terclim by ICS banner
IVES 9 IVES Conference Series 9 Combination of NIR multispectral information acquired from a ground moving vehicle with AI methods to assess the vine water status in a Tempranillo (Vitis vinifera L.) commercial vineyard

Combination of NIR multispectral information acquired from a ground moving vehicle with AI methods to assess the vine water status in a Tempranillo (Vitis vinifera L.) commercial vineyard

Abstract

Increasing water scarcity and unpredictable rainfall patterns necessitate efficient water management in grape production. This study proposes a novel approach for monitoring grapevine water status in a commercial vertically-shoot-positioned Vitis vinifera L. Tempranillo vineyard using non-invasive spectroscopy with a battery of different AI methods to assess vineyard water status, that could drive precise irrigation. A contactless, miniature NIR spectrometer (900-1900 nm) mounted on a moving vehicle (3 Km/h) was employed to collect spectral data from the vines’ northeast side along six dates in season 2021.Grapevines were monitored at solar noon using stem water potential (Ψs) as reference parameter of plant water status. At each date, 36 measurements of Ψs were taken making a total of 396 data in the whole season. AI techniques, including linear regression, gaussian process regression (GPR) support vector machine (SVM), and neural networks, trained with Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) algorithms were implemented in MATLAB (using the Regression Learner and Natural Net Fitting apps) to analyze the spectral data and predict vine water status. The optimized GPR model achieved the best performance, with a determination coefficient (R2P) above 0.83 and a root mean squared error of prediction (RMSEP) of 0.112 MPa. However, several neural network models trained with the LM algorithm exhibited superior performance, with R2P values over 0.92 and RMSEP values of approximately 0.080 MPa. This study demonstrates the potential of non-invasive spectroscopy combined with AI methods for accurate prediction of grapevine water status, paving the way for precision irrigation in vineyards.

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Article

Authors

Fernando Rubio-Ordoyo1, María Paz Diago,1,2, Ignacio Barrio1,2, Juan Fernández-Novales1,2*

1 Department of Agriculture and Food Science. University of La Rioja. C/Madre de Dios 53. 26007. Logroño, (La Rioja) Spain
2 Institute of Sciences of Vine and Wine (CSIC, University of La Rioja, La Rioja Government) Finca La Grajera. Ctra. de Burgos Km 6. 26007. Logroño. (La Rioja). Spain

Contact the author*

Keywords

Vine water status, NIR spectrophotometer, Stem water potential, Gaussian Regression Process, Levenberg-Marquardt algorithm

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

The antioxidant properties of wine lees extracts in model wine

While the ethanol and tartaric acid contained in wine lees are typically recovered by distilleries, the remaining solid fraction (yeast biomass) is usually disposed of, thus negatively affecting the overall sustainability of the wine industry.

Towards a better understanding of the root system diversity and plasticityin young grafted vines using 2D imaging and 3D modelling tools

Three-dimensional functional-structural root architecture models, which decompose the root system architecture (RSA) into elementary developmental processes such as root emission, axial growth, branching patterns and tropism have become useful tools for (i) reconstructing in silico the spatial and temporal dynamics of root systems in a soil volume, (ii) analyzing their genotypic diversity and plasticity to the environment, and (iii) overcoming the bottleneck associated with their visualization and measurement in situ. Here, we present an original work on RSA phenotyping and modelling in grapevine. First, we developed 2D image-based analysis pipelines to quantify morphological and architectural traits in young grafts. Second, we parametrized and validated the 3D root model Archisimple on two rootstock genotypes (RGM, 1103P) grafted with V. vinifera Cabernet-Sauvignon and grown in different controlled conditions (rhizotrons, pots, tubes).

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.

Leaf necrosis induced by the insecticide carbaryl in Vitis rupestris ‘B38’

Carbaryl is an acetylcholine esterase inhibitor-type insecticide used for pest control on grapevine. We repeatedly observed the occurrence of interveinal leaf necrosis following carbaryl spray application in a Vitis rupestris x Vitis riparia F1 hybrid progeny vineyard. Spray applications induced necrosis in this progeny under both Missouri and New York field conditions an approximate one-to-one sensitive-to-insensitive segregation ratio and with 42% concordance. Results of subsequent in vitro experiments established causality between carbaryl treatment and leaf necrosis and confirmed the pattern of segregation observed in the field. We consistently map this phenotype to a major QTL on chromosome 16 of the female parent V. rupestris ‘B38’ regardless of whether we used field or in vitro-generated phenotype data.

Regulation of terpene production in methyl jasmonate treated cell-cultures

Terpenes are responsible for flavors and aromas of grapes, however, they also protect from radiation, participate in biotic stress and antioxidant mechanisms. The phytohormone methyl jasmonate (MeJA) mediates many of these stress responses and has been associated with increased terpene content in berries. Here, we generated transcriptomic data of Vitis vinifera cv. ‘Gamay’ cells treated with MeJA (100 μM) and cyclodextrins (50 μM) to understand these responses. Ontology analysis revealed that up-regulated genes (URGs) were enriched in jasmonic acid biosynthesis and signaling terms, as expected. Inspection of transcription factors (TFs) among URGs allowed us to study uncharacterized TFs.