Paper · 2019 · Frontiers in Plant Science

Understanding the Biostimulant Action of Vegetal-Derived Protein Hydrolysates by High-Throughput Plant Phenotyping and Metabolomics: A Case Study on Tomato

Kenny Paul; Mirella Sorrentino; Luigi Lucini; et al.

8
claims
17
verbatim quotes
131
citations
3
research areas
✓
Open access · cc-by

Abstract

Designing and developing new biostimulants is a crucial process which requires an accurate testing of the product effects on the morpho-physiological traits of plants and a deep understanding of the mechanism of action of selected products. Product screening approaches using omics technologies have been found to be more efficient and cost effective in finding new biostimulant substances. A screening protocol based on the use of high-throughput phenotyping platform for screening new vegetal-derived protein hydrolysates (PHs) for biostimulant activity followed by a metabolomic analysis to elucidate the mechanism of the most active PHs has been applied on tomato crop. Eight PHs (A-G, I) derived from enzymatic hydrolysis of seed proteins of Leguminosae and Brassicaceae species were foliarly sprayed twice during the trial. A non-ionic surfactant Triton X-100 at 0.1% was also added to the solutions before spraying. A control treatment foliarly sprayed with distilled water containing 0.1% Triton X-100 was also included. Untreated and PH-treated tomato plants were monitored regularly using high-throughput non-invasive imaging technologies. The phenotyping approach we used is based on automated integrative analysis of photosynthetic performance, growth analysis, and color index analysis. The digital biomass of the plants sprayed with PH was generally increased. In particular, the relative growth rate and the growth performance were significantly improved by PHs A and I, respectively, compared to the untreated control plants. Kinetic chlorophyll fluorescence imaging did not allow to differentiate the photosynthetic performance of treated and untreated plants. Finally, MS-based untargeted metabolomics analysis was performed in order to characterize the functional mechanisms of selected PHs. The treatment modulated the multi-layer regulation process that involved the ethylene precursor and polyamines and affected the ROS-mediated signaling pathways. Although further investigation is needed to strengthen our findings, metabolomic data suggest that treated plants experienced a metabolic reprogramming following the application of the tested biostimulants. Nonetheless, our experimental data highlight the potential for combined use of high-throughput phenotyping and metabolomics to facilitate the screening of new substances with biostimulant properties and to provide a morpho-physiological and metabolomic gateway to the mechanisms underlying PHs action on plants.

Abstract from the paper’s OpenAlex record; open copy licensed cc-by. Read at the source ↗

The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.

Claims 8

Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Protein hydrolysates generally increased digital biomass.

Treatment
PHe0
Outcome
digital biomasse0
Direction
increasede0

Not reportedComparator

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“The digital biomass of the plants sprayed with PH was generally increased”

✓ located verbatim in the source · abstract, characters 1300–1373 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Intervention effectobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

PH A significantly improved relative growth rate compared with untreated controls.

Treatment
PHs Ae0
Outcome
relative growth ratee0
Direction
improvede0
Comparator
untreated control plantse0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“the relative growth rate and the growth performance were significantly improved by PHs A and I, respectively, compared to the untreated control plants”

✓ located verbatim in the source · abstract, characters 1390–1540 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Intervention effectobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

PH I significantly improved growth performance compared with untreated controls.

Treatment
Ie0
Outcome
growth performancee0
Direction
improvede0
Comparator
untreated control plantse0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“the relative growth rate and the growth performance were significantly improved by PHs A and I, respectively, compared to the untreated control plants”

✓ located verbatim in the source · abstract, characters 1390–1540 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Chlorophyll fluorescence imaging did not differentiate photosynthetic performance between treated and untreated plants.

Outcome
photosynthetic performancee0
Direction
did not allow to differentiatee0
Comparator
treated and untreated plantse0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“Kinetic chlorophyll fluorescence imaging did not allow to differentiate the photosynthetic performance of treated and untreated plants”

✓ located verbatim in the source · abstract, characters 1542–1676 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Mechanismauthor interpretationoriginal resultmeasured

Claim · model-written summary

Treatment modulated a regulatory process involving ethylene precursor and polyamines.

Treatment
treatmente0
Compound
ethylene precursor and polyaminese0
Outcome
multi-layer regulation processe0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“The treatment modulated the multi-layer regulation process that involved the ethylene precursor and polyamines”

✓ located verbatim in the source · abstract, characters 1811–1921 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Mechanismauthor interpretationoriginal resultmeasured

Claim · model-written summary

Treatment affected ROS-mediated signaling pathways.

Treatment
treatmente1
Outcome
ROS-mediated signaling pathwayse0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“affected the ROS-mediated signaling pathways”

✓ located verbatim in the source · abstract, characters 1926–1970 · show in text ↑
e1

“The treatment modulated the multi-layer regulation process that involved the ethylene precursor and polyamines and affected the ROS-mediated signaling pathways”

✓ located verbatim in the source · abstract, characters 1811–1970 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Observationauthor interpretationoriginal resultmeasured

Claim · model-written summary

Metabolomic data suggest metabolic reprogramming after biostimulant application.

Treatment
tested biostimulantse0
Outcome
metabolic reprogramminge0

Not reportedDirection

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“metabolomic data suggest that treated plants experienced a metabolic reprogramming following the application of the tested biostimulants”

✓ located verbatim in the source · abstract, characters 2041–2177 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑
Method / resourceauthor interpretationoriginal resultpositivemeasured

Claim · model-written summary

Combined phenotyping and metabolomics may facilitate screening of biostimulant substances.

Outcome
screening of new substances with biostimulant propertiese0
Qualifier
combined use of high-throughput phenotyping and metabolomicse0

Not reportedComparatorValue

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Solanum lycopersicum
Solanum lycopersicum · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“combined use of high-throughput phenotyping and metabolomics to facilitate the screening of new substances with biostimulant properties”

✓ located verbatim in the source · abstract, characters 2242–2377 · show in text ↑
t0

“Tomato”

✓ located verbatim in the source · title, characters 149–155 · show in text ↑

ph · growth · Solanum lycopersicum (tomato)Positive and negative results

19 papers: 10 positive, 9 negative or no effect

9 papers in the same direction as this paper · 9 in the opposite direction

  1. positive
  2. positive
  3. no effect

15 papers more in this group

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Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.