Assessing nutritional and genetic variations within foxtail millet (Setaria italica) landraces collected from indigenous communities across the Philippines
Bibliographic record
Abstract
(L.) P. Beauv.). We collected together accessions of this crop from different eco-geographical locations within the Philippines, along with a few accessions from Lanyu, Taiwan, to undertake a study of their nutritional value and genetic diversity. All accessions were field-grown in 2022, dry season (DS) at the Institute of Plant Breeding (IPB) Experiment Station, Los Baños, Laguna, Philippines. The accessions were tested for micronutrients, including Zn and Fe, nitrogen as a proxy for protein, β-carotene, phytic acid, and a number of phenolic compounds with known nutritional potential. Of the 20 accessions tested, the accessions Bayaras and GB61438 had the highest level of Zn (107.1 mg/kg) and Fe (70.52 mg/kg), respectively, higher than levels found in traditional rice varieties. For β-carotene the highest concentration was found in the accession Balles (∼10 μg/g). Twelve phenolic compounds were detected, with catechin, syringic acid, ferulic acid and kaempferol having the highest concentrations. To assess the genetic diversity, we sequenced a set of eight samples selected from among the accessions to a depth of at least 25-fold using whole-genome re-sequencing. Analysis of the population structure, using genome-wide, high-quality SNPs, showed modest diversity among the accessions, with two unadmixed groups. The accessions are monophyletic relative to their earliest common ancestor, with the very light brown accessions emerging earlier than the light brown and reddish-brown varieties. Analysis of zinc-regulated, iron-regulated transporter-like protein (ZIP) transporters within the foxtail millet reference sequence, var. Yugu1 identified 17 putative ZIP transporters. Variant calling identified SNPs primarily within 3' and 5' regions, and introns, indicating variation between foxtail millet accessions within regulatory gene regions rather than in structural proteins. The local foxtail millet accessions, therefore, represent a potential alternative source of nutrients which may help in addressing malnutrition in the Philippines.
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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".