Influence of seasonal variation on post-farrowing dysgalactia syndrome (PFDS) and serum biochemistry profiles in the periparturient sow

Evaluation of circulating immune cells, analytes, and inflammatory markers in sows affected with postpartum dysgalactia syndrome

Postpartum dysgalactia syndrome (PDS) is a condition affecting periparturient sows, characterized by a reduction in milk and colostrum synthesis shortly after farrowing. Insufficient milk production results in substantial economic losses due to increased piglet morbidity/mortality and premature sow culling. Since PDS develops within a few days following farrowing, the study objectives were to determine if periparturient immune cell profiles and circulating biomarkers differ in sows affected by PDS. We hypothesized differences in immune cells, circulating analytes, and inflammatory markers would exist at farrowing in sows that subsequently developed PDS compared to healthy herd-mates. Thirty-six sows with PDS symptoms were matched by parity and day of lactation with 36 healthy control (CON) sows. Diagnosis of PDS (timepoint 2) occurred on average 9.25 ± 2.67 d after farrowing. Blood samples and litter weights were collected at farrowing (timepoint 1) and at the onset of clinical PDS (timepoint 2). Piglets from PDS sows had lower average daily gain and higher mortality than piglets from CON (P < 0.01). Aspartate aminotransferase was increased (20%; P ≤ 0.06) in PDS sows compared to CON at both timepoints. Additionally, blood urea nitrogen was increased in PDS sows at timepoint 1 and timepoint 2 (13%; P = 0.08 and 16%; P = 0.01, respectively). At timepoint 2, total protein, globulin, magnesium, and cholesterol were increased (P ≤ 0.03) while γ-glutamyl transferase and albumin were decreased (P ≤ 0.02) in PDS sows. Lipopolysaccharide-binding protein, an inflammatory biomarker, was increased (48%; P = 0.07) at timepoint 2 in PDS compared to CON sows. Collectively, these data indicate PDS sows have altered metabolism and appear immune activated compared to healthy herd-mates, and further investigation is needed to determine if PDS can be predicted at farrowing.

Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity

Precision livestock farming can combine sensors and complex data to provide a simple score of meaningful productivity, pig welfare, and farm sustainability, which are the main drivers of modern pig production. Examples include using infrared thermography to monitor the temperature of sows to detect the early stages of the disease. To take account of these drivers, we assigned 697 hybrid (BHZP db. Viktoria) sows to four parity groups. In addition, by pooling clinical findings from every sow and their piglets, sows were classified into three groups for the annotation: healthy, clinically suspicious, and diseased. Besides, the udder was thermographed, and performance data were documented. Results showed that the piglets of diseased sows with eighth or higher parity had the lowest daily weight gain [healthy; 192 g ± 31.2, clinically suspicious; 191 g ± 31.3, diseased; 148 g ± 50.3 (p < 0.05)] and the highest number of stillborn piglets (healthy; 2.2 ± 2.39, clinically suspicious; 2.0 ± 1.62, diseased; 3.91 ± 4.93). Moreover, all diseased sows showed higher maximal skin temperatures by infrared thermography of the udder (p < 0.05). Thus, thermography coupled with Artificial Intelligence (AI) systems can help identify and orient the diagnosis of symptomatic animals to prompt adequate reaction at the earliest time.