Grape Harvest Research Articles

A horizontal collaborative approach for planning the wine grape harvesting

A horizontal collaborative approach for planning the wine grape harvesting

ВЛИЯНИЕ СХЕМЫ ПОСАДКИ И НАГРУЗКИ ВИНОГРАДНЫХ РАСТЕНИЙ СОРТА РИСЛИНГ РЕЙНСКИЙ ПОБЕГАМИ НА ФИЗИКО-ХИМИЧЕСКИЕ ПОКАЗАТЕЛИ СУСЛА И ВИНА

The article considers the issue of the influence of anthropogenic factors (planting schemes and the load of bushes with shoots) on the physico-chemical parameters of must and wine of the Riesling Rhenish grape variety. The data obtained on the quality indicators of wine ma-terials from the Riesling Rhenish grape harvest in 2021, obtained from experimental bushes of different planting patterns and shoot loads, are analyzed. The possibility of modeling the indi-cators and stylistics of wine at the stage of grape cultivation, depending on the planting scheme and the load of the grape plant, is shown. The influence of the planting scheme and the load on the cationic composition of wine was studied. It was revealed that with a 3×2 m planting scheme, the content of potas-sium cations in wines increases, which can lead to the formation of crystalline turbidity during the storage of finished wine. Based on the conducted research, it was found that the ac-cumulation of potassium cations is on average less with a planting scheme of 3×1.5 m, how-ever, with a planting scheme of 3×1 m and a load of shoots of 50 thousand pcs./ha, the lowest value was revealed – 867.0 mg/dm3. For white grape varieties of medium growth strength, a planting scheme of 3×1.5 m with a load of shoots of 50 thousand pcs./ha is rec-ommended.

Coordinating harvest planning and scheduling in an agricultural supply chain through a stochastic bilevel programming

AbstractThis paper addresses a selective harvest planning problem in the context of a hierarchical agricultural supply chain, which integrates the definition of management zones for harvest planning, and the coordination between the producer and the wholesaler. The problem is represented through a stochastic bilevel program that allows the representation of the hierarchy between the producer (leader) and a wholesaler (follower). The producer decides planning and scheduling of the selective harvest for each homogeneous management zone into the resulting partition, and the wholesaler decides the amount to be acquired to satisfy demand requirements. At each decision level, a stochastic optimization model is proposed for representing the uncertainty in future crop yields, prices, and demands, using a finite set of scenarios. A reformulation of the bilevel model into a mixed‐integer linear program is provided using Karush–Kuhn–Tucker conditions and replacing the nonlinear complementary constraints allowing for the introduction of auxiliary binary variables and a big‐M term. This model was applied in a case study for selective harvesting of grapes with data collected from a farm located in the south central zone of Chile. Our research shows valuable results of the proposed methodology from a set of instances representing the behavior of both decision makers under uncertainty.

In-field pose estimation of grape clusters with combined point cloud segmentation and geometric analysis

In-field object detection and pose estimation are challenging tasks in industrial harvesting scenarios. This study investigates a method for object detection and 6D pose estimation using a depth camera to prevent harvesting robots from collisions while harvesting grape clusters. First, the Mask Region Convolutional Neural Network (Mask R-CNN) is deployed to segment 2D images and output binary mask images of grape clusters. Second, the grape cluster point cloud is segmented based on the binary mask image and the mapping relationship between the image and point cloud to provide a high-quality point cloud through pre-processing. Third, the optimal cutting point is located by constructing the grape peduncle region of interest (RoI). Finally, the peduncle surface is fit based on the locally weighted scatterplot smoothing (LOWESS) algorithm, and the pose of the peduncle is estimated using geometric methods. The detection results from 238 test images show that the mean Precision (mP) is 86.0%, the mean Recall (mR) is 79.9%, the F1-score is 0.828, and mean Intersection Over Union (mIOU) for instance segmentation is 87.9%. The pose estimation results from 172 grape peduncles yield an error angle of 22.22 degrees ± 17.96 degrees in pose estimation. The detection and pose estimations for each grape cluster require approximately 1.786 s. The demonstrated performance of the proposed method indicates it can be applied to collision-free grape harvesting using robots in unstructured environments.

