Drought phenotyping in Vitis vinifera using RGB and NIR imaging

Briglia, Nunzio; Montanaro, Giuseppe; Petrozza, Angelo; Summerer, Stephan; Cellini, Francesco; Nuzzo, Vitale

doi:10.1016/j.scienta.2019.108555

Cited by 44 publications

(44 citation statements)

References 61 publications

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“…Four images were acquired per vine: a Top View (TV) image taken from above and 3 Side Views (SV) taken at 0 • , 45 • and 90 • . Image analyses were performed using the software LemnaGrid v2 following Zaman-Allah et al (2015) and the segmentation procedure reported in Briglia et al, 2019. RGB images were then converted to HIS (hue, intensity, saturation) color space. Next, the component H (hue, in degree) was used to calculate the "greener fraction" (GGF) as the number of green pixels (80 • < hue < 180 • ) relative to the total number of pixels of a given image (Casadesús and Villegas, 2014).…”

Section: Rgb Imaging and Ggf Indexmentioning

confidence: 99%

“…Information derived from images has the potential to parameterize ecophysiological models and predict the impact of environmental factors on various plant and fruit traits including growth, diseases incidence and chemical composition (Gago et al, 2017;Zhao et al, 2019). Drought events are predicted to be more frequent and longer in coming decades in many cultivated regions (e.g., Mediterranean) (Raymond et al, 2019), so image-based assessment of drought stress in crop species are urgent (Berger et al, 2010;Briglia et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…In grapevine, the relationship between manual and imagebased measurements of leaf angle and leaf water potential is unknown. It has been reported that manually measured leaf angles might change from the vertical axis by 60-70 • in well irrigated vines up to 80-120 • in drought stressed ones when approaching severe drought condition (approximately −1.8 MPa early morning) (Smart, 1974;Palliotti et al, 2008;Briglia et al, 2019). However, a systematic characterization of leaf angle response to drought stress using 3D image-based plantphenotyping domain has not been adequately explored.…”

Section: Introductionmentioning

confidence: 99%

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Image-Based Assessment of Drought Response in Grapevines

Briglia

Williams

et al. 2020

Front. Plant Sci.

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Many plants can modify their leaf profile rapidly in response to environmental stress. Image-based data are increasingly used to retrieve reliable information on plant water status in a non-contact manner that has the potential to be scaled to high-throughput and repeated through time. This paper examined the variation of leaf angle as measured by both 3D images and goniometer in progressively drought stressed grapevine. Grapevines, grown in pots, were subjected to a 21-day period of drought stress receiving 100% (CTRL), 60% (IRR 60%) and 30% (IRR 30%) of maximum soil available water capacity. Leaf angle was (i) measured manually (goniometer) and (ii) computed by a 3D reconstruction method (multi-view stereo and structure from motion). Stomatal conductance, leaf water potential, fluorescence (F v /F m), leaf area and 2D RGB data were simultaneously collected during drought imposition. Throughout the experiment, values of leaf water potential ranged from −0.4 (CTRL) to −1.1 MPa (IRR 30%) and it linearly influenced the leaf angle when measured manually (R 2 = 0.86) and with 3D image (R 2 = 0.73). Drought was negatively related to stomatal conductance and leaf area growth particularly in IRR 30% while photosynthetic parameters (i.e., F v /F m) were not impaired by water restriction. A model for leaf area estimation based on the number of pixels of 2D RGB images developed at a different phenotyping robotized platform in a closely related experiment was successfully employed (R 2 = 0.78). At the end of the experiment, top view 2D RGB images showed a ∼50% reduction of greener fraction (GGF) in CTRL and IRR 60% vines compared to initial values, while GGF in IRR 30% increased by approximately 20%.

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Section: Rgb Imaging and Ggf Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Image-Based Assessment of Drought Response in Grapevines

Briglia

Williams

et al. 2020

Front. Plant Sci.

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“…Images of plants were acquired, throughout the experiment, with the plant phenotyping platform Scanalyzer 3D (LemnaTec GmbH). Detailed information on the platform is reported in Briglia et al (2019) [38]. Briefly, it is composed of 2 imaging chambers visible light (RGB) and fluorescence (FLUO), respectively.…”

Section: Non-destructive Measurementsmentioning

confidence: 99%

“…Plant development was assessed through the DB which is a morphometric measurement previously employed in high-throughput (HTP) studies to monitor the influence of abiotic stresses, mainly drought, on plant growth [34,38].…”

Section: Digital Biovolumementioning

confidence: 99%

Investigating the Impact of Biostimulants on the Row Crops Corn and Soybean Using High-Efficiency Phenotyping and Next Generation Sequencing

Briglia

Petrozza²,

Hoeberichts³

et al. 2019

Agronomy

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Row crops represent the most important crops in terms of global cultivated area. Such crops include soybean, corn, wheat, rice, rapeseed, sunflower, and cotton. Row crops agriculture is generally an intensive system of farming used to obtain high yields by employing elevated quantities of organic and mineral fertilizers. Considering this, and the decrease in area of arable land, it becomes crucial to ensure high yield and quality using alternative strategies, such as the use of plant biostimulants. These compounds are increasingly recognized as sustainable solution to optimize nutrient uptake, crop yield, quality, and tolerance to abiotic stresses. In this work, by means of high-throughput plant phenotyping, we evaluated the effectiveness of a set of three new foliar biostimulant prototypes (coded as 52096, 52097, 52113) applied on corn and soybean at application rates 2.5 and 5 mL/L (corresponding to 1 and 2 L/ha respectively). This allowed us to select the most effective prototype (52097, commercial name “YieldOn®”) in increasing digital biovolume (DB) and greener area (GGA) either in soybean (both application rates) or corn (rate 5 mL/L) and decreasing Stress Index (SI) in soybean (both application rates). Molecular mechanism of action of selected prototype 52097 was subsequently characterized through Next Generation Sequencing (NGS). In corn, genes involved in hormone (cytokinin and auxin) metabolism/catabolism, maltose biosynthesis, sugar transport and phloem loading were upregulated after application of prototype 52097. In soybean, genes involved in nitrogen metabolism, metal ion transport (mainly zinc and iron), sulfate reduction, and amino acid biosynthesis were induced. The proposed approach supports the integration of multiple omics to open new perspectives in the discovery, evaluation, and development of innovative and sustainable solutions to meet the increasing needs of row-crops agriculture.

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Genetics and Genomics of Drought and Heat Tolerance in Cowpea, Mung Bean and Black Gram

Dhanasekar¹,

Souframanien²

2023

Legumes: Physiology and Molecular Biology of Abiotic Stress Tolerance

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Drought phenotyping in Vitis vinifera using RGB and NIR imaging

Cited by 44 publications

References 61 publications

Image-Based Assessment of Drought Response in Grapevines

Image-Based Assessment of Drought Response in Grapevines

Investigating the Impact of Biostimulants on the Row Crops Corn and Soybean Using High-Efficiency Phenotyping and Next Generation Sequencing

Genetics and Genomics of Drought and Heat Tolerance in Cowpea, Mung Bean and Black Gram

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