OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 OENO IVAS 9 OENO IVAS 2019 9 Analytical developments from grape to wine, spirits : omics, chemometrics approaches… 9 Integrated multiblock data analysis for improved understanding of grape maturity and vineyard site contributions to wine composition and sensory domains

Integrated multiblock data analysis for improved understanding of grape maturity and vineyard site contributions to wine composition and sensory domains

Abstract

Much research has sought to define the complex contribution of terroir (varieties x site x cultural practices) on wine composition. This investigation applied recent advances in chemometrics to determine relative contributions of vine growth, berry maturity and site mesoclimate to wine composition and sensory profiles of Shiraz and Cabernet Sauvignon for two vintages. 

Grape maturation was monitored using a berry sugar accumulation model and wines made from sequentially harvested grapes at three stages for each variety and vintage. Comprehensive targeted grape analysis of amino acids, carotenoids, sugars, organic acids, anthocyanins and volatile compounds were combined with targeted wine volatile and non-volatile chemical measures of composition and sensory descriptive analysis. Chemometric models of balanced sample sets derived from the pool samples were used in an ANOVA multiblock framework with orthogonal projection to latent structures (Boccard and Rudaz, 2016) to elucidate the relative importance of model design factors. 

Multiple data matrices derived from the experimental design factors are subtracted from the original data matrix to obtain pure effects and interaction submatrices with structured orthogonal data. A response matrix is derived from the positive eigenvalues associated with SVD of each effect matrix and residuals are then added to each submatrix prior to kernel OPLS. Model performance evaluated from residual structure ratio (RSR), goodness of fit (R2Y) and permutation testing identified the significant factors from each model. Projection of sample scores of significant factors against scores of the residual matrix is used to assess sample clusters with confidence intervals based on Hotelling T2. 

Loadings from significant experimental factors of each model were used for hierarchical cluster analysis (HCA) with Euclidean distance measures and Wards grouping criteria. Prior to HCA scores and loadings are rotated to consistent presentation of factor levels in model plots. A conservative interpretation of loadings heat maps was considered appropriate and a summary heat map for explanatory factors is presented that enable interpretation of the impact of cultivar, site (soil x mesoclimate), grape maturity and region on grape and wine composition. The integrated data driven approach used in this investigation may be of assistance for other investigators for omics based experiments.

Ref: Boccard, J. & Rudaz, S. 2016. Anal Chim Acta. 920:18-28.

DOI:

Publication date: June 19, 2020

Issue: OENO IVAS 2019

Type: Article

Authors

Leigh Schmidtke, Guillaume Antalick, Katja Suklje, John Blackman, Alain Deloire

National Wine and Grape Industry Centre, Charles Sturt University, Locked Bag 588 – Wagga Wagga – New South Wales 2678 – AUSTRALIA
Wine Research Centre, University of Nova Gorica, Vipavska, 5000 Nova Gorica, Slovenia
Agricultrual Institute of Solvenia, Lubljana, 1000, Slovenia
Montpellier SupAgro, Montpellier 34060,

Contact the author

Keywords

AMOPLS, sequential harvest, berry sugar accumulation, targeted metabolomics 

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

Rapid damage assessment and grapevine recovery after fire

There is increasing scientific consensus that climate changeis the underlying cause of the prolonged dry and hot conditions that have increased the risk of extreme fire weather in many countries around the world. In December 2019, a bushfire event occurred in the Adelaide Hills, South Australia where 25,000 hectares were burnt and in vineyards and surrounding areas various degrees of scorching and infrastructure damage occurred. The ability to coordinate and plan recovery after a fire event relies on robust and timely data. The current practice for measuring the scale and distribution of fire damage is to walk or drive the vineyard and score individual vines based on visual observation. The process is time consuming, subjective, or semi-quantitative at best. After the December 2019 fires, it took many months to access properties and estimate the area of vineyard damaged. This study compares the rapid assessment and mapping of fire damage using high-resolution satellite imagery with more traditional ground based measures. Satellite imagery tracking vineyard recovery in the season following the bushfire is being correlated to field assessments of vineyard productivity such as canopy health and development, fertility and carbohydrate storage. Canopy health in the seasons following the fires correlated to the severity of the initial fire damage. Severely damaged vines had reduced canopy growth, were infertile or had very low fertility as well as lower carbohydrate levels in buds and canes during dormancy, which reduced productivity in the seasons following the bushfire event. In contrast, vines that received minor damage were able to recover within 1-2 years. Tools that rapidly and affordably capture the extent and severity of damage over large vineyard area will allow producers, government and industry bodies to manage decisions in relation to fire recovery planning, coordination and delivery, improving the efficiency and effectiveness of their response.

