Assessment of the Protein Quality of 15 New Northern Adapted Cultivars of Quality Protein Maize Using Amino Acid Analysis
Bibliographic record
Abstract
Amino acid determinations were carried out on 15 new northern adapted cultivars of quality protein maize (QPM) containing opaque-2 modifier genes to ascertain whether their amino acid scoring patterns could be used to select high-lysine QPM genotypes and to assess their protein quality. Total protein in these cultivars ranged from 8.0 to 10.2% compared to two commercial maize varieties, Dekalb DK435 (7.9%) and Pioneer 3925 (10.3%). Four of these QPM genotypes, QPM-C26, QPM-C21, QPM-C79, and QPM-C59, contained high levels of lysine (4.43-4.58 g of lysine/100 g of protein), whereas the remaining varied from 3.43 to 4.21 g of lysine/100 g of protein, compared to Dekalb DK435 and Pioneer 3925, which contained 2.9 and 3. 1 g of lysine/100 g of protein, respectively. Although lysine is the first limiting amino acid in QPM inbreds, the high-lysine QPM genotypes may supply approximately 70.2-72.6% of human protein requirements, compared to 46.2% for Dekalb DK435 and 50.1% for Pioneer 3925, 55-63% for oats, and 59-60.3% for barley. Northern adapted QPM genotypes may have the potential to increase their lysine content even further, either by an increase in specific high-lysine-containing nonzein proteins, such as the synthesis of factor EF-1a, or by a further reduction in the 19 and 22 kDa alpha-zein in the endosperm or both. This knowledge could assist maize breeders in the selection of new high-performance QPM genotypes with improved protein quality and quantity.
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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 | 0.000 | 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 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".