Genotype by environment interaction effect on yield and quality of potatoes
Why this work is in the frame
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Bibliographic record
Abstract
Colour is an important character in the processing of potatoes for French fries. French fry colour is closely associated with sugar content in the tuber. This study examines the stability of yield, sugar content and French fry colour for eight potato cultivars and advanced selections in four environments. Stability was determined using three approaches based on the Eberhart-Russell, Tai and GGE Biplot analyses. The GGE Biplot analysis provided a better characterization of stability than the other two analyses. The most stable and best performing genotypes for both French fry colour and total sugars were Russet Burbank and Umatilla Russet. Cal White had high yield and yield stability but had average stability for poor (dark) French fry colour. The GGE biplot analysis was able to identify mega-environments and those environments which optimized differentiation between genotypes. Both factors are important for the optimization of resources for testing new genotypes. Stability for quality factors in potato can be as important or more important than yield for some processing uses. In this study, genotypes with stability for sugar content and French fry colour were identified and these may be used as parents in breeding for stability. Key words: Potato, yield stability, quality, French fry
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it