Appraisal of Micronutrient Impact on Absorption of Macro- and Micronutrients in Tellar Cultivar of Soybean
Bibliographic record
Abstract
In order to study the effects of applying the micronutrients zinc, boron, and manganese (which are added to the soil and sprayed on the crop) on the absorption of the macro- and micronutrients in soybean seeds, an experiment was carried out using the factorial design with the two factors of adding the micronutrients zinc, manganese, and boron to the soil and spraying them on the crop, with 16 treatments and four replications (a total of 64 trials). On the basis of the soil test which had been conducted, the required amounts of the micronutrients (40, 30, and 10 Kg.h of zinc sulphate, manganese sulphate, and boric acid, respectively) were added to the soil before seeding. In the spray treatments, zinc and manganese (0.30 %) and boron (0.20 %) were sprayed on the crop at the start of stem elongation a d at flower bud formation. Results of the comparison of the means showed that the highest concentration of nitrogen (6.65 %) and phosphorous (0.18 %) in the seeds were obtained when zinc was sprayed on the crop, the highest potassium concentration in the seeds (0.92 %) was achieved when manganese was added to the soil, and the highest zinc concentration in the seeds (52.5 ppm) was observed when zinc was applied to the soil. These results also indicated that, among the treatments of spraying the micronutrients on the crop, the highest manganese concentration in the seeds (24.77 ppm) was obtained when manganese was sprayed on the crop, that the highest boron concentration in the seeds(46.58 ppm) was achieved when boron was added to the soil (and that this boron treatment had a statistically significant difference with the others). Comparison of the interaction effects of the data showed that the highest seed nitrogen concentration (6.72 %) was observed when zinc was sprayed on the crop, that the highest seed phosphorous concentration (0.22 %) was obtained when boron was added to the soil, that the highest seed potassium concentrations (0.93 % and 0.94 %) were achieved when zinc and manganese were sprayed on the crop, respectively, that the highest seed zinc concentrations were observed by adding manganese to the soil plus spraying zinc on the crop (55.33 ppm) and by adding zinc to the soil plus spraying zinc on the crop(55 ppm), that the highest seed manganese concentration (23.67 ppm) was obtained by adding zinc to the soil plus spraying manganese on the crop or by adding manganese to the soil plus spraying boron on the crop, and, finally, that the highest seed boron concentrations (44 and 41.67 ppm) were achieved by spraying boron on the crop and by adding manganese to the soil plus spraying boron on the crop, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".