longevity is measured at the end of the sow’s productive life, indicator traits like age at first farrowing, leg conformation, and other traits are utilized in gilt selection programs. The genetic correlations between sow longevity and lifetime production traits range have been reported to range from 0.64 to 0.94, suggesting that selection will improve sow longevity. Genetic markers have been identified that affect both sow longevity and other indicator traits. Selection to improved sow longevity still requires phenotypes. Future technologies, e.g. CT scans, digital images, and automated disease detection, will provide additional phenotypes. Continued hardware, software, and molecular developments will improve selection accuracy for sow longevity traits and related traits. Research is needed to evaluate the impact that non-additive genetic effects have on sow longevity and other fitness-related traits. Sow longevity seems to be an ideal trait to employ genomic selection in order to make more rapid trait improvements because it is measured late in life, it is sex-limited, and the trait is not directly measured on nucleus animals. In conclusion, sow longevity and related traits have sufficient heritability and variation to improve through traditional and genomic enhanced selection methods. Selection programs employing effective genomic selection programs will be more effective in improving sow longevity trait and related traits and ultimately economical return.

PSVIII-22 Utilization of NUtrack to assess sire influence on pig activity and activity effects on weight

Structural conformation and behavior are integral components in sows remaining productive in the herd. This initial investigation studied the impact of activity data on weight and the impact of sires on overall activity of group housed replacement gilts. Beginning at 19 wk of age, video recorded data of approximately 75 gilts/wk for a total of 230 gilts over 3 wk was collected for 7 consecutive d using the NUtrack system, which tracks distance travelled (m), time standing (s), eating (s), and laying (s), and angle rotated (degrees). Any d that logged for less than 24 hr were dropped from analysis. Data were analyzed using mixed models (SAS V 9.4) including random effects of dam, barn, pen, and on-test date, and fixed effects including total laying time, angle rotated, distance travelled, time standing, and sire. For 20 wk wt, the mixed model included distance, laying, angle, and standing. Sire had an effect on distance traveled (P < 0.05). The following traits also had an effect on distance: angle (P < 0.01), laying (P < 0.001), standing (P < 0.001), sitting (P < 0.01), and eating (P < 0.01). Pearson correlation coefficient showed a positive correlation between wt and laying (0.26), and negative correlations between wt and distance (-0.34), standing (-0.28) and angle (-0.42). The regression of distance on 20 wk wt yielded a regression coefficient of -0.027 (P < 0.05) m/d per lb and the model explained 11.85% of the variation in 20 wk wt. NUtrack can be utilized to track activities and distance travelled of swine in group pens. Given the results presented herein, continued investigation into the heritability of these activity traits and their association with sow longevity is warranted.

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

Our objectives in this review are 1) to define the four components of sow lifetime performance, 2) to organize the four components and other key measures in a lifetime performance tree, and 3) to compile information about sow and herd-level predictors for sow lifetime performance that can help producers or veterinarians improve their decision making. First, we defined the four components of sow lifetime performance: lifetime efficiency, sow longevity, fertility and prolificacy. We propose that lifetime efficiency should be measured as annualized piglets weaned or annualized piglets born alive which is an integrated measure for sow lifetime performance, whereas longevity should be measured as sow life days and herd-life days which are the number of days from birth to removal and the number of days from date of first-mating to removal, respectively. We also propose that fertility should be measured as lifetime non-productive days, whereas prolificacy should be measured as lifetime pigs born alive. Second, we propose two lifetime performance trees for annualized piglets weaned and annualized piglets born alive, respectively, and show inter-relationships between the four components of the lifetime performance in these trees. Third, we describe sow and herd-level predictors for high lifetime performance of sows. An example of a sow-level predictor is that gilts with lower age at first-mating are associated with higher lifetime performance in all four components. Other examples are that no re-service in parity 0 and shorter weaning-to-first-mating interval in parity 1 are associated with higher fertility, whereas more piglets born in parity 1 is associated with higher prolificacy. It appears that fertility and prolificacy are independent each other. Furthermore, sows with high prolificacy and high fertility are more likely to have high longevity and high efficiency. Also, an increased number of stillborn piglets indicates that sows have farrowing difficulty or a herd health problem. Regarding herd-level predictors, large herd size is associated with higher efficiency. Also, herd-level predictors can interact with sow level predictors for sow lifetime performance. For example, sow longevity decreases more in large herds than small-to-mid herds, whereas gilt age at first-mating increases. So, it appears that herd size alters the impact of delayed gilt age at first-mating on sow longevity. Increased knowledge of these four components of sow lifetime performance and their predictors should help producers and veterinarians maximize a sow’s potential and optimize her lifetime productivity in breeding herds.

