Bibliographic record
Abstract
【Objective】High-amylose maize starch is an important industrial raw material.This study investigated its physicochemical properties to improve the cultivation of new varieties and industrial exploitation.【Method】Using thirteen high-amylose maize inbreds and one common inbred(Zheng 58),the differences in phenotypic characteristics of starch granules,thermal properties,pasting properties,solubility and expansion power of high-amylose maize starch and normal maize starch were investigated.【Result】The amylose content of common maize inbred starch was 27.72%.The amylose content of high-amylose maize inbred starch was 44.22%-78.81%,and could be divided into four levels.According to scanning electron micrographs,A-type starch granules from common inbred were full and smooth spheres or polyhedrons with waxy luster but those from high-amylose maize inbred were shrunken irregular and dull polyhed-rons.There were also significant differences in B-type starch granules and full and smooth spheres gradually changed to dull ovals,even to distorted irregular shapes.With increase of amylose content,To,Tp,Tc and To-Tc gradually increased butΔHgradually reduced.The pasting properties(RVA)of common inbred starch showed typicaldoubletscurve,while that of high-amylose maize inbred starch showedScurve with the increase of amylose content.The melting curves and expansion curves of common inbred starch and high-amylose maize inbred starch showed same trends,while starch solubility and swelling degree decreased significantly with the increase of amylose content.【Conclusion】Compared to common corn starch,high-amylose corn starch was different in the phenotypic characteristics of starch granules,thermal properties,pasting properties,solubility and swelling power.The difference increased as the increase of amylose content.
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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".