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…

The potential of multispectral/hyperspectral technologies for early detection of “flavescence dorée” in a Portuguese vineyard

“Flavescence dorée” (FD) is a grapevine quarantine disease associated with phytoplasmas and transmitted to healthy plants by insect vectors, mainly Scaphoideus titanus. Infected plants usually develop symptoms of stunted growth, unripe cane wood, leaf rolling, leaf yellowing or reddening, and shrivelled berries. Since plants can remain symptomless up to four years, they may act as reservoirs of FD contributing to the spread of the disease. So far, conventional management strategies rely mainly on the insecticide treatments, uprooting of infected plants and use of phytoplasma-free propagation material. However, these strategies are costly and could have undesirable environmental impacts. Thus, the development of sustainable and noninvasive approaches for early detection of FD and its management are of great importance to reduce disease spread and select the best cultural practices and treatments. The present study aimed to evaluate if multispectral/hyperspectral technologies can be used to detect FD before the appearance of the first symptoms and if infected grapevines display a spectral imaging fingerprint. To that end, physiological parameters (leaf area, chlorophyll content and photosynthetic rate) were collected in concomitance to the measurements of plant reflectance (using both a portable apparatus and a remote sensing drone). Measurements were performed in two leaves of 8 healthy and 8 FD-infected grapevines, at four timepoints: before the development of disease symptoms (21st June); and after symptoms appearance (ii) at veraison (2nd August); at post-veraison (11th September); and at harvest (25th September). At all timepoints, FD infected plants revealed a significant decrease in the studied physiological parameters, with a positive correlation with drone imaging data and portable apparatus analyses. Moreover, spectra of either drone imaging and portable apparatus showed clear differences between healthy and FD-infected grapevines, validating multispectral/ hyperspectral technology as a potential tool for the early detection of FD or other grapevine-associated diseases.

An analytical framework to site-specifically study climate influence on grapevine involving the functional and Bayesian exploration of farm data time series synchronized using an eGDD thermal index

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

De novo Vitis champinii whole genome assembly allows rootstock-specific identification of potential candidate genes for drought and salt tolerance

Vitis champinii cultivars Ramsey and Dog-ridge are main choices for rootstocks to adapt viticulture in semi-arid and arid regions thanks to their distinctive tolerance to drought and salinity. However, genetic studies on non-vinifera rootstocks have heavily relied on the grapevine (Vitis vinifera) reference genome, which difficulted the assessment of the genetic variation between rootstock species and grapevines. In the present study, this limitation is addressed by introducing a novo phased genome assembly and annotation of Vitis champinii. This new Vitis champinii genome was employed as reference for mapping RNA-seq reads from the same species under drought and salt stresses, and for comparison the same reads were also mapped to the Vitis vinifera PN40024.V4 reference genome. A significant increase in alignment rate was gained when mapping Vitis champinii RNA-seq reads to its own genome, compared to the Vitis vinifera PN40024.V4 reference genome, thus revealing the expression levels of genes specific to Vitis champinii. Moreover, differences in coding sequences were observed in ortholog genes between Vitis champinii and Vitis vinifera, which therefore challenges previous differential expression analyses performed between contrasting Vitis genotypes on the same gene from the Vitis vinifera genome. Genes with possible implications in drought and salt tolerance have been identified across the genome of Vitis champinii, and the same genomic data can potentially guide the discovery of candidate genes specific from Vitis champinii for other traits of interest, therefore becoming a valuable resource for rootstock breeding designs, specially towards increased drought and salinity due to climate change.

Exploring resilience and competitiveness of wine estates in Languedoc-Roussillon in the recent past: a multi-level perspective

The Languedoc-Roussillon wineries are facing a decline in wine yields particularly PGI yields due to many factors. Climate change is just ones, but is expected to increase in the future. There is also structurally a large heterogeneity of yield profiles among terroirs, varieties and strategies. This work investigates the link between yield, competitiveness and resilience to explore how resilient winegrowers have been in the recent past. To this end two approaches have been combined; (i) an accountancy database analysis at estate scale and (ii) municipality level competitiveness analysis. A new resilience indicator that characterizes the capacity of an estate to absorb yield variation is also defined. The FADN database between 2000 and 2018 of ex-Languedoc-Roussillon (France) and other data are used to analyse the current situation and the past evolution of competitiveness and resilience by type of estate (type of farm: PGI and/or PDO & type of commercialization: bulk and/or bottles). The net margin, which defines competitiveness, is not correlated to yield for all types but depends on the type of commercialization and the level of specialisation. The resilience indicator shows that the net margin of estates specialized in PGI is particularly sensitive to yield declines. We also show that price evolutions seem to compensate the effect of yield losses for the majority of types. Municipality scale analysis shows the links between local pedoclimate, yield, commercialization strategies and price. Overlapping a PDO with a PGI does not always increase a municipality’s PGI competitiveness. It is difficult to make links between causes and effects due to the complexity of the wine production system. Production diversification may be a solution. Resorting to the two level of analysis helps resolving the data gap that is necessary to explore the links between yield and economic performance of the wine estates in the long term.

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.