Leaf vine content in nutrients and trace elements in La Mancha (Spain) soils: influence of the rootstock

The use of rootstock of American origin has been the classic method of fighting against Phylloxera for more than 100 years. For this reason, it is interesting to establish if different rootstock modifies nutrient composition as well as trace elements content that could be important for determining the traceability of the vine products. A survey of four classic rootstocks (110-Richter, SO4, FERCAL and 1103-Paulsen) and four new ones (M1, M2, M3 and M4) provided by Agromillora Iberia. S.L.U., all of them grafted with the Tempranillo variety, has been carried out during 2019. The eight rootstocks were planted in pots of 500 cc, on three soils with very different characteristics from Castilla-La Mancha (Spain). In the month of July, the leaves were collected and dried in a forced air oven for seven days at 40ºC. Then, the samples were prepared for the analysis determination, carried out by X-Ray fluorescence spectrometry. The results obtained showed that in the case of content in mineral elements in leaf, separated by soil type, we can report the importance of few elements such as Si, Fe, Pb and, especially, Sr. The rootstock does not influence the composition of the vine leaf for the studied elements that are the most important in determining the geochemical footprint of the soil. The influence of the soil can be discriminated according to some elements such as Fe, Pb, Si and, especially, Sr.

20-Year-Old data set: scion x rootstock x climate, relationships. Effects on phenology and sugar dynamics

Global warming is one of the biggest environmental, social, and economic threats. In the Douro Valley, change to the climate are expected in the coming years, namely an increase in average temperature and a decrease in annual precipitation. Since vine cultivation is extremely vulnerable and influenced by the climate, these changes are likely to have negative effects on the production and quality of wine.
Adaptation is a major challenge facing the viticulture sector where the choice of plant material plays an important role, particularly the rootstock as it is a driver for adaptation with a wide range of effects, the most important being phylloxera, nematode and salt, tolerance to drought and a complex set of interactions in the grafted plant.
In an experimental vineyard, established in the Douro Region in 1997, with four randomized blocs, with five varieties, Touriga Nacional, Tinta Barroca, Touriga Franca and Tinta Roriz, grafted in four rootstocks, Rupestris du Lot, R110, 196-17C, R99 and 1103P, data was collected consecutively over 20 years (2001-2020). Phenological observations were made two to three times a week, following established criteria, to determine the average dates of budbreak, flowering and veraison. During maturation, weekly berry samples were taken to study the dynamics of sugar accumulation, amongst other parameters. Climate data was collected from a weather station located near the vineyard parcel, with data classified through several climatic indices.
The results achieved show a very low coefficient of variations in the average date of the phenophases and an important contribution from the rootstock in the dynamic of the phenology, allowing a delay in the cycle of up to10-12 days for the different combinations. The Principal Component Analysis performed, evaluating trends in the physical-chemical parameters, highlighted the effect of the climate and rootstock on fruit quality by grape varieties.

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Modelling vine water stress during a critical period and potential yield reduction rate in European wine regions: a retrospective analysis

Most European vineyards are managed under rainfed conditions, where seasonal water deficit has become increasingly important. The flowering-veraison phenophase represents an important period for vine response to water stress, which is seldomly thoroughly evaluated. Therefore, we aim to quantify the flowering-veraison water stress levels using Crop Water Stress Indicator (CWSI) over 1986–2015 for important European wine regions, and to assess the respective potential Yield Lose Rate (YLR). Additionally, we also investigate whether an advanced flowering-veraison phase may help alleviating the water stress with improved yield. A process-based grapevine model STICS is employed, which has been extensively calibrated for flowering and veraison stages using observed data at 38 locations with 10 different grapevine varieties. Subsequently, the model is being implemented at the regional level, considering site-specific calibration results and gridded climate and soil datasets. The findings suggest wine regions with stronger flowering-veraison CWSI tend to have higher potential YLR. However, contrasting patterns are found between wine regions in France-Germany-Luxembourg and Italy-Portugal-Spain. The former tends to have slight-to-moderate drought conditions (CWSI<0.5) and a negligible-to-moderate YLR (<30%), whereas the latter possesses severe-to-extreme CWSI (>0.5) and substantial YLR (>40%). Wine regions prone to a high drought risk (CWSI>0.75) are also identified, which are concentrated in southern Mediterranean Europe. An advanced flowering-veraison phase may have benefited from cooler temperatures and a higher fraction of spring precipitation in wine regions of Italy-Portugal-Spain, resulting in alleviated CWSI and moderate reductions of YLR. For those of France-Germany-Luxembourg, this can have reduced flowering-veraison precipitation, but prevalent alleviations of YLR are also found, possibly because of shifted phase towards a cooler growing season with reduced evaporative demands. Overall, such a retrospective analysis might provide new insights towards better management of seasonal water deficit for conventionally vulnerable Mediterranean wine regions, but also for relatively cooler and wetter Central European regions.