Growth Promotion of Parsley (Petroselinum crispum L.) Using Commercial Strains of Trichoderma spp.
Bibliographic record
Abstract
The growth of plants by the use of Trichoderma occurs through distinct mechanisms, among which it can highlight the synthesis of phytohormones and auxins analogues. The objective of this work was to evaluate Trichoderma spp. commercial strains in the promoting seedlings growth and in the productivity of parsley plants. In laboratory assay, seeds of parsley cv. ‘Graúda Portuguesa’ were treated with 2 mL of Trichoderma suspension (2.5 × 108 ml-1 conidia per 100 g of seeds) submitted to growth test until 28 days after sowing (DAS). For the greenhouse experiment, parsley seedlings were transplanted into 3.0 L pots containing soil, which was previously treated with 5 mL Trichoderma suspension, totaling 1.5 × 108 conidia per pot. In both, a control without Trichoderma application was included, being arranged in a completely randomized design (CRD). The evaluations were: percentage of germination (PG), root length (RL), shoot length (SL), total length (TL = RL + SL), fresh root mass (FRM), fresh shoot mass (FSM), total fresh mass (TFM = FRM + FSM), root dry mass (RDM), shoot dry mass (SDM), total dry mass (BIO = RDM + SDM), root mass ratio (RMR = RDM/BIO), shoot mass ratio (SMR = SDM/BIO), aerial part/root system retio (AP/RS = SDM/RDM) and productivity at 110 DAS. Althougth no diferences was observed among the Trichoderma treatments and the control about yield, Trichoderma spp. strains provided better TFM (18.98 to 22.92 mg), BIO (3.37 to 4.31 mg) and root system superior to the control (14.20 and 2.44 mg, respectively) under greenhouse conditions. T. harzianum ESALQ1306 was the better strain in laboratory assyas, suggsting this isolate for applied in the seeds when it aims the promotion of initial growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".