MétaCan
Menu
Back to cohort
Record W2166167390

Moisture adsorption and spoilage characteristics of pea under adverse storage conditions

2005· article· en· W2166167390 on OpenAlexfundaboutno aff
Samira Dadgar

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2005
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersMinistry of Agriculture - Saskatchewan
KeywordsFood spoilageMoistureEnvironmental scienceAdsorptionChemistryMaterials scienceBiologyComposite material
DOInot available

Abstract

fetched live from OpenAlex

Field pea is the most produced and exported pulse crop in Canada, and makes a major contribution to Western Canadian agricultural diversification programs.Canada is now the world largest exporter of pea, lentil and chickpea and is fourth in dry bean.The demand for Canadian pulse products is steadily rising and the export market would continue to rise with the expected increased in production.Field pea exported to countries with tropical climates is at particular risk due to rapid loss of quality.It is therefore important to develop practical strategies for safe storage of feed pea.Knowledge on the moisture adsorption and spoilage characteristics of pea stored in adverse storage conditions is important in the transportation and storage of this export commodity.This study was initiated to examine the conditions that lead to quality losses in storage and transport of pea.Tropical and subtropical conditions were simulated in airtight chambers.Relative humidities (RH) of 60, 70, 80 and 90% were created by saturated salt solutions in airtight chambers at temperatures of 10, 20 and 30C, while the same range of humidity was provided by dilute sulphuric acid in airtight chambers at 40C in environmental cabinets.The four RH levels at each temperature for both whole and feed-grade pea were tested in duplicate.The samples were observed for changes in moisture content (MC), mold appearance and RH in specific time intervals.The amount of produced carbon dioxide (CO 2 ) was measured in airtight chambers during storage to control the condition existing in sealed airtight chambers.Also, all components of feedgrade pea were exposed to RH of 90% and temperature of 40C in separate airtight chambers to find the effect of each component on mold appearance.Molds were identified after appearance on the samples in order to pinpoint potential toxicity.Both feed and whole sound peas became molded after a short time of storage at high temperatures and high RH, but those stored at 70% and below did not develop mold after 175 days at 30 and 40C (experiment duration) and 216 days at 10 and 20C (experiment duration).Molds were identified mostly as species of Aspergillus and Penicillium.The amount of CO 2 in the airtight chambers showed almost no difference from the ambient CO 2 except at high temperature and high RH when samples had gone molded.Moisture adsorption equations were developed based on the moisture adsorption data in dynamic environment.Although the Page model showed to fit the data better, the exponential model was chosen to fit the data because its parameters can be better expressed as a function of temperature and RH of the storage environment.The mold-free days for both feed pea and clean pea were modeled at temperatures of 10, 20, 30 and 40C and RH of 80 and 90%.v

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.171
Teacher spread0.163 · 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.

Study designQualitative
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

Citations3
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueUniversity Library - University of Saskatchewan (University of Saskatchewan)Same topicFood composition and propertiesFrench-language works237,207