Establishing critical limits for nickel in soil and plant for predicting the response of spinach (spinacia oleracea)
Bibliographic record
Abstract
Nickel (Ni) is an essential element for plants and research reports are available indicating its beneficial effects on growth of higher plants as well. Though abundant information exists on Ni toxicity in soil and plant system but not much is available on its critical level of deficiency (CLD) in soils and plants. A pot experiment was conducted in net-house of the micronutrient research project, Anand Agricultural University, Anand, Gujarat. For assessing the critical limit in soil, three bulk soils viz., low (<0.5 mg Ni kg-1), medium (0.5 to 1.0 mg Ni kg-1) and high (>1.0 mg Ni kg-1) were collected from different locations of Anand district. Six levels of Ni, i.e. Ni0, Ni2, Ni4, Ni6, Ni8 and Ni10 (0, 2.0, 4.0, 6.0, 8.0 and 10.0 mg Ni kg-1 soil) were applied in all 20 soils (10 low, 6 medium and 4 high in Ni content in soil). The experiment was conducted in factorial completely randomized design with three replications. The critical limit of Ni in soil was determined by Bray's per cent yield plotted against soil available Ni using the scattered diagram in graphical as well as statistical method. Wide variation in dry matter produce was observed across the soils. The concentration of Ni in spinach plant increased with increasing the level of Ni in soil. The CLD of the 0.005 M DTPA-CaCl2 extractable Ni in soil and plant was worked out as 0.46 and 2.27 mg kg-1, respectively with statistical method. Whereas, in graphical method it was reported as 0.50 and 2.20 mg kg-1, respectively in spinach crops.
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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 | 0.003 | 0.002 |
| 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".