Grape Sugar Content Research Articles

Shading Treatment Reduces Grape Sugar Content by Suppressing Photosynthesis-Antenna Protein Pathway Gene Expression in Grape Berries.

To explore the impact of shade treatment on grape berries, 'Marselan' grape berries were bagged under different light transmission rates (100% (CK), 75% (A), 50% (B), 25% (C), 0% (D)). It was observed that this treatment delayed the ripening of the grape berries. The individual weight of the grape berries, as well as the content of fructose, glucose, soluble sugars, and organic acids in the berries, was measured at 90, 100, and 125 days after flowering (DAF90, DAF100, DAF125). The results revealed that shading treatment reduced the sugar content in grape berries; the levels of fructose and glucose were higher in the CK treatment compared to the other treatments, and they increased with the duration of the shading treatment. Conversely, the sucrose content exhibited the opposite trend. Additionally, as the weight of the grape berries increased, the content of soluble solids and soluble sugars in the berries also increased, while the titratable acidity decreased. Furthermore, 16 differentially expressed genes (DEGs) were identified in the photosynthesis-antenna protein pathway from the transcriptome sequencing data. Correlation analysis revealed that the expression levels of genes VIT_08s0007g02190 (Lhcb4) and VIT_15s0024g00040 (Lhca3) were positively correlated with sugar content in the berries at DAF100, but negatively correlated at DAF125. qRT-PCR results confirmed the correlation analysis. This indicates that shading grape clusters inhibits the expression of genes in the photosynthesis-antenna protein pathway in the grape berries, leading to a decrease in sugar content. This finding contributes to a deeper understanding of the impact mechanisms of grape cluster shading on berry quality, providing important scientific grounds for improving grape berry quality.

Irrigation decreases flower cover and beneficial arthropod abundances in Mediterranean vineyards

Over the last decades, the use of irrigation in vineyards has grown exponentially in response to climate change. In the Mediterranean region, irrigation is the most widely used method of preventing water stress and high sugar content in grapes. However, little is known about potential irrigation effects on biodiversity. This study aims to understand the effect of irrigation on inter-row vegetation, on the abundance of beneficial arthropods and on the predation of pest insects. In the Luberon region of South-Eastern France, nine irrigated and nine non-irrigated vineyards were analysed. Drip irrigation was applied only during the two driest months of the growing season. We found lower flower cover in irrigated vineyards but no difference in species richness and total vegetation cover. Similarly, abundances of several beneficial arthropods were directly affected by irrigation, such as crab spiders, ladybirds, ladybird larvae and parasitic wasps. Structural equation modelling (SEM) revealed that negative irrigation effects on these arthropods were mediated by negative effects on flower cover. Predation rates were also lower in irrigated vineyards but only during daytime. Grapevine yield was not affected by irrigation. Experiments manipulating water availability under controlled conditions may help to understand this surprisingly strong effect of irrigation on flower cover and beneficial arthropod abundance.

Exploration of 5-Azacytidine and Trichostatin A in the modulation of postharvest quality of 'Shine Muscat' grape berries

Grapes have excellent commercial characteristics and high nutritional value, but postharvest storage inevitably reduces their quality. Previously, we studied the regulatory mechanisms of methylation for grape ripening. To further investigate the effects of epigenetic modifications on postharvest quality of grape berries, Transcriptome deep sequencing (RNA-seq) and metabolome sequencing were performed on 5-Azacytidine (5azaC) or Trichostatin A (TSA) treated grape berries. TSA delayed the depletion of soluble sugar and organic acid content in postharvest grapes compared to controls, while 5azaC had the opposite effect. In addition, TSA and 5azaC affected the content and composition of volatile organic compounds (VOCs) in the berries, of which the decrease in linalool content may be directly responsible for the reduction of muscat flavor in the berries. RNA-Seq analysis showed that 626 and 2253 differentially expressed genes (DEGs) were generated by 5azaC and TSA treatments, respectively. GO and KEGG enrichment analyses revealed significant differences in the biological pathways involved in the two collections of DEGs. Metabolomic analyses further clarified the marker metabolites induced by TSA and 5azaC related to fruit quality. In addition, the results of HDAC activity and transcript levels of acetylation-related genes suggest that VvHDA15 may acetylation modification affects the key regulators of postharvest fruit quality. This study not only provides abundant data information, but also offers new insights into the regulation of fruit quality by epimodification.

