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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., Results: In this work, the use of near-infrared (NIR) spectroscopy to estimate the aromatic composition and total soluble solids (TSS) of Tempranillo Blanco grape berries during ripening was evaluated. For this purpose, the spectra in the NIR range (1100-2100 nm) of 240 intact berry samples were acquired in the laboratory. From these same samples, the concentration of volatile compounds was analyzed by thin film-solid-phase microextraction-gas chromatography-mass spectrometry (TF-SPME-GC-MS), and the TSS were quantified by refractometry. These two methods were used as reference methods for model building. Calibration, cross-validation and prediction models were built from spectral data using partial least squares (PLS). Determination coefficients of cross-validation (R 2 CV ) above 0.5 were obtained for all volatile compounds, their families, and TSS., Conclusions: These findings support that NIR spectroscopy can be successfully use to estimate the aromatic composition as well as the TSS of intact Tempranillo Blanco berries in a non-destructive, fast, and contactless form, allowing simultaneous determination of technological and aromatic maturities. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

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. Contemporarily to the spectral measurements collected from the ground vehicle at solar noon, stem water potential (Ψ s ) was used as the reference method to evaluate the grapevine water status. Calibration and prediction models for grapevine water status assessment were performed using the Partial least squares (PLS) regression and the Variable Importance in the Projection (VIP) method. The best regression models returned a determination coefficient for cross validation (R 2 cv ) and external validation (R 2 p ) of 0.70 and 0.75 respectively, and the standard error of cross validation (RMSECV) values were lower than 0.105 MPa and 0.128 MPa for Tempranillo and Graciano varieties using a more expensive and heavier near-infrared (NIR) spectrometer (spectral range 1200-2100 nm). Remarkable models were also built with the miniaturized, low-cost spectral sensor (operating between 900-1860 nm) ranging from 0.69 to 0.71 for R 2 cv , around 0.74 in both varieties for R 2 p and the RMSECV values were below 0.157 MPa, while the RMSEP values did not exceed 0.151 MPa in both commercial vineyards. This work also includes the development of a software which automates data acquisition and allows faster (up to 40% of time saving in the field) and more efficient deployment of the developed algorithm. The encouraging results presented in this work demonstrate the great potential of this methodology to assess the water status of the vineyard and estimate its spatial variability in different commercial vineyards, providing useful information for better irrigation scheduling., (© 2023. Springer Nature Limited.)

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 Vitis vinifera L. Tempranillo Blanco berries during ripening. A total of 236 spectra in the VIS+short wave near-infrared (VIS+SW-NIR) range (400-1000 nm) of intact berries were acquired contactless under laboratory conditions. As gold standard values, a total of 20 volatile compounds were quantified by gas chromatography-mass spectrometry (GC-MS), and the concentration of total soluble solids (TSS) was measured by refractometry. Calibration, cross-validation, and prediction models were built using partial least squares (PLS). Values of R CV 2 ≥ 0.70 were obtained for α-terpineol, p- cymene, β-damascenone, β-ionone, benzaldehyde, benzyl alcohol, hexanal, citral, linalool, 2-phenylethanol, octanoic acid, nonanoic acid, 2-hexenal, 2-hexen-1-ol, (Z)-3-hexen-1-ol, total C 13 norisoprenoids, total C6 compounds, total positive compounds (i.e., the sum of all families except C6 compounds), total benzenoids, and total soluble solids (TSS). Therefore, it can be affirmed that HSI in the VIS + SW-NIR range could be a good tool to estimate the aromatic composition of Tempranillo Blanco grape berries in a contactless, fast, and nondestructive way.

