Terroir 2020 banner
IVES 9 IVES Conference Series 9 Distinguishing of red wines from Northwest China by colour-flavour related physico-chemical indexes

Distinguishing of red wines from Northwest China by colour-flavour related physico-chemical indexes

Abstract

Aim: Northwest China occupies an important position in China’s wine regions due to its superior geographical conditions with dry climate and sufficient sunlight. In this work, we aimed to investigate the physico-chemical colour and flavour characteristics of red wine in Northwest China.

Methods and Results: A total of 196 commercial dry red wines from Ningxia autonomous region, Gansu province and Xinjiang autonomous region in Northwest China were sampled. Spectro-analysis and chemical titration were used to quantify physico-chemical indicators related to wine colour and flavour, including total anthocyanins, co-pigments, monomeric anthocyanins, polymeric anthocyanins, ionisation index, CIE color space, total phenols, flavonol, ethanol index, total tannin, gelatin index, HCl index, DPPH antioxidant activity, tartrate ester, titratable acid, and pH value. Principal Component Analysis (PCA) of the data showed that wine samples in Ningxia, Gansu and Xinjiang region had obvious clustering phenomena. Among them, total anthocyanin and polymeric anthocyanins in Ningxia wines were higher compared to other wines. Ningxia wines also had the highest total acids and lighter colour whereas Gansu wines had greater amounts of monomeric anthocyanins, co-pigments and phenolic indexes. Gansu wines were darker in colour with the highest pH values. The parameters of Xinjiang wines were ranged between Ningxia wines and Gansu wines. PCA also showed good discriminant results on wine vintages. Wines older than 3 years had more polymeric anthocyanins and stable colour whilst younger wines had more total anthocyanin and monomeric anthocyanin with brighter colour. In addition, younger wines had the highest phenolics. Grape cultivars also contributed to the difference of colour and flavour associated indexes. Among them, Cabernet Sauvignon wines displayed distinct characteristics compared to other wines. Values of total anthocyanins, DPPH antioxidant activity, ionisation index, Cab and HCl acid indexes of Cabernet Sauvignon wines were higher than those of other wines. Finally, a convolutional neuralnetwork model was used to discriminate and analyses the categorical data of wines. These data were standardized and analysised using TensorFlow. The corresponding fitness indexes were 99.14%, 90.52%, and 89.66% from Northwest China based on region, cultivar, and vintage.

Conclusions: 

Colour and flavour associated indexes of wines from Northwest China are strongly impacted by wine regions, cultivars, and vintages.

Significance and Impact of the Study: Wine regions in Northwest China are developing drastically in recent decades, however relevant criteria of colour-flavour quality to help manipulate winemaking practices are lacking in local wineries to ensure the quality of wine style. Our results highlighted the possibility of establishing such wine quality criteria specially for Northwest China based on building a discrimination model on wine physico-chemical related indicators.

DOI:

Publication date: March 17, 2021

Issue: Terroir 2020

Type: Video

Authors

Yu Zhao1, Guojie Jin1, Jiao Jiang1, Shijin Xue1, Kai Hu1*, Yongsheng Tao1,2*

College of Enology, Northwest A&F University, Yangling, Shaanxi 712100, China
Shaanxi Engineering Research Center for Viti-viniculture, Yangling, Shaanxi 712100, China

Contact the author

Keywords

Wine region, spectro-analysis, discrimination analysis, neural network analysis, colour-flavour physico-chemical indicators

Tags

IVES Conference Series | Terroir 2020

Citation

Related articles…

The plantation frame as a measure of adaptation to climate change

The mechanization of vineyard work originally led to a reduction in planting densities due to the lack of machinery adapted to the vineyard. The current availability of specific machinery makes it possible to establish higher planting densities. In this work, three planting densities (1.40×0.80 m, 1.80×1 m and 2.20×1.20 m, corresponding to 8928, 5555 and 3787 plants/ha respectively) were studied with four varieties autochthonous of Galicia (northwestern Spain): Albariño and Treixadura (white), Sousón and Mencía (red). The vines were trained in a vertical shoot positioning system using a single Royat cordon, and pruned to spurs with two buds each. Agronomic data (yield, pruning wood weight, Ravaz index) and oenological data in must were collected. The higher planting density (1.40×0.80 m) had no significant effect on grape yield per vine in white varieties, although production per hectare was much higher due to the greater number of plants. In red varieties, this planting density resulted in a significantly lower production per vine, compensated by the greater number of plants. In addition, it significantly reduced the Brix degree in the must of the Albariño, Treixadura and Sousón varieties, and increased the total acidity in the latter two and Mencía. It also caused an increase in extractable and total anthocyanins and IPT in red grapes. The effects of high planting density on grapes are of great interest for the adaptation of varieties in the context of climate change. In the future, it could be advisable to modify the limits imposed by the appellations of origin on the planting density of these varieties in order to obtain more balanced wines.