Effect of Supplementary Light with Different Wavelengths on Anthocyanin Composition, Sugar Accumulation and Volatile Compound Profiles of Grapes.

Protected cultivation is currently one of the main cultivation modes for grape production, but the long-term use of plastic film will have a certain negative impact on the light environment in vineyards, which in turn causes poor colouring, low sugar content and a lack of aroma in some red grape varieties. Supplementing light can be an effective way to mitigate these problems. In this study, vines of three red table grape varieties ('Summer Black', 'Xinyu' and 'Queen Nina') cultivated in a plastic greenhouse were supplemented with red, blue, white and red-blue light from veraison to harvest. All four supplemental light treatments increased the content of anthocyanins, sugars and volatile compounds in three grape varieties compared to CK (no supplemental lighting). Red-blue light treatment was the most favourable for the accumulation of anthocyanins and sugars, and the grapes treated with blue light had the highest content of volatile compounds. The grapes treated with red-blue light all obtained the highest composite scores via principal component analysis. For most of the sensory properties, the highest scores were obtained by the red-blue light-treated grapes. The results of this study will be useful in improving the colouring, sugar, and aroma content of grapes under protected cultivation.

Quality Characteristics and Antioxidant Activities of Six Types of Korean White Wine.

The cultivation of European grape cultivars suitable for winemaking in Korea presents challenges due to factors such as climate, soil conditions, precipitation, and sunlight. Consequently, Korea has traditionally resorted to adding sugar to its wine production to counteract the low sugar content in Korean grapes, yielding lower-quality wines. However, recent success in the cultivation of five European grape cultivars and the development of the domestic grape cultivar Cheongsoo have increased the possibility of achieving high-quality Korean wines. This study aimed to explore the potential of European grape cultivars and Cheongsoo as wine grapes in Korea. This study also conducted sensory evaluation and analyzed the physicochemical properties of the grapes and wines, including antioxidant capacity and color. Despite originating from the same vineyard, the composition of grapes and wines, including volatile aromatic compounds, significantly differed among the grape cultivars. In particular, Vidal wine exhibited superior antioxidant capacity compared with other wines. Moreover, Cheongsoo wine showed higher levels of essential volatile aromatic compounds, such as monoterpenes, than other wines. Sensory evaluation of these two wines also revealed excellent results. In conclusion, these findings hold promise for enhancing the diversity of Korean white wine and fostering growth in the wine industry.

Delay in the Ripening of Wine Grapes: Effects of Specific Phytotechnical Methods on Harvest Parameters

Due to climate change, the sugar content of grapes in Hungary has increased to such an extent that the high alcohol content alone can make wines disharmonious. In most vintages, this phenomenon is only a problem for early-ripening varieties. In order to prevent and treat this difficulty, we have carried out experiments in grape canopy management for four years with the aim of delaying ripening and thus reducing the sugar content of the grapes. The experiments were set up on an early (Pinot noir) and a late (Welshriesling) variety; two treatments (leaf removal—LR and short topping—ST) were applied and compared to untreated controls in the years 2019–2022. Our results showed that grape juice sugar yield was significantly reduced in all four years and for both cultivars, while the other measured parameters (yield, acidity, pH, and Botrytis infection) were only lightly affected.

Effect of Drought on the Future Sugar Content of Wine Grape Varieties till 2100: Possible Adaptation in the Hungarian Eger Wine Region.