Different response of proanthocyanidins from Vitis vinifera cv. Monastrell depending on time of elicitor application.

Proanthocyanidins (PAs) are phenolic compounds present in skins and seeds of wine grapes and have great implications for plant physiology and wine quality. There are several strategies to increase PA concentration, such as application of elicitors methyl jasmonate (MeJ) and benzothiadiazole (BTH), compounds that can stimulate defence responses like phenolic compound biosynthesis in wine grapes, which have been applied mainly at veraison (beginning of ripening). We recently evaluated the application of MeJ and BTH on Vitis vinifera cv. Monastrell grapes during veraison and mid-ripening (3 weeks after veraison). Grapes treated at mid-ripening showed higher anthocyanin concentrations than those at veraison. In this trial, over two seasons, we evaluated whether time of application (veraison or mid-ripening) of MeJ and BTH on 'Monastrell' grapes is a determining factor in the biosynthesis and composition of PAs in grapes and their subsequent release into wines. Application of elicitors at different ripening times produced significant differences in the PAs of 'Monastrell' grapes, since those treated at mid-ripening recorded a higher PAs concentration in skin and seeds, and then in the wines produced, compared to grapes treated at veraison. Results suggest that despite different environmental conditions endured in each of the two seasons evaluated, application of elicitors at mid-ripening of Monastrell grapes could be used to harvest grapes with higher PA concentration, increasing the functional value of the wines, without altering their organoleptic quality. © 2022 Society of Chemical Industry.

Feature Normalization Reweighting Regression Network for Sugar Content Measurement of Grapes

The measurement of grape sugar content is an important index for classifying grapes based on their quality. Owing to the correlation between grape sugar content and appearance, non-destructive measurements are possible using computer vision and deep learning. This study investigates the quality classification of the Red Globe grape. The number of collected grapes in the range of the 15~16% measure is three times more than in the range of <14% or in the range of the >18% measure. This study presents a framework named feature normalization reweighting regression (FNRR) to address this imbalanced distribution of sugar content of the grape datasets. The experimental results show that the FNRR framework can measure the sugar content of a whole bunch of grapes with high accuracy using typical convolution neural networks and a visual transformer model. Specifically, the visual transformer model achieved the best accuracy with a balanced loss function, with the coefficient of determination R = 0.9599 and the root mean squared error RMSE = 0.3841%. The results show that the effect of the visual transformer model is better than that of the convolutional neural network. The research findings also indicate that the visual transformer model based on the proposed framework can accurately predict the sugar content of grapes, non-destructive evaluation of grape quality, and could provide reference values for grape harvesting.

Effect of early cane pruning on yield components, grape composition, carbohydrates storage and phenology in <i>Vitis vinifera</i> L. cv. Merlot

Dormant cane pruning has a great impact on vineyard management both in terms of labour costs and the time required to complete this field operation in the absence of mechanisation. In this study, we investigated over three seasons the influence of five pruning dates on yield components, grape composition, phenology and carbohydrate reserves in the variety Merlot, grown in a warm climate area. Pruning was conducted soon after harvest, at the end of leaf fall, two bud dormancy stages and vine bleeding. Early pruning, carried out a few days after the grape harvest, did not significantly affect vine productivity or grape composition in the next season compared to full winter pruning. Similarly, non-structural carbohydrate concentration in trunk and roots showed no difference just before budburst, no matter the timing of pruning. Late winter pruning at vine bleeding slightly postponed budburst and flowering; it also delayed veraison in one out of two years of observation without affecting grape maturity. Our findings suggested that, in a warm-climate area where leaf fall occurs within a ten-week period after harvest, early pruning had no detrimental effects on reserve accumulation in storage organs and, therefore, in vine yield and grape composition in the next harvest, thus allowing viticulturists to operate winter pruning over an extended interval of time.

