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Record W112646780 · doi:10.3844/ajbbsp.2012.128.142

KINETICS OF THIN LAYER DRYING OF POULTRY MANURE

2012· article· en· W112646780 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican journal of biochemistry & biotechnology/American journal of biochemistry and biotechnology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsManureEnvironmental scienceWater contentMoistureAgronomyManure managementMaterials scienceBiology

Abstract

fetched live from OpenAlex

The poultry industry is one of the largest and fastest growing sectors of livestock production in the world. The estimated 2010 world flock was over 18 billion birds with a yearly manure output of 22 million tonnes. Storage and disposal of raw poultry manure has become an environmental problem because of the associated air, water and soil pollution. Environmental and health problems such as odor and pathogens that may arise during and after land application of raw manure can be eliminated by drying. Dried manure can be utilized as a soil conditioner to improve soil tilth and reduce the problems associated with soil compaction and as a feed for ruminants because of its high nitrogen content. The aim of this study was to investigate the kinetics of thin layer drying of poultry manure and evaluate the effects of drying with heated air on the chemical and biological properties of manure. The effects of temperature and depth of manure layer were evaluated. The profile of the moisture content of poultry manure followed an exponential decay curve. The moisture decay constant was affected by the drying temperature and the depth of the manure layer. At the three temperature levels studied, the time required to dry poultry manure in 1 cm-deep layer was the least, followed by 2 and 3 cm-deep layers, respectively. The diffusion coefficient increased with both temperature and depth of drying layer, but did not show a linear increase with either variable. The optimum depth for drying manure (at which the highest drying effectiveness occurred) was 3 cm. Drying manure at 40-60C resulted in the loss of 44-55% of the total Kjeldahl nitrogen, with losses increasing with both the temperature and depth of manure. The pH of the manure decreased from the initial value of 8.4 before drying to about 6.6 after drying. The odor analysis indicated that dried poultry manure did not have an offensive odor. Drying achieved 65.3 and 69.3% reductions in odor intensity and offensiveness, respectively. Reductions in the number of bacteria, mold/yeast and E.coli were 65-99, 74-99 and 99.97% respectively. The greatest reductions in microbial population occurred at the highest temperatures (60C) and the thinest manure depths (1 cm). Heated air drying of poultry manure at temperatures between 40 and 60C was effective in killing pathogens and removing odor.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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