Evidence map›Paper›PMID 37111953›Full record

ArticlePlants (Basel, Switzerland)2023

Low-Cost Hyperspectral Imaging to Detect Drought Stress in High-Throughput Phenotyping.

Andrea Genangeli, Giovanni Avola, Marco Bindi, Claudio Cantini, Francesco Cellini, Stefania Grillo, Angelo Petrozza, Ezio Riggi, Alessandra Ruggiero, Stephan Summerer and 2 more

Open access · goldAbstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
7.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 21 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Andrea GenangeliDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy.ORCID 0000-0001-5359-7101
Giovanni AvolaInstitute of Bioeconomy (IBE), National Research Council (CNR), Via Caproni 8, 50145 Florence, Italy.ORCID 0000-0002-8353-1784
Marco BindiDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy.ORCID 0000-0002-8968-954X
Claudio CantiniInstitute of Bioeconomy (IBE), National Research Council (CNR), Via Caproni 8, 50145 Florence, Italy.ORCID 0000-0002-0938-6013
Francesco CelliniCentro Ricerche Metapontum Agrobios-Agenzia Lucana di Sviluppo e di Innovazione in Agricoltura (ALSIA), S.S. Jonica 106, km 448,2, 75010 Metaponto di Bernalda, Italy.
Stefania GrilloD1 National Research Council of Italy, Institute of Biosciences and Bioresources, Via Università 133, 80055 Portici, Italy.
Angelo PetrozzaCentro Ricerche Metapontum Agrobios-Agenzia Lucana di Sviluppo e di Innovazione in Agricoltura (ALSIA), S.S. Jonica 106, km 448,2, 75010 Metaponto di Bernalda, Italy.
Ezio RiggiInstitute of Bioeconomy (IBE), National Research Council (CNR), Via Caproni 8, 50145 Florence, Italy.ORCID 0000-0002-4891-2864
Alessandra RuggieroD1 National Research Council of Italy, Institute of Biosciences and Bioresources, Via Università 133, 80055 Portici, Italy.ORCID 0000-0002-3336-6143
Stephan SummererCentro Ricerche Metapontum Agrobios-Agenzia Lucana di Sviluppo e di Innovazione in Agricoltura (ALSIA), S.S. Jonica 106, km 448,2, 75010 Metaponto di Bernalda, Italy.
Anna TedeschiD1 National Research Council of Italy, Institute of Biosciences and Bioresources, Via Università 133, 80055 Portici, Italy.ORCID 0000-0002-3442-5117
Beniamino GioliInstitute of Bioeconomy (IBE), National Research Council (CNR), Via Caproni 8, 50145 Florence, Italy.ORCID 0000-0001-7631-2623
National Research Council · ITInstitute of Biosciences and Bioresources · ITIstituto Nazionale di Documentazione Innovazione e Ricerca Educativa · ITUniversity of Florence · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent developments in low-cost imaging hyperspectral cameras have opened up new possibilities for high-throughput phenotyping (HTP), allowing for high-resolution spectral data to be obtained in the visible and near-infrared spectral range. This study presents, for the first time, the integration of a low-cost hyperspectral camera Senop HSC-2 into an HTP platform to evaluate the drought stress resistance and physiological response of four tomato genotypes (770P, 990P, Red Setter and Torremaggiore) during two cycles of well-watered and deficit irrigation. Over 120 gigabytes of hyperspectral data were collected, and an innovative segmentation method able to reduce the hyperspectral dataset by 85.5% was developed and applied. A hyperspectral index (H-index) based on the red-edge slope was selected, and its ability to discriminate stress conditions was compared with three optical indices (OIs) obtained by the HTP platform. The analysis of variance (ANOVA) applied to the OIs and H-index revealed the better capacity of the H-index to describe the dynamic of drought stress trend compared to OIs, especially in the first stress and recovery phases. Selected OIs were instead capable of describing structural changes during plant growth. Finally, the OIs and H-index results have revealed a higher susceptibility to drought stress in 770P and 990P than Red Setter and Torremaggiore genotypes.

Indexed as

drought stresshigh-throughput phenotypinghuehyperspectral indexlow-cost hyperspectral cameraoptical sensorprojected shoot areared-edgesenescence indextomato

Identifiers

PMID37111953
PMCPMC10143644
OpenAlexW4366772333

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.