The concentrations and distribution of phytic acid-phosphorus and other mineral nutrients in wild-type and<i>low phytic acid</i>1-1 (<i>lpa</i>1-1) corn (<i>Zea mays</i>L.) grains and grain parts
Bibliographic record
Abstract
A comparison of mineral nutrient and phytic acid-phosphorus (PA-P) distribution in the grains of wild-type (WT) and low phytic acid1-1 (lpa1-1) corn (Zea mays L.) was conducted to determine how the lpa1-1 mutation influences mineral element concentrations in different grain parts and impacts the structure of phosphorus-rich inclusions (globoids) in the grain cells. This is the first report regarding total phosphorus (P) and PA-P concentrations in scutellum and root-shoot axis portions of cereal embryos of WT in comparison to its matching lpa1-1 genotype. In WT, 95% of the grain PA-P was located in the embryo, mostly in the scutellum. The lpa1-1 mutation reduced whole-grain PA-P by 62% but influenced the scutella more than the root-shoot axes and rest-of-grain fractions. In spite of the lpa1-1 mutants containing greatly reduced PA-P, whole-grain amounts of Mg, Fe, and Mn were higher in lpa1-1 than in WT, K and Zn were similar, and Ca was lower. Iron was 1/3 higher in lpa1-1 grains than WT while Ca was 18% lower. Decreased phytic acid in lpa1-1 grains resulted in reduction in globoid size in both scutellum and aleurone layer cells. Most lpa1-1 aleurone globoids were non-spherical and scutellum globoids were clusters of small spheres while WT globoids were large discrete spheres. X-ray analyses of globoids in both grain types revealed major amounts of P, K, and Mg and traces of Ca, Fe, and Zn. Both grain types contained almost no mineral nutrient stores in the starchy endosperm.Key words: corn (Zea mays L.), phytic acid-phosphorus, low phytic acid1-1 (lpa1-1) grains, mineral nutrients, globoids, electron microscopy.
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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 | 0.001 | 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) | 0.001 | 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".