Precision technologies to address dairy cattle welfare: focus on lameness, mastitis and body condition

Specific animal-based indicators that can be used to predict animal welfare have been the core of protocols for assessing the welfare of farm animals, such as those produced by the Welfare Quality project. At the same time, the contribution of technological tools for the accurate and realtime assessment of farm animal welfare is also evident. The solutions based on technological tools fit into the precision livestock farming (PLF) concept, which has improved productivity, economic sustainability, and animal welfare in dairy farms. PLF has been adopted recently; nevertheless, the need for technological support on farms is getting more and more attention and has translated into significant scientific contributions in various fields of the dairy industry, but with an emphasis on the health and welfare of the cows. This review aims to present the recent advances of PLF in dairy cow welfare, particularly in the assessment of lameness, mastitis, and body condition, which are among the most relevant animal-based indications for the welfare of cows. Finally, a discussion is presented on the possibility of integrating the information obtained by PLF into a welfare assessment framework.FE1B-06B2-126F | Jos? Pedro Pinto de Ara?joN/

Farm Animals’ Behaviors and Welfare Analysis with AI Algorithms: A Review

peer reviewedNumerous bibliographic reviews related to the use of AI for the behavioral detection of farm animals exist, but they only focus on a particular type of animal. We believe that some techniques were used for some animals that could also be used for other types of animals. The application and comparison of these techniques between animal species are rarely done. In this paper, we propose a review of machine learning approaches used for the detection of farm animals’ behaviors such as lameness, grazing, rumination, and so on. The originality of this paper is matched classification in the midst of sensors and algorithms used for each animal category. First, we highlight the most implemented approaches for different categories of animals (cows, sheep, goats, pigs, horses, and chickens) to inspire researchers interested to conduct investigation and employ the methods we have evaluated and the results we have obtained in this study. Second, we describe the current trends in terms of technological development and new paradigms that will impact the AI research. Finally, we critically analyze what is done and we draw new pathways of research to advance our understanding of animal’s behaviors

Sperm quality, semen production, and fertility in young Norwegian Red bulls

Ved bruk av genomisk seleksjon i storfeavlen blir eliteokser selektert basert på deres estimerte genomiske avlsverdier i stedet for ved avkomsgransking. Oksene er derfor yngre når de blir tatt i bruk i sædproduksjon enn tidligere. Hovedmålet med denne avhandlingen var å identifisere nye indikatorer for når sædproduksjonen er i gang hos unge Norsk Rødt Fe okser, og som kan måles i løpet av testperioden og gi informasjon om oksenes potensielle fremtidige sædproduksjon, aksept for semin-stasjonen samt fruktbarhet i felt. I Artikkel 1 ble flowcytometri og Computer-Aided Sperm Analysis brukt til å analysere ulike spermiekvalitetsparametere i ejakulater fra 65 okser i alderen 9-13 måneder. Sædprøver ble utsatt for stresstester og kryokonservering. Oksene ble klassifisert i tre grupper med ulik respons på spermie-stresstester. Ved å benytte spermie-stresstester, kryokonservering og morfologianalyse tidlig i testperioden, kan en få verdifull innsikt i når oksene er tilstrekkelig utviklet for sædproduksjon. Med denne tilnærmingen vil en kunne ta i bruk yngre okser i sæduttak og -produksjon, og dermed bidra til redusert generasjonsintervall og økt genetisk framgang. I Artikkel 2 ble det fokusert på å undersøke potensialet til insulin-like factor 3 som en biomarkør for å predikere når sædproduksjonen starter hos unge Norsk Rødt Fe okser. Det ble tatt blodprøver og samtidig utført målinger av skrotumomkrets på 142 okser på fire tidspunkt mellom 2 og 12 måneders alder. Studien hadde som mål å belyse sammenhenger mellom nivået av insulin-like factor 3, skrotumomkrets og ulike sædparametere. Det ble funnet en positiv korrelasjon mellom insulin-like factor 3 og skrotumomkretsen, men det ble ikke funnet signifikante sammenhenger mellom skrotumomkretsen og sædparametere. På grunn av betydelige individuelle variasjoner i den undersøkte norske okse-populasjonen, er insulin-like factor 3 foreløpig ikke en egnet biomarkør til å kunne predikere når sædproduksjonen starter hos denne rasen. I Artikkel 3 presenteres en automatisert metode for å måle skrotumomkretsen hos Norsk Rødt Fe okser ved hjelp av 3D-bilder og konvolusjonelle nevrale nettverk. 3D-bilder ble tatt samtidig som manuelle målinger av skrotumomkretsen ble utført på oksene, noe som ble gjentatt ved ulike aldere. Studien sammenlignet de manuelle og automatiserte målingene oppnådd ved semantisk segmentering. Det ble vist at de automatiserte målingene av skrotumomkretsen ga tilsvarende resultater som de manuelle målingene. Gjennomsnittlig prediksjonsfeil varierte med oksenes alder og kvaliteten på 3D-bildene. Denne nye målemetoden har potensiale til å kunne implementeres i breeding soundness evaluation ved testings- og seminstasjoner, og kan gi en rask og effektiv vurdering av skrotumomkretsen.Abstract. With the application of genomic selection in dairy cattle breeding, the choice of elite sires is based on their estimated genomic breeding values instead of progeny testing. Consequently, bulls are introduced into semen production at a younger age than previously. The main aim of this thesis was to identify novel early indicators of sperm production onset and maturity status of young Norwegian Red bulls during their performance test period, to provide insight into their potential future semen production, acceptance for the AI station, and field fertility. In Paper 1, flow cytometry and computer-aided sperm analysis were used to analyse various sperm quality parameters in ejaculates collected from 65 bulls aged 9-13 months. Semen samples were subjected to stress tests and cryopreservation. The bulls were classified into three clusters with different responses to sperm stress tests. By incorporating sperm stress tests, cryopreservation, and early morphology analysis, valuable insights into the maturity of bulls for sperm production could be gained. This approach would allow for the integration of younger bulls into semen collection, facilitating reduced generation interval and increased genetic gain. The focus in Paper 2 is on investigating the potential of insulin-like factor 3 as a biomarker for predicting the onset of sperm production in young Norwegian Red bulls. Blood samples and scrotal circumference measurements were collected from 142 bulls at four time-points between 2 and 12 months of age. The aim of the study was to determine the relationship between insulin-like factor 3, scrotal circumference, and semen characteristics. While a positive correlation was found between insulin-like factor 3 and scrotal circumference, no significant correlations were observed between scrotal circumference and semen characteristics. Due to the substantial interindividual variability in the Norwegian Red bull population, insulin-like factor 3 is currently not a reliable biomarker for predicting the onset of sperm production in this breed. In Paper 3 an automated method for measuring scrotal circumference of Norwegian Red bulls using 3D images and convolutional neural networks is presented. 3D images were captured, and manual scrotal circumference measurements made of bulls at different ages. The study compared the manual and automated measurements obtained through semantic segmentation. The results showed that the automated scrotal circumference measurements were similar to manual measurements. Mean prediction error varied depending on bull age and image quality. This novel measurement method has the potential to be implemented in bull breeding soundness evaluations at performance test stations and semen collection centers, providing a fast and efficient approach for assessing scrotal circumference.publishedVersio