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Shinichiro Ogawa

助教 / Assistant Professor

Kyoto University
Country flagJapan

Research Interests

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Articles (16)

Year:

2026

Year:

2026

Year:

2024

Year:

2024

Jinhua pigs have excellent meat quality and intramuscular fat content (IMF). Crossbreeding of Jinhua with Duroc pigs with high productivity was conducted to develop a new composite breed that possesses the beneficial characteristics of both breeds. The objective of this study was to estimate the crossbreeding parameters (additive breed, dominance, and epistatic loss effects) using the Kinghorn model and genetic parameters (heritability and genetic correlation) for carcass and meat quality traits by analysing the phenotypic data of Jinhua, Duroc, and their crossbred pigs. Backfat thickness at the thinnest point above the 9th to 13th thoracic vertebrae (BF), longissimus muscle area between the 4th and 5th thoracic vertebrae (LMA), meat shear force value (SFV), and IMF were measured. The additive breed effects were significant for all traits: 1.59 cm, −8.30 cm 2 , −6.38 lb/cm 2 , and 1.76% for BF, LMA, SFV, and IMF, respectively. The dominance effect was significant for LMA (7.41 cm 2 ) and IMF (−2.46%), whereas the epistatic loss effect was significant for only LMA (−15.18 cm 2 ). The estimated heritability values were high, ranging from 0.58 for IMF to 0.76 for LMA. A negative but non‐significant genetic correlation of −0.11 was estimated between BF and IMF; however, previous studies have reported that the genetic correlation between these traits is moderately positive in modern western pigs. Our results imply that, with the estimation of crossbreeding and genetic parameters, genetic improvement could be implemented to produce a new composite breed with good meat quality and productivity, to meet Japanese market requirements, by crossbreeding Jinhua and Duroc pigs.

Year:

2023

We estimated genetic parameters for two pork production and six litter performance traits of Landrace, Large White, and Duroc pigs reared in Japan. Pork production traits were average daily gain from birth to end of performance testing and backfat thickness at end of testing (46,042 records for Landrace, 40,467 records for Large White, and 42,920 records for Duroc). Litter performance traits were number born alive, litter size at weaning (LSW), number of piglets dead during suckling (ND), survival rate of piglets during suckling (SV), total piglet weight at weaning (TWW), and average piglet weight at weaning (AWW) (27,410, 26,716, and 12,430 records for Landrace, Large White, and Duroc, respectively). ND was calculated as the difference between LSW and litter size at start of suckling (LSS). SV was calculated as LSW/LSS. AWW was calculated as TWW/LSW. Pedigree data for Landrace, Large White, and Duroc breeds contained 50,193, 44,077, and 45,336 pigs, respectively. Trait heritability was estimated via single‐trait analysis and genetic correlation between two traits was estimated via two‐trait analysis. When considering the linear covariate of LSS in the statistical model for LSW and TWW, for all breeds, the heritability was estimated to be 0.4–0.5 for pork production traits and below 0.2 for litter performance traits. Estimated genetic correlation between average daily gain and backfat thickness was small, ranging from 0.057 to 0.112, and those between pork production traits and litter performance traits were negligible to moderate, ranging from −0.493 to 0.487. A wide range of genetic correlation values among the litter performance traits was estimated, while that between LSW and ND could not be obtained. The results of genetic parameter estimation were affected by whether the linear covariate of LSS was included in the statistical model for LSW and TWW or not. This finding implies the necessity of carefully interpreting the results according to the choice of statistical model. Our results could give fundamental information on simultaneously improving productivity and female reproductivity for pigs.

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (4)

Masahiro Satoh

-

JAPAN
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Keiichi Inoue

Professor

University of Miyazaki

JAPAN
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Yo Fukuzawa

Chief of gene analysis 3rd section

National Institute of Animal Science

JAPAN
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Hiroyuki Hirooka

-

JAPAN
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