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., Case Presentation: The report describes a 22-year-old female with a traumatic bone cyst in anterior mandible as accidental discovery from a routine orthopantomography. A conservative approach was conducted to treat the lesion through a submarginal incision, an osteotomy with ultrasound, a filling of the cavity with advanced platelet-rich fibrin membranes, and repositioning of the cortical bone. The radiological follow-up to 6 months confirmed the healing of the lesion., Conclusion: The conservative approach through submarginal incision, osteotomy with ultrasound, filling with A-PRF+ membranes and repositioning of cortical bone ensures optimal bone healing and avoids gingival recessions at six months follow-up, showing to be a good alternative for satisfactory defect resolution in similar clinical cases., (© 2020 American Academy of Periodontology.)

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. A mobile sensing platform was used to automatically capture RGB images of grapevine canopies and fruiting zones at night using artificial illumination. Likewise, a set of 195 clusters of four red grapevine varieties of three commercial vineyards were photographed during several years one week prior to harvest. After image acquisition, cluster compactness was evaluated by a group of 15 experts in the laboratory following the International Organization of Vine and Wine (OIV) 204 standard as a reference method. The developed algorithm comprises several steps, including an initial, semi-supervised image segmentation, followed by automated cluster detection and automated compactness estimation using a Gaussian process regression model. Calibration (95 clusters were used as a training set and 100 clusters as the test set) and leave-one-out cross-validation models (LOOCV; performed on the whole 195 clusters set) were elaborated. For these, determination coefficient (R 2 ) of 0.68 and a root mean squared error (RMSE) of 0.96 were obtained on the test set between the image-based compactness estimated values and the average of the evaluators' ratings (in the range from 1-9). Additionally, the leave-one-out cross-validation yielded a R 2 of 0.70 and an RMSE of 1.11. The results show that the newly developed computer vision based method could be commercially applied by the wine industry for efficient cluster compactness estimation from RGB on-the-go image acquisition platforms in commercial vineyards., Competing Interests: The authors declare no conflict of interest.

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. A total of 22 free amino acids in 128 grape clusters were quantified by HPLC. Partial least squares was used to build calibration, cross validation and prediction models. The best performances (R 2 P ~ 0.60) were found for asparagine (SEP: 0.45 mg N/l), tyrosine (SEP: 0.33 mg N/l) and proline (SEP: 17.5 mg N/l) in the 570-1000 nm range, and for lysine (SEP: 0.44 mg N/l), tyrosine (SEP: 0.26 mg N/l), and proline (SEP: 15.54 mg N/l) in the 1100-2100 nm range. Remarkable models (R 2 P ~0.90, SEP~1.60 ºBrix, and RPD~3.79) were built for total soluble solids in both spectral ranges. Contactless, non-destructive spectroscopy could be an alternative to provide information about grape amino acids composition., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This multidisciplinary research work evaluated the effects of soil erosion on grape yield and quality and on different soil functions, namely water and nutrient supply, carbon sequestration, organic matter recycling, and soil biodiversity, with the aim to understand the causes of soil malfunctioning and work out a proper strategy of soil remediation. Degraded areas in nineteen organically farmed European and Turkish vineyards resulted in producing significantly lower amounts of grapes and excessive concentrations of sugar. Plants suffered from decreased water nutrition, due to shallower rooting depth, compaction, and reduced available water capacity, lower chemical fertility, as total nitrogen and cation exchange capacity, and higher concentration of carbonates. Carbon storage and organic matter recycling were also depressed. The general trend of soil enzyme activity mainly followed organic matter stock. Specific enzymatic activities suggested that in degraded soils, alongside a general slowdown in organic matter cycling, there was a greater reduction in decomposition capacity of the most recalcitrant forms. The abundance of Acari Oribatida and Collembola resulted the most sensitive indicator of soil degradation among the considered microarthropods. No clear difference in overall microbial richness and evenness were observed. All indices were relatively high and indicative of rich occurrence of many and rare microbial species. Dice cluster analyses indicated slight qualitative differences in Eubacterial and fungal community compositions in rhizosphere soil and roots in degraded soils. This multidisciplinary study indicates that the loss of soil fertility caused by excessive earth movement before planting, or accelerated erosion, mainly affects water nutrition and chemical fertility. Biological soil fertility is also reduced, in particular the ability of biota to decompose organic matter, while biodiversity is less affected, probably because of the organic management. Therefore, the restoration of the eroded soils requires site-specific and intensive treatments, including accurately chosen organic matrices for fertilization, privileging the most easily decomposable. Restoring soil fertility in depth, however, remain an open question, which needs further investigation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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 ( Vitis vinifera L.) varieties under field conditions using on-the-go hyperspectral imaging and different machine learning algorithms. On-the-go imaging was performed under natural illumination using a hyperspectral camera mounted on an all-terrain vehicle at 5 km/h. Spectra were acquired over two different leaf phenological stages on the canopy of 30 different varieties on a commercial vineyard located in La Rioja, Spain. A total of 1,200 spectral samples were generated. Support vector machines (SVM) and artificial neural networks (multilayer perceptrons, MLP) were used for the development of a large number of models, testing different algorithm parameters and spectral pre-processing techniques. Both classifiers yielded notable performance values and were able to train models with recall F1 scores and area under the receiver operating characteristic curve marks up to 0.99 for 5-fold cross validation. Statistical analyses supported that the best SVM kernel was linear and the best activation function for MLP was the hyperbolic tangent function. The prediction performance for individual varieties of MLP ranged from 0.94 to 0.99, displaying low levels of variability. In the case of SVM, slightly higher differences were obtained, ranging from 0.83 to 0.97 for individual varieties. These results support the possibility of deploying an on-the-go hyperspectral imaging system in the field capable of successfully classifying leaves from different grapevine varieties. This technology could thus be considered as a new useful non-destructive tool for plant phenotyping under field conditions.

