繁殖
肉牛
偏最小二乘回归
线性判别分析
数学
动物科学
生物
食品科学
统计
作者
Greta Bischof,Franziska Witte,Edwin Januschewski,Frank Schilling,Nino Terjung,Volker Heinz,Andreas Juadjur,Monika Gibis
出处
期刊:Food Chemistry
[Elsevier BV]
日期:2023-09-21
卷期号:435: 137531-137531
被引量:3
标识
DOI:10.1016/j.foodchem.2023.137531
摘要
Meat authenticity addresses parameters such as species, breed, sex, housing system and postmortem treatment. Seventy-four beef backs from two breeds ('Fleckvieh' and 'Schwarzbunt') and three cattle types (heifer, cow, young bull) were dry-aged and wet-aged up to 28 days and analyzed by 1H NMR spectroscopy. Statistical models based on partial least squares regression and discriminant analysis were performed to classify the beef samples by breed, cattle type, aging time, and aging type based on their 1H NMR spectra. The aging time of beef samples can be predicted with an error ± 2.28 days. The cattle type model has an accuracy of cross-validation of 99.2 %, the breed models of 100 % and the aging type model for 28-days aged samples of 99.6 %. These models allow the authentication of beef samples in terms of breed, cattle type, aging time, and aging type with a single 1H NMR measurement.
科研通智能强力驱动
Strongly Powered by AbleSci AI