On-The-Go VIS plus SW - NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard

Visible-Short Wave Near Infrared (VIS + SW - NIR) spectroscopy is a real alternative to break down the next barrier in precision viticulture allowing a reliable monitoring of grape composition within the vineyard to facilitate the decision-making process dealing with grape quality sorting and harvest scheduling, for example. On-the-go spectral measurements of grape clusters were acquired in the field using a VIS + SW - NIR spectrometer, operating in the 570-990 nm spectral range, from a motorized platform moving at 5 km/h. Spectral measurements were acquired along four dates during grape ripening in 2017 on the east side of the canopy, which had been partially defoliated at cluster closure. Over the whole measuring season, a total of 144 experimental blocks were monitored, sampled and their fruit analyzed for total soluble solids (TSS), anthocyanin and total polyphenols concentrations using standard, wet chemistry reference methods. Partial Least Squares (PLS) regression was used as the algorithm for training the grape composition parameters' prediction models. The best cross-validation and external validation (prediction) models yielded determination coefficients of cross-validation (R-cv(2)) and prediction (R-P(2)) of 0.92 and 0.95 for TSS, R-cv(2) = 0.75, and R-p(2) = 0.79 for anthocyanins, and R-cv(2) = 0.42 and R-p(2) = 0.43 for total polyphenols. The vineyard variability maps generated for the different dates using this technology illustrate the capability to monitor the spatiotemporal dynamics and distribution of total soluble solids, anthocyanins and total polyphenols along grape ripening in a commercial vineyard

A feasibility study on the use of a miniature fiber optic NIR spectrometer for the prediction of volumic mass and reducing sugars in white wine fermentations

NIR spectroscopy was used to assess two physical/chemical parameters in white wines during alcoholic fermentation. NIR calibration models were developed using a set of 64 samples scanned in a rectangular quartz cuvette with a 50 mm path-length in the 700-1060 nm region, in a miniature fiber optic NIR spectrometer system working in transmission mode. Principal component analysis (PCA) and partial least squares (PLS) regressions were used to interpret spectra and develop calibrations for wine composition. The correlation coefficient (r) and the standard error of cross-validation (SECV) were 0.99, 4.22 g/dm3 for volumic mass and 0.99, 10.44 g/l, for reducing sugars, respectively. Suitable wavelengths for volumic mass and reducing sugars were also proposed according to x-loading weights and regression coefficients. The results obtained suggest that the miniature fiber optic NIR spectrometer is a promising tool for monitoring the white wine fermentation process. © 2008 Elsevier Ltd. All rights reserved

Feasibility of using a miniature fiber optic UV-VIS-NIR spectrometer to assess total polyphenol index, color intensity and volumic mass in red wine fermentations

This study sought to assess the feasibility of using ultraviolet-visible- near infrared (UV-VIS-NIR) spectroscopy to monitor changes in total polyphenol index, color intensity and volumic mass, three indicators of quality during red wine fermentation. Samples (n = 68) collected from eleven tanks during fermentation were scanned in three types of quartz flow cells, path lengths 0.1, 2 and 50 mm, in the UV-VIS-NIR region (200-1,100 nm), using a fiber spectrometer system in transmission mode. Principal component analysis and partial least squares regression were used to interpret spectra and develop calibrations for predicting wine composition during fermentation. Models for the prediction of total polyphenol index displayed coefficients of determination (r 2) ranging between 0.21-0.98, whereas values for the standard error of cross-validation (SECV) ranged from 2.29 to 14.91, depending on the spectral region used. Values for the prediction of color intensity were: r 2 = 0.56-0.98 and SECV = 0.43-1.88. Corresponding values for volumic mass were r 2 = 0.31-0.94 and SECV = 8.71-30.20 g/dm 3. These results suggest that UV-VIS-NIR spectroscopy using a miniature fiber optic spectrometer as a promising tool could be used as an alternative method for the rapid monitoring of quality parameters during red wine fermentation. PRACTICAL APPLICATIONS The study develops ultraviolet-visible-near infrared calibrations to monitor changes in total polyphenol index, color intensity and volumic mass, main indicators of quality during red-wine fermentation, taking into account and responding to the requirements of the enological industry that looks for a swift, efficient, economical and - particularly - nondestructive analytical technique for measuring quality parameters during fermentation process with a single instrument and in a matter of seconds, saving time and enhancing the decision-making process. The work also evaluates the efficacy of a simple, efficient and low-cost instrument that belongs to so called new near infrared spectroscopy (NIRS) generation, which are most suitable to be implemented for on-line analysis in the winemaking industry. The results suggest that the miniature fiber optic NIR spectrometer is a promising tool for monitoring the red wine fermentation process, allowing the instantaneous prediction of the main parameters to be controlled. At the same time, suitable wavelengths for these parameters are also proposed according to x-loading weights and regression coefficients. © 2009 Wiley Periodicals, Inc

