Fatty acid and triacylglycerol compositions of seed oils of five <i>Amaranthus</i> accessions and their comparison to other oils
Bibliographic record
Abstract
Abstract This paper reports the fatty acid and triacylglycerol (TAG) compositions of five Amaranthus accessions (RRC1011, R149, A.K343, A.K432, and A. K433) representing two species and a cross between one of these and a third species. Seed oils of these were analyzed by gas chromatography and reversed‐phase high‐performance liquid chromatography, and their compositional properties compared with buck‐wheat (Fagopyrum esculentum), corn (Zea mays), rice bran (Oryza sativa), soybean (Glycine max L. Merr.), sesame (Sesamum indicum), quinoa (Chenopodium quinoa), and cottonseed (Gossypium hirsutum) oils. All Amaranthus accessions were relatively high in palmitic (21.4–23.8%) and low in oleic (22.8–31.5%) and linolenic (0.65–0.93%) acids when compared to most of the grain and seed oils. The fatty acid composition of Amaranthus accessions K343, K433, and K432 (group I) were different from R149 and RRC1011 (group II) in mono and polyunsaturated fatty acids, but the saturate/unsaturate (S/U) ratios were very similar. All Amaranthus accessions were similar in TAG type, but showed slight differences in percentage. High similarities in UUU, UUS, and USS composition were observed among Amaranthus K343, K433 and K432, and between R149 and RRC1011. The fatty acid compositions of Amaranthus oil (group I) and cottonseed oil were similar, but their TAG compositions were different. The grain and oilseed oils were different from each other and from the Amaranthus accessions oils in terms of fatty acid composition, S/U, and TAG ratios. The UUU, UUS, and USS percentages were very diverse in grain and seed oils. The percentages of squalene in the TAG sample from the Amaranthus accessions were 8.05% in K343, 11.10% in K433, 11.19% in K432, 9.96% in R149, and 9.16% in RRC1011. Squalene was also tentatively identified in quinoa and ricebran oils at levels of 3.39 and 3.10%, respectively.
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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 | 0.001 |
| 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".