A Non-Destructive Method for Grape Ripeness Estimation Using Intervals’ Numbers (INs) Techniques

Grape harvesting based on estimated in-field maturity indices can reduce the costs of pre-harvest exhaustive sampling and chemical analysis, as well as the costs of post-harvest storage and waste across the production chain due to the non-climacteric nature of grapes, meaning that they are not able to reach desired maturity levels after being removed from the vine. Color imaging is used extensively for intact maturity estimation of fruits. In this study, color imaging is combined with Intervals’ Numbers (INs) technique to associate grape cluster images to maturity-related indices such as the total soluble solids (TSSs), titratable acidity (TA), and pH. A neural network regressor is employed to estimate the three indices for a given input of an IN representation of CIELAB color space. The model is tested on one hundred Tempranillo cultivar images, and the mean-square error (MSE) is calculated for the performance evaluation of the model. Results reveal the potential use of the Ins’ NN regressor for TSS, TA, and pH assessment as a non-destructive, efficient, fast, and cost-effective tool able to be integrated into an autonomous harvesting robot.

Aromatic maturity is a cornerstone of terroir expression in red wine

Harvesting grapes at adequate maturity is key to the production of high-quality red wines. Viticulturists, enologists, and wine makers define several types of maturity, including physiological maturity, technological maturity, phenolic maturity, and aromatic maturity. Physiological maturity is a biological concept. Technological maturity and phenolic maturity are relatively well documented in the scientific literature, being linked to quantifiable compounds in grape must. Articles on aromatic maturity are scarcer. This is surprising, because aromatic maturity is, probably, the most important of the four in determining wine quality and typicity, including terroir expression, i.e. the identifiable taste of wine in relation to its origin. Optimal terroir expression can be obtained when technological, phenolic, and aromatic maturity are reached at the same time, or within a short time frame. This is more likely to occur when the ripening takes place under mild temperatures, neither too cool, nor too hot.Aromatic expression in wine can be driven, in order from low to high maturity, by green, herbal, spicy, floral, fresh fruit, ripe fruit, jammy fruit, dried fruit, candied, or cooked fruit aromas. Green and cooked fruit aromas are not desirable in red wines, while the levels of other aromatic nuances contribute to the typicity of the wine in relation to its place of origin. Wines produced in cool climates, or on cool soils in temperate climates, are likely to express herbal or fresh fruit aromas, while wines produced under warm climates, or on warm soils in temperate climates, may express ripe fruit, jammy fruit, or candied fruit aromas.This article reviews the state of the art of compounds underpinning the aromas of wines obtained from grapes harvested at different stages of maturity. Advances in the understanding of how aromatic maturity shapes terroir expression and how it can be manipulated by variety choices and management practices, under current and future climatic conditions, are shown. Early ripening varieties perform better in cool climates and late ripening varieties in warm climates. Additionally, maturity can be advanced or delayed by different canopy management practices or training systems. Timing of harvest also impacts aromatic expression of the produced wine. Gaps in the literature are highlighted to guide future directions of research.

Historical long-term cultivar×climate suitability data to inform viticultural adaptation to climate change

Grape quality is regulated by complex interactions between environments and cultivars. Growing suitable cultivars in a given region is essential for maintaining viticulture sustainability, particularly in the face of climate change. We created a database composed of three different subsets of data. The first subset was created by digitizing and curating the seminal report of Amerine and Winkler (1944), which provided grape harvest dates (GHDs), the quality of musts and wines, and wine tasting notes for 148 cultivars from 1935–1941 across five contrasting climatic regions of California. To put this dataset into a climate change context, we collected GHDs and must sugar content (°Brix) records from 1991 to 2018 for four representative cultivars in one of the five studied regions (Napa). Finally, we integrated meteorological data of the five regions during 1911–2018 and calculated bioclimatic indices important for grape. The resulting database is unique and valuable for assessing the fitness between cultivars across environments in order to mitigate the effects of climate change.Design Type(s)Cultivars design • Regions designMeasurement Type(s)Climate data • Harvest date • Quality • Tasting notesTechnology Type(s)Phenology characterization • Quality determinationSample Characteristic(s)Grape harvest dates • °Brix • Tannin • Total acid • pH • Alcohol • Fixed acid • ExtractMeasurement(s)maximum air temperature • minimum air temperature • total soluble solids (oBrix) • must total acid • must pH • wine alcohol • wine extract • wine tannin • wine total acid • wine volatile acidTechnology Type(s)weather station • a oBrix hydrometer • titration with sodium hydroxide to a phenolphthalein end point • a quinhydrone electrode or a Beckman pH meter • hydrometer • a special 0° to 8° Balling hydrometer • the Association of Official Agricultural Chemists method • titration with phenolphthalein as an indicator • titration with pretreated wines by method II of the Association of Official Agricultural Chemists

