Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Effects of maternal parity on the pork quality traits of progeny

Jun-Mo Kim A , Dong-Geun Kang B , Sang-Hoon Lee C , Kyung-Bo Ko B and Youn-Chul Ryu B D
+ Author Affiliations
- Author Affiliations

A Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, 1500, Wanju, 55365, Republic of Korea.

B Division of Biotechnology, Sustainable Agriculture Research Institute, Jeju National University, Jeju, 63243, Republic of Korea.

C Division of Pediatric General and Thoracic Surgery, Cincinnati Children’s Hospital Medical Centre, Cincinnati, OH 45229, USA.

D Corresponding author. Email: ycryu@jejunu.ac.kr

Animal Production Science - https://doi.org/10.1071/AN16829
Submitted: 3 June 2016  Accepted: 19 June 2017   Published online: 7 August 2017

Abstract

This study aimed to identify the influence of sow parity on the meat quality of progeny. A total of 656 progeny from 196 sows were categorised into three different groups based on parity: stage 1 (gilt), 2 (second to fourth parities), and 3 (over fifth parity). According to the significant differences between the parity stage groups in the multiple meat quality properties (P < 0.05), the parity stage 1 had higher muscle pH and lower drip loss in meat quality traits and showed smaller area composition of type IIb muscle fibres in muscle fibre characteristics than the other older groups. Moreover, the parity stage 1 group had significantly higher springiness, adhesiveness and chewiness (P < 0.001), whereas the stage 3 group showed relatively lower cohesiveness (P < 0.05) in the meat texture properties. The principal component analysis displayed more distance between stage 1 and other two groups than the distance between stage 2 and 3. Therefore, we suggest that maternal parity may affect pork quality in progeny and the younger stage group could have better meat quality than the older group.

Additional keywords: meat texture analysis, muscle fibre characteristics, principal component analysis, sow parity.


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