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. A thermal camera was embedded on an all-terrain vehicle moving at 5 km/h to take on-the-go thermal images of the vineyard canopy at 1.2 m of distance and 1.0 m from the ground. The two sides of the canopy were measured for the development of side-specific and global models. Stem water potential was acquired and used as reference method. Additionally, reference temperatures Tdry and Twet were determined for the calculation of two thermal indices: the crop water stress index (CWSI) and the Jones index (Ig). Prediction models were built with and without considering the reference temperatures as input of the training algorithms. When using the reference temperatures, the best models casted determination coefficients R2 of 0.61 and 0.58 for cross validation and prediction (RMSE values of 0.190 MPa and 0.204 MPa), respectively. Nevertheless, when the reference temperatures were not considered in the training of the models, their performance statistics responded in the same way, returning R2 values up to 0.62 and 0.65 for cross validation and prediction (RMSE values of 0.190 MPa and 0.184 MPa), respectively. The outcomes provided by the machine learning algorithms support the use of thermal imaging for fast, reliable estimation of a vineyard water status, even suppressing the necessity of supervised acquisition of reference temperatures. The new developed on-the-go method can be very useful in the grape and wine industry for assessing and mapping vineyard water status.

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. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψ s ) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction ([Formula: see text]) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

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. Spectral measurements were acquired in the field on the adaxial and abaxial sides of 160 individual leaves (20 leaves per variety) using a commercially available handheld spectrophotometer (1600-2400 nm)., Results: Principal component analysis (PCA) and modified partial least squares (MPLS) were used to interpret the spectra and to develop reliable prediction models for stem water potential (Ψ s ) (cross-validation correlation coefficient (r cv ) ranged from 0.77 to 0.93, and standard error of cross validation (SECV) ranged from 0.10 to 0.23), and leaf relative water content (RWC) (r cv ranged from 0.66 to 0.81, and SECV between 1.93 and 3.20). The performance differences between models built from abaxial and adaxial-acquired spectra is also discussed., Conclusions: The capability of non-invasive NIR spectroscopy to reliably assess the grapevine water status under field conditions was proved. This technique can be a suitable and promising tool to appraise within-field variability of plant water status, helpful to define optimised irrigation strategies in the wine industry. © 2017 Society of Chemical Industry., (© 2017 Society of Chemical Industry.)

