Genetics of drought tolerance during seed germination in tomato: inheritance and QTL mapping
Bibliographic record
Abstract
A BC1 population (N = 1000) of an F1 hybrid between a stress-sensitive Lycopersicon esculentum breeding line (NC84173; maternal and recurrent parent) and a germination stress-tolerant Lycopersicon pimpinellifolium accession (LA722) was evaluated for seed germination rate under drought stress (DS) (14% w/v polyethyleneglycol-8000, water potential approximately -680 kPa), and the most rapidly germinating seeds (first 3% to germinate) were selected. The 30 selected BC1 seedlings were grown to maturity and self pollinated to produce BC1S1 progeny seeds. Twenty of the 30 selected BC1S1 progeny families were evaluated for germination rate under DS and their average performance was compared with that of a "nonselected" BC1S1 population of the same cross. Results indicated that selection for rapid germination under DS significantly improved progeny germination rate under DS (selection gain = 19.6%), suggesting a realized heritability of 0.47 for rate of germination under DS in this population. The 30 selected BC1 plants were subjected to restriction fragment length polymorphism (RFLP) analysis, and marker allele frequencies for 119 RFLP markers which spanned 1153 cM of the 12 tomato chromosomes were determined. A distributional extreme marker analysis, which measures statistical differences in marker allele frequencies between a selected and a nonselected population, detected four quantitative trait loci (QTLs) for rate of germination under DS in this population. Of these, two QTLs, located on chromosomes 1 and 9, were contributed by the L. pimpinellifolium donor parent and had larger effects than the other two QTLs, located on chromosomes 8 and 12, which were contributed by the L. esculentum recurrent parent. A few BC1S1 families were identified with all or most of the identified QTLs and with germination rates comparable with that of LA722. These families should be useful for the development of germination drought-tolerant tomato lines using marker-assisted selection (MAS). The overall results indicate that drought tolerance during seed germination in tomato is genetically controlled and potentially could be improved by directional phenotypic selection or MAS.
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 | 0.000 |
| 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".