Analysis of short videos of bovine embryos can detect presence of cryodamage

Abstract

Cryopreservation of bovine embryos has transformed animal breeding strategies by allowing storage of genetic material which enables efficient recipient utilization, sale and market­ing of embryos, and shipping and transport of embryos around the world. Advancements have been made in cryopreserva­tion techniques including the introduction of direct transfer ethylene glycol media, controlled rate freezers allowing pre­cise temperature control of the freezing curve and vitrifica­tion techniques. However, little advancement has been made to evaluate embryo survival of cryopreservation which results in the transfer of embryos which have suffered cryodamage and have no chance of establishing a pregnancy. The objective of this study was to use graphic image processing (GIP) and machine-learning (ML) techniques to evaluate embryo health post-cryopreservation.