Evaluation of Sugarcane Agroindustrial Wastes as Substrate in Soilless Cultivation of Tomato (S. lycopersicum Linnaeus): Effect of Substrate Composition on Yield Production
Bibliographic record
Abstract
Traditionally, biochar is generally proposed to substitute Canadian Sphagnum peat moss. Sugarcane bagasse, filter press mud and sugarcane bagasse ash were mixed in different ratios and proposed as an alternative to substitute commercial Sphagnum peat moss (SPM) for the soilless cultivation of tomato (S. lycopersicum Linnaeus). The choice of the agroindustrial waste ratio was performed from physical-chemical sample characterization. During vegetable production, an adequate ratio was evaluated based on plant height, substrate pH, number of leaves, yield, and fruit size. The addition of essential macro- and micro-nutrients was performed manually. The results show that as-received materials contain different minerals with a structure that corresponds to the quartz, cristobalite, and feldspar phases. A morphology composed of lamellate structures was observed for sugarcane bagasse, whereas the filter press mud and the sugarcane bagasse ash presented compact agglomerates with a surface area of 1.60, 3.78, and 1.07 m2 g−1, respectively. The properties of each component promote the water adsorption, retention and releasing capacity. Important differences were observed as the quantity of filter press mud increased, but also it is required an amount of sugarcane bagasse above of 18 wt% to reach a superior performance. This work demonstrated that, in adequate quantities, agroindustrial wastes can be used as a soilless substrate for growing tomatoes in greenhouse, reducing their disposal problems.
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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".