Amino acid composition, protein content and accurate nitrogen-to-protein conversion factor for sheepgrass (<i>Leymus chinensis</i>)
Bibliographic record
Abstract
The protein content of plants is commonly estimated by multiplying the total nitrogen content (Kjeldahl; KN) by a nitrogen-to-protein conversion factor of 6.25. This method is based on the incorrect assumption that all nitrogen in the ammonia/ammonium and organic substances in plants is protein nitrogen, usually resulting in overestimation of protein content. We have examined amino acid composition, amino acid nitrogen, total nitrogen (KN), and actual protein content (AP) determined from amino acid residues in 16 accessions of perennial sheepgrass (Leymus chinensis (Trin.) Tzvelev). We determined a new nitrogen-to-protein conversion factor, k P , as the ratio of AP to KN, and applied this factor to estimate the total protein content (TP) as KN × k P . The non-protein nitrogen accounted for 40.5% to 62.4% of the total nitrogen. The average k P value was 3.17 overall, 3.20 in the accessions sampled at the jointing stage, and 3.15 in the accessions sampled at the flowering stage. The TP, calculated as KN × 3.17, was about half that of crude protein contents, calculated as KN × 6.25. Our study suggests that the AP-based k P of 3.17 can be used to more accurately estimate the total protein content in sheepgrass.
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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".