Effect of Particle Size on the Kinetic Parameters of the Deproteinization Process of Galactose Supplemented Shrimp Shells by Aspergillus niger
Bibliographic record
Abstract
The aim of the research was to evaluate the ability of the fungus Aspergillus niger to carry out the deproteinization of shrimp shells supplemented with galactose as a carbon source and study the effect of the particle size of the shrimp shells on the kinetic parameters of the deproteinization process. Grounding of the shells resulted in a higher specific growth rate of A. niger and enhanced protease production by 2.6 fold. The temperatures of the shrimp shells and exhaust gas declined at the beginning as the heat losses from the bioreactor (due to evaporation) were higher than the heat generated by the metabolic activity. After 24h, the temperature of the shrimp shells and exhaust gas started to rise as a result of increased metabolic activity. Temperature peaks of 38.3 °C and 37.8 °C for the shrimp shells and 29.1 oC and 29.0 oC for the exhaust gas were noticed after 60 and 72 h of deproteinization for the ground and intact shrimp shells, respectively. There were no temperature gradients in the radial or axial direction because of mixing. The pH first decreased with time due to production of acid protease and then increased due to the buffering capacity of the calcium carbonate released from shrimp shells and the production of ammonium nitrogen. A significant reduction in the moisture content was noticed during the deproteinization process. In order to maintain the moisture in the bioreactor at the desired level, the exhaust gas should be passed through a condensation tower and the recovered water be pumped back into the bioreactor through the aeration tube. The galactose concentration decreased with time and the rate of galactose utilization was significantly higher in case of ground shrimp shells. Size reduction results in higher surface area and shorter pathways for nutrients diffusion. The protein removal efficiency (30.45% - 33.23%) did not correspond to the protease production. This could be a result of unsuitable pH and temperature conditions for the hydrolysis of shells proteins. The chitin concentration increased over time from the initial value of 16.59 % to final values of 21.99 %and 22.68% for the intact and ground shells, respectively. The color of the intact and ground shells was pale pink-orange with some tan patches. Some of the ground shrimp shells agglomerated and formed small balls. This problem was not observed with the intact shells. The ground shells had more white precipitants which were believed to be a result of break down of substances from the shell matrix.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".