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Record W4211234217 · doi:10.1002/9781119098935.ch9

Postharvest Physiology of Vegetables

2018· other· en· W4211234217 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPostharvestRipeningRespirationBiologyInflorescenceRespiration rateHorticultureBotany

Abstract

fetched live from OpenAlex

This chapter focuses on the physiological processes of vegetables that determine changes in both perceptible quality and nutrient and functional constituents. The storage potential of vegetables depends upon their structure, developmental stage, the respiration rate at harvest and the subsequent physiology. There are essentially three subgroups of vegetables, with different postharvest physiologies and therefore storage requirements: leaves, stems, flower buds and inflorescences; fruit-vegetables; and biennial vegetables. The chapter tabulates the differing vegetable types and their respiratory characteristics. Beyond basal metabolism (respiration), there are other unique physiological characteristics of specific vegetables that result in differing considerations in postharvest handling. The chapter also discusses all these considerations. Phytohormones are a fundamental component of plant growth and development. Bulb vegetables such as onion show differing patterns of change for all the major classes of phytohormones. Ethylene has been the most studied phytohormone in fruit ripening.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0320.001

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 head0.020
GPT teacher head0.223
Teacher spread0.202 · 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