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AutoFom III设备在预测韩国猪胴体原始切割重量和商业切割重量方面的应用。

Application of AutoFom III equipment for prediction of primal and commercial cut weight of Korean pig carcasses.

作者信息

Choi Jung Seok, Kwon Ki Mun, Lee Young Kyu, Joeng Jang Uk, Lee Kyung Ok, Jin Sang Keun, Choi Yang Il, Lee Jae Joon

机构信息

Swine Science and Technology Center, Gyeongnam National University of Science and Technology, Jinju 52725, Korea.

Korea Institute for Animal Products Quality Evaluation, Sejong 30100, Korea.

出版信息

Asian-Australas J Anim Sci. 2018 Oct;31(10):1670-1676. doi: 10.5713/ajas.18.0240. Epub 2018 Jul 26.

Abstract

OBJECTIVE

This study was conducted to enable on-line prediction of primal and commercial cut weights in Korean slaughter pigs by AutoFom III, which non-invasively scans pig carcasses early after slaughter using ultrasonic sensors.

METHODS

A total of 162 Landrace, Yorkshire, and Duroc (LYD) pigs and 154 LYD pigs representing the yearly Korean slaughter distribution were included in the calibration and validation dataset, respectively. Partial least squares (PLS) models were developed for prediction of the weight of deboned shoulder blade, shoulder picnic, belly, loin, and ham. In addition, AutoFom III´s ability to predict the weight of the commercial cuts of spare rib, jowl, false lean, back rib, diaphragm, and tenderloin was investigated. Each cut was manually prepared by local butchers and then recorded.

RESULTS

The cross-validated prediction accuracy (R2cv) of the calibration models for deboned shoulder blade, shoulder picnic, loin, belly, and ham ranged from 0.77 to 0.86. The R2cv for tenderloin, spare rib, diaphragm, false lean, jowl, and back rib ranged from 0.34 to 0.62. Because the R2cv of the latter commercial cuts were less than 0.65, AutoFom III was less accurate for the prediction of those cuts. The root mean squares error of cross validation calibration (RMSECV) model was comparable to the root mean squares error of prediction (RMSEP), although the RMSECV was numerically higher than RMSEP for the deboned shoulder blade and belly.

CONCLUSION

AutoFom III predicts the weight of deboned shoulder blade, shoulder picnic, loin, belly, and ham with high accuracy, and is a suitable process analytical tool for sorting pork primals in Korea. However, AutoFom III's prediction of smaller commercial Korean cuts is less accurate, which may be attributed to the lack of anatomical reference points and the lack of a good correlation between the scanned area of the carcass and those traits.

摘要

目的

本研究旨在通过AutoFom III实现对韩国屠宰猪的原始切块和商业切块重量的在线预测,该设备使用超声波传感器在屠宰后早期对猪胴体进行非侵入性扫描。

方法

校准数据集和验证数据集中分别纳入了162头长白猪、大白猪和杜洛克猪(LYD)以及154头代表韩国年度屠宰分布的LYD猪。开发了偏最小二乘(PLS)模型来预测去骨肩胛骨、肩前腿肉、腹部、里脊肉和火腿的重量。此外,还研究了AutoFom III预测排骨、脸颊肉、假瘦肉、背肋、隔膜和嫩腰等商业切块重量的能力。每个切块均由当地屠夫手工制备,然后进行记录。

结果

去骨肩胛骨、肩前腿肉、里脊肉、腹部和火腿校准模型的交叉验证预测准确率(R2cv)在0.77至0.86之间。嫩腰、排骨、隔膜、假瘦肉、脸颊肉和背肋的R2cv在0.34至0.62之间。由于后几种商业切块的R2cv小于0.65,AutoFom III对这些切块的预测准确性较低。交叉验证校准(RMSECV)模型的均方根误差与预测均方根误差(RMSEP)相当,尽管去骨肩胛骨和腹部的RMSECV在数值上高于RMSEP。

结论

AutoFom III能够高精度地预测去骨肩胛骨、肩前腿肉、里脊肉、腹部和火腿的重量,是韩国猪肉原始切块分类的合适过程分析工具。然而,AutoFom III对韩国较小商业切块的预测准确性较低,这可能归因于缺乏解剖参考点以及胴体扫描区域与这些性状之间缺乏良好的相关性。

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