{"id":3371,"date":"2023-01-17T07:36:11","date_gmt":"2023-01-17T07:36:11","guid":{"rendered":"https:\/\/genus-develop.go-vip.co\/pic-gb\/?post_type=resources&p=3371"},"modified":"2023-10-09T14:38:44","modified_gmt":"2023-10-09T13:38:44","slug":"dr-saskia-bloemhof-pic-camera-scores-pigs-better-than-humans-can","status":"publish","type":"resources","link":"https:\/\/genus-develop.go-vip.co\/pic-gb\/resources\/dr-saskia-bloemhof-pic-camera-scores-pigs-better-than-humans-can\/","title":{"rendered":"Dr Saskia Bloemhof (PIC): \u201cCamera scores pigs better than humans can\u201d"},"content":{"rendered":"\n

Swine genetics company PIC applies digital selection to determine breeding values. With the right software, the possibilities are endless, says the company\u2019s Genetic Services Director, Dr Saskia Bloemhof.<\/em><\/strong><\/p>\n\n\n\n

Data play a significant role in breeding to take genetic expression to the next level. In addition to sharing and interpreting data from developments for estimating breeding values, technological means such as cameras offer more possibilities for objective observations and creation of new phenotypes. In China, for example, facial recognition technology for pig identification has been underway for some years. This has not yet resulted in systems that can be used in practice, partly because pigs differ little from each other in appearance.<\/strong><\/p>\n\n\n\n

Automatic interpretation of images<\/h2>\n\n\n\n

However, the use of cameras and digital imaging still has the potential to have a large impact at the pen and\/or pig level. The biggest challenge lies in the automatic interpretation of images and drawing conclusions based on those images. Dr Saskia Bloemhof is Genetic Services Director at PIC. She says, \u201cDigital selection is still in its infancy, but there are many possibilities. To get a better grip on this, we started working with Professor Dr Tomas Norton from the Catholic University (KU) Leuven in Belgium in 2020. PIC currently employs two engineers who solely focus on translating video images into usable data.\u201d The company now uses digital selection to determine leg scores of breeding gilts and boars.<\/p>\n\n\n\n

She explains, \u201cWe have been working for decades with a leg score for how a pig stands on its front and hind legs. Employees are trained to score gilts on a scale of 1 to 10. Ideal front scores are 5\u20136, back between 5 and 10. Good or bad feet and legs are easily identified, but the difference between a 4 and a 5 score, for instance, can be subjective. Until now the industry has remained dependent on the human eye.\u201d<\/p>\n\n\n\n

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But still, scoring the leg remains important.<\/h2>\n\n\n\n

\u201cThe leg score has proven itself in breeding, and animals with a better score have better longevity; but it remains subjective. A gilt can still get a different score from different employees. Labour efficiency also plays a role. It is difficult to get and keep good and trained employees. Of course, you can always correct a breeding value estimate, but you really do not want that. By having the gilts walk past a camera that is recording the angles of movement, a more objective assessment can be made.\u201d<\/p>\n\n\n\n

Can you explain that?<\/h2>\n\n\n\n

\u201cWe have had software built that assesses the camera images. The software is based on the ratings of our top evaluator. We let the gilts walk past that camera at the end of the test period and the programme automatically evaluates their movements. The engineers are also constantly updating the programme to optimise the score. It might sound a bit na\u00efve, but at first, we assumed that we needed a full-view image, so we adjusted a piece of fencing near the camera to only get the animal in the video. And then the engineers told us that it was not necessary; because it is constantly in the video, the fencing can be filtered out.\u201d<\/p>\n\n\n\n