The most significant risk for viticulture is that the sugar content of the grapes will increase in the future due to rising temperatures. As a result, it will be possible to produce wines with increasing alcohol content in the future. Excessively high alcohol content can significantly reduce the wines' marketability and viticulture's profitability. Our study seeks to answer how the expected drought in the Southern and Central regions of Europe will affect the future change in the sugar content of grapes. The degree of dryness was examined using the dryness index in the study. Finally, it was analyzed how the dryness index affects the past and future occurrence of maximum sugar content for six grape varieties. The probability of the occurrence of maximum sugar content for most vine grape varieties will decrease in the near future. However, in the distant future, there is a likelihood that the occurrence of maximum sugar content will increase again. If we can maintain the DI ≥ -10 condition with regulated deficit irrigation, the probability of the occurrence of maximum sugar content may decrease significantly in the near future. Ensuring moderate dryness is the only way to achieve the proper sugar content.

Ethanol-lactate transition of Lachancea thermotolerans is linked to nitrogen metabolism

Climate change increases sugar content in grapes, resulting in unwanted increase in ethanol content of wine. Lachancea thermotolerans ferments glucose and fructose into both ethanol and lactate, decreasing final ethanol content and positively affecting wine acidity. Reported Lachancea thermotolerans strains show big variation in lactate production during fermentation. However, a mechanistic understanding of this lactate producing phenotype is currently lacking. Through a combination of metabolomics, transcriptomics, genomics and computational methods we show that the lactate production is induced by amino acid limitation in a high lactate producing strain. We found in fermentations in synthetic grape juice media that lactate production starts in the last stages of growth, marked by decreased growth rate and increased expression levels of stress related genes. This onset of lactate production is specific for the high lactate producing strain and independent of oxygen availability. The onset of lactate production was changed by increased amino acid content of the media, and it is shown by both computational methods and amino acid measurements that at the onset of lactate production amino acids become limiting for growth. This study shows that lactate production of Lachancea thermotolerans is directly linked to nitrogen availability in the media, an insight that can further aid in the improvement of wine quality.

Pre-Harvest Application of Multi-Walled Carbon Nanotubes Improves the Antioxidant Capacity of ‘Flame Seedless’ Grapes during Storage

As a widely distributed fruit, grapes are susceptible to oxidative damage during storage and transportation, resulting in declining quality and commodity value. This study aimed to investigate the effects of preharvest application of different concentrations of multi-walled carbon nanotubes (MWCNTs) on the postharvest quality of ‘Flame Seedless’ grapes. The results showed that low-concentration (25 and 50 mg L−1) MWCNTs treatments maintained the comprehensive quality index, firmness, soluble sugar, titratable acid, pH value, and ascorbic acid (AsA) content of grapes. MWCNTs at 25 and 50 mg L−1 increased the activities of peroxidase (POD), catalase (CAT), superoxide dismutase (SOD), and ascorbic acid (APX). Furthermore, MWCNTs reduced the malondialdehyde (MDA) content and decreased the accumulation of excessive reactive oxygen species (ROS) in grape peel and pulp tissues. In addition, transmission electron microscopy (TEM) images demonstrated that MWCNTs were absorbed by parenchymal cells in the grape peel and pulp through the epidermal cell layer. MWCNTs with a specific concentration can be used as a new inducer for the biosynthesis of antioxidants to reduce oxidative damage in grapes during storage.

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.

Methods for comparing and improving the quality of local storage of grapes in Uzbekistan

In this article, several methods of storing the harvest of the grape varieties in a natural way, including storage, vine method, storage in water-filled containers (by the method of legumes) were studied. During the experiments, discrepancy between their quality indicators, advantages and disadvantages of these methods, storage periods and conditions, as well as the amount of dry matter, the amount of nitrate, the pH environment were researched and analyzed. The pertinent results showed that the sugar content of grapes was the lowest according to the characteristics of varieties in the vine method, accounted for 16.3% and the highest in the storage method, which was 21.17 %, the amount of nitrate was not more than 60 mg/kg in the norm, which was also allowed in all methods. Noteworthy, the most acceptable method among them was the bottle method, however, the method needed to be improved in the future.