Uncertainty appraisal provides useful information for the management of a manual grape harvest

This contribution presents a novel approach to characterise uncertainty in the manual grape harvest of a winery in Tuscany (Italy). After identifying the potential sources of variability arising from randomness, weather, and management options, a model to define useful output variables is built. These output variables include the discrepancy in the harvest date of the vineyards ( harvest date discrepancy) , the discrepancy in the required workforce across harvest dates (labour discrepancy), and, finally, the potential deficit of working hours throughout the grape harvest campaign (labour deficit) . The range spanned by these variables is first assessed through a Monte Carlo uncertainty analysis wherein the model is repeated approximately 16,000 times with variable combinations of the input parameters per their probability distribution. The assessed uncertainty is then apportioned to the input parameters through a global sensitivity analysis. In turn, a regional sensitivity analysis characterises the circumstances producing a deficit of working hours, which corresponds to sufferance in the grape harvest campaign. The discussed approach could be implemented in a user-friendly decision-support tool for risk characterisation and efficient grape harvest management. • We developed a model to define sensitive variables in manual grape harvest. • We characterise their uncertainty through Monte Carlo simulations. • Output uncertainty was apportioned onto inputs with a global sensitivity analysis. • Criticalities were identified and analysed through regional sensitivity analysis. • The approach proposed could support decision making in grape harvest management.

Yeast diversity in Cabernet-Sauvignon and Merlot grapes grown in the highlands of Southern Brazil

Considering the influence of natural yeasts on wine production and the organoleptic properties of the final product, the objective of the present study was to evaluate the diversity of yeasts in Cabernet-Sauvignon and Merlot (Vitis vinifera L.) grown in the highlands of the Northeast region of Rio Grande do Sul State, “Serra Gaúcha”, Brazil. Grape samples were collected from commercial vineyards between February and March in the 2017, 2018 and 2019 vintages. One hundred sixty-six isolated yeasts were classified at the species level by D1/D2 domain of 26S rRNA sequencing. A total of 31 yeast species were identified. The most prevalent species were Hanseniaspora uvarum, Issatchenkia terricola, Saturnispora diversa and Starmerella bacillaris. These same yeasts were the most frequent regardless of the year evaluated. The results indicated that there is a great diversity of yeast species in grapes cultivated in the highlands of Southern Brazil. However, the yeast communities remain similar in Cabernet-Sauvignon and Merlot grapes the analysed parameters (grape variety/vintage) are not interfering in the yeast populations found in the region highlands of Rio Grande do Sul, “Serra Gaúcha”, Brazil. This study enabled the knowledge of the yeast populations present in the region and their variations during the harvesting of wine grapes, showing that there is a majority pattern of species independent of the harvest.

Deep learning and computer vision for assessing the number of actual berries in commercial vineyards

The number of berries is one of the most relevant yield components that drives grape production in viticulture. The goal of this work was to estimate the number of actual berries per grapevine using computer vision and deep learning in commercial vineyards. Images from the visible range (RGB) were acquired from a set of 96 grapevines (Vitis vinifera L.) at pea-size berry stage using a red, green and blue camera (RGB). At harvest, the number of berries and per vine was manually assessed as the ground-truth values. The algorithm involved computer vision to detect berries in the images and to extract canopy features, in order to gain information about canopy occlusion. These were used by the machine learning regression models built to estimate the number of actual berries per vine. A SegNet architecture was used to segment individual berries and several canopy related features. Four datasets were created combining the number of estimated visible berries and different canopy features. Three different regression models were tested on the four datasets. The best results were achieved with support vector regression (SVR) on a dataset including six canopy features. This method yielded a root mean squared error (RMSE) of 205 berries, a normalised root mean squared error (NRMSE) of 24.99% and a coefficient of determination (R2) of 0.83 between the number of estimated and the number of actual berries per vine. The results show that the number of actual berries in grapevines can be assessed with high accuracy up to 60 days prior to grape harvest, using the developed algorithm based on computer vision and deep learning.

