Rapid non-destructive monitoring and quality assessment of the fumigation process of Shanxi aged vinegar based on Vis-NIR hyperspectral imaging combined with multiple chemometric algorithms.
Spectrochim Acta A Mol Biomol Spectrosc
; 320: 124539, 2024 Nov 05.
Article
in En
| MEDLINE
| ID: mdl-38870693
ABSTRACT
The quality of the grains during the fumigation process can significantly affect the flavour and nutritional value of Shanxi aged vinegar (SAV). Hyperspectral imaging (HSI) was used to monitor the extent of fumigated grains, and it was combined with chemometrics to quantitatively predict three key physicochemical constituents moisture content (MC), total acid (TA) and amino acid nitrogen (AAN). The noise reduction effects of five spectral preprocessing methods were compared, followed by the screening of optimal wavelengths using competitive adaptive reweighted sampling. Support vector machine classification was employed to establish a model for discriminating fumigated grains, and the best recognition accuracy reached 100%. Furthermore, the results of partial least squares regression slightly outperformed support vector machine regression, with correlation coefficient for prediction (Rp) of 0.9697, 0.9716, and 0.9098 for MC, TA, and AAN, respectively. The study demonstrates that HSI can be employed for rapid non-destructive monitoring and quality assessment of the fumigation process in SAV.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Algorithms
/
Fumigation
/
Acetic Acid
/
Spectroscopy, Near-Infrared
/
Hyperspectral Imaging
Language:
En
Journal:
Spectrochim Acta A Mol Biomol Spectrosc
Journal subject:
BIOLOGIA MOLECULAR
Year:
2024
Document type:
Article
Country of publication:
Reino Unido