Relationship between the El Niño-Southern Oscillation and yield and sugar content of wine grapes grown in Santana do Livramento, RS, Brazil

The El Niño-Southern Oscillation (ENSO) is a well-known source of interannual variability in the climate of Santana do Livramento, Campanha Gaúcha, Brazil. It affects the agronomic responses of several crops grown in the region. Analysis of a dataset comprising observations of grape yield and sugar content in 11 white and 17 red grape cultivars over the last 3 decades revealed some patterns. In the long term (several years or decades), yield and sugar content showed a negative relationship, that is, larger crop loads resulted in lower sugar content at harvest. However, a number of calculations and principal component analyses showed that annual yield and sugar content fluctuations in the short term can be better explained by considering as reference points only the results obtained for each crop one and two years before. Based on these simple calculations, there was a clear separation between El Niño and La Niña events. In the vineyards of this region, La Niña events typically tend to result in higher grape yields and sugar content at harvest, while the opposite is true for El Niño, which tend to produce lower grape yields and sugar content at harvest. The results of neutral events are typically closer to those of El Niño events.

Predicting Grape Sugar Content under Quality Attributes Using Normalized Difference Vegetation Index Data and Automated Machine Learning.

Wine grapes need frequent monitoring to achieve high yields and quality. Non-destructive methods, such as proximal and remote sensing, are commonly used to estimate crop yield and quality characteristics, and spectral vegetation indices (VIs) are often used to present site-specific information. Analysis of laboratory samples is the most popular method for determining the quality characteristics of grapes, although it is time-consuming and expensive. In recent years, several machine learning-based methods have been developed to predict crop quality. Although these techniques require the extensive involvement of experts, automated machine learning (AutoML) offers the possibility to improve this task, saving time and resources. In this paper, we propose an innovative approach for robust prediction of grape quality attributes by combining open-source AutoML techniques and Normalized Difference Vegetation Index (NDVI) data for vineyards obtained from four different platforms-two proximal vehicle-mounted canopy reflectance sensors, orthomosaics from UAV images and Sentinel-2 remote sensing imagery-during the 2019 and 2020 growing seasons. We investigated AutoML, extending our earlier work on manually fine-tuned machine learning methods. Results of the two approaches using Ordinary Least Square (OLS), Theil-Sen and Huber regression models and tree-based methods were compared. Support Vector Machines (SVMs) and Automatic Relevance Determination (ARD) were included in the analysis and different combinations of sensors and data collected over two growing seasons were investigated. Results showed promising performance of Unmanned Aerial Vehicle (UAV) and Spectrosense+ GPS data in predicting grape sugars, especially in mid to late season with full canopy growth. Regression models with both manually fine-tuned ML (R² = 0.61) and AutoML (R² = 0.65) provided similar results, with the latter slightly improved for both 2019 and 2020. When combining multiple sensors and growth stages per year, the coefficient of determination R² improved even more averaging 0.66 for the best-fitting regressions. Also, when considering combinations of sensors and growth stages across both cropping seasons, UAV and Spectrosense+ GPS, as well as Véraison and Flowering, each had the highest average R² values. These performances are consistent with previous work on machine learning algorithms that were manually fine-tuned. These results suggest that AutoML has greater long-term performance potential. To increase the efficiency of crop quality prediction, a balance must be struck between manual expert work and AutoML.

Effects of grape phylloxera leaf infestation on grapevine growth and yield parameters in commercial vineyards: a pilot study

