24–25 Feb 2021
online event
Europe/Ljubljana timezone

Development of a Diffuse Reflectance FT-NIR Spectroscopy Method for the Shell Egg Quality Assessment

Not scheduled
20m
online event

online event

Poster agro-food

Description

Egg industries are more and more interested in non-destructive and rapid methods for the assessment of freshness and quality of shell eggs. Some studies showed that NIR spectroscopy is a valid technique to determine shell egg freshness (Lin et al., 2011) and internal quality parameters (Abdanan Mehdizadeh et al., 2014). However, poor attention has been given to the method development and none of these papers demonstrated that the acquired spectra are really representative of the egg content rather than the eggshell. Thus, the aim of this work was the evaluation of the beam penetration in a diffuse reflectance FT-NIR spectroscopy method intended for shell egg quality assessment.
To the aim, twelve eggs of different sizes were emptied and diffuse reflectance spectra were collected by using the fibre optic probe of a FT-NIR spectrometer. For each egg, four spectra were acquired in the equatorial region, in the 12,500-4,500 cm-1 range, with a resolution of 8 cm-1 and 16 scans for both sample and background. Afterwards, the eggs were filled first with ethanol and then with distilled water before collecting again the spectra in the same conditions.
Principal Component Analysis (PCA) was performed on the reduced spectra (7,300-4,200 cm-1) pre-treated with smoothing, SNV and first derivative. The score plot of the first two PCs, which explained about 96% of the variance, showed a clear pattern of the different samples. In particular, empty eggs and those filled with water were well distinguished along PC1, whereas eggshells containing ethanol showed positive values of PC2, in contrast with the negative values of the other two groups of samples. This sample distribution confirmed the beam penetration beyond the shell thickness and the reliability of the developed method.

Consider for full paper in JNIRS No, thank you

Primary authors

Prof. Cristina Alamprese (DeFENS-Università degli Studi di Milano) Dr Eleonora Loffredi (DeFENS-Università degli Studi di Milano) Dr Silvia Grassi (DeFENS-Università degli Studi di Milano)

Presentation materials