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., Results: Inflorescence images from 11 grapevine Vitis vinifera L. varieties were acquired under field conditions. The flower number per inflorescence and the flower number visible in the images were calculated manually, and automatically using an image analysis algorithm. These datasets were used to calibrate and evaluate the behaviour of two linear (single-variable and multivariable) and a nonlinear variety-independent model. As a result, the integrated tool composed of the image analysis algorithm and the nonlinear approach showed the highest performance and robustness (RPD = 8.32, RMSE = 37.1). The yield estimation capabilities of the flower number in conjunction with fruit set rate (R 2  = 0.79) and average berry weight (R 2  = 0.91) were also tested., Conclusion: This study proves the accuracy of flower number per inflorescence estimation using an image analysis algorithm and a nonlinear model that is generally applicable to different grapevine varieties. This provides a fast, non-invasive and reliable tool for estimation of yield at harvest. © 2016 Society of Chemical Industry., (© 2016 Society of Chemical Industry.)

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. Additional aim was to compare the effect of these cementation techniques using two different abutment designs., Material & Methods: Forty-six patients requiring double implant-supported restoration in the posterior maxilla were randomly divided in two groups according to the cementation modality: intraoral and extraoral. According to the abutment finishing line, implants in each patient were randomly assigned to shoulderless or chamfer subgroup. In the intraoral group, crowns were directly seated onto the titanium abutment. In the extraoral group, crowns were firstly seated onto a resin abutment replica and immediately removed, then cleansed of the cement excess and finally seated on the titanium abutment. After cement setting, in both groups, cement excess was carefully tried to remove. Three months later, framework/abutment complexes were disconnected and prepared for microscopic analysis: surface occupied by exposed cement remnants and marginal gaps were measured. Additionally, crown/abutment complexes were grinded, and voids of cement were measured at abutment/crown interface. Related-samples Friedman's two-way analysis of variance by ranks was used to detect differences between groups and subgroups (P ≤ 0.5)., Results: At the end of the study, a mean value of 0.45 mm 2 (±0.80), 0.38 mm 2 (±0.84), and 0.065 mm 2 (±0.13) and 0.07 mm 2 (±0.15) described surface occupied by cement remnants in shoulderless and chamfer abutment with intraoral cementation and shoulderless and chamfer abutment with extraoral cementation, respectively. A mean value of 0.40 mm 2 (±0.377), 0.41 mm 2 (±0.39) and 0.485 mm 2 (±0.47) and 0.477 mm 2 (±0.43) described cement voids at the abutment/crown interface; a mean value of 0.062 mm (±0.03), 0.064 mm (±0.35), 0.055 mm (±0.016) and 0.054 mm (±0.024) described marginal gaps. Statistics showed tendency of intraoral cementation to have significantly higher cement remnants compared with abutments with extraoral cementation groups. At the same time, the presence of voids was significantly higher in case of extraoral cementation. No significant differences between groups for the variable "gap"., Conclusions: Despite the presence of more voids, extraoral cementation reduces cement excess. However, using low adhesivity cement and careful cement removal, a very limited quantity of cement remnants was observed also in the intraoral cementation., (© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

In the present study we assessed the effects of ambient solar UV exclusion on leaf physiology, and leaf and berry skin phenolic composition, of a major grapevine cultivar (Tempranillo) grown under typically Mediterranean field conditions over an entire season. In general, the effects of time were stronger than those of UV radiation. Ambient UV caused a little stressing effect (eustress) on leaf physiology, with decreasing net photosynthesis rates and stomatal conductances. However, it was not accompanied by alterations in F v /F m or photosynthetic pigments, and was partially counterbalanced by the UV-induced accumulation of protective flavonols. Consequently, Tempranillo leaves are notably adapted to current UV levels. The responses of berry skin phenolic compounds were diverse, moderate, and mostly transitory. At harvest, the clearest response in UV-exposed berries was again flavonol accumulation, together with a decrease in the flavonol hydroxylation level. Contrarily, responses of anthocyanins, flavanols, stilbenes and hydroxycinnamic derivatives were much more subtle or nonexistent. Kaempferols were the only compounds whose leaf and berry skin contents were correlated, which suggests a mostly different regulation of phenolic metabolism for each organ. Interestingly, the dose of biologically effective UV radiation (UV BE ) was correlated with the leaf and berry skin contents of quercetins and kaempferols; relationships were linear except for the exponential relationship between UV BE dose and berry skin kaempferols. This opens management possibilities to modify kaempferol and quercetin contents in grapevine through UV manipulation., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)

