Effect of foliar application of iron,zinc mixed fertilizers on the content of iron,zinc,soluble sugar and Vitamin C in green pea seeds
Bibliographic record
Abstract
Effects of foliar application of ferrous sulphate,zincic sulphate,urea and humic acid(HA) mixed fertilizers on the Fe,Zn content and the nutritional quality indexes such as Vitamin C,soluble sugar,and nitrate contents in green pea(Pisum Sativum L) seeds were studied with series of field trials.The results showed that the ferrous sulphate,urea and humic acid mixture(0.1%FeSO_4+0.2%HA+0.5%Urea) could significantly increase iron content in green pea seeds,but adversely affect zinc accumulation.The zinc sulphate,urea and humic acid mixture(0.2%ZnSO_4+0.1% HA +0.5% Urea) could enhance markedly zinc content in green pea seeds but adversely affect iron absorption.And the most appropriate formula of iron and zinc mixed fertilizer recommended was 0.1% FeSO_4+0.2%ZnSO_4+0.2% HA +0.5% Urea.Ferrous sulphate,zincic sulphate,urea and humic acid mixed fertilizer could enhance notably the content of iron and zinc,Vc and the soluble sugar content in green pea seeds and evidently lower the content of NO~-_3-N.Hence,the nutritional quality of green pea seeds was greatly improved.
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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 | 0.001 | 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 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".