“Investigation On the Utilization of Horse Manure Extract as an Additive in the Growth Of Spirulina Sp”
Bibliographic record
Abstract
This study attempts to evaluate the feasibility of using horse manure as a cost-effective alternative nutrient source for microalgae cultivation. By harnessing its abundant minerals and cost-effectiveness, this study seeks to reduce expenses associated with nutrient mediums, ultimately enhancing the economic appeal of microalgae-derived products for commercial use. The horse manure obtained from the stables was sun-dried and then ground into a powder using a mixer grinder. To obtain horse manure extract, 10 g of powdered manure is mixed with 200 ml of water and boiled in a water bath for 30 minutes. In the cultivation process of Spirulina sp, horse manure extract supplements were introduced at different concentrations (0.2ml, 1ml, 2ml, 3ml, 4ml) into the indoor modified growth medium. A control group was included, utilizing an indoor modified growth medium without any addition of horse manure extract supplement. The research focused on exploring the effects of various concentrations of horse manure extract on indoor Spirulina cultivation, showing encouraging results. Using a 4ml/200ml concentration of horse manure extract led to Spirulina exhibiting a dry weight of 0.098±0.0015 g, a specific growth rate of 0.0051±0.00009, and a density of 0.0138±0.00003. Moreover, when subjected to a concentration of 0.2 ml/200 ml, Spirulina demonstrated 5.322±0.011 µg/l of carotenoids. Chlorophyll a, b, and c were detected in Spirulina across a range of horse manure extract concentrations, namely 1ml/200ml (9.770±0.018 mg/L), 3ml/200ml (3.176±0.010 mg/L), and (0.805±0.031 mg/L). These levels of chlorophyll were notably higher compared to the control medium in indoor culture settings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".