Genetic improvement of sow longevity and its economic impact on commercial pork production

Sow longevity (sow productive lifetime) plays an important role in economically efficient piglet production. Direct selection for sow longevity is not commonly practiced in any pig-breeding program. In recent years, an increased number of peer reviewed articles addressing the economic impact, genetic parameter estimates, and genomic information (including markers and single nucleotide polymorphisms for sow longevity) have been published in the scientific literature. The studies in the literature indicate that sow longevity is a complex trait having economic value and is an animal well-being concern for commercial pork producers. Studies have concluded that sufficient genetic variation exists so that selection to improve sow longevity should be effective. Unlike the dairy industry, the primary parent animal used in the swine industry is a crossbred female, typically F1 (Landrace X Large White or Yorkshire). Sow longevity has shown to be genetically related with prolificacy and leg conformation traits. Sow longevity seems to be the ideal trait to utilize genomic selection when attempting to improve the trait. The genetic correlation between purebred and crossbred sow longevity is low. Since the crossbred sow is the breeding objective, phenotypic data from the crossbred females should ideally be used when estimating the breeding values for sow longevity that are used in the indexes to evaluate nucleus animals. Genomic selection is best suited for sex-limited traits, traits expressed later in life, and many animals do not reach some defined end-point parity, sow longevity seems ideally suited to be evaluated using the latest genome enabled selection technology. Keywords: heritability, leg conformation, selection, sow productive lifetime

The effect of group composition and mineral supplementation during rearing on the behavior and welfare of replacement gilts

Sow longevity supported by good health and reproductive performance is necessary to optimize sow lifetime performance. In some countries, replacement gilts are reared with finisher pigs destined for slaughter, so they are exposed to sexual and aggressive behaviors performed by males. This is associated with stress and injury. Moreover, diets formulated for finishers are not designed to meet the needs of replacement gilts and may not supply the necessary minerals to promote limb health, optimal reproduction, and, thus, sow longevity. In this 2 × 2 factorial design experiment with 384 animals (32 pens [12 animals per pen]), we investigated the effect of female-only (FEM) or mixed-sex (MIX) rearing, with (SUPP) or without (CON) supplementary minerals (copper, zinc, and manganese) on locomotion, salivary cortisol levels, behavior, body lesions (BL), and hoof health of gilts. The experimental period began at transfer to the finisher stage (day 81.3 ± 0.5 of age; day 0) until breeding age (day 196 ± 0.5 of age; day 115). Locomotion was scored (0–5) biweekly from day 0 until slaughter day 67 or breeding age day 115 for the remaining gilts. Saliva samples were taken monthly from four focal gilts per pen. All counts of aggressive, harmful, sexual, and play behavior were recorded by direct observation 1 d biweekly (5- × 5-min observations/pen/d). BL scores were recorded on focal pigs biweekly from day 1 until day 99 on the back, neck, shoulder, flank, and hind quarter on each side of the body. Hind hooves were scored for eight disorders (heel erosion [HE], heel sole separation [HSS], and white line separation [WLS], dew claw length and dew claw cracks, toe length and both vertical and horizontal toe cracks) by severity, and a total hoof lesion score was calculated by summing individual scores. General linear mixed models were used to analyze cortisol, behavior, BL, and total hoof scores. Generalized linear mixed models were used for locomotion, bursitis and individual hoof disorders. There was less aggression (P < 0.05) and sexual behavior in the FEM compared to the MIX groups with more play behavior in MIX compared to FEM groups (P < 0.01). Gilts in the MIX groups had higher BL scores than gilts in the FEM groups (P < 0.001). Total hoof scores were higher in MIX (8.01 ± 0.15) than FEM (7.70 ± 0.12; P < 0.02) gilts. CON diet gilts had higher HE scores than SUPP gilts (P < 0.05). HSS (P < 0.05) and WLS (P < 0.05) scores were higher in MIX than FEM gilts. Rearing gilts in FEM groups had benefits for hoof health likely mediated through lower levels of activity due to male absence, and minerals helped reduce HE.