Grape phylloxera (Daktulosphaira vitifoliae) can infest both roots and leaves of Vitis species. In commercial vineyards planted with Vitis vinifera scions grafted on rootstocks, grape phylloxera infestation is generally limited to root feeding. Vineyards are, however, increasingly subjected to vineyard-wide foliar infestations that last throughout the growing season. While some vineyards are affected by the infestation pressure of external leaf-feeding populations, other annually affected V. vinifera vineyards do not have these in their vicinity. Much is known about the damage potential of grape phylloxera root feeding; however, data on how phylloxera leaf infestation affects V. vinifera grapevines in commercial vineyards are lacking. This study, therefore, aimed to assess whether grapevine growth and yield are affected due to leaf infestation as it occurred in three commercial vineyards in the study area. Treatments were based on phylloxera leaf infestation and additional defoliation. Single-leaf carbon acquisition was measured with gas exchange analyses on healthy and galled leaves. Pruning weight and internode length were measured to assess the effect of leaf infestation and the effect of plant growth and vigour on leaf gall outbreaks. Yield quantity and quality were measured, and grapes were vinified for sensory analyses. Furthermore, using enzymatic analyses, non-structural carbohydrates were analysed in perennial wood. A significant decrease in sugar content in grapes (10 %) and starch reserves in perennial wood (11 %) was found in the most heavily infested vineyard. Grape must of infested plants in another vineyard furthermore showed a significantly higher level of titratable acid (7.5 %). Significant infestation effects seen in one vineyard were not significant in the other two vineyards. No significant differences were seen for carbon acquisition, harvest quantity, wine sensory analysis, pruning weight or internode length. The overall effect of phylloxera leaf infestation in the studied vineyards was, therefore, marginal. Grapevine vigour did not differ between infested vines, insecticide-sprayed vines, and vines on which no leaf infestation outbreaks took place. By analysing phylloxera leaf infestation under field conditions, these preliminary results form a basis for future long-term field studies about phylloxera leaf feeding on Vitis vinifera within the context of other biotic and abiotic plant stresses.

Influence of Plant Growth Regulators to Improve the Colour and Sugar Content of Grapes (Vitis vinifera L.). cv. Red Globe

Studies on Effect of plant growth regulators to improve the colour and sugar content of Grapes” (Vitis vinifera L.).cv. Red Globe was conducted in the field of a progressive grape grower at Kaalampalyam (10 O 58’49.17” N and 76 O 55’ 15. 81”E and elevation of 1352 ft from MSL) near Perur area of Coimbatore district in Tamil Nadu. The experiment was laid out in a randomized Block design with 7 treatments and each treatment was replicated four times. The data recorded on various parameters viz., vegetative growth, flowering, fruit yield, Quality etc., were statistically analysed. Significant differences were observed among the growth regulators on various vegetative growth parameters in Grapes (Vitis vinifera L.). cv. Red Globe. Among all the treatments, number of bunches per vine was significantly higher when sprayed with ethephon 200ppm (T4) compared to other treatments. (6.53 cm), the berry size and berry weight of the grapes were found to be maximum in the bunches treated with CCC 500ppm (T2) (6.57 g), There was no impact on the number of seeds by the treatments. The ethephon 200ppm (T4) treatment exhibited superior quality in terms of juice content, total sugars and colour value.

Biotechnological Approaches to Lowering the Ethanol Yield during Wine Fermentation.

One of the most prominent consequences of global climate warming for the wine industry is a clear increase of the sugar content in grapes, and thus the alcohol level in wines. Among the several approaches to address this important issue, this review focuses on biotechnological solutions, mostly relying on the selection and improvement of wine yeast strains for reduced ethanol yields. Other possibilities are also presented. Researchers are resorting to both S. cerevisiae and alternative wine yeast species for the lowering of alcohol yields. In addition to the use of selected strains under more or less standard fermentation conditions, aerobic fermentation is increasingly being explored for this purpose. Genetic improvement is also playing a role in the development of biotechnological tools to counter the increase in the wine alcohol levels. The use of recombinant wine yeasts is restricted to research, but its contribution to the advancement of the field is still relevant. Furthermore, genetic improvement by non-GMO approaches is providing some interesting results, and will probably result in the development of commercial yeast strains with a lower alcohol yield in the near future. The optimization of fermentation processes using natural isolates is, anyway, the most probable source of advancement in the short term for the production of wines with lower alcohol contents.

