Maize kernel moisture, carbon and nitrogen concentrations from silking to physiological maturity
Bibliographic record
Abstract
Grain characteristics prior to physiological maturity are important for silage harvest and for grain harvest when grain fill has been prematurely terminated by factors such as hail or early frost. The objective of this study was to investigate changes in grain moisture, C and N concentrations associated with the progression of milk line from silking to physiological maturity for hybrids with maturity ratings between 76 and 95 Minnesota relative maturity days. A field experiment with a total of 15 hybrids was carried out on a well-drained sandy loam soil at Ottawa, Canada, from 1995 to 1997, inclusive. A large number of uniform plants with the same phenology were marked in each plot near tasseling, and ears were sampled from these plants at weekly intervals from R1 to final harvest. It was noted that 50% milk line was associated with a range of kernel moisture concentrations: in 1995, a relatively warm year, kernel moisture was 389 g kg –1 when 50% milk line occurred; in 1996, a relatively cool year, kernel moisture was over 420 g kg –1 at 50% milk line. During the course of grain fill, C concentrations remained relatively constant whereas N concentrations were dramatically reduced from as high as 50 g kg –1 to approximately 15 g kg –1 . Maximum dry matter accumulation was reached at 325 g kg –1 moisture. In general, later-maturing hybrids appeared to have longer duration from silking to 50% milk line; however, they took less time to reach physiological maturity (faster grain fill and dry down). Although benchmarks of 50% milk line and 0% milk line are commonly used for silage and grain production, there is a range of grain moisture-milk line relationships among genotypes and under different environmental conditions during grain fill. Key words: Maize, milk line progression, kernel moisture, carbon and nitrogen
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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".