Estimation of Growth Curves and Suitable Slaughter Weight of the Liangshan Pig
The Liangshan pig is a traditional Chinese small-sized breed; it has a relatively long feeding period and low meat production ability but superior meat quality. This study utilized three non-linear growth models (Von Bertalanffy, Gompertz, and logistic) to fit the growth curve of Liangshan pigs from...
| Veröffentlicht in: | Asian-Australasian journal of animal sciences. - 1998. - 28(2015), 9 vom: 20. Sept., Seite 1252-8 |
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| Weitere Verfasser: | , , , , , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2015
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| Zugriff auf das übergeordnete Werk: | Asian-Australasian journal of animal sciences |
| Schlagworte: | Journal Article Growth Curve Growth Development Liangshan Pig Non-linear Model Slaughter Weight |
| Zusammenfassung: | The Liangshan pig is a traditional Chinese small-sized breed; it has a relatively long feeding period and low meat production ability but superior meat quality. This study utilized three non-linear growth models (Von Bertalanffy, Gompertz, and logistic) to fit the growth curve of Liangshan pigs from an unselected, random-bred pig population and estimate the pigs most suitable slaughter weight. The growth development data at 20 time points of 275 Liangshan pigs (from birth to 250 d) were collected. To analyze the relative gene expression related to development, seven slaughter weight phases (50, 58, 66, 74, 82, 90, and 98 kg) (20 pigs per phase) were examined. We found that the Liangshan pig growth curve fit the typical S-curve well and that their growth turning point was 193.4 days at a weight of 62.5 kg, according to the best fit Von Bertalanffy model based on the goodness of fit criteria. Furthermore, we estimated that the most suitable slaughter weight was 62.5 to 74.9 kg based on the growth curve and the relative expression levels of growth-related genes |
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| Beschreibung: | Date Completed 02.09.2015 Date Revised 30.09.2020 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1011-2367 |
| DOI: | 10.5713/ajas.15.0010 |