title: Use of combinations of in vitro quality assessments to predict fertility of bovine semen.
abstract: Predicting in vivo fertility of bull ejaculates using in vitro-assessed semen quality criteria remains challenging for the breeding industry. New technologies such as computer-assisted semen analysis (CASA) and flow cytometry may provide accurate and objective methods to improve semen quality control. The aim of this study was to evaluate the relationship between semen quality parameters and field fertility of bull ejaculates. A total of 153 ejaculates from 19 Holstein bulls have been analyzed using CASA (postthawing semen motility and morphology) and several flow cytometric tests, including sperm DNA integrity, viability (estimated by membrane integrity), acrosomal integrity, mitochondria aerobic functionality and oxidation. Samples were analyzed both immediately after thawing and after 4 hours at 37 °C. A fertility value (FV), based on nonreturn rate at 56 days after insemination and adjusted for environment factors, was calculated for each ejaculate. Simple and multiple regressions have been used to correlate FV with CASA and flow cytometric parameters. Significant simple correlations have been observed between some parameters and FV (e.g., straight line velocity [μm/s], r(2) = -0.12; polarized mitochondria sperm (%), r(2) = 0.07), but the relation between simple parameter and FV was too week to predict the fertility. Partial least square procedure identified several mathematical models combining flow cytometer and CASA variables and had better correlations with FV (adjusted r(2) ranging between 0.24 and 0.40 [P < 0.0001], depending on the number of included variables). In conclusion, this study suggests that quality assessment of thawed bull sperm using CASA and flow cytometry may provide a reasonable prediction of bovine semen fertility. Additional work will be required to increase the prediction reliability and promote this technology in routine artificial insemination laboratory practice.
authors: R&D Department, ALLICE, Paris, France. Electronic address: eli.sellem@allice.fr.
authors: E
authors: E
authors: Sellem
authors: Innovation Department, CRV B.V., Arnhem, The Netherlands.
authors: M L W J
authors: ML
authors: Broekhuijse
authors: R&D Department, IMV Technologies, L'Aigle, France.
authors: L
authors: L
authors: Chevrier
authors: R&D Department, IMV Technologies, L'Aigle, France.
authors: S
authors: S
authors: Camugli
authors: R&D Department, IMV Technologies, L'Aigle, France.
authors: E
authors: E
authors: Schmitt
authors: R&D Department, ALLICE, Paris, France.
authors: L
authors: L
authors: Schibler
authors: Innovation Department, CRV B.V., Arnhem, The Netherlands.
authors: E P C
authors: EP
authors: Koenen
mesh_terms: D000818:Animals; D002417:Cattle / Q000502:physiology*; D002462:Cell Membrane; D005298:Fertility / Q000502:physiology; D005434:Flow Cytometry; D007091:Image Processing, Computer-Assisted; D008297:Male; D010084:Oxidation-Reduction; D011237:Predictive Value of Tests; D011786:Quality Control; D055101:Semen Analysis / Q000379:methods / Q000592:standards / Q000662:veterinary*
keywords: Bovine semen; Computer-assisted semen analysis system; Fertility prediction; Flow cytometry; Sperm assessment