Study on RP-HPLC Analysis on HMW-GS Wheat Cultivars in Heilongjiang Province and Its Method
Bibliographic record
Abstract
To investigate the HMW-GS over-expression of main wheat cultivars and advanced lines in the Heilongjiang province,48 wheat cultivars/lines were analyzed by SDS-PAGE and Reversed-phase high-performance liquid chromatography(RP-HPLC)in 2009 and 2011.Three HPLC columns from the same manufacturer and same Part No but different packing lots were used.The columns from different lots required inconsistent temperatures in separation of 8* subunit.Each HMW-GS could be effectively separated at a column temperature of 60℃ for one column,but 8* subunit submerged in the peak of 2 or 5 subunits at a column temperature of 60℃ for other two columns,and could only be effectively separated at a column temperature of 70℃.Therefore,in the analysis of wheat storage protein in the application of RP-HPLC,full account should be taken on the differences in column performance to determine the optimum column temperature in order to achieve better separation effect.The results indicated that over-expression subunit was limited to Bx7oe subunit in wheat cultivars/lines developed in Heilongjiang province and the Bx7oe subunit were from Canada Western Extra strong wheat cultivar Glenlea.In the different cultivars/lines with five HMW-GSs,the mean of relative content(single subunit peak area/total HMW-GS peak area×100)of Bx7oe subunit was 46%(range 43%~49%),other Glu-Blx subunit was 31%(range 26%~35%).Therefore,Bx7oe subunit was useful in wheat breeding and production for strong gluten or extra strong gluten.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".