Effect of the brown midrib trait and stage of development at harvest on cell wall composition and degradability of forage pearl millet leaves and stems
Bibliographic record
Abstract
This study was conducted to determine the effect of the brown midrib trait and stage of development [vegetative (VS) vs. heading (HS) stage] on chemical composition and in situ rumen disappearance of forage millet leaves and stems. Forage yield of brown midrib millet was 80 and 50% of that of regular millet at VS and HS, respectively. The reduction in brown midrib millet yield was mainly due to reduction in plant height and tillers m -2 . The brown midrib trait reduced concentrations of neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) in stems by 8, 16, and 58%, respectively, and concentrations of ADF and ADL in leaves by 6 and 49%, respectively. Effects of stage of development on fiber fractions were more pronounced in stems than in leaves. Millet stems harvested at HS had greater concentration of NDF, ADF and ADL than at VS, while only ADL concentration in millet leaves increased with advancing development. Leaves and stems of brown midrib millet (BM) contained more arabinose and xylose than those of regular millet (RM), while glucose concentration was not affected by millet type. Concentrations of xylose and arabinose were higher in leaves, while those of glucose and arabinose were higher in stems of millet harvested at HS than at VS. The brown midrib trait reduced concentrations of ester- linked p-coumaric acid and ether-linked p-coumaric and ferulic acids in both leaves and stems. However, concentration of ester-linked ferulic acid was only reduced in stems. Concentrations of all phenolic acids were higher in stems of millet harvested at HS than at VS. However, the effects of stage of development for most phenolic acids were more pronounced for stems of RM than BM. In situ DM and NDF disappearances were higher in leaves and stems of BM than RM and were higher in leaves and stems of millet harvested at VS than at HS. The brown midrib trait reduced the negative impact of increasing maturity on in situ DM and NDF disappearance in leaves and in situ DM disappearance in stems. It was concluded that the brown midrib trait caused significant changes in cell wall composition of both leaf and stem fractions which resulted in improved in situ nutrient disappearances. The trait also reduced the negative effect of advanced maturity on nutrient digestibility. Key words: Brown midrib; forage millet; in situ disappearance; Pennisetum glaucum (L.) R. Br.; phenolic acids
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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 | 0.001 | 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 | 0.001 |
| 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".