Effects of salinity stress on starch morphology, composition and thermal properties during grain development in triticale
Bibliographic record
Abstract
He, J.-F., Goyal, R., Laroche, A., Zhao, M.-L. and Lu, Z.-X. 2013. Effects of salinity stress on starch morphology, composition and thermal properties during grain development in triticale. Can. J. Plant Sci. 93: 765-771. Triticale is a man-made cereal crop developed from a cross between wheat and rye. It has excellent agronomic traits for starch production on arid and semi-arid lands. This study investigated the effects of salinity stress on the alterations of starch morphology, composition and physicochemical properties during triticale grain development. Three triticale varieties (AC Certa, AC Ultima and Blue Alta) were treated with three levels of NaCl solutions (50, 100 and 200 mM), termed low salinity stress (LSS), moderate salinity stress (MSS) and high salinity stress (HSS), respectively. Reduction in seed weight and starch content were observed under salinity stress; the values decreased by 9-42% under MSS and 18-51% under HSS. MSS and HSS favored an increase of amylose synthesis and accumulation in triticale starch. Triticale starch synthesized under salinity stress showed a decreased population of small granules and an increased ratio on A-type to B-type granules. MSS and HSS decreased the peak temperature and increased the starch enthalpy, and an inverse relationship between salinity stress and a range of starch gelatinization temperature was also observed. This is the first report demonstrating that starch morphology, composition and thermal properties in triticale grains can be significantly affected by salinity stress.
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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".