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Record W2343145535 · doi:10.1002/jsfa.7783

Natural variation of sucrose, glucose and fructose contents in Colombian genotypes of <i>Solanum tuberosum</i> Group Phureja at harvest

2016· article· en· W2343145535 on OpenAlexafffund
Diana Duarte‐Delgado, Carlos Eduardo Ñústez López, Carlos‐Eduardo Narváez‐Cuenca, Luz‐Patricia Restrepo‐Sánchez, Sandra E. Melo, Felipe Sarmiento, Ajjamada C. Kushalappa, Teresa Mosquera

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsMcGill UniversitySte. Anne's Hospital
FundersMinistry of Environment and Sustainable DevelopmentMinistry of EnvironmentInternational Development Research Centre
KeywordsGermplasmFructoseSucroseSugarBiologySolanum tuberosumSolanumFood scienceHorticultureTraitBotany

Abstract

fetched live from OpenAlex

BACKGROUND: Potato frying quality is a complex trait influenced by sugar content in tubers. Good frying quality requires low content of reducing sugars to avoid the formation of dark pigments. Solanum tuberosum Group Phureja is a valuable genetic resource for breeding and for genetic studies. The sugar content after harvest was analyzed in a germplasm collection of Group Phureja to contribute to the understanding of the natural variation of this trait. RESULTS: Sucrose, glucose and fructose genotypic mean values ranged from 6.39 to 29.48 g kg(-1) tuber dry weight (DW), from 0.46 to 28.04 g kg(-1) tuber DW and from 0.29 to 27.23 g kg(-1) tuber DW, respectively. Glucose/fructose and sucrose/reducing sugars ratios ranged from 1.01 to 6.67 mol mol(-1) and from 0.15 to 7.78 mol mol(-1) , respectively. Five clusters of genotypes were recognized, three of them with few genotypes and extreme phenotypic values. CONCLUSION: Sugar content showed a wide variation, representing the available variability useful for potato breeding. The results provide a quantitative approach to analyze the frying quality trait and are consistent with frying color. The analyzed germplasm presents extreme phenotypes, which will contribute to the understanding of the genetic basis of this trait. © 2016 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.165

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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 designBench or experimental
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

Citations42
Published2016
Admission routes2
Has abstractyes

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