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Record W2886361914 · doi:10.5539/jas.v10n9p225

Postharvest of ‘Tommy Atkins’ Mango Submitted to Coating of Chlorella sp.

2018· article· en· W2886361914 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPostharvestRipeningPulp (tooth)HorticultureChlorellaFood scienceChemistryBotanyBiologyAlgaeMedicine

Abstract

fetched live from OpenAlex

The use of natural products as coatings to preserve the fruit quality during storage is an important step to maintain food safety for consumer health. The use of microalgae in coatings, therefore, may be promising in the preservation of mango. The present work had the objective to evaluate the effect of coatings based on Chlorella sp. on the postharvest preservation of ‘Tommy Atkins’ mango during storage at room temperature (23 °C). We carried out a completely randomized design experiment consisting of 0%, 1%, 2%, 3% and 4% of Chlorella sp., using 10 fruits per treatment (n = 10). Analyzing the L*, a* and, b* indices, in the peel and the pulp of the mango fruit, we observed a delay in the ripening with the increase of the biofilm concentration. The firmness of the pulp and maintenance of the organic acids of the fruits were higher in the treatments with a large amount of Chlorella sp. The use of biofilm with Chlorella sp. at 2% preserved the quality of ‘Tommy Atkins’ mango until ten days of storage, at 23 °C and 42% RH.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.282
Teacher spread0.255 · 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