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Increasing litter size has created the need for more sophisticated, accurate, and welfare-oriented systems for assessing the foster performance of lactating sows. The estimation of milk yield alone is not sufficient for meeting these requirements. Therefore, the aim of the current study was to develop a grading system for assessing the foster performance of lactating sows that can be easily applied in commercial farm practice. Data were collected in two German conventional farrow-to-feeder farms with a total sample size of 639 sows (4.05 ± 2.86 parities) and 1 728 litters. Besides general performance data, the piglets were weighed individually within the first 24 hours after birth and at the peak of lactation (day 18.22 ± 2.48). Based on these data, we proposed a new score referring to the milk score (MS). This score was compared with the commonly used formula for estimating milk yield (est. MY), which solely involves litter weight gain and litter size. The improvement of the developed MS allowed us to distinguish between the birth and foster performances of the lactating sows through considering cross-fostering, litter size, individual piglet weights, and piglet mortality during lactation. Both scores showed a similar progression across parities. It was found that litter size had a significant impact on the performance of lactating sows. A high est. MY was found to be associated with a significantly higher number of piglets per litter (15.79 ± 2.20), lower weight gain per piglet, and increased piglet mortality during lactation compared with sows with high MS, which showed a smaller litter size (13.51 ± 2.18) (P < 0.05). The focus on smaller litter size indicates a performance limitation, which seems to be related to the average teat number of 13-15 teats per sow. We recommend the consideration of the number of functional teats, because a litter size above it will not result in a sow having higher foster performance. In conclusion, as an extension of the common est. MY calculation, the MS considers cross-fostering as current farm-management practice when dealing with larger litters. Our recommendations emphasise the importance of an MS which indicates smaller litter size, higher piglet weight gain, and lower piglet mortality during lactation; these factors are related to an improvement in animal welfare for sows and piglets. Moreover, the presented MS could be used to develop a management tool for farmers to assess the foster performance of lactating sows, considering individual farm-management practices., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

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., Competing Interests: Author AD was employed by EVH Select GmbH, Meppen, Germany. Author HH was employed by BHZP GmbH, Dahlenburg-Ellringen, Germany. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rosengart, Chuppava, Trost, Henne, Tetens, Traulsen, Deermann, Wendt and Visscher.)