Background: Anthocyanins are the main compounds responsible for the colour of red wines and therefore it may be important to evaluate the content of the aforesaid secondary metabolites during grape ripening due to the crucial importance to determine wine colour. Nowadays, there is a growing demand of rapid and non-destructive analytical tools for analysing grapes, such as the emerging hyperspectral analysis.
Results: The hyperspectral images of intact grapes (Vitis vinifera L. cv. Tempranillo, Graciano, Garnacha and Mazuelo red grape from vineyards located in the D.O.Ca. Rioja at two different developmental stages) were recorded using a near infrared hyperspectral imaging device (900-1700 nm). Reference values of anthocyanins were obtained by HPLC-DAD. Calibrations were performed by modified partial least squares regression and present a good potential (coefficient of determination of 0.72 and standard error of cross-validation values of 0.78 and 0.70 mg per grape for total and non-acylated anthocyanins respectively).
Conclusion: The procedure reported here presents a good potential for a fast and reasonably inexpensive screening of these compounds in intact single berries. Moreover, the heterogeneity of anthocyanins within the same ripeness stage could be evaluated using this non-detructive tool.
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http://dx.doi.org/10.1002/jsfa.7266 | DOI Listing |
Sci Rep
January 2025
Fischell Department of Bioengineering, University of Maryland, College Park, USA.
The development of optical sensors for label-free quantification of cell parameters has numerous uses in the biomedical arena. However, using current optical probes requires the laborious collection of sufficiently large datasets that can be used to calibrate optical probe signals to true metabolite concentrations. Further, most practitioners find it difficult to confidently adapt black box chemometric models that are difficult to troubleshoot in high-stakes applications such as biopharmaceutical manufacturing.
View Article and Find Full Text PDFCurr Res Food Sci
December 2024
Empa Swiss Federal Laboratories for Material Science and Technology, ETH Zurich, Lerchenfeldstrasse 5, 9014, St. Gallen, Switzerland.
This study detected the macronutrients retained in glutinous rice (GR) under different drying conditions by innovatively applying visible-near infrared hyperspectral imaging coupled with different spectra preprocessing and effective wavelength selection techniques (EWs). Subsequently, predictive models were developed based on processed spectra for the detection of the macronutrients, which include protein content (PC), moisture content (MC), fat content (FC), and ash content (AC). The result shows the raw spectra-based model had a prediction accuracy ( ) of 0.
View Article and Find Full Text PDFPhotosynthetica
January 2025
Chengde Bijiashan Ecological Agriculture Technology Development Co., Ltd., 067000 Chengde, Hebei, China.
Application of hyperspectral reflectance technology to track changes in photosynthetic activity in () remains underexplored. This study aimed to investigate the relationship between hyperspectral reflectance and photosynthetic activity in the leaves of in response to a decrease in soil water content. Results demonstrated that the reflectance in both the visible light and near-infrared bands increased in conjunction with reduced soil water content.
View Article and Find Full Text PDFSci Rep
January 2025
School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
In this study, we used desert soil from Gansu, China, as a sample to propose a method for designing hyperspectral stealth coatings against desert soil backgrounds within the spectral range of 400-2500 nm, and the corresponding coating was prepared. Firstly, the correlation between the composition and typical spectral detected characteristics of the desert soil was systematically analyzed. It was found that the color and the spectrum of the desert soil in the range of 400-1000 nm were influenced by different types of iron oxides.
View Article and Find Full Text PDFPlant Biotechnol J
January 2025
School of Wine & Horticulture, Ningxia University, Yinchuan, Ningxia, China.
Superoxide dismutase (SOD) plays an important role to respond in the defence against damage when tomato leaves are under different types of adversity stresses. This work employed microhyperspectral imaging (MHSI) and visible near-infrared (Vis-NIR) hyperspectral imaging (HSI) technologies to predict tomato leaf SOD activity. The macroscopic model of SOD activity in tomato leaves was constructed using the convolutional neural network in conjunction with the long and short-term temporal memory (CNN-LSTM) technique.
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