Mobile device to induce heat-stress on grapevine berries

Studying heat stress response of grapevine berries in the field often relies on weather conditions during the growing season. We constructed a mobile heating device, able to induce controlled heat stress on grapes in vineyards. The heater consisted of six 150 W infrared lamps mounted in a profile frame. Heating power of the lamps could be controlled individually by a control unit consisting of a single board computer and six temperature sensors to reach a pre-set temperature. The heat energy applied to individual berries within a cluster decreases by the squared distance to the heat source, enabling the establishment of temperature profiles within individual clusters. These profiles can be measured by infrared thermography once a steady state has been reached. Radiant flux density received by a berry depending on the distance was calculated based on a view factor and measured lamp surface temperature and resulted to 665 Wm-2 at 7cm. Infrared thermography of the fruit surface was in good agreement with measurements conducted with a thermocouple inserted at epidermis level. In combination with infrared thermography, the presented device offers possibilities for a wide range of applications like phenotyping for heat tolerance in the field to proceed in the understanding of the complex response of plants to heat stress. Sunburn necrosis symptoms were artificially induced with the aid of the device for cv. Bacchus and cv. Sylvaner in the 2020 and 2021 growing season. Threshold temperatures for sunburn induction (LT5030min) were derived from temperature data of single berries and visual sunburn assessment, applying logistic regression. A comparison of threshold temperatures for the occurrence of sunburn necrosis confirmed the higher susceptibility of cv. Bacchus. The lower susceptibility of cv. Sylvaner did not seem to be related to its phenolic composition, rendering a thermoprotective role of berry phenolic compounds unlikely.

The impact of leaf canopy management on eco-physiology, wood chemical properties and microbial communities in root, trunk and cordon of Riesling grapevines (Vitis vinifera L.)

In the last decades, climate change required already adaptation of vineyard management. Increase in temperature and unexpected weather events cause changes in all phenological stages requiring new management tools. For example, defoliation can be a useful tool to reduce the sugar content in the berries creating differences in the wine profiles. In a ten-year field experiment using Riesling (Vitis vinifera L, planted 1986, Geisenheim, Germany), various mechanical defoliation strategies and different intensities were trialed until 2016 before the vineyard was uprooted. Wood was sampled from the plant compartments root, trunk, cordon and shoot for analyses of physicochemical properties (e.g. lignin and element content, pH, diameter), nonstructural carbohydrates and the microbial communities. The aim of the study was to investigate the influence of reduced canopy leaf area on the sink-source allocation into different compartments and potential changes of the fungal and prokaryotic wood-inhabiting community using a metabarcoding approach. Severe summer pruning (SSP) of the canopy and mechanical defoliation (MDC) above the bunch zone decreased the leaf area by 50% compared to control (C). SSP reduced the photosynthetic capacity, which resulted in an altered source-sink allocation and carbohydrate storage. With lower leaf area, less carbohydrates are allocated. This for example resulted in a decreased trunk diameter. Further, it affected the composition of the grapevine wood microbiota. SSP and MDC management changed significantly the prokaryotic community composition in wood of the root samples, but had no effect in other compartments. In general, this study found strong compartment and less management effects of the microbial community composition and associated physicochemical properties. The highest microbial diversities were identified in the wood of the trunk, and several species were recorded the first time in grapevine.

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Biodiversity in the vineyard agroecosystem: exploring systemic approaches

Biodiversity conservation and restoration are essential for guarantee the provision of ecosystem services associated to vineyard agroecosystem such as climate regulation trough carbon sequestration and control of pests and diseases. Most of published research dealing with the complexity of the vineyard agroecosystems emphasizes the necessity of innovative approaches, including the integration of information at different temporal and spatial scales and development of systemic analysis based on modelling. A biodiversity survey was conducted in the Franciacorta wine-growing area (Lombardy, Italy), one of the most important Italian wine-growing regions for sparkling wine production, considering a portion of the territory of 112 ha. The area was divided into several Environmental Units (EUs), defined as a whole vineyard or portion of vineyard homogenous in terms of four agronomic characteristics: planting year, planting density, cultivar, and training system. In each EU a set of compartments was identified and characterised by specific variables. The compartments are meteorology, morphology (altitude, slope, aspect, row orientation, and solar irradiance), ecological infrastructures and management. The landscape surrounding EU was also characterised in terms of land-use in a buffer zone of 500 m. For each component a specific methodology was identified and applied. Different statistical approaches were used to evaluate the method to integrate the information related to different compartments within the EU and related to the buffer zone. These approaches were also preliminarily evaluated for their ability to describe the contribution of biodiversity and landscape components to ecosystem services. This methodological exploration provides useful indication for the development of a fully systemic approach to structural and functional biodiversity in vineyard agroecosystems, contributing to promote a multifunctional perspective for the all wine-growing sector.