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. Predictive models based on modified partial least-squares (MPLS) were built for 14 individual anthocyanins with coefficients of determination of cross-validation (R 2 CV ) ranging from 0.70 to 0.93. For the grouping of total and nonacylated anthocyanins, external validation was conducted with coefficient of determination of prediction (R 2 P ) of 0.86. HSI could potentially become an alternative to HPLC with reduced analysis time and labor costs while providing reliable and robust information on the anthocyanin composition of grape berries.

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. A statistically significant error reduction (ΔRMSECV = 0.1°Brix) with P < 0.001 was observed when measuring berries without epicuticular wax, which was negligible from a practical point of view. Under field conditions, the prediction errors (RMSEP = 1.68°Brix, and SEP = 1.67°Brix) were close to those obtained with the laboratory dataset (RMSEP = 1.42°Brix, SEP = 1.40°Brix)., Conclusion: This work clarifies several methodological factors to develop a protocol for in-field assessing TSS in grape berries using an affordable, non-invasive, portable NIR spectral analyser. © 2015 Society of Chemical Industry., (© 2015 Society of Chemical Industry.)

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 (SVM), rotation forests and M5 trees models were built using NIR spectra acquired in the field directly on the adaxial side of grapevine leaves, with a non-invasive portable spectrophotometer working in the spectral range between 1600 and 2400 nm. The ν-SVM algorithm was used for the training of a model for varietal classification. The classifiers' performance for the 10 varieties reached, for cross- and external validations, the 88.7% and 92.5% marks, respectively. For water stress assessment, the models developed using the absorbance spectra of six varieties yielded the same determination coefficient for both cross- and external validations (R² = 0.84; RMSEs of 0.164 and 0.165 MPa, respectively). Furthermore, a variety-specific model trained only with samples of Tempranillo from two different vintages yielded R² = 0.76 and RMSE of 0.16 MPa for cross-validation and R² = 0.79, RMSE of 0.17 MPa for external validation. These results show the power of the combined use of data mining and non-invasive NIR sensing for in-field grapevine phenotyping and their usefulness for the wine industry and precision viticulture implementations.

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. Spectral measurements were obtained on the near-infrared (NIR) spectral range between 1600 to 2400 nm under field conditions in a non-destructive way using a portable spectrophotometer. For the site specific approach, spectra were collected from the adaxial side of 400 individual leaves of 20 grapevine (Vitis vinifera L.) varieties one week after veraison. For the global model, two additional sets of spectra were collected one week before harvest from two different vineyards in another vintage, each one consisting on 48 measurement from individual leaves of six varieties. Several combinations of spectra scatter correction and smoothing filtering were studied. For the training of the models, support vector machines and artificial neural networks were employed using the pre-processed spectra as input and the varieties as the classes of the models. The results from the pre-processing study showed that there was no influence whether using scatter correction or not. Also, a second-degree derivative with a window size of 5 Savitzky-Golay filtering yielded the highest outcomes. For the site-specific model, with 20 classes, the best results from the classifiers thrown an overall score of 87.25% of correctly classified samples. These results were compared under the same conditions with a model trained using partial least squares discriminant analysis, which showed a worse performance in every case. For the global model, a 6-class dataset involving samples from three different vineyards, two years and leaves monitored at post-veraison and harvest was also built up, reaching a 77.08% of correctly classified samples. The outcomes obtained demonstrate the capability of using a reliable method for fast, in-field, non-destructive grapevine varietal classification that could be very useful in viticulture and wine industry, either global or site-specific.

Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower(®), firstly guides the user to appropriately take an inflorescence photo using the smartphone's camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower(®) has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application's efficiency on four different devices covering a wide range of the market's spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

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., Results: Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%., Conclusion: The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods., (© 2014 Society of Chemical Industry.)

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. Graciano under field conditions. Phenolic compounds were analyzed globally and individually in both the vacuolar fraction and, for the first time in grapevine, the cell wall-bound fraction. These different locations may represent diverse modalities of phenolic response to and protection against UV., Results: UV exclusion led to a decrease in Fv /Fm in leaves, revealing that solar UV is needed for adequate photoprotection. Only p-caffeoyl-tartaric acid from the soluble fraction of leaves and myricetin-3-O-glucoside from the soluble fraction of berry skins were significantly higher in the presence of UV radiation, and thus they could play a role in UV protection. Other hydroxycinnamic acids, flavonols, flavanols and stilbenes did not respond to UV exclusion., Conclusion: UV exclusion led to subtle changes in leaves and berry skins of Graciano cultivar, which would be well adapted to current UV levels. This may help support decision-making on viticultural practices modifying UV exposure of leaves and berries, which could improve grape and wine quality., (© 2014 Society of Chemical Industry.)

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., Results: Ninety images of individual inflorescences of Vitis vinifera L. cultivars Tempranillo, Graciano and Carignan were acquired in the vineyard with a pocket RGB camera prior to flowering, and used to develop and test the 'flower counting' algorithm. Strong and significant relationships, with R(2) above 80% for the three cultivars were observed between actual and automated estimation of inflorescence flower numbers, with a precision exceeding 90% for all cultivars., Conclusion: The developed algorithm proved that the analysis of digital images captured by pocket cameras under uncontrolled outdoors conditions was able to automatically provide a useful estimation of the number of flowers per inflorescence of grapevines at early stages of flowering., (© 2013 Society of Chemical Industry.)

Background: Ultraviolet (UV) radiation modulates secondary metabolism in the skin of Vitis vinifera L. berries, which affects the final composition of both grapes and wines. The expression of several phenylpropanoid biosynthesis-related genes is regulated by UV radiation in grape berries. However, the complete portion of transcriptome and ripening processes influenced by solar UV radiation in grapes remains unknown., Results: Whole genome arrays were used to identify the berry skin transcriptome modulated by the UV radiation received naturally in a mid-altitude Tempranillo vineyard. UV radiation-blocking and transmitting filters were used to generate the experimental conditions. The expression of 121 genes was significantly altered by solar UV radiation. Functional enrichment analysis of altered transcripts mainly pointed out that secondary metabolism-related transcripts were induced by UV radiation including VvFLS1, VvGT5 and VvGT6 flavonol biosynthetic genes and monoterpenoid biosynthetic genes. Berry skin phenolic composition was also analysed to search for correlation with gene expression changes and UV-increased flavonols accumulation was the most evident impact. Among regulatory genes, novel UV radiation-responsive transcription factors including VvMYB24 and three bHLH, together with known grapevine UV-responsive genes such as VvMYBF1, were identified. A transcriptomic meta-analysis revealed that genes up-regulated by UV radiation in the berry skin were also enriched in homologs of Arabidopsis UVR8 UV-B photoreceptor-dependent UV-B -responsive genes. Indeed, a search of the grapevine reference genomic sequence identified UV-B signalling pathway homologs and among them, VvHY5-1, VvHY5-2 and VvRUP were up-regulated by UV radiation in the berry skin., Conclusions: Results suggest that the UV-B radiation-specific signalling pathway is activated in the skin of grapes grown at mid-altitudes. The biosynthesis and accumulation of secondary metabolites, which are appreciated in winemaking and potentially confer cross-tolerance, were almost specifically triggered. This draws attention to viticultural practices that increase solar UV radiation on vineyards as they may improve grape features.

