Genus plc

Feed represents the largest cost in pig production, making improvement in feed efficiency (FE) essential for maximizing the profitability for pig producers. The objective was to model different FE traits and to estimate the phenotypic and genetic correlations among these FE traits, growth traits, and feeding behavior traits. The FE traits included feed conversion ratio (FCR), six measures of residual feed intake (RFI1-6), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR). The RFIs were calculated by regressing daily feed intake (DFI) on different combinations of covariates, including metabolic midweight, average daily gain (ADG120), backfat thickness (BF120), and loin depth (LD120). Feeding behavior traits analyzed were the number of visits to the feeder per day (NVD), total time spent eating per day (TPD), feed intake rate (FR), feed intake per visit (FPV), and time spent eating per visit (TPV). Genetic parameters of the studied traits from 14,939 Duroc pigs were estimated using ASReml-R version 4.2. The univariate model indicated that fixed effects (sex, herd-year-season), covariates (initial body weight, adjusted age at 120 kg), and random effects (pen, litter, maternal genetics) are all significant for FE and performance traits (P < 0.05). Heritability estimates (±SE) for FE traits ranged from 0.28 ± 0.03 for RFI1 to 0.34 ± 0.03 for FCR indicating moderate heritability. Similarly, most of the performance and feeding behavior traits had moderate heritability, with higher estimates observed for BF120 (0.51 ± 0.03), FR (0.62 ± 0.02) and TPD (0.60 ± 0.02). All six RFI traits had weak to moderate positive genetic correlations (±SE) with BF120 (from 0.13 ± 0.06 for RFI6 to 0.58 ± 0.04 for RFI1 and RFI2). Only RFI1, RFI2, and RFI3 had significant genetic correlations with LD120 estimated at -0.40 ± 0.05, -0.41 ± 0.05 and -0.23 ± 0.06, respectively. FCR displayed significant genetic correlations with ADG120 (-0.64 ± 0.07), BF120 (0.55 ± 0.05), and LD120 (-0.61 ± 0.07). RG and RIG had significant positive genetic correlations with ADG120 and low or non-significant genetic correlations with BF120 and LD120. FE traits had weak genetic correlations with feeding behavior traits. Overall, the results demonstrate that RFI is a more reliable and advantageous trait for improving FE compared with FCR, as it maintains favorable relationships with growth traits while minimizing negative effects on carcass quality. The weak associations between FE and feeding behavior traits further suggest that selecting for RFI can enhance feed utilization without unintended behavioral consequences. These findings highlight the potential of RFI as a selection criterion to advance genetic improvement programs focused on sustainable production efficiency without compromising key economic and quality traits.

Abstract The use of artificial insemination (AI) in swine is a management tool that is practiced at a global scale such that >90% of the world’s pigs are bred using AI with fresh semen. Historically, AI doses have been produced using multiple billions of sperm per dose allowing acceptable farrow rates and total pigs born per litter. Following the cattle AI industry pattern, there is a continued movement within the swine industry to produce and utilize AI doses having fewer sperm per AI dose. Unexpectedly, more than a few swine producers have observed an increase in total pigs born when switching to using AI doses possessing less sperm than previously used. The objective of this report is to provide retrospective data based on thousands of services across dozens of farms showing a slight increase in number of pigs born when a production system chooses to use an AI dose with less total sperm. A secondary objective is to propose a possible explanation for the trending results. Data from a particular sow farm is provided as example. We compared farrow rates (FAR) and total number of pigs born (TBN) for sows receiving 2.5 billion total cells/AI dose (n = 758 matings) versus 2.25 billion total cells/AI dose (n = 721 matings) when bred over a 12-week period within farm. Matings were performed consecutively (i.e. 6 weeks at 2.5B and 6 weeks at 2.25B) using 70mL dose volume as conventional AI with technicians unaware of the cell number change. The mean FAR and TBN trends were 85.9% and 15.9 versus 90.0% and 16.5 for the 2.5B and 2.25B, respectively. We propose that a reduction in polyspermy may contribute to the upward fertility trend because fewer sperm may reside at the sperm reservoir leading to an increase in fertility.