Super Absorbent Polymer and Irrigation Regime Effects on Growth and Water Use Efficiency of Container-Grown Cherry Tomatoes
Bibliographic record
Abstract
Abstract. There is a need to develop innovative techniques to effectively use water in agriculture to meet the growing demands for food. Super absorbent polymers (SAPs), or hydrogels, can absorb and retain large amounts of water against gravitational forces and release it on demand to meet plant water requirements. Being an artificially synthesized compound, it is imperative that SAPs should not introduce toxicity to the growing medium or produce. The objectives of this study were to determine whether SAPs can improve water use efficiency (WUE) and the physiological growth of cherry tomatoes ( var. ) without causing soil toxicity. A pot-trial experiment was carried out in 2014 at the Research Greenhouse of McGill University’s Macdonald Campus (Ste-Anne-de-Bellevue, Quebec, Canada) in a completely randomized design, with three concentrations of SAP (0%, 0.1%, and 0.5%) and three irrigation intervals (daily, each alternate day, and every third day). The mean yield of the experimental cherry tomatoes was statistically significantly higher where 0.5% SAP was applied, compared to where SAP was not applied (p = 0.0056). The mean WUE was also higher where 0.5% SAP was applied when compared to where SAP was not applied (p = 0.05). To ascertain food safety, the presence of free acrylamide monomer in tomatoes was checked. The acrylamide concentrations were below the detection limit of 5 µg kg-1 in all tomato samples. To assess environmental toxicity, a Microtox toxicology analysis was also conducted on the growing medium, which revealed that the SAP used in the study was not toxic. Therefore, it can be concluded that the application of SAP could increase yield and WUE of greenhouse-grown cherry tomatoes. It also appears that SAP did not introduce toxic side-effects in the soil nor in the tomatoes, as determined by Microtox acute toxicity test and acrylamide residue analysis with LC-MS. Keywords: Acrylamide, Cherry tomatoes, Greenhouse, Microtox, Monomer, Super absorbent polymer, Toxicity, Water use efficiency, Yield.
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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 | 0.001 |
| 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".