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Record W4398145591 · doi:10.1201/9781003309888-4

Silo Bag Storage

2024· book-chapter· en· W4398145591 on OpenAlexaboutno aff
Ricardo Bartosik, Leandro de Morais Cardoso, Hernán Alejandro Urcola

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicSilicon Effects in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsSiloEnvironmental scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Silo bags are a flexible, hermetic storage system made of polyethylene; they are available in a variety of sizes and can be used to store grains and their byproducts. Silo bags have gained extensive adoption as a hermetic storage solution in Argentina. Annually, this method is employed for the storage of roughly 50 million tonnes (Mt) of grain across various levels, including farms, grain elevators, industries, and even port facilities. Moreover, silo bags have gained recognition as a viable storage alternative in over 50 countries globally, ranging from cold climates like Canada and Russia to tropical regions such as Brazil and Colombia. In addition to the plastic bags themselves, the silo bag system involves other essential components, including bagging and extracting machines, as well as grain carts. These pieces of equipment have been specially designed with a high working capacity, enabling them to handle impressive volumes of 300–400 t per hour. Furthermore, silo bag monitoring systems have been developed based on CO2 concentration measurements and airtightness evaluations through a pressure decay test. In general, when dry grain is stored in silo bags, the CO2 levels range from 1% to 3%, while the O2 levels range from 18% to 16%. As the moisture content (MC) and temperature of the grain increase, the modification of the interstitial atmosphere becomes more pronounced, resulting in CO2 concentrations of up to 30% and O2 levels of 5% to 0% for moist grain. Few instances of insect presence in silo bags have been reported, with data analysis indicating that unfavorable environmental conditions hinder insect development. Nevertheless, suitable pest control strategies, based on phosphine fumigation and controlled atmospheres, have been successfully implemented. The quality of grains stored in silo bags is influenced by the interaction between MC and temperature. When the MC is sufficiently low to inhibit microbiological activity, the temperature itself has minimal impact, allowing for storage even during the summer without deterioration in quality. When the MC is sufficiently high to permit microbial activity, the deterioration of quality parameters during winter is mitigated by the synergistic of low temperature and the modified atmosphere. However, in spring and summer heightened microbial activity and other detrimental processes intensify, resulting in a decline in quality parameters that cannot be compensated for by the modified atmosphere alone.

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 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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.706
Threshold uncertainty score0.994

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0200.007

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 head0.013
GPT teacher head0.192
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2024
Admission routes1
Has abstractyes

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