Non-destructive freshness assessment of shell eggs using FT-NIR spectroscopy

Non-destructive freshness assessment of shell eggs using FT-NIR spectroscopy
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DOI:
10.1016/j.jfoodeng.2008.04.013
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发表时间:
2008-11-01
影响因子:
5.5
通讯作者:
Silaghi, Florina Aurelia
Silaghi, Florina Aurelia
中科院分区:
农林科学1区
文献类型:
--
作者:
Giunchi, Alessandro;Berardinelli, Annachiara;Silaghi, Florina Aurelia

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利用傅立叶变换近红外光谱仪和光纤探头对20 ℃下贮藏16天的带壳鸡蛋进行了无损新鲜度评估。在833-2500 nm的光谱范围内,从三个不同的农场收集的鸡蛋样品上获得漫反射光谱。以不同的饲养方法为特点。在每次光谱采集后,破坏性地测量新鲜度参数,如气室高度、厚蛋白高度和哈氏单位。对于每种饲养方法,主成分分析(PCA),偏最小二乘回归(PLS)和偏最小二乘判别分析(PLS-DA),进行了建立模型,以预测新鲜度参数和分类鸡蛋样品根据存储的日子。还进行了层次聚类分析,以测试在不同天数的存储和饲养方法的值之间的相似性。预测模型显示,气室高度、厚蛋白高度和Haugh单位的R-2值分别高达0.722、0.789和0.676(测试集验证)。鸡蛋样品被正确分类(100%),根据储存的日子。层次聚类分析表明,低水平的异质性的三种饲养方法内的存储天。(c)2008爱思唯尔有限公司保留所有权利。
Non-destructive freshness assessment of shell eggs during 16 days of storage at 20 degrees C was carried out by means of an FT-NIR spectrometer and a fiber optic probe. Diffuse reflectance spectra were acquired in the spectral range 833-2500 nm on samples of eggs collected from three different farms. characterized by different rearing methods. After each spectral acquisition, the freshness parameters such as air cell height, thick albumen heights and Haugh unit were destructively measured. For each rearing method, PCA (principal component analysis), PLS (partial least square regression) and PLS-DA (partial least square discriminant analysis), were carried out in order to set up models to predict the freshness parameters and to classify egg samples according to the days of storage. Hierarchical cluster analysis was also conducted to test similarity between values at different days of storage and rearing methods. Predictive models showed R-2 value up to 0.722, 0.789 and 0.676 for air cell height, thick albumen heights and Haugh unit, respectively (test set validations). Egg samples were correctly classified (100%) according to the days of storage. Hierarchical cluster analysis showed a low level of heterogeneity for the three rearing methods within the days of storage. (c) 2008 Elsevier Ltd. All rights reserved.