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Harnessing Solar Energy: A Novel Hybrid Solar Dryer for Efficient Fish Waste Processing

2023· article· en· W4389919760 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

VenueAgriEngineering · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSolar dryerRenewable energyEnvironmental scienceWater contentFood wasteSolar energyFish <Actinopterygii>MoistureWaste managementPulp and paper industryMaterials scienceEngineeringEcologyBiologyComposite materialFishery

Abstract

fetched live from OpenAlex

Facing severe climate change, preserving the environment, and promoting sustainable development necessitate innovative global solutions such as waste recycling, extracting value-added by-products, and transitioning from traditional to renewable energy sources. Accordingly, this study aims to repurpose fish waste into valuable, nutritionally rich products and extract essential chemical compounds such as proteins and oils using a newly developed hybrid solar dryer (HSD). This proposed HSD aims to produce thermal energy for drying fish waste through the combined use of solar collectors and solar panels. The HSD, primarily composed of a solar collector, drying chamber, auxiliary heating system, solar panels, battery, pump, heating tank, control panel, and charging unit, has been designed for the effective drying of fish waste. We subjected the fish waste samples to controlled drying at three distinct temperatures: 45, 50, and 55 °C. The results indicated a reduction in moisture content from 75.2% to 24.8% within drying times of 10, 7, and 5 h, respectively, at these temperatures. Moreover, maximum drying rates of 1.10, 1.22, and 1.41 kgH2O/kg dry material/h were recorded at 45, 50, and 55 °C, respectively. Remarkable energy efficiency was also observed in the HSD’s operation, with savings of 79.2%, 75.8%, and 62.2% at each respective temperature. Notably, with an increase in drying temperature, the microbial load, crude lipid, and moisture content decreased, while the crude protein and ash content increased. The outcomes of this study indicate that the practical, solar-powered HSD can recycle fish waste, enhance its value, and reduce the carbon footprint of processing operations. This sustainable approach, underpinned by renewable energy, offers significant environmental preservation and a reduction in fossil fuel reliance for industrial operations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.364

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)0.0000.000

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 head0.022
GPT teacher head0.206
Teacher spread0.184 · 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