MétaCan
Menu
Back to cohort
Record W2963675462 · doi:10.5539/jfr.v8n4p131

Association between Fruit Characteristics and Postharvest Stability of Different Pumpkin (Cucurbita) Species

2019· article· en· W2963675462 on OpenAlexvenueno aff
Nulu Nansikombi, John H. Muyonga, Yusuf B. Byaruhanga

Bibliographic record

VenueJournal of Food Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsnot available
FundersDeutscher Akademischer Austauschdienst
KeywordsPectinasePostharvestPectinCucurbita maximaSucroseHemicelluloseStarchLigninChemistryMoistureCelluloseSugarBotanyFood scienceHorticultureBiologyBiochemistry

Abstract

fetched live from OpenAlex

This study aimed at understanding peel and flesh characteristics of Cucurbita maxima Duchesne subsp maxima, Cucurbita pepo L var. fastigata and Cucurbita moschata Decne pumpkin varieties and how the fruit characteristics relate to its postharvest stability. Mature fruits were stored at ambient conditions (28oC and 78% Relative humidity) for eight months. Cell microscopic structure, intercellular space size, sugars, starch, cellulose, hemicellulose, lignin, degree of esterification of pectin, polygalacturonase activity, and cumulative moisture lost were determined monthly. Sucrose, starch, cellulose and hemicellulose content and degree of esterification of pectin of different varieties decreased with storage. Glucose and fructose content increased to a maximum and then reduced. Polygalacturonase activity and lignin generally increased with storage time. Size of intercellular spaces, and cumulative moisture lost from both flesh and peel increased with storage. Sucrose breakdown was key during 0 to 3 months, while moisture loss was important at 4 months of storage. Polygalacturonase activity became paramount from 7th month of storage. Postharvest stability of pumpkins is determined by an interplay of factors. The deterministic factor changes with time. Pumpkin varieties with more lignified peel had lower rates of sucrose breakdown and moisture loss and tended to be more stable postharvest. Varieties with low level of hemicellulose had their cell walls degrade early, while deterioration of pumpkins with highly esterified pectin and closely packed cells was delayed.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.066
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.130
GPT teacher head0.316
Teacher spread0.185 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Food ResearchSame topicPostharvest Quality and Shelf Life ManagementFrench-language works237,207