Fish effluents promote root growth and suppress fungal diseases in tomato transplants
Bibliographic record
Abstract
Gravel, V., Dorais, M., Dey, D. and Vandenberg, G. 2015. Fish effluents promote root growth and suppress fungal diseases in tomato transplants. Can. J. Plant Sci. 95: 427–436. Aquaculture systems generate large amounts of wastes which may constitute a beneficial amendment for horticultural crop in terms of nutrients, plant growth promoter and disease suppressiveness. This study aimed to determine (1) the nutrient value of rainbow trout farming effluents coming from two feed regimes and (2) the plant growth and disease suppressiveness effects of those fish farming effluents on tomato transplants. The effluent sludge from Skretting Orient™ (SO) had a higher content of P (38 vs. 32 mg L −1 ), K (23 vs. 11 mg L −1 ), N (19 vs. to 11 mg NO 3 L −1 ; 186 vs. 123 mg NH 4 L −1 ), and a higher NO 3 :NH 4 ratio (1:9 vs. 1:13) compared with the Martin Classic (MC), while MC was richer in Mg (42 vs. 24 mg L −1 ) and Ca (217 vs. 169 mg L −1 ). For the first trial, a stimulating effect of the fish effluent was observed on plant height, leaf area and root dry biomass, while only the root biomass was increased during the second trial. Fish sludge was rich in microorganisms (97 and 142 µg fluorescein h −1 mL −1 for SO and MC, respectively) and their ability to suppress Pythium ultimum Trow and Fusarium oxysporum f.sp. lycopersici (Sacc.) Snyder & Hansen was observed. Both crude fish effluents reduced in vitro mycelial growth of P. ultimum and F. oxysporum, by 100 and 32%, respectively, while MC effluents showed a higher inhibition against F. oxysporum. When fish effluents were sterilized by filtration or autoclaving, lower in vitro inhibition of P. ultimum and F. oxysporum was observed. Mixed fish effluents reduced tomato plant root colonization by P. ultimum (by up to 5.7-fold) and F. oxysporum (by up to 2.1-fold). These results showed that fish effluent can be used as soil amendments to promote plant growth and increase soil suppressiveness, which in turn can prevent soil-borne diseases.
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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 | 0.001 | 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".