Towards the automation of NIR spectroscopy to assess vineyard water status spatial-temporal variability from a ground moving vehicle.

Irrigation has a strong impact in terms of yield regulation and grape and wine quality, so the implementation of precision watering systems would facilitate the decision-making process about the water use efficiency and the irrigation scheduling in viticulture. The objectives of this work were two-fold. On one hand, to compare and assess grapevine water status using two different spectral devices assembled in a mobile platform and to evaluate their capability to map the spatial variability of the plant water status in two commercial vineyards from July to early October in season 2021, and secondly to develop an algorithm capable of automate the spectral acquisition process using one of the two spectral sensors previously tested.

Application of near-infrared spectroscopy for the estimation of volatile compounds in Tempranillo Blanco grape berries during ripening.

Background: The knowledge of volatile compounds concentration in grape berries is very valuable information for the winemaker, since these compounds are strongly involved in the final wine quality, and in consumer acceptance. In addition, it would allow to set the harvest date according to aromatic maturity, to classify grape berries according to their quality and to make wines with different characteristics, among other implications. However, so far, there are no tools that allow the volatile composition to be measured directly on intact berries, either in the vineyard or in the winery.

Monitorization of Varietal Aroma Composition Dynamics during Ripening in Intact L. Tempranillo Blanco Berries by Hyperspectral Imaging.

The measurement of aromatic maturity during grape ripening provides very important information for determining the harvest date, particularly in white cultivars. However, there are currently no tools that allow this measurement to be carried out in a noninvasive and rapid way. For this reason, in the present work, we have studied the use of hyperspectral imaging (HSI)) to estimate the aromatic composition of L.

On-The-Go VIS + 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.

Assessment of amino acids and total soluble solids in intact grape berries using contactless Vis and NIR spectroscopy during ripening.

The amino acid concentration assessment along grape ripening would provide valuable information regarding harvest scheduling, wine aroma potential and must nitrogen supplement addition. In this work the use of Visible (Vis) and near-infrared (NIR) spectroscopy to estimate the grape amino acid content along maturation on intact berries was investigated. Spectral data on two ranges (570-1000 and 1100-2100 nm) were acquired contactless from intact Grenache berries.

On-The-Go Hyperspectral Imaging Under Field Conditions and Machine Learning for the Classification of Grapevine Varieties.

Grapevine varietal classification is an important plant phenotyping issue for grape growing and wine industry. This task has been achieved from destructive techniques like classic ampelography and DNA analysis under laboratory conditions. This work displays a new approach for the classification of a high number of grapevine ( L.

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy.

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy.

Vineyard water status assessment using on-the-go thermal imaging and machine learning.

The high impact of irrigation in crop quality and yield in grapevine makes the development of plant water status monitoring systems an essential issue in the context of sustainable viticulture. This study presents an on-the-go approach for the estimation of vineyard water status using thermal imaging and machine learning. The experiments were conducted during seven different weeks from July to September in season 2016.

Non-destructive assessment of grapevine water status in the field using a portable NIR spectrophotometer.

Background: Until now, the majority of methods employed to assess grapevine water status have been destructive, time-intensive, costly and provide information of a limited number of samples, thus the ability of revealing within-field water status variability is reduced. The goal of this work was to evaluate the capability of non-invasive, portable near infrared (NIR) spectroscopy acquired in the field, to assess the grapevine water status in diverse varieties, grown under different environmental conditions, in a fast and reliable way. The research was conducted 2 weeks before harvest in 2012, in two commercial vineyards, planted with eight different varieties.

Use of Visible and Short-Wave Near-Infrared Hyperspectral Imaging To Fingerprint Anthocyanins in Intact Grape Berries.

In red grape berries, anthocyanins account for about 50% of the skin phenols and are responsible for the final wine color. Individual anthocyanin levels and compositional profiles vary with cultivar, maturity, season, region, and yield and have been proposed as chemical markers to differentiate wines and to provide valuable information regarding the adulteration of musts and wines. A fast, easy, solvent-free, nondestructive method based on visible, short-wave, and near-infrared hyperspectral imaging (HSI) in intact grape berries to fingerprint the color pigments in eight different grape varieties was developed and tested against HPLC.

Data Mining and NIR Spectroscopy in Viticulture: Applications for Plant Phenotyping under Field Conditions.

Plant phenotyping is a very important topic in agriculture. In this context, data mining strategies may be applied to agricultural data retrieved with new non-invasive devices, with the aim of yielding useful, reliable and objective information. This work presents some applications of machine learning algorithms along with in-field acquired NIR spectral data for plant phenotyping in viticulture, specifically for grapevine variety discrimination and assessment of plant water status.

Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR Spectrophotometer.

The identification of different grapevine varieties, currently attended using visual ampelometry, DNA analysis and very recently, by hyperspectral analysis under laboratory conditions, is an issue of great importance in the wine industry. This work presents support vector machine and artificial neural network's modelling for grapevine varietal classification from in-field leaf spectroscopy. Modelling was attempted at two scales: site-specific and a global scale.

Feasibility of using a miniature NIR spectrometer to measure volumic mass during alcoholic fermentation.

Volumic mass-a key component of must quality control tests during alcoholic fermentation-is of great interest to the winemaking industry. Transmitance near-infrared (NIR) spectra of 124 must samples over the range of 200-1,100-nm were obtained using a miniature spectrometer. The performance of this instrument to predict volumic mass was evaluated using partial least squares (PLS) regression and multiple linear regression (MLR).

Assessment of quality parameters in grapes during ripening using a miniature fiber-optic near-infrared spectrometer.

Changes in the chemical properties of wine grapes during ripening were studied using near-infrared (NIR) spectroscopy. A miniature fiber-optic NIR spectrometer system working in transmission mode in the spectral region (700 - 1,060 nm) was evaluated for this purpose. Spectra and analytical data were used to develop partial least square calibration models to quantify changes in the major parameters used to chart ripening in this fruit.

[Characterization of a group of patients with cryptococcosis of the central nervous system].

Introduction: Incidence of cryptococcosis of the central nervous system has risen sharply since AIDS became pandemic; from early 1998, the Instituto de Neurología y Neurocirugía in Havana has beaten its own record in the number of cases attended.

Aim: To describe the clinical epidemiological characteristics of patients with this disease who were hospitalised in this centre between 1991 and 2000.

Patients And Methods: We present a descriptive study of 16 adult individuals who were admitted for this reason.