Development and Physicochemical Characterization of New Resistant Citrate Starch from Different Corn Starches
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Bibliographic record
Abstract
Abstract Resistant starch has drawn broad interest for both potential health benefits and functional properties. In this study, a technology was developed to increase resistant starch content of corn starch using esterification with citric acid at elevated temperature. Waxy corn, normal corn and high‐amylose corn starches were used as model starches. Citric acid (40% of starch dry weight) was reacted with corn starch at different temperatures (120–150°C) for different reaction times (3–9 h). The effect of reaction conditions on resistant starch content in the citrate corn starch was investigated. When conducting the reaction at 140°C for 7 h, the highest resistant starch content was found in waxy corn citrate starch (87.5%) with the highest degree of substitution (DS, 0.16) of all starches. High‐amylose corn starch had 86.4% resistant starch content and 0.14 DS, and normal corn starch had 78.8% resistant starch and 0.12 DS. The physicochemical properties of these citrate starches were characterized using various analytical techniques. In the presence of excess water upon heating, citrate starch made from waxy corn starch had no peak in the DSC thermogram, and small peaks were found for normal corn starch (0.4 J/g) and Hylon VII starch (3.0 J/g) in the thermograms. This indicates that citrate substitution changes granule properties. There are no retrogradation peaks in the thermograms when starch was reheated after 2 weeks storage at 5°C. All the citrate starches showed no peaks in RVA pasting curves, indicating citrate substitution changes the pasting properties of corn starch as well. Moreover, citrate starch from waxy corn is more thermally stable than the other citrate starches.
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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 it