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.

Regenerated Traumatic Bone Cyst With Platelet-Rich Fibrin in the Mandible: A Case Report.

Introduction: Traumatic bone cyst is a pseudocyst which is characterized as an asymptomatic unilocular single lesion with an empty cavity without epithelial lining. Its etiology is still debated, it is more frequent among young people and it is often localized in the posterior mandible zone. A case report is described about diagnosis and conservative treatment of a traumatic bone cyst in anterior zone of lower mandible.

A Non-Invasive Method Based on Computer Vision for Grapevine Cluster Compactness Assessment Using a Mobile Sensing Platform under Field Conditions.

Grapevine cluster compactness affects grape composition, fungal disease incidence, and wine quality. Thus far, cluster compactness assessment has been based on visual inspection performed by trained evaluators with very scarce application in the wine industry. The goal of this work was to develop a new, non-invasive method based on the combination of computer vision and machine learning technology for cluster compactness assessment under field conditions from on-the-go red, green, blue (RGB) image acquisition.

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.

Image analysis-based modelling for flower number estimation in grapevine.

Background: Grapevine flower number per inflorescence provides valuable information that can be used for assessing yield. Considerable research has been conducted at developing a technological tool, based on image analysis and predictive modelling. However, the behaviour of variety-independent predictive models and yield prediction capabilities on a wide set of varieties has never been evaluated.

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.

Estimation of total soluble solids in grape berries using a hand-held NIR spectrometer under field conditions.

Background: Recent studies have reported the potential of near infrared (NIR) spectral analysers for monitoring the ripeness of grape berries as an alternative to wet chemistry methods. This study covers various aspects regarding the calibration and implementation of predictive models of total soluble solids (TSS) in grape berries using laboratory and in-field collected NIR spectra.

Results: The performance of the calibration models obtained under laboratory conditions indicated that at least 700 berry samples are required to assure enough prediction accuracy.

Clinical evaluation of an improved cementation technique for implant-supported restorations: a randomized controlled trial.

Background: Cement remnants were frequently associated with peri-implantitis. Recently, a shoulderless abutment was proposed, raising some concern about cement excess removal.

Aim: To compare different cementation techniques for implant-supported restorations assessing the amount of cement remnants in the peri-implant sulcus.

Assessment of cluster yield components by image analysis.

Background: Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way.

Effects of UV exclusion on the physiology and phenolic composition of leaves and berries of Vitis vinifera cv. Graciano.

Background: Ultraviolet (UV) radiation induces adaptive responses that can be used for plant production improvement. The aim of this study was to assess the effect of solar UV exclusion on the physiology and phenolic compounds of leaves and berry skins of Vitis vinifera L. cv.

Assessment of flower number per inflorescence in grapevine by image analysis under field conditions.

Background: Flowers, flowering and fruit set are key determinants of grapevine yield. Currently, practical methods to assess the flower number per inflorescence, necessary for fruit set estimation, are time and labour demanding. This work aims at developing a simple, cheap, fast, accurate and robust machine vision methodology to be applied to RGB images taken under field conditions, to estimate the number of flowers per inflorescence automatically.

Ultrastructural study by backscattered electron imaging and elemental microanalysis of biomaterial-to-bone interface and mineral degradation of bovine xenografts in maxillary sinus floor elevation.

Objectives: The aim of this study was to perform an ultrastructural study of the bone-to-biomaterial interface and biomaterial mineral degradation in retrieved bone biopsies following maxillary sinus augmentation using bovine xenografts (Endobon(®)) in 15 clinical cases.

Materials And Methods: Nine months after sinus lifting, bone cores were harvested from the maxillary sinus. The specimens were processed for observation under a scanning electron microscope with backscattered electron imaging (SEM-BSE).

Early leaf removal impact on volatile composition of Tempranillo wines.

Background: Early defoliation is a very innovative technique in viticulture used for yield management. The effects of early leaf removal performed manually and mechanically at two different phenological stages, pre-bloom and fruit set, on the volatile composition of Tempranillo (Vitis vinifera L.) wines were studied.