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Record W2180879481 · doi:10.4141/cjps2011-066

Stability of eight potato genotypes for sugar content and French fry quality at harvest and after storage

2012· article· en· W2180879481 on OpenAlexaffvenue
Ian Affleck, J. Alan Sullivan, Richard Tarn, Rickey Y. Yada

Bibliographic record

VenueCanadian Journal of Plant Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
Fundersnot available
KeywordsBiplotSugarSowingCropHorticultureAgronomyBiologyGenotypeFood science

Abstract

fetched live from OpenAlex

Affleck, I., Sullivan, J. A., Tarn, R. and Yada, R. 2012. Stability of eight potato genotypes for sugar content and French fry quality at harvest and after storage. Can. J. Plant Sci. 92: 87–96. Processing quality of potatoes for French fries is partially determined by reducing sugar content of the tuber. Much of the potato crop is processed after a storage period when sugar content can change and affect processing quality. In this study, the stability of sugar levels in eight potato genotypes was studied over four environments (i.e., two locations over 2 yr). The GGE biplot analysis was used to measure the stability of, and the association between, quality traits and sugar content. Quality and sugar content were measured 105 and 120 d after planting and 60 and 120 d after storage. The biplots indicated a change in French fry colour scores and stability between the 105 and 120 d after planting harvest dates. Genotypic differences were noted for French fry colour scores and glucose content. Genotypes were identified that were stable for French fry colour during the two storage periods indicating low genotype by environment interaction. The GGE biplot identified mega-environments that encompassed a group of environments with similar attributes. Based on this finding potatoes from only one environment within the mega-environment would need to be stored for quality evaluations.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.217
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2012
Admission routes2
Has abstractyes

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