Xie Chuanqi, He Yong
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Sci Rep. 2016 Feb 17;6:21130. doi: 10.1038/srep21130.
This study was carried out to use hyperspectral imaging technique for determining color (L*, a* and b*) and eggshell strength and identifying cracked chicken eggs. Partial least squares (PLS) models based on full and selected wavelengths suggested by regression coefficient (RC) method were established to predict the four parameters, respectively. Partial least squares-discriminant analysis (PLS-DA) and RC-partial least squares-discriminant analysis (RC-PLS-DA) models were applied to identify cracked eggs. PLS models performed well with the correlation coefficient (rp) of 0.788 for L*, 0.810 for a*, 0.766 for b* and 0.835 for eggshell strength. RC-PLS models also obtained the rp of 0.771 for L*, 0.806 for a*, 0.767 for b* and 0.841 for eggshell strength. The classification results were 97.06% in PLS-DA model and 88.24% in RC-PLS-DA model. It demonstrated that hyperspectral imaging technique has the potential to be used to detect color and eggshell strength values and identify cracked chicken eggs.
本研究旨在利用高光谱成像技术测定鸡蛋颜色(L*、a和b)和蛋壳强度,并识别破裂的鸡蛋。基于回归系数(RC)法建议的全波长和选定波长建立了偏最小二乘(PLS)模型,分别预测这四个参数。应用偏最小二乘判别分析(PLS-DA)和RC-偏最小二乘判别分析(RC-PLS-DA)模型识别破裂鸡蛋。PLS模型表现良好,L的相关系数(rp)为0.788,a为0.810,b为0.766,蛋壳强度为0.835。RC-PLS模型的L、a*、b*和蛋壳强度的rp也分别为0.771、0.806、0.767和0.841。PLS-DA模型的分类结果为97.06%,RC-PLS-DA模型的分类结果为88.24%。结果表明,高光谱成像技术有潜力用于检测鸡蛋颜色和蛋壳强度值,并识别破裂的鸡蛋。