Diverse Grain‐Filling Dynamics Affect Harvest Management of Forage Barley and Triticale Cultivars
Bibliographic record
Abstract
Core Ideas Decision‐making criteria are needed to optimize silage production in barley and triticale. The critical factors, yield, forage quality, and dry matter interact in the grain‐filling period. Optimization of factors is required and the indicator for harvest may differ between species. Comparison on a growing degree day scale during grain filling provided an assessment of dynamics. Triticale needed more degree days than barley to optimize yield and dry matter shown by dough stage. Harvest time for small‐grain forage is impacted by changes in yield, dry matter concentration (DMC) and forage quality during grain‐filling. Little information exists for hulless and two‐rowed barley ( Hordeum vulgare L.) and triticale (X Triticosecale Wittmack) grown in Alberta. Two barley and two triticale cultivars were grown at three planting dates and two locations over 2 yr at Lacombe, AB, Canada. Forage was harvested five times after boot stage at 7‐ and 10‐d intervals for barley and triticale, respectively. Relationships were developed by regressing variables with growing degree days (GDD) after the boot stage for triticale cultivars, combined, and each barley cultivar (‘Falcon’ and ‘Gadsby’). Comparisons were made at GDD positions. Triticale out‐yielded and dried slower than barley and had higher DMC for 560 GDD after the boot stage; Gadsby out‐yielded Falcon. The soft dough stage (DS 85) indicated optimum yield, 93% of relative dry matter yield (RDMY) at less than 400 g kg −1 DMC for barley and triticale, but occurred at 400 and 500 GDD after the boot stage, respectively. Triticale had lower in vitro true digestibility (IVTD) and higher fiber levels than barley at boot stage; but triticale IVTD decreased slower than barley and Falcon declined faster than Gadsby. Starch accumulated more rapidly for Gadsby than Falcon, while triticale increased slowly initially, then rapidly later in the grain filling period. Delaying harvest by 100 GDD for triticale compared to barley (both at DS 85) resulted in the higher triticale yield, while allowing more starch to accumulate.
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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".