Interpretable Artificial Intelligence for Analysing Changes in Gases in the Uterine Environment of Cows According to Physiological Structures in the Ovary

Abstract

The objective of the present study was to examine the relationship between the gases in a cow's uterine environment and its ovarian physiological structures using the sunflower optimisation algorithm (SFOA) deployed in a device called Metris & ouml;r, developed by our project team. A total of 500 uteruses obtained from slaughtered cows served as the experimental sample. Gas measurements were taken from 489 uteruses with no clinical metritis or microbiological growth. Additionally, the diameters of the corpus luteum and follicles in the ovaries were measured using callipers. These results were then analysed based on the presence or absence of a corpus luteum (CL) and follicles larger or smaller than 1.5 cm. According to uterine gas fluctuations, the presence and absence of CL could be detected at rates of 80.60% and 79.60%, respectively. Also, based on uterine gas changes, the presence of ovarian follicles larger than 1.5 cm was determined 82% of the time, and the presence of follicles smaller than 1.5 cm was determined 80% of the time. In conclusion, it was found that different stages of a cow's sexual cycle might involve changes in uterine gases. Thus, the data from this study may enable the development of a new estrus detection method for cows.