Plug Tray Cell Volume Effects on Sweet Corn Transplant Root Architecture and Biomass Accumulation
Bibliographic record
Abstract
Sweet corn ( Zea mays L.) is difficult to transplant due to poor root regeneration. Despite reduced yields, growers are transplanting sweet corn to hasten maturity time to target profitable early markets in the Northeast. Researchers have ascribed the negative impacts on yield to restricted rooting volume. Therefore, the impacts plug cell volume had on sweet corn transplant root architecture and biomass accumulation were investigated. `Temptation' sweet corn was sown in volumes of 15, 19, 14, and 29 mL correlating to transplant plug trays with plug counts of 200, 162, 128, and 72 plugs per tray. Plug cells were exposed to three substrate environments; a dairy manure based organic compost media, a commercial soil-less germination mix, and the soil-less media supplemented 2X with 200 ppm soluble 3-3-3 organic fertilizer. A 4 × 3 factorial randomized complete-block experimental design with two blocks and five replicates per treatment was repeated twice in the greenhouse. For each experiment a total of three center cells were harvested from each replicate for analysis using the WinRhizo Pro root scanning system (Regent Instruments Inc., Montreal). Three cells per treatment were also transplanted into 8-inch pots to stimulate field transplanting. Based on mean separation tests (n = 30), increased cell volume before transplanting significantly increased root surface area, average diameter, and root volume after transplanting (n = 18). Mean root surface area for a 29-mL cell was 30% greater than a 15-mL cell before transplanting and 22% greater after transplanting. Plug cell volume also significantly impacted shoot and root biomass ( P <0.0001). A 14-mL increase in cell volume resulted in a root and shoot dry weight increase of about 15%.
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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".