title: Calculated follicle deviation using segmented regression for modeling diameter differences in cattle.
abstract: Segmented linear regression alone or in combination with simple linear regression was evaluated as an objective method to calculate the beginning of follicle deviation by modeling the sequential (Experiment 1) and non-sequential or single-point (Experiment 2) differences in diameter between the future dominant (F1) and largest subordinate (F2) follicles of Wave 1 in cattle. The segmented regression consisted of Segment 1 representing the common growth phase, Segment 2 representing the period of dominance, and a Join Point connecting the two segments and representing the end of the common growth phase and the beginning of deviation. The model was fit to the diameter differences for each heifer in Experiment 1 (n=15) and the group of heifers in Experiment 2 (n=40). The optimal Join Point value that corresponded to the maximum R(2) was designated the calculated hour (Experiment 1) or diameter of F1 (Experiment 2) at the beginning of deviation. In Experiment 1, simple linear regression was used to calculate the corresponding diameter of F1 at the beginning of deviation. Observed deviation was determined by inspection of the diameter profiles of F1 and F2 for comparison to calculated deviation. In Experiment 1, the observed method determined the beginning of deviation in 80% of the heifers, whereas, the regression method calculated deviation in 93% of the heifers including two of the three heifers in which observed deviation was not discernable (no significant difference between methods). The mean hours of deviation after wave emergence (Hour 0) and diameters of F1 at the corresponding hours were not significantly different between the observed (62 h and 8.4 mm) and calculated (61 h and 8.8 mm) methods. In Experiment 2, the diameter of F1 at the beginning of calculated deviation was 8.2 mm. The results indicated that the segmented regression model can provide an objective and more accurate alternative to estimate follicle deviation, especially when observed deviation is obscured by the complexity of follicle development in some waves.
authors.affiliation: Department of Animal Health and Biomedical Sciences, University of Wisconsin, 1656 Linden Drive, Madison, WI 53706-1581, USA. drb@ahabs.wisc.edu
authors.forename: D R
authors.initials: DR
authors.lastname: Bergfelt
authors.forename: L H
authors.initials: LH
authors.lastname: Sego
authors.forename: M A
authors.initials: MA
authors.lastname: Beg
authors.forename: O J
authors.initials: OJ
authors.lastname: Ginther
mesh_terms: D000818:Animals; D002417:Cattle / Q000033:anatomy & histology*; D005260:Female; D016014:Linear Models; D006080:Ovarian Follicle / Q000033:anatomy & histology*