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基于智能手机的近红外光谱(NIRS)在不同温度下用于咸肉末成分诊断的可行性研究。

Feasibility study of smartphone-based Near Infrared Spectroscopy (NIRS) for salted minced meat composition diagnostics at different temperatures.

机构信息

IRTA, Food Technology Program, Finca Camps i Armet, 17121 Monells, Girona, Spain.

IRTA, Food Technology Program, Finca Camps i Armet, 17121 Monells, Girona, Spain; Universitat Rovira i Virgili, C/Marcel·lí Domingo, 1, 43007 Tarragona, Spain.

出版信息

Food Chem. 2019 Apr 25;278:314-321. doi: 10.1016/j.foodchem.2018.11.054. Epub 2018 Nov 10.

Abstract

This research work evaluates the feasibility of a smartphone-based spectrometer (740-1070 nm) for salted minced meat composition diagnostics at industrial scale. A commercially available smartphone-based spectrometer and a benchtop NIR spectrometer (940-1700 nm) were used for acquiring 1312 spectra from meat samples stored at four different temperatures ranging from -14 °C to 25 °C. Thereafter, for each spectrometer, PLS and Random Forest regression models specific for each temperature and global models were created to predict the fat, moisture and protein contents. Fat and moisture can be estimated with the global model in a wide range of temperatures by using the smartphone-based spectrometer, which has an acceptable accuracy for quality control purposes (RPD > 7) and comparable to the accuracy of a benchtop spectrometer.

摘要

本研究工作评估了基于智能手机的分光仪(740-1070nm)在工业规模下用于盐渍肉末成分诊断的可行性。使用市售的基于智能手机的分光仪和台式近红外分光仪(940-1700nm)从存储在从-14°C至25°C的四个不同温度下的肉样中采集了 1312 个光谱。此后,对于每个分光仪,为每个温度和全局模型创建了特定于 PLS 和随机森林回归模型,以预测脂肪、水分和蛋白质含量。使用基于智能手机的分光仪可以在较宽的温度范围内通过全局模型来估计脂肪和水分,其对于质量控制目的具有可接受的准确性(RPD>7),并且与台式分光仪的准确性相当。

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