Stomatal conductance and stomatal resistance studies in relation to haulm yield in potato.
Bibliographic record
Abstract
The major potato growing countries in the world are China, Russian Federation, India, USA, Ukraine, Poland, Germany, Belarus, Netherlands, France, UK, Canada, Turkey and Romania. India ranks 4th in area and 3rd in production in the world. The total potato production in India is about 36.57 million tonnes from about 1.83 million ha with productivity of 19.98 t ha during 2009-2010. Potato is grown over the states under very diverse conditions. The plant leaves must remain turgid for leaf expansion, to keep stomata open for higher photosynthetic rate. In plant, leaves functions as an optical organs and spectral radiation properties are attuned to environment in which they live. The efficiency of absorption of PAR partly determines the efficiency of photosynthesis of plant. The PAR is absorbed more efficiently and centering around 400-700 nm, determines the plant development. Among the main factors which affect the rapid establishment of the crop canopy are genotypes, planting date, planting density, temperature and the availability of water and nutrients in the soil. Potato is a weather sensitive crop influenced by environmental conditions. With this back ground in view, the present investigation was undertaken to know the relationship between stomatal conductance with haulm yield as affected by irrigation levels in potato.
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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 | 0.000 | 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 | 0.001 |
| 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".