Drench Application of Soy Protein Hydrolysates Increases Tomato Plant Fitness, Fruit Yield, and Resistance to a Hemibiotrophic Pathogen
Bibliographic record
Abstract
At a time when growers have to increase food production, while facing many environmental challenges, biostimulants and plant defence stimulators (PDS) may help reduce the use of chemical fertilizers and pesticides and to promote agriculture that is more respectful of the environment. For organic farming, they may contribute to increasing plant resilience and crop productivity. Several studies have shown that plant-derived protein hydrolysates may increase nutrient use efficiency and promote plant resistance to abiotic or biotic stresses. We therefore hypothesized that soy protein hydrolysates increase tomato growth and productivity, while promoting plant disease resistance. Our results showed that one or two drench applications of soy protein hydrolysates (SPH13 and SPH18 at 10 g L−1) to the growing medium increased tomato (‘Micro Tom’) plant growth and fruit production, while one studied hydrolysate enriched in glycine (SPH18) increased the expression levels of PR1 and PR8, two defence-related genes. Although no significant effect was observed on Botrytis cinerea resistance of Micro Tom plants, SPHs significantly increased ‘M82’ plant resistance to foliar inoculation with Pseudomonas syringae pv. tomato DC3000, which further confirmed the systemic activation of plant defence mechanisms by SPHs in tomatoes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".