Influence of manual and mechanical grape harvest on Merlot wine composition

Effects of mechanical and manual grape harvest on the composition of Merlot musts and wines produced in the Campanha Gaúcha region (Rio Grande do Sul, Brazil) were investigated. Must analyses comprised several basic physicochemical parameters. Wine analyses comprised a screening of phenolics, volatiles, elements, and several physicochemical parameters. In total, 100 variables were investigated. Wines elaborated with grapes from mechanical and manual harvesting were very similar; only 6 parameters showed statistically significant differences, although of low magnitude. These results indicate that - for Campanha Gaúcha's Merlot wines: mechanical grape harvesting itself does not negatively affect wine composition; moreover, grapes harvested manually and mechanically result in almost identical wines.

Assessment of “Sugranineteen” Table Grape Maturation Using Destructive and Auto-Fluorescence Methods

The optimal harvesting of table grapes is commonly determined based on technological and phenolic indices analyzed over the course of its maturity. The classical techniques used for these analyses are destructive, time-consuming, and work for a limited number of samples that may not represent the heterogeneity of the vineyard. This study aimed to follow the ripening season of table grapes using non-destructive tools as a rapid and accurate alternative for destructive techniques. Grape samples were collected from a Sugranineteen vineyard during the ripening season to measure the basic maturity indices via wet chemistry, and total polyphenols, anthocyanins, and flavonoids were evaluated by spectrophotometry. Fluorescent readings were collected from intact clusters with a portable optical sensor (Multiplex® 3, Force-A, France) that generates indices correlated to different maturity parameters. Results revealed strong relationships between the Multiplex® indices ANTH_RG and FERARI and the skin anthocyanin content, with R2 values equal to 0.9613 and 0.8713, respectively. The NBI_R index was also related to total anthocyanins (R2 = 0.8032), while the SFR_R index was linked to the titratable acidity (R2 = 0.6186), the sugar content (R2 = 0.7954), and to the color index of red grapes (CIRG) (R2 = 0.7835). Results demonstrated that Multiplex® 3 can be applied on intact clusters as an effective non-destructive tool for a rapid estimation of table grapes’ anthocyanin content.

Comparison of different maceration and non-maceration treatments for enhancement of phenolic composition, colour intensity, and taste attributes of Malvazija istarska (Vitis vinifera L.) white wines

To investigate the effect of several vinification techniques aimed to enhance wine phenolic profile and sensory quality, maceration treatments of different duration and temperature (pre-fermentative cold one day maceration at 10 °C, seven days maceration at 16 °C, and prolonged post-fermentative 21 day maceration at 16 °C) and non-maceration treatments including tannin addition and late harvest grapes vinification were performed and compared to a standard white grape processing treatment. Produced wines were subjected to the analysis of phenols by high-performance liquid chromatography, colour intensity, and quantitative descriptive and hedonic sensory analysis. The increase in individual phenolic compound concentrations was mostly pronounced in maceration treatment wines, for both phenolic acids and flavan-3-ols, as well as for the sum of phenolic compound concentrations determined by high-performance liquid chromatography that tripled in relation to that determined in control treatment wine. Pre-fermentative cold maceration led to a moderate increase in phenolic compounds content without accentuating bitterness and astringency sensations. Wine phenolic composition and colour intensity were mostly affected by the prolonged post-fermentative 21 day maceration. Vinification of late harvest grapes produced a wine graded with the highest positive score for taste. The obtained distinct wine styles resulting from the application of the investigated practices may lead to a further diversification of white wine market.

