Remote sensing and other imaging technologies to monitor grapevine performance

Jones, Hamlyn G.; Grant, Olga M.

doi:10.1002/9781118735985.ch8

Cited by 13 publications

(14 citation statements)

References 80 publications

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“…However, K leaf plasticity along leaf lifespan was different between the two cvs. Only the cv Tempranillo showed an increase of K leaf at −2 MPa in the months of June and July, while Q4 Jones and Grant (2015) osmotic potential at full turgor was lower in Tempranillo than in Grenache. They showed as well that leaf resistance to hydraulic dysfunction is cultivar dependent and also a seasonal plastic trait that can be mediated by osmotic adjustment (Martorell, 2014;Martorell et al, 2015).…”

Section: Morpho-hydraulics and Water Transportmentioning

confidence: 99%

“…However, the legislation regulating their use in certain EU countries demands still clarification for a broader use in agriculture . Satellite imaging has also been used in grapevine studies namely to assess water stress (Consoli and Barbagallo, 2012) and intra-variability in vigour and leaf expansion (Matese et al, 2015;Jones and Grant, 2015) Soil monitoring is another relevant aspect of remote sensing. Assessment of soil water in field conditions must be accurate especially over large and heterogeneous surfaces.…”

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

“…Manual ground-based and aerial manned and unmanned remote sensing measurements are being progressively implemented in modern viticulture not only in research but also in commercial vineyards to monitor plant stress and or to assess canopy and/or berry traits Grant et al, 2007;Grant, 2012;Fuentes et al, 2014;Fernández et al, 2013;Jones and Grant, 2015). These new approaches combine the use of different types of detectors and spectral wavelengths ranging from visible (red, green, blue) (RGB) and infrared thermal imaging to multispectral and tomography measurements (Leionen et al, 2006;Diago et al, 2012;Fuentes et al, 2012;Costa et al, 2013;Jones and Grant, 2015;Rustioni et al, 2014). Robots and unmanned Aerial Vehicles (UAVs) have been recently applied in precision viticulture (Baluja et al, 2012; ZarcoTejada et al, 2009 ZarcoTejada et al, , 2012Gago et al, 2015).…”

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

“…Precision Viticulture is based on technologies that are able to detect spatial heterogeneity of vineyards either due to intrinsic factors (soil and crop management) and/or external variables (climate) and that ultimately will determine inter-annual and intra-vineyard variability with regards to yield and quality output (Mazzeto et al, 2010;Matese et al, 2015;Jones and Grant, 2015). Manual ground-based and aerial manned and unmanned remote sensing measurements are being progressively implemented in modern viticulture not only in research but also in commercial vineyards to monitor plant stress and or to assess canopy and/or berry traits Grant et al, 2007;Grant, 2012;Fuentes et al, 2014;Fernández et al, 2013;Jones and Grant, 2015).…”

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

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Modern viticulture in southern Europe: Vulnerabilities and strategies for adaptation to water scarcity

