Prediction and visualisation of S-ovalbumin content in egg whites using hyperspectral images

Dan Dan Fu,Qiao Hua Wang,Mei Hu Ma,Yi Xiao Ma,Chin Nee Vong

doi:10.1080/10942912.2019.1628775

Abstract

ABSTRACT This study proposed a method using hyper-spectral imaging technology in determining eggs’ quality in term of freshness from a biochemical perspective by estimating the S-ovalbumin content. This method has the potential in assessing eggs’ quality rapidly and non-destructively. Hyper-spectral image of egg was captured using a hyper-spectral imaging system and regression model was built to estimate the S-ovalbumin content. The successive projections algorithm (SPA) was used to select significant wavebands followed by building a partial least squares regression (PLSR) model and a multiple linear regression (MLR) model. The MLR model could predict S-ovalbumin content better than PLSR model with a higher correlation coefficient (0.922) and lower root mean square error (0.086) of the calibration set, a higher correlation coefficient (0.911) and lower root mean square error (0.119) of the validation set, and a higher residual predictive deviation (2.348). The regression equation from the MLR model was used to compute each pixel of the image in the validation set and visualisation of S-ovalbumin content distribution in the egg was obtained using pseudo-color image. The findings implied that the proposed hyper-spectral imaging system with the regression model developed has the potential in determining and visualising the eggs’ quality.

Highlights

Eggs are one of the most important food in daily life due to its rich nutrition, which contains high protein
The spectral pretreatment methods such as savitzky-golay smoothing (SG), first derivatives (FD), second derivatives (SD), standard normal variate (SNV), multiple scattering correction (MSC), and min-max normalisation were investigated in order to gain the optimal conditions of the calibration model for S-ovalbumin content
The results indicated that the content of S-ovalbumin increases with increasing storage time (R2 = 0.954, p ≤ .01), indicating the higher the S-ovalbumin content, the less fresh the egg

Summary

Introduction

Eggs are one of the most important food in daily life due to its rich nutrition, which contains high protein. Egg quality changes during storage is complex, which include increasing egg weight loss rate, changing pH, and protein content.[1] evaluating and predicting egg quality during storage period is critical in food processing and preservation. Non-destructive testing methods for evaluating egg freshness are mainly focus on the external quality of eggs, such as weight and egg-shaped index, and the changes of basic physical and chemical indicators, for instance, nitrogen content and moisture.[2] The performance of these methods is limited to the various changes of each individual egg. there are few methods proposed to evaluate egg freshness in its biological properties

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Results

Conclusion