Analysis of Genotype, Environment, and Their Interaction Effects on the Phytochemicals and Antioxidant Capacities of Red Rice (<i>Oryza sativa</i> L.)
Why this work is in the frame
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Bibliographic record
Abstract
Fourteen red rice varieties were planted in two locations during summer (Hangzhou) and winter (Hainan) to study the effect of genotype and environment on the phytochemicals and antioxidant capacities of rice grain. B‐type proanthocyanidins in red rice were detected by LC‐MS/MS and quantified by using the vanillin assay. Analysis of variance showed that total phenolic content (TPC), total flavonoid content (TFC) and 2,2′‐azino‐bis‐(3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS) radical scavenging capacity were mainly affected by environmental factors, which accounted for more than 60% of the total variance. However, total proanthocyanidin content (TPAC) and 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) radical scavenging capacity were equally affected by both genotype and environment. The genotype × environment effects were significant for all traits. The pairwise correlations among TPC, TFC, TPAC, ABTS, and DPPH were also significant ( r > 0.900, P < 0.001). Principal component analysis identified the genotypes that had higher contents of antioxidants and more stability across environments. This study showed that indirect selection of a simple trait (i.e., TPC) is an effective way to select rice high in antioxidant capacity in breeding programs. This study also suggests that rice should be produced specifically in a certain environment for the end user to minimize the variation in the functional properties and maximize their contents.
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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