Effect of Harvesting Corn after Frost in Alberta (Canada) on Whole-Plant Yield, Nutritive Value, and Kernel Properties
Bibliographic record
Abstract
This study compares yield, nutritive value, and kernel properties of whole plant corn (WPC) harvested before and after a light frost in short growing season areas. Six corn hybrids grown in two years at three locations within Alberta (Canada) were harvested before or after the first frost. Samples of WPC were analyzed for dry matter (DM) content, neutral detergent fiber (NDF) concentration, starch concentration, and 48-h in vitro DM and NDF digestibility (DMD and NDFD, respectively). Cob samples were analyzed for DM, and kernels were analyzed for DM, hardness, particle size distribution, density, and stage of maturity. Delaying harvest to after frost increased DM content of WPC at all locations but exceeded the recommended range (32–38%) in the two warmest locations. Whatever the year and hybrid, DM yield was either not affected or decreased after frost. Postfrost harvest increased starch concentration and modified kernel characteristics only if these were less than expected before frost. Fiber concentration was not affected by harvesting time. Frost had either no impact or increased DMD or NDFD of WPC. We conclude that delaying harvest until after frost in short growing season areas can be beneficial when whole-plant DM content is low before frost.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".