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). In addition, chemical analysis and elemental mapping of the mineral composition were generated using a microanalytical system based on energy-dispersive X-ray spectrometry (EDX)., Results: No clinical complications occurred during surgery. Scanning electron microscopy revealed that newly formed bone was closely attached to the xenograft. Elemental analysis showed a significantly high Ca/P ratio in the residual biomaterials (3.031 ± 0.104) compared with the interface (2.908 ± 0.115) and new bone (2.889 ± 0.113), which suggests that there may be a gradual diffusion of Ca ions from the biomaterial into the newly forming bone at the interface as part of the biomaterial's resorption process. EDX analysis of the residual bovine biomaterial showed particle categories with different mean Ca/P ratios according to size, pointing to different stages of the resorption process., Conclusions: The biomaterial proved to be biocompatible and osteoconductive when used as a bone substitute for maxillary sinus elevation. The grafting material used is not a completely resorbable material over the time period covered by this study., (© 2012 John Wiley & Sons A/S.)

Spatial information on vineyard soil properties can be useful in precision viticulture. In this paper a combination of high resolution soil spatial information of soil electrical resistivity (ER) and ancillary topographic attributes, such as elevation and slope, were integrated to assess the spatial variability patterns of vegetative growth and yield of a commercial vineyard (Vitis vinifera L. cv. Tempranillo) located in the wine-producing region of La Rioja, Spain. High resolution continuous geoelectrical mapping was accomplished by an Automatic Resistivity Profiler (ARP) on-the-go sensor with an on-board GPS system; rolling electrodes enabled ER to be measured for a depth of investigation approximately up to 0.5, 1 and 2 m. Regression analysis and cluster analysis algorithm were used to jointly process soil resistivity data, landscape attributes and grapevine variables. ER showed a structured variability that matched well with trunk circumference spatial pattern and yield. Based on resistivity and a simple terrain attribute uniform management units were delineated. Once a spatial relationship to target variables is found, the integration of point measurement with continuous soil resistivity mapping is a useful technique to identify within-plots areas of vineyard with similar status.

The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine's leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.

Background: Early defoliation is a viticultural practice aimed at crop control. So far, the impact of early leaf removal on the monomeric phenolic composition of wines has not been explored. This study examines the effects of early defoliation on the phenolic profile and content in Tempranillo wines. The influence of the defoliation method (manual vs mechanical) and the timing of leaf removal (pre-bloom vs fruit set) was investigated., Results: Over two consecutive seasons, 2007 and 2008, the monomeric phenolic composition in Tempranillo wines was studied by high-performance liquid chromatography with photodiode array detection, and 22 compounds were identified and quantified. Overall, early defoliation led to wines more intensely coloured, of higher alcohol content and with larger concentrations of hydroxycinnamic acids, flavonols and anthocyanins (in 2008 only for mechanical treatments). In the absence of fungal infection, resveratrol was found to increase in wines corresponding to early defoliation treatments. The method of leaf removal seemed to be more critical than the timing of intervention, and larger effects on wine phenolic composition were observed for mechanical treatments., Conclusion: Early defoliation proved to be an effective technique for improving the phenolic composition of Tempranillo wines, by favouring the accumulation of hydroxycinnamics, flavonols and anthocyanins. This is an important achievement, as wine quality is often described by its colour and phenolic attributes., (Copyright © 2011 Society of Chemical Industry.)