Costa

Vaz

Escalona

et al. 2016

Agricultural Water Management

170

114

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b s t r a c tWater is now considered the most important but vulnerable resource in the Mediterranean region. Nevertheless, irrigation expanded fast in the region (e.g. South Portugal and Spain) to mitigate environmental stress and to guarantee stable grape yield and quality. Sustainable wine production depends on sustainable water use in the wine's supply chain, from the vine to the bottle. Better understanding of grapevine stress physiology (e.g. water relations, temperature regulation, water use efficiency), more robust crop monitoring/phenotyping and implementation of best water management practices will help to mitigate climate effects and will enable significant water savings in the vineyard and winery. In this paper, we focused on the major vulnerabilities and opportunities of South European Mediterranean viticulture (e.g. in Portugal and Spain) and present a multi-level strategy (from plant to the consumer) to overcome region's weaknesses and support strategies for adaptation to water scarcity, promote sustainable water use and minimize the environmental impact of the sector. © 2015 Published by Elsevier B.V. The wine grape industry in south Mediterranean EuropeWorld's wine production are located in a wide geographical Q2and climatic range, often in mid-latitude regions characterized by climate variability and stressful environments, such as the Mediterranean region (Fraga et al., 2013;Lionello et al., 2014). The European Union , is the world's leader in wine production with about 50% of world's vine-growing area and about 60% of total volume of production (USDA, 2014). France, Italy, Spain, Germany and Portugal are the five leading EU wine producers and altogether they represent 90% of EU production (USDA, 2014). Spain has the largest vineyard area in the world (950,541 ha in 2014) with an increasing irrigated area (36% of the total, in 2014) (MAGRAMA, 2014) (Fig. 1). Portugal is the EU's 5th largest wine producer with a total of 6.7 Mhl in 2013 and it has a cultivated area estimated to be about 224,000 ha (IVV, 2015). In 2010, the irrigated area was estimated in 15% of the total area of vineyards (INE, 2010). However, irrigation continued expanding in the recent years in Portugal, in particular in the Alentejo region, and presently, the percentage of irrigated vines should be slightly higher and around 20%. * Corresponding author.E-mail address: miguelc@itqb.unl.pt (J.M. Costa).Mediterranean fresh water resources are under high pressure due to fast-growing population, increased water scarcity, extreme climate variability and intensive water use in agriculture, industry and tourism activities (Lange et al., 2005;Costa et al., 2007; EEA, 2012a,b; Lereboullet et al., 2013a,b;Blum, 2014). Water is now considered by EU experts as the most important but vulnerable resource in the Mediterranean region (EU-ERANETMED, 2014). In addition, climate scenarios for South Mediterranean Europe are not favourable for agriculture. The predicted lower precipitation, higher air and soil temperatures, more frequent and l...

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Section: Morpho-hydraulics and Water Transportmentioning

confidence: 99%

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

Section: Precise Plant Monitoring and Phenotypingmentioning

confidence: 99%

See 2 more Smart Citations

Modern viticulture in southern Europe: Vulnerabilities and strategies for adaptation to water scarcity

Costa

Vaz

Escalona

et al. 2016

Agricultural Water Management

170

114

View full text Add to dashboard Cite

show abstract

“…Of the various techniques to appraise the plant water status, plant-based methods have shown the advantage of integrating the soil and atmospheric effects (Jones, 2004 ). Likewise, the usefulness of different physiological parameters and their applicability for water stress detection and irrigation management in grapevines was reviewed by different authors (Jones, 2004 ; Acevedo-Opazo et al, 2008 ; Jones and Grant, 2016 ). However, conventional plant-based methods to monitor water stress, such as those based on the use of Scholander-type chambers, are destructive as well as time and labor consuming (Fernández, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

et al. 2018

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Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψs) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction (RP2) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

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Estimation of soil classes and their relationship to grapevine vigor in a Bordeaux vineyard: advancing the practical joint use of electromagnetic induction (EMI) and NDVI datasets for precision viticulture

et al. 2021

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Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p < 0.01) was revealed between the geophysically-identified Bordeaux soil classes and NDVI (both 2 m resolution), showing that the highest grapevine vigor was associated with the Bordeaux soil classes having the largest clay fraction. The results suggest that within-block variability of grapevine vigor was largely controlled by variability in soil classes, and that carefully collected EMI and NDVI datasets can be exceedingly helpful for providing quantitative estimates of vineyard soil and vigor variability, as well as their covariation. The method is expected to be transferable to other viticultural regions, providing an approach to use easy-to-acquire, high resolution datasets to guide viticultural practices, including routine management and replanting.

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Remote sensing and other imaging technologies to monitor grapevine performance

Cited by 13 publications

References 80 publications

Modern viticulture in southern Europe: Vulnerabilities and strategies for adaptation to water scarcity

Modern viticulture in southern Europe: Vulnerabilities and strategies for adaptation to water scarcity

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

Estimation of soil classes and their relationship to grapevine vigor in a Bordeaux vineyard: advancing the practical joint use of electromagnetic induction (EMI) and NDVI datasets for precision viticulture

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