On-Vine Monitoring of Grape Ripening Using Near-Infrared Spectroscopy

This study evaluated the ability of near-infrared (NIR) spectroscopy to characterise the behaviour of white and red grapes during on-vine ripening, as a function of grape position in the bunch (high, middle and low) and bunch orientation (north, south, east and west) and to distinguish between different ripening stages with a view to optimising harvesting times depending on the grape variety and the type of wine to be made. A total of 24 bunches of two wine-grape varieties (cv. Pedro Ximénez and cv. Cabernet Sauvignon) were labelled and analysed directly on the vine using a commercially available handheld micro-electro-mechanical system spectrophotometer (1,600-2,400 nm). Principal component analysis was performed to study relationships between the various configurations (grape position and bunch orientation), ripening stages and spectral data. Results for the white-grape variety showed that grapes high on the bunch behaved differently during ripening from those in central or low positions and that east-facing bunches behaved differently from the rest. For both varieties, analysis of bunch spectral characteristics enabled three stages of ripening to be distinguished: early, middle and late. Subsequently, the ability of NIR technology to classify wine grapes as a function of reducing-sugar content, with a view to optimising harvest timing, was evaluated by partial least squares discriminant analysis: 88 % of white grapes and 88 % of red grapes were correctly classified while over 79 % of samples were correctly assigned to representative groups. These results confirmed that NIR technology in the spectral range 1,600-2,400 nm is an appropriate technique for on-vine monitoring of the ripening process, enabling selective harvesting depending on the type of wine to be made. © 2012 Springer Science+Business Media, LLC

Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot

[EN] There is a growing need to provide support and applicable tools to farmers and the agro-industry in order to move from their traditional water status monitoring and high-water-demand cropping and irrigation practices to modern, more precise, reduced-demand systems and technologies. In precision viticulture, very few approaches with ground robots have served as moving platforms for carrying non-invasive sensors to deliver field maps that help growers in decision making. The goal of this work is to demonstrate the capability of the VineScout (developed in the context of a H2020 EU project), a ground robot designed to assess and map vineyard water status using thermal infrared radiometry in commercial vineyards. The trials were carried out in Douro Superior (Portugal) under different irrigation treatments during seasons 2019 and 2020. Grapevines of Vitis vinifera L. Touriga Nacional were monitored at different timings of the day using leaf water potential (psi(l)) as reference indicators of plant water status. Grapevines' canopy temperature (T-c) values, recorded with an infrared radiometer, as well as data acquired with an environmental sensor (T-air, RH, and AP) and NDVI measurements collected with a multispectral sensor were automatically saved in the computer of the autonomous robot to assess and map the spatial variability of a commercial vineyard water status. Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r(cv)(2)) of 0.57 in the morning time and a r(cv)(2) of 0.42 in the midday. The root mean square error of cross-validation (RMSEcv) was 0.191 MPa and 0.139 MPa at morning and midday, respectively. Spatial-temporal variation maps were developed at two different times of the day to illustrate the capability to monitor the grapevine water status in order to reduce the consumption of water, implementing appropriate irrigation strategies and increase the efficiency in the real time vineyard management. The promising outcomes gathered with the VineScout using different sensors based on thermography, multispectral imaging and environmental data disclose the need for further studies considering new variables related with the plant water status, and more grapevine cultivars, seasons and locations to improve the accuracy, robustness and reliability of the predictive models, in the context of precision and sustainable viticulture.This research was funded by the European Union under grant agreement number 737669 (Vinescout project).Fernández-Novales, J.; Saiz Rubio, V.; Barrio, I.; Rovira Más, F.; Cuenca-Cuenca, A.; Alves, FS.; Valente, J.... (2021). Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot. Remote Sensing. 13(14):1-20. https://doi.org/10.3390/rs13142830120131

