Variations in the body surface temperature of sows during the post weaning period and its relation to subsequent reproductive performance

Technological Tools and Artificial Intelligence in Estrus Detection of Sows-A Comprehensive Review

In animal farming, timely estrus detection and prediction of the best moment for insemination is crucial. Traditional sow estrus detection depends on the expertise of a farm attendant which can be inconsistent, time-consuming, and labor-intensive. Attempts and trials in developing and implementing technological tools to detect estrus have been explored by researchers. The objective of this review is to assess the automatic methods of estrus recognition in operation for sows and point out their strong and weak points to assist in developing new and improved detection systems. Real-time methods using body and vulvar temperature, posture recognition, and activity measurements show higher precision. Incorporating artificial intelligence with multiple estrus-related parameters is expected to enhance accuracy. Further development of new systems relies mostly upon the improved algorithm and accurate data provided. Future systems should be designed to minimize the misclassification rate, so better detection is achieved.

Using deep learning to accurately detect sow vulva size in a group pen with a single camera

This paper presents a non-contact method for the detection of changes in sow vulva size in a group pen. The traditional approach to estrus detection is manually pressing down on the back of the sow to elicit standing responses; however, this method causes undue distress for sows not in estrus. When a sow is in estrus, the vulva is red and swollen due to the presence of endocrine. Monitoring changes in vulva size to detect estrus with as little impact on the sow as possible is the focus of this study. This is achieved using a single camera combined with a deep learning framework. Our approach comprises two steps: vulva detection and vulva size conversion. Images of sows of Yorkshire, Landrace, and Duroc breeds were collected in group housing, and the vulva was detected through artificial markers and the network architecture of YOLO v4. Based on the internal and external parameters of the camera, the detected size was converted into millimeters and the results of manual measurement (MM) and automatic calculation combined to calculate the size of the vulva. Analysis of the calculated size compared with MM indicates that the object recognition rate of the system exceeds 97.06%, with a size error of only + 1.70 to -4.47 mm and high-calculation efficiency (>2.8 frames/s). Directions for future research include the automatic detection of pig width.

Infrared thermography as a possible technique for the estimation of parturition onset in sows

BACKGROUND

This study explores the possibility of using infrared thermography to estimate the onset of parturition in sows. Infrared camera (IRC) and infrared laser thermometer (IRT) were used to obtain the auricular skin temperature of sows along with rectal temperatures, from approximately one week before the anticipated farrowing until 24 h post-partum. Three commercial piglet producing farms were included in the study.

RESULTS

There were large variations in observed auricular skin temperature, both by IRC and IRT per time point. Graphical exploration of the observed auricular skin temperature measured by the two methods showed the same parallel patterns, although temperatures measured by IRC were higher at any time point compared to IRT. Auricular skin thermography revealed a clear increase in temperatures before farrowing. Statistical analyses, adjusting for differences between farms, sow activity and respiration rate, confirmed this increase. When controlling for these variables, and comparing the baseline temperatures to temperatures at farrowing, the difference was 3.9 and 4.1 °C measured with IRT and IRC, respectively. The greatest increase, of more than 2 °C, was found between 16 and 8 h and 8 to 4 h before farrowing. Rectal temperature increased by 0.5 °C in the same time interval and reached a temperature peak after farrowing.

CONCLUSION

Sows showed a more than 2 °C increase in auricular skin temperature, measured by either IRC or IRT, 8 to16 hours before the first piglet was born. Hence, monitoring auricular skin temperatures of sows using infrared thermography one week before expected farrowing may provide a baseline temperature for each sow from which a sudden rise is indicative of parturition in the following 8 to 16 h. This may lead to more efficient allocation of human assistance during farrowing time and thereby improve farrowing management and the welfare of sows and their offspring.

Thermoregulation mechanisms and perspectives for validating thermal windows in pigs with hypothermia and hyperthermia: An overview

Specific anatomical characteristics make the porcine species especially sensitive to extreme temperature changes, predisposing them to pathologies and even death due to thermal stress. Interest in improving animal welfare and porcine productivity has led to the development of various lines of research that seek to understand the effect of certain environmental conditions on productivity and the impact of implementing strategies designed to mitigate adverse effects. The non-invasive infrared thermography technique is one of the tools most widely used to carry out these studies, based on detecting changes in microcirculation. However, evaluations using this tool require reliable thermal windows; this can be challenging because several factors can affect the sensitivity and specificity of the regions selected. This review discusses the thermal windows used with domestic pigs and the association of thermal changes in these regions with the thermoregulatory capacity of piglets and hogs.

Morphometric changes on the vulva from proestrus to oestrus of nulliparous and multiparous HYPERPROLIFIC sows

The aim of this study was to assess whether vulvar morphometric changes occurring in female pigs during proestrus and oestrus could be objective, accurate and predictive indicators of the onset to oestrus and thus performed artificial inseminations at the most appropriate time. For that purpose, pictures of vulvas from 60 hyperprolific females (30 gilts and 30 sows) during proestrus and oestrus were taken once a day. Vulva measurements (area, perimeter, length and width) on these pictures were performed using the image processing ImageJ software. Gilts and sows showed statistical differences (p < .01) in all vulvar morphometric measurements between proestrus and oestrus. Statistical differences in vulvar metrics were detected 24 h before the onset to oestrus, affecting all vulvar measurements in gilts, whereas only vulvar width was affected in sows. The image analysis used in this study may contribute to the development of smart technology in swine farming.