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Egg freshness prediction using a comprehensive analysis based on visible near infrared spectroscopy
Spectroscopy Letters ( IF 1.7 ) Pub Date : 2020-07-03 , DOI: 10.1080/00387010.2020.1787455
Xiaoguang Dong 1, 2 , Beibei Zhang 1 , Jun Dong 1 , Bing Lu 1 , Can Hu 1 , Xiuying Tang 1
Affiliation  

Abstract The aim of this study was to calculate six single freshness indices into a synthesized indicator named “comprehensive freshness indicator” which could predict egg freshness based on visible near infrared spectroscopy. The transmission spectra were acquired in the equatorial region of 91 White Leghorn eggs. After each spectral measurement, six single freshness indices including egg shape index, yolk index, Haugh unit, albumen pH, air cell diameter and eggshell thickness were destructively measured. Pearson correlation analysis was used to analyze correlations between single indices. The six single freshness indices were calculated into the comprehensive freshness indicator based on contribution rates and load coefficients obtained from principal components analysis. A partial least squares regression with different preprocessing methods was developed to predict the six single freshness indices and the comprehensive freshness indicator based on wavelength from 480 to 960 nm. The comprehensive freshness indicator compared with single freshness indices achieved better predictive ability with predictive correlation coefficient of 0.891 and root mean square error of 1.000. The results illustrated that the comprehensive freshness indicator could predict egg freshness, while evaluation standards need further researched. Highlights Calculate a synthesized indicator named comprehensive freshness indicator (CFI). Correlations between six single freshness indices were analyzed. Build models for comprehensive and nondestructive assessment of egg freshness. Comprehensive freshness indicator (CFI) successfully predict egg freshness.

中文翻译:

基于可见近红外光谱的综合分析预测鸡蛋新鲜度

摘要 本研究的目的是将六个单一的新鲜度指标计算成一个综合指标,称为“综合新鲜度指标”,该指标可以基于可见近红外光谱预测鸡蛋的新鲜度。透射光谱是在 91 个白来航蛋的赤道地区获得的。每次光谱测量后,对蛋形指数、蛋黄指数、哈夫单位、蛋白pH、气泡直径和蛋壳厚度等6个单一新鲜度指标进行破坏性测量。Pearson相关分析用于分析单个指标之间的相关性。根据主成分分析得到的贡献率和负荷系数,将6个单项新鲜度指标计算为综合新鲜度指标。开发了具有不同预处理方法的偏最小二乘回归,以预测基于 480 至 960 nm 波长的六个单一新鲜度指数和综合新鲜度指标。综合新鲜度指标与单一新鲜度指标相比具有更好的预测能力,预测相关系数为0.891,均方根误差为1.000。结果表明综合新鲜度指标可以预测鸡蛋的新鲜度,但评价标准有待进一步研究。亮点 计算一个名为综合新鲜度指标 (CFI) 的综合指标。分析了六个单一新鲜度指数之间的相关性。建立全面和无损评估鸡蛋新鲜度的模型。
更新日期:2020-07-03
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