Initial Development and Tolerance of Lettuce (Lactuca sativa) Cultivars Irrigated with Saline Water
Bibliographic record
Abstract
The objective was to study the initial development and tolerance of lettuce cultivars subjected to different levels of water salinity in the seedling production stage in order to determine the genotypes of the cultivars that are most sensitive and tolerant to saline water. The experiment was carried out in protected environment at the Center of Sciences and Agri-food Technology-CCTA of the Federal University of Campina Grande-UFCG, located in Pombal, Paraíba, Brazil, from August to September 2014. The study evaluated five lettuce cultivars (C1-’Simpson Semente Preta’, C2-’Alba’, C3-’Mimosa Vermelha’, C4-’Veneranda’ and C5-’Mônica Sf 31’) and five levels of irrigation water salinity (0.6 (control), 1.2, 1.8, 2.4 and 3.0 dS m-1), arranged in a factorial scheme 5 × 5, in a completely randomized experimental design, with four replicates. Plants were grown on trays for 20 days after sowing, period in which irrigations were daily applied, and evaluated for emergence, growth, phytomass accumulation and tolerance index of the lettuce cultivars. The increase in irrigation water salinity reduced emergence, growth and dry matter accumulation in the lettuce plants, and the cultivars C2-’Alba’ and C4-’Veneranda’ were the most tolerant to salinity. Tolerance to salinity occurred in the following order C2-’Alba’ = C4-’Veneranda’ > C1-’Simpson Semente Preta’ > C3-’Mimosa Vermelha’ = C5-’Mônica Sf 31’.
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 | 0.000 | 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".