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. Volatiles were identified and quantified by gas chromatography., Results: Early leaf removal only modified the total concentrations of C₆ compounds and acetates, whereas total alcohols, esters, volatile acids and terpenes remained generally unaffected. Early defoliation induced a significant reduction in C₆ compounds and increased the concentrations of acetates in Tempranillo wines. An effect of timing (pre-bloom vs fruit set) alone was observed for all acetates analysed. Regarding the method of defoliation (manual vs mechanical), significant differences in some ethyl ester (ethyl-2-methylbutyrate and ethyl octanoate) and volatile acid concentrations were observed among treatments. Ethyl octanoate, 2-phenylethyl acetate, 3-methylbutyl acetate and hexanoic acid, with OAV (odour activity value) > 1 and mainly fruity and floral odour descriptors, showed higher levels after early defoliation treatments compared with non-defoliated vines. Principal component analysis illustrated the difference in wines from defoliated and non-defoliated treatments based on their volatile composition., Conclusion: It can be concluded that early leaf removal significantly modified the wine aroma compounds, increasing or decreasing several of these compounds., (Copyright © 2011 Society of Chemical Industry.)

Objective: This study attempted to clarify whether differential immunocytokeratin expression occurs in cystic and epithelialized noncystic lesions., Study Design: From January 2003 to June 2004, periapical surgery was carried out on 70 teeth, collecting 70 histologic samples. Serial sections of original histologic slices were prepared for immunostaining. The antibodies used were against cytokeratins CK7, AE1, AE3, AE1-3, and CAM52. The intensity of staining was evaluated as follows: 0 = no cells stained; 1 = weak staining (11%-25%); 2 = moderate staining (26%-75%); and 3 = intense staining (>or=76%)., Results: Ten epithelized granulomas and 6 cysts were included. Intense staining was seen for AE1 and AE1-3 in the 2 types of lesion; staining with AE3 was moderate for epithelized granulomas and cysts. CK7 demonstrated a light reactivity in the outermost epithelial layer. CAM52 showed weak staining for the epithelized granuloma and moderate for the cyst., Conclusions: Cysts and epithelized granulomas presented the same cytokeratin expression, though with marked differences in distribution and degree of staining of cytokeratins. This immunochemical technique is interesting for the determination of the histologic type and the prognosis, but may not be clinically practicable.

Apical periodontitis is produced in the majority of cases by intraradicular infection. Treatment consists in the elimination of the infectious agents by endodontia. Even when carrying out a correct cleansing and filling of canals, it is possible that periapical periodontitis will persist in the form of an asymptomatic radiolucency, giving rise to the post-endodontic periapical lesion. The chronic inflammatory periapical lesion is the most common pathology found in relation to alveolar bone of the jaw. From the histological point of view, it can be classified as chronic periapical periodontitis (periapical granuloma), radicular cyst, and as scar tissue. The most frequent is the periapical granuloma, constituted by a mass of chronic inflammatory tissue, in which isolated nests of epithelium can be found. The radicular cyst is characterized by the presence of a cavity, partially or wholly lined by epithelium. Scar tissue is a reparative response by the body, producing fibrous connective tissue. The aim of this study is to review and update the etiopathogenic and histological aspects of chronic post-endodontic periapical lesions.

Objective: This study investigated whether oral contraceptive use affects the incidence of complications (pain, trismus, dry socket) in women undergoing removal of impacted mandibular third molars., Patients and Method: Two hundred and sixty seven women, aged 17 - 45 years, underwent removal of an impacted mandibular third molar. Eighty seven of the women were regular users of oral contraceptives. All patients were evaluated for postoperative pain, trismus and dry socket (localized alveolar osteitis)., Results: Mean trismus values (measured as maximum interincisal distance) were similar in the two groups of patients. Postoperative pain was significantly more frequent among women taking contraceptives, both on day 1 (30% of women taking contraceptives used analgesics, versus 11% of women not taking contraceptives, p < 0.001) and on day 5 (14% versus 5%, p = 0.024). Similarly, dry socket occurred more frequently among women taking contraceptives than among women not taking contraceptives (11% versus 4%, p = 0.017)., Conclusions: The results of this study support the view that oral contraceptive use favours the appearance of dry socket and postoperative pain after extraction, but has no effect on trismus.