Nondestructive Determination of Diastase Activity of Honey Based on Visible and Near-Infrared Spectroscopy

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 °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.

Keywords: diastase activity; diastase number; honey; kinetic mechanism; least squares-support vector machine; spectral pretreatment methods; visible and near-infrared spectroscopy.

Figure 1

DN of the heat-treated honeys. Changes of diastase number in acacia, linen and longan honeys with different heating conditions.

Figure 2

Visible (400–780 nm) and near-infrared (780–1000 nm) spectra of all the 110 honeys samples. Vis/NIR spectra of acacia (n = 37), linen (n = 35) and longan (n = 38) honeys.

Figure 3

Cluster analysis of origins of honey from three botanical origins. (AC, LE, and LG represent acacia, linen, and longan separately). Acacia honeys can be clearly distinguished from linen and longan honeys, and the results of the cluster between linen and longan honeys are closed.

Figure 4

Measured vs. predicted diastase numbers in honeys by GF-SNV-LS-SVM models based on the characteristic wavelengths (Cal and Pre represent calibration and prediction, separately).

Figure 5

Characteristic wavelengths of the spectra based on the pretreatment of GF-SNV. SPA selected 6 characteristic wavelengths in red dot.

Figure 6

The configuration of the Vis/NIR spectroscopy imaging system. The probe receives the spectral information and transmits it to the spectrometer through the optical fiber. The spectrometer transmits the spectral information to the computer through the data line.