Rootstock and potassium fertilization, in terms of phenology, thermal demand and chemical evolution, of berries on Niagara Rosada grapevine under subtropical conditions

This study aimed to assess the effect of rootstocks (IAC 572 and IAC 766) and potassium fertilization at different concentrations (0, 75, 150 and 300 kg·ha-1 K2O) on the phenology and thermal demand of the Niagara Rosada grapevine, and to evaluate the development of chemical traits during maturation stage. The length of the main phenological stages was recorded within two production seasons. Total thermal demand was calculated using the degree-day concept. The berries’ titratable acidity and soluble solids contents were determined during maturation. Results indicated that IAC 572 and IAC 766 rootstocks along with potassium fertilization had no influence on the phenological cycle or thermal demand of the Niagara Rosada grapevine. The production cycle lasted 144 to 148 days with thermal demands ranging from 1,465.2 to 1,615.1 degree-days. For better grape quality, i.e., with a balance between soluble solids and acidity levels, it is estimated that the grape harvest is carried out around 21 to 24 days after the veraison.

Влияние регуляторов роста на качество урожая винограда сортов Московский устойчивый и Хасанский Боуса в условиях Москвы

The article presents the results of studying the influence of growth regulators on the quality of the grape harvest of varieties of interspecific variety Moskovsky ustojchivyj (Skuin 675) and Khasansky Bousa when growing them in Moscow. An assessment of the quality of the crop was carried out when using shock freezing as a processing of fruit and berry raw materials, which makes it possible to obtain a well-preserved, transportable and not losing its properties product. Keywords: GRAPES, GROWTH REGULATORS, CROP QUALITY, TOTAL SUGARS, SHOCK FREEZING, CRYOPRESERVATION

Automated Method for Controlling Oil Filling of Polymer and Composite Materials

For the modernization of polymer and composite materials in order to increase their operational properties, namely strength and wear resistance, there are created oil-filled polymer and composite materials. Filling the manufactured part with oil is problematic in the automating the control of the filled state. The filling process is applicable for polymer or composite bearing separators of agricultural machines (forage harvesters, cotton harvesters, grape harvesters and others) in order to increase their service life in conditions of a large amount of dust and dirt, as well as in cases of dry start. (Research purpose) The research purpose is in developing a methodology for automated filling control of structural polymers and composites used in agricultural machinery with antifriction materials. (Materials and methods) The article presents designed and produced experimental installation and field tests. The developed sensor placement scheme allows performing experimental studies on measuring the volumetric body temperature of a polymer or composite sample during the impregnation process online. The differentiation of the obtained results, presented in graphical form, makes it possible to quickly analyze the dynamics of temperature changes in the thickness of the material. (Results and discussion) The article presents the optimal proportion of a mixture of hexane and M-8B engine oil and the most favorable temperature conditions. It was confirmed the possibility of using this technique in the technology of oil filling of antifriction products made of polymer and composite materials. (Conclusions) The technique makes it possible to identify the filled state of manufactured polymer or composite parts used in friction units of agricultural machines without the introduction of thermal sensors. The control is carried out according to the previously obtained values of the speed and time of impregnation to a given depth of penetration of the oil filler, depending on the type of material.

Mitigating Grapevine Red Blotch Virus Impact on Final Wine Composition

Grapevine red blotch virus (GRBV), the causative agent of red blotch disease, causes significant decreases in sugar and anthocyanin accumulation in grapes, suggesting a delay in ripening events. Two mitigation strategies were investigated to alleviate the impact of GRBV on wine composition. Wines were made from Cabernet Sauvignon (CS) (Vitis vinifera) grapevines, grafted onto 110R and 420A rootstocks, in 2016 and 2017. A delayed harvest and chaptalization of diseased grapes were employed to decrease chemical and sensory impacts on wines caused by GRBV. Extending the ripening of the diseased fruit produced wines that were overall higher in aroma compounds such as esters and terpenes and alcohol-related (hot and alcohol) sensory attributes compared to wines made from diseased fruit harvested at the same time as healthy fruit. In 2016 only, a longer hangtime of GRBV infected fruit resulted in wines with increased anthocyanin concentrations compared to wines made from GRBV diseased fruit that was harvested at the same time as healthy fruit. Chaptalization of the diseased grapes in 2017 produced wines chemically more similar to wines made from healthy fruit. However, this was not supported by sensory analysis, potentially due to high alcohol content masking aroma characteristics.