STUDY OF AIR-SPORA OVER THE GROUND NUT FIELD IN JALGAON DIST. MAHARASHTRA
Bibliographic record
Abstract
Aerobiology is the science of biological, airborne organisms and their movement and effect on plant, animal and human health.Arachis hypogea is susceptible to various diseases such as seed boarn, soil boarn and air boarn diseases, which is caused by bacteria, viruses, fungi and nematodes.Important fungal diseases of ground nut plant are as follows.Leaf spot disease caused by Cercospora arachidicola.More focus has been given to fungal air-spora during this present investigation.Effect of some environmental factors such as rainfall, humidity and temperature on the diseases causing and the percentage contribution of all air boarn fungal air-spora components were recorded.In this aerobiological research investigation includes quantitative as well as qualitative analysis of fungal air spora over ground nut crop at Jalgaon dist., in Maharashtra.The metrological data for each day of relative humidity, temperature and rainfall was obtained from metrological department of Jalgaon district.After the observation of all slides, with the help of visual observation, identification of fungal spores takes place.It is observed that some factors like Humidity, temperature, rainfall, growth and age of the plant affects the frequency and the spread of the disease.During this present investigation some allergic fungal spores were found abundantly.For e.g.Alternaria, Cladosporium, curvularia and pollen grains.The crop variety i.e.Arachis hypogea L., JL-24, was recorded to be highly resistant for the diseases development.So the Arachis hypogea L plant was found to be very healthy.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".