Shading on Yield and Quality of Lettuce Cultivars in Semiarid Conditions
Bibliographic record
Abstract
Lettuce is a crop originating from temperate climate, and for this reason, when cultivated in semiarid region, characterized by high luminosity and temperature, major losses in productivity and quality occur. The objective of this work was to evaluate the influence of different levels of shade on yield and quality of lettuce cultivars in semiarid conditions. The experiment was conducted under field conditions at the Human and Agricultural Sciences Center at State University of Paraiba, Brazil, in randomized blocks with parcels divided into 4 × 4 factorial space, and four repetitions. The parcels received different shading levels (0, 30, 50 and 70%) with black polypropylene screen and sub parcels by lettuce cultivars: ‘Americana Irene’, ‘White Boston’, ‘Regina de Verão’ and ‘Green Salad Bowl’. The shading promoted higher performance in height, stem diameter, root length, pH and dry mass of lettuce plants when compared to those grown in the open-air, being the shading of 70% the more efficient. The ‘Americana Irene’ cultivar was distinguished in terms of plant height, foliage area, leaves dry mass and soluble solids, independently from the cultivation environment. With the shading, this cultivar improved the aerial shoot-root ratio and root dry mass.
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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 | 0.000 |
| 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".