Variance Analysis of Grain Fe and Zn Concentrations in Nine Beer Barley Cultivars
Bibliographic record
Abstract
Investigation of cereal concentration of mineral elements including the grain iron and zinc concentrations (GFeC and GZnC) of barley is very important for human health.Nine beer barley cultivars introduced from five provinces in China were grown in the Center of Guizhou province (Huaxi in Guiyang),and then the GFeC and GZnC of these barley cultivars were detected by inductively coupled plasma mass spectroscopy (ICP-MS) and optical emission spectrometry (ICP-OES),respectively.The obtained results showed that there were significant differences of GFeC and GZnC among the varieties by one way ANOVA (p0.000 1).GFeC and GZnC among the nine cultivars varied from 36.45 to 140.85 mg/kg and 47.99 to 98.69 mg/kg.The highest varieties of GFeC and GZnC were Yunpi 6 and Supi 4,while the lowest ones both were Ganpi 3.According to Spearman's Rho Correlation analysis,the GZnC had significant negative correlations with booting stage,heading stage,maturity stage,flag leaf length,negative area,plant height and spike length,and the GZnC displayed significant negative correlations with flag leaf width,spikelets per main spike,and positive correlations with number of tiller per plant and availability number of tiller,respectively.The results provided the valuable data for choosing both high yield and quality beer barley cultivars for future improvement.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".