Varietal Screening Of Wheat Germplasms Against Resistance To Shoot Fly Atherigona Oryzae Malloch
Bibliographic record
Abstract
Wheat (Triticum spp.) is a stuff of life and has been considered as the “versatile cereal food”. It is also described as “King of cereals” for centuries. Greatest food grain source satisfies hunger of world population more than 35 per cent. Today, India ranks second in wheat production with 31.2 M ha as under cultivation and production of 107 million metric tonne with an average productivity of 30q/ha. The productivity of wheat is very low (988 kg/ha) in Karnataka as compared to the national average of 2900 kg/ha. This is mainly due to the fact that large area of wheat (60%) is grown under rain fed condition, non-adaptability of improved technologies and attack of many insect pests and diseases. In the past fifty years there has been an increase in wheat productivity and have also been marked by considerable changes in the pest complex. Introduction of high yielding wheat varieties has changed the wheat ecosystem and the changes in the crop environment have become conducive for the development and multiplication of certain insect pest species and have accelerated the incidence of older but innocuous pests and also have led to emergence of new ones. In the last five years shoot fly, stem borer and aphids are causing more damage in the various district of northern Karnataka. Shoot fly is causing more than 26 per cent dead heart in the early stage of the crop. However, the information available on pest of wheat is very scanty under north Karnataka conditions. There is need to document per cent damage of shoot fly in wheat, so as to generate information related economics of its incidence in wheat, particularly at Dharwad during rabi season of the year 2013-14. Hence, the present study was undertaken with the varietal screening of wheat germplasms against resistance to shoot fly.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".