Spectral technology and multispectral imaging for estimating the photosynthetic pigments and SPAD of the Chinese cabbage based on machine learning

Honey is known for its content of biomolecules, such as enzymes. The enzymes of honey originate from bees, plant nectars, secretions or excretions of plant-sucking insects, or from microorganisms such as yeasts. Honey can be characterized by enzyme-catalyzed and non-enzymatic reactions. Notable examples of enzyme-catalyzed reactions are the production of hydrogen peroxide through glucose oxidase activity and the conversion of hydrogen peroxide to water and oxygen by catalase enzymes. Production of hydroxymethylfurfural (HMF) from glucose or fructose is an example of non-enzymatic reactions in honey.

/pdf/biochemical-reactions-and-their-biological-contributions-in-v5vmneo4.pdf

Biochemical Reactions and Their Biological Contributions in Honey

Properties and composition of honey are essential in providing information regarding their quality as well as in their differentiation based on production region characteristics, e.g., floral sources. This paper presents physicochemical properties and floral sources (botanical origin) of 21 honey samples obtained from arid and semiarid areas of Kenya, specifically, West Pokot, Baringo, and Kitui Counties. Physicochemical parameters which were analyzed to determine honey quality included moisture content, hydroxymethylfurfural (HMF), diastase activity, free acidity, and electrical conductivity. Values of these parameters were compared with those of the existing local, regional, and international standards for honey. Melissopalynological analysis (pollen analysis) was also carried out to provide information on botanical origin of the honeys. Results showed mean parameter values of moisture, 16.34%; HMF, 23.28 mg/kg; diastase activity, 10.67 Schade units; free acidity, 22.95 meq/kg; and electrical conductivity, 0.40 mS/cm. Free acidity and electrical conductivity values of honey samples obtained from West Pokot were significantly lower than the values of honeys from Baringo and Kitui. Eighteen (18) honey samples had all parameter values within the limits set in the East African, Codex Alimentarius, and the European Union directive standards for honey. Results also showed a total of 29 pollen types in the honey samples analyzed, and Acacia spp. was the predominant pollen type in 4 of the 21 honey samples. Findings of this study showed that Kenyan origin honeys can tap into the existing regional and international markets based on their quality which can be attributed to their botanical origin. Results of this study also suggested that honey producers have undertaken appropriate measures in honey harvesting, processing, handling, and storage. However, there is a need to build capacity of producers whose honey were of unacceptable quality. This would involve training on proper honey production, processing, and handling practices as well establishment of honey collection and processing centres at the local level in order to improve honey quality. This will enhance access to existing honey markets. Conservation of bee floral sources would also be needed to maintain honey quality.

/pdf/characterization-of-kenyan-honeys-based-on-their-5gqip1ruzm.pdf

Characterization of Kenyan Honeys Based on Their Physicochemical Properties, Botanical and Geographical Origin.

Quantitative prediction models for sensory quality scores, total catechins, and caffeine based on near-infrared spectroscopy were established for different quality grades of Yuezhou Longjing tea. One-way ANOVA and multiple comparison test analyses were first conducted on the obtained sensory quality scores and physical and chemical quality indices to check the accuracy and reliability of the experimental data. There were significant differences in the sensory quality, total catechins, and caffeine of different grades of tea. Secondly, the obtained near-infrared spectrum data were preprocessed, and then the competitive adaptive reweighted sampling (CARS) and variables combination population analysis combined with iterative retained information variable algorithm (VCPA-IRIV) were used to screen the optimal characteristic wavenumbers of each quality index. Along with principal component analysis (PCA) to establish prediction models for the partial least squares regression (PLSR), support vector regression (SVR), and random forest algorithm (RF). The results showed that the best predictive models for sensory scores, total catechins, and caffeine were VCPA-IRIV + SVR, VCPA-IRIV + RF, and CARS + SVR, and the relative percent deviation (RPD) were 2.485, 2.584, and 2.873, respectively. Indicates that the model has good predictive performance. In conclusion, it is feasible to evaluate the quality of Yuezhou Longjing tea with near-infrared spectroscopy. 

Establishment of a rapid detection model for the sensory quality and components of Yuezhou Longjing tea using near-infrared spectroscopy

Robustness and accuracy evaluation of moisture prediction model for black tea withering process using hyperspectral imaging

Improved generalization of spectral models associated with Vis-NIR spectroscopy for determining the moisture content of different tea leaves

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.

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

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Improved generalization of spectral models associated with Vis-NIR spectroscopy for determining the moisture content of different tea leaves

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