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Nondestructive Determination of Diastase Activity of Honey Based on Visible and Near-Infrared Spectroscopy
- Source :
- Molecules, Vol 24, Iss 7, p 1244 (2019), Molecules, Volume 24, Issue 7
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- The activities of enzymes are the basis of evaluating the quality of honey. Beekeepers usually use concentrators to process natural honey into concentrated honey by concentrating it under high temperatures. Active enzymes are very sensitive to high temperatures and will lose their activity when they exceed a certain temperature. The objective of this work is to study the kinetic mechanism of the temperature effect on diastase activity and to develop a nondestructive approach for quick determination of the diastase activity of honey through a heating process based on visible and near-infrared (Vis/NIR) spectroscopy. A total of 110 samples, including three species of botanical origin, were used for this study. To explore the kinetic mechanism of diastase activity under high temperatures, the honey of three kinds of botanical origins were processed with thermal treatment to obtain a variety of diastase activity. Diastase activity represented with diastase number (DN) was measured according to the national standard method. The results showed that the diastase activity decreased with the increase of temperature and heating time, and the sensitivity of acacia and longan to temperature was higher than linen. The optimum temperature for production and processing is 60 &deg<br />C. Unsupervised clustering analysis was adopted to detect spectral characteristics of these honeys, indicating that different botanical origins of honeys can be distinguished in principal component spaces. Partial least squares (PLS) and least squares-support vector machine (LS-SVM) algorithms were applied to develop quantitative relationships between Vis/NIR spectroscopy and diastase activity. The best result was obtained through Gaussian filter smoothing-standard normal variate (GF-SNV) pretreatment and the LS-SVM model, known as GF-SNV-LS-SVM, with a determination coefficient (R2) of prediction of 0.8872, and root mean square error (RMSE) of prediction of 0.2129. The overall results of this paper showed that the diastase activity of honey can be determined quickly and non-destructively with Vis/NIR spectral methods, which can be used to detect DN in the process of honey production and processing, and to maximize the nutrient content of honey.
- Subjects :
- kinetic mechanism
Pharmaceutical Science
Honey production
honey
01 natural sciences
Article
Analytical Chemistry
spectral pretreatment methods
lcsh:QD241-441
0404 agricultural biotechnology
lcsh:Organic chemistry
Drug Discovery
Partial least squares regression
Food science
Physical and Theoretical Chemistry
National standard
Spectroscopy
Spectroscopy, Near-Infrared
biology
Chemistry
Spectrum Analysis
010401 analytical chemistry
Organic Chemistry
Temperature
Visible and near infrared spectroscopy
04 agricultural and veterinary sciences
040401 food science
least squares-support vector machine
0104 chemical sciences
Nutrient content
Diastase
Enzyme Activation
Kinetics
diastase activity
diastase number
Chemistry (miscellaneous)
Principal component analysis
Amylases
biology.protein
Molecular Medicine
visible and near-infrared spectroscopy
Subjects
Details
- Language :
- English
- ISSN :
- 14203049
- Volume :
- 24
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- Molecules
- Accession number :
- edsair.doi.dedup.....0771cd7e7b558379b705c8bac8776f2b