Using CT Data to Improve the Quantitative Analysis of 18F-FBB PET Neuroimages

18F-FBB PET is a neuroimaging modality that is been increasingly used to assess brain amyloid deposits in potential patients with Alzheimer’s disease (AD). In this work, we analyze the usefulness of these data to distinguish between AD and non-AD patients. A dataset with 18F-FBB PET brain images from 94 subjects diagnosed with AD and other disorders was evaluated by means of multiple analyses based on t-test, ANOVA, Fisher Discriminant Analysis and Support Vector Machine (SVM) classification. In addition, we propose to calculate amyloid standardized uptake values (SUVs) using only gray-matter voxels, which can be estimated using Computed Tomography (CT) images. This approach allows assessing potential brain amyloid deposits along with the gray matter loss and takes advantage of the structural information provided by most of the scanners used for PET examination, which allow simultaneous PET and CT data acquisition. The results obtained in this work suggest that SUVs calculated according to the proposed method allow AD and non-AD subjects to be more accurately differentiated than using SUVs calculated with standard approaches.This work was supported by the MINECO/FEDER under the TEC2012-34306 and TEC2015-64718-R projects and the Ministry of Economy, Innovation, Science and Employment of the Junta de Andalucía under the Excellence Project P11-TIC- 7103. The work was also supported by the Vicerectorate of Research and Knowledge Transfer of the University of Granada

Impact of amyloid-PET in daily clinical management of patients with cognitive impairment fulfilling appropriate use criteria

To evaluate the use of amyloid-positron emission tomography (PET) in routine clinical practice, in a selected population with cognitive impairment that meets appropriate use criteria (AUC). A multicenter, observational, prospective case-series study of 211patients from 2 level-3 hospitals who fulfilled clinical AUC for amyloid-PET scan in a naturalistic setting. Certainty degree was evaluated using a 5-point Likert scale: 0 (very low probability); 1 (low probability); 2 (intermediate probability); 3 (high probability); and 4 (practically sure), before and after amyloid PET. The treatment plan was considered as cognition-specific or noncognition-specific. Amyloid-PET was positive in 118 patients (55.9%) and negative in 93 patients (44.1%). Diagnostic prescan confidence according amyloid-PET results showed that in both, negative and positive-PET subgroup, the most frequent category was intermediate probability (45.7% and 55.1%, respectively). After the amyloid-PET, the diagnostic confidence showed a very different distribution, that was, in the negative-PET group the most frequent categories are very unlikely (70.7%) and unlikely (29.3%), while in the positive- PET group were very probable (57.6%) and practically sure (39%). Only in 14/211 patients (6.6%) the result of the amyloid-PET did not influence the diagnostic confidence, while in 194 patients (93.4%), the diagnostic confidence improved significantly after amyloid- PET results. The therapeutic intention was modified in 93 patients (44.1%). Specific treatment for Alzheimer disease was started, before amyloid-PET, in 80 patients (37.9%). This naturalistic study provides evidence that the implementation of amyloid-PET is associated with a significant improvement in diagnostic confidence and has a high impact on the therapeutic management of patients with mild cognitive impairment fulfilled clinical AUC