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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Simple Summary

The efficiency of swine production measured as litter size influences the profitability of the pig industry. Furthermore, sow fertility potential depends in part on the boar semen quality and reproductive efficiency. The objective of this study is to compare boar sperm head size and morphometric features of shape to evaluate their relationships with reproductive success after artificial insemination (AI). A morphometric analysis of boar ejaculate reveals morphometrically separate sub-populations. The differences between sub-populations are displayed for sperm head size. In addition, sperm clustering into sub-populations did not have a predictive capacity on litter size variables. Nevertheless, the morphometric variables of the sperm may have a predictive, albeit reduced, capacity regarding litter size variables. The results of this study therefore open up possibilities for future assessments of fertility.

Abstract

The aim of the study was to compare the morphometric features of sperm head size and shape from the Pietrain line and the Duroc × Pietrain boar crossbred terminal lines, and to evaluate their relationship with reproductive success after artificial insemination of sows produced from crossbreeding the York, Landrace and Pietrain breeds. Semen samples were collected from 11 sexually mature boars. Only ejaculates with greater than 70% motility rate and <15% of abnormal sperm were used for artificial inseminations (AI) and included in the study. Samples were analyzed using an ISAS®v1 computer-assisted sperm analysis system for eight morphometric parameters of head shape and size (CASA-Morph). Sub-populations of morphometric ejaculates were characterized using multivariate procedures, such as principal component (PC) analysis and clustering methods (k-means model). Four different ejaculate sub-populations were identified from two PCs that involved the head shape and size of the spermatozoa. The discriminant ability of the different morphometric sperm variables to predict sow litter size was analyzed using a receiver operating characteristics (ROC) curve analysis. Sperm head length, ellipticity, elongation, and regularity showed significant predictive capacity on litter size (0.59, 0.59, 0.60, and 0.56 area under curve (AUC), respectively). The morphometric sperm sub-populations were not related to sow litter size.

Details

Title
Predictive Capacity of Boar Sperm Morphometry and Morphometric Sub-Populations on Reproductive Success after Artificial Insemination
Author
Barquero, Vinicio 1   VIAFID ORCID Logo  ; Roldan, Eduardo R S 2 ; Soler, Carles 3 ; Yániz, Jesús L 4   VIAFID ORCID Logo  ; Camacho, Marlen 1 ; Valverde, Anthony 1   VIAFID ORCID Logo 

 Animal Reproduction Laboratory, School of Agronomy, Costa Rica Institute of Technology, San Carlos Campus, Alajuela 223-21002, Costa Rica; [email protected] (V.B.); [email protected] (M.C.) 
 Department of Biodiversity and Evolutionary Biology, Museo Nacional de Ciencias Naturales (CSIC), 28006 Madrid, Spain; [email protected] 
 Department of Cellular Biology, Functional Biology and Physical Anthropology, University of Valencia, Campus Burjassot, C/Dr Moliner 50, 46100 Burjassot, Spain; [email protected] 
 BIOFITER Research Group, Higher Polytechnic School of Huesca, Institute of Environmental Sciences of Aragón (IUCA), University of Zaragoza, Ctra. Cuarte s/n, 22071 Huesca, Spain; [email protected] 
First page
920
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20762615
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2528299139
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.