GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 NIR spectroscopy as a contacless rapid tool to estimate the amino acids profile in intact grape berries

NIR spectroscopy as a contacless rapid tool to estimate the amino acids profile in intact grape berries

Abstract

Context and purpose of the study – Nitrogen composition of grape berries plays a key role in determining wine quality, affecting the development of alcoholic fermentation and the formation of volatile compounds. Grape nitrogen composition is influenced by several factors such as viticultural practices, soil management, timing or rate of fertilization and use of rootstock, among others.In this study a proximal, non-destructive tool based on NIR spectroscopy is presented to track the accumulation of a wide range of amino acids in intact grape berries during the ripening process.

Material and methods – Clusters of grapevines of Vitis vinifera L. cv. Tempranillo were collected in a commercial vineyard located in Tudelilla, La Rioja, Spain (Lat. 42°18′ 18.26″, Long. -2°7′ 14.15″, Alt. 515 m) on five different dates from veraison to harvest in 2016 season. Contactless (at 25 cm from berries) spectral measurements from intact grape berries were acquired using a NIR spectrometer working in the 1100 – 2100 nm spectral range under laboratory conditions.A total of 19 individual amino acids in 120 grape clusters were quantified by HPLC, which was used as the reference method for the validation of the spectral tool. Principal component analysis (PCA) and Modified partial least squares (MPLS) regressions were used to explore the data structure and for the prediction of the amino acids profile in grape berries, by building calibration and validation models.

Results – A wide variability of all studied parameters was found during the ripening process with amino acid content ranging from 0.07 mg N/l (Glycine) to 534 mg N/l (Arginine). On average, Arginine was the most abundant amino acid (46.64 %), followed by Glutamine (14.70 %) and Proline (6.76 %). The best calibration and cross-validation models were built for Arginine, Cysteine and Proline with correlation coefficients values of 0.80, 0.77 and 0.75, while the standard errors of cross validation (SECV) were 43.04 mg N/l, 0.40 mg N/l and 5.87 mg N/l, respectively. In terms of the Free Amino Nitrogen content (FAN) the values of 0.71 and 104.85 mg N/l were gathered for the correlation coefficient of cross validation and SECV, respectively. The potential of NIR technology to fingerprinting the amino acid content in intact berries has been investigated. This technology could be used to select or classify grape berries during ripening in the vineyard, or at harvest time at the reception of the grapes in the production line (winery). This could be very useful to adapt the enological fate or grape berries to different wine qualities or styles, as well as to adopt different viticultural (thinning, selective harvesting) or enological decisions. Nevertheless, further examination of the influence of more varieties, seasons, and origins should be conducted with the aim of developing more robust, global, and predictive models.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Juan FERNÁNDEZ-NOVALES1, Teresa GARDE-CERDÁN1, Javier TARDÁGUILA1, Sandra MARÍN-SAN ROMÁN1, Eva P. PÉREZ-ÁLVAREZ1, Eugenio MOREDA1, Maria-Paz DIAGO1*

Instituto de Ciencias de la Vid y del Vino (Universidad de La Rioja, CSIC, Gobierno de La Rioja) Finca La Grajera, Ctra. de Burgos Km 6. 26007 Logroño, La Rioja, Spain

Contact the author

Keywords

grape ripening, non-destructive evaluation of berries, nitrogen composition, spectral techniques

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

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.

How can historical cultivars mitigate the effects of climate change?

IFV, INRAe and the national network “Partenaires de la Sélection Vigne” representing 37 organizations from the different wine regions, have been working increasingly closely over the last 2 decades towards the preservation of the French varietal patrimony. There are approximately 600 patrimonial varieties according to INRAe and SupAgro Montpellier experts, including ancient cultivars (400) and intravarietal crossbreeds obtained since the 19th century. In the context of a drastic reduction in such varieties from the mid 1980’s in favor of mainstream varieties, it was essential to carry out an inventory of old vines and vineyards. INRAe Vassal collection plays a key role here as it holds the largest diversity available, along with a rich bibliography and herbariums, offering us the opportunity to document and double check the identity of a cultivar, consolidating the expertise of ampelographers. The work is carried out in several stages, from verifying the existence of a variety in a small region, through to rehabilitation. During this session, the authors present the process that leads to the official registration of a variety. After this, IFV selection center takes over to initiate the process of selection and propagation. A specific focus within regions such as the Alps, Champagne and the South-West will provide details of the full procedure. Bia, Bouysselet, Chardonnay rose, Mecle and the aptly named Tardif, are some of the cultivars that have followed this procedure. Furthermore, a recent regulation established by INAO on “varieties of interest for adaptation purposes” might boost uptake by growers. Since 2006, 36 historical cultivars have been registered. Most of these have been neglected in the past due to late maturity, lack of sugar and high titratable acidity at harvest time. Such characteristics are today considered as positive qualities, not only in mitigation of the effects of climate change, but also as an opportunity for restoring diversity…

Underpinning terroir with data: rethinking the zoning paradigm

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

Metabolomic discrimination of grapevine water status for Chardonnay and Pinot noir

Water status impact in viticulture has been widely explored, as it strongly affects grapevine physiology and grape chemical composition. It is considered as a key component of vitivinicultural terroir. Most of the studies concerning grapevine water status have focused on either physiological traits, or berry compounds, or traits involved in wine quality. Here, the response of grapevine to water availability during the ripening period is assessed through non-targeted metabolomics analysis of grape berries by ultra-high resolution mass spectrometry. The grapevine water status has been assessed during 2 consecutive years (2019 & 2020), through carbon isotope discrimination on juices from berries collected at maturity (21.5 brix approx.) for 2 Vitis vinifera cv. Pinot noir (PN) and Chardonnay (CH). A total of 220 grape juices were collected from 5 countries worldwide (Italy; Argentina; France; Germany; Portugal). Measured δ13C (‰) varied from -28.73 to -22.6 for PN, and from -28.79 to -21.67 for CH. These results also clearly revealed higher water stress for the 2020 vintage. The same grape juices have been analysed by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) and Liquid Chromatography coupled to Mass Spectrometry (LC-qTOF-MS), leading to the detection of up to 4500 CHONS containing elemental compositions, and thus likely tens of thousands of individual compounds, which include fatty acids, organic acids, peptides, phenolics, also with high levels of glycosylation. Multivariate statistical analysis revealed that up to 160 elemental compositions, covering the whole range of detected masses (100 –1000 m/z), were significantly correlated to the observed gradients of water status. Examples of chemical markers, which are representative of these complex fingerprints, include various derivatives of the known abscisic acid (ABA), such as phaesic acid or abscisic acid glucose ester, which are significantly correlated with higher water stress, regardless of the variety. Cultivar-specific behaviours could also be identified from these fingerprints. Our results provide an unprecedented representation of the metabolic diversity, which is involved in the water status regulation at the grape level, and which could contribute to a better knowledge of the grapevine mitigation strategy in a climate change context.

VINIoT – Precision viticulture service

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).