Bibliographic record
Abstract
India is the largest producer of banana in the world and assumes much greater significance in enhancing farmers’ income, besides providing nutrition to consumers. Productivity is also highest, if locally grown traditional cultivars are excluded, and only area and production of Cavendish group is accounted which is about 45 percent of total area. Total production of banana in India is 29.2 million tonnes from 0.85 million hectares and accounts for more than 35 percent share in total fruit production and contributes about 2.5 percent to the Agricultural Gross Domestic Product (AGDP) of the country. Dramatic change in the production of banana, from 7.7 million tons in 1991 to about 30 million tonnes currently is attributed to technological changes and improvement in value chain management. Government has provided focused attention and investment for the research and development, considering its importance in socio-economics in the country by establishing National Research Centre for Banana, and through programs of National Horticulture Mission, which facilitates farmers to take up banana cultivation with improved techniques. A major private player for banana research and development in the country is Jain Irrigation Systems Limited (JISL), Jalgaon, Maharashtra, India, which produces about 70 million tissue cultured plants annually, assured with freeness from diseases, and is the largest producer of tissue cultured plants of banana in the world. They also provide technical and equipment for fertigation support to the network of 5 million farmers. Although India has provided leadership in production of banana, export has been limited, due to highly competitive export market. Now focus is on export and many companies in India are working for the export of banana from the country. The paper presents various facets and milestone of innovations which has led to the transformation in banana production in India.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".