Utjecaj prorjeđivanja grozdova na kakvoću mošta kultivara Chardonnay u kutjevačkom vinogorju

Kutjevo wine-hills are located on southern slopes of Papuk and Krndija mountains. The area is the most famous by production of Graševina grapes, but increasing share of other varieties cannot be ignored. Chardonnay is the most widespread variety all over the world, and in Požeško-slavonska county is represented by 5 % of total vineyards area. The aim of this research was to determine the influence of cluster thinning in Kutjevo wine-hills on maturation and must quality of Chardonnay grapes. Research was conducted in 2020 in Podgorje location (Kutjevo wine-hills). Experiment was established by a randomized block schedule in two treatments with three repetitions. Five vines in a row makes one repetition. The following parameters have been determined: sugar content and total acidity in grapes in period of one month before harvest, number of clusters per vine, cluster mass, mass of 100 berries, density, total acidity, volatile acidity, tartaric acid, malic acid, lactic acid, pH, reducing sugars, extract, glucose, fructose, glycerol, alfa amino nitrogen, ammonia nitrogen and potassium. Results have showed that cluster thinning had a significant influence on cluster mass and number of clusters per vine, but majority of chemical parameters were not significantly different between two treatments. Statistically significant difference was only in case of pH, lactic acid and ammonium nitrogen

Prediction of Sugar Content in Port Wine Vintage Grapes Using Machine Learning and Hyperspectral Imaging

The high quality of Port wine is the result of a sequence of winemaking operations, such as harvesting, maceration, fermentation, extraction and aging. These stages require proper monitoring and control, in order to consistently achieve the desired wine properties. The present work focuses on the harvesting stage, where the sugar content of grapes plays a key role as one of the critical maturity parameters. Our approach makes use of hyperspectral imaging technology to rapidly extract information from wine grape berries; the collected spectra are fed to machine learning algorithms that produce estimates of the sugar level. A consistent predictive capability is important for establishing the harvest date, as well as to select the best grapes to produce specific high-quality wines. We compared four different machine learning methods (including deep learning), assessing their generalization capacity for different vintages and varieties not included in the training process. Ridge regression, partial least squares, neural networks and convolutional neural networks were the methods considered to conduct this comparison. The results show that the estimated models can successfully predict the sugar content from hyperspectral data, with the convolutional neural network outperforming the other methods.

Food-scanner applications in the fruit and vegetable sector

In the past few years, portable and smartphone-based diagnostic technologies have found their way into the agri-food industry. The aim of this research was to evaluate the performance of portable near-infrared (NIR) spectrometers, so called food-scanners, with regard to their predictive accuracy of important quality parameters of fruit and vegetables. Food-scanner measurements were performed in combination with destructive measurements of the corresponding quality trait (sugar content, dry matter, relative water content) on a wide range of produce from the fruit and vegetable assortment. This study evaluated dry matter content of apple, avocado, blueberry, table grape and tangerine, which yielded cross validation results (r²) of up to 0.95, 0.87, 0.94, 0.92 and 0.92 respectively. Furthermore, the evaluation of food-scanner spectra for the prediction of sugar content of blueberry, kiwi, mango, persimmon, table grape, tangerine and tomato yielded cross validations (r²) of up to 0.95, 0.84, 0.80, 0.75, 0.95, 0.93, and 0.87. Furthermore, relative water content of ginger obtained a cross validation correlation of r² = 0.91. The results show that these traits can be predicted with a high degree of accuracy using non-destructive measurements performed with three commercially available food-scanners SCiO™, F-750 Produce Quality Meter, and H-100F. Consequently, food-scanners can be used as objective measurement tools along the supply chain of fresh produce to quickly determine fruit quality. In addition, a practical example shows the potential of these instruments for non-destructive quality assessment in incoming goods control at fruit and vegetable wholesalers over a time period of several weeks. Furthermore, possible areas of application of food-scanners along the supply chain of fresh produce are discussed, possibilities for practical applications are presented and time-saving means are highlighted.

Non-destructive testing of red globe grape sugar content and moisture content based on visible/near infrared spectroscopy transmission technology

Non-destructive testing of red globe grape sugar content and moisture content based on visible/near infrared spectroscopy transmission technology