Bioprocessing of underutilized Artocarpus altilis fruit to bioethanol by Saccharomyces cerevisiae: A fermentation condition improvement study
Bibliographic record
Abstract
Raw materials availability needed for commercial bioethanol production is one of the challenges against its global adoption. Identifying rich, cheap, underused, and readily available starch sources for bioethanol production could help address the problem. Thus, this current study investigated the bioconversion of underutilized Artocarpus altilis (breadfruit) starch to bioethanol using Saccharomyces cerevisiae. The effects of the essential fermentation conditions (fermentation time, breadfruit starch hydrolysate (BSH) concentration, pH, and inoculum size) and their interactions on bioethanol production were investigated. The central composite design was used to generate twenty-one experiments conducted under batch fermentation conditions in the laboratory. The breadfruit starch hydrolysis led to a BSH concentration of 108.9 g/L under a starch concentration of 122 g/L, microwave output of 720 W, and an incubation time of 6 min. For the fermentation of BSH, maximum bioethanol production of 4.99% (V) was reached under the cultivation conditions of BSH concentration of 80 g/L, medium pH of 4.7, inoculum size of 2% (V), and fermentation time of 20.41 h. Except for pH, the impact of each parameter on the bioethanol production was in this order: BSH concentration, inoculum size, and fermentation time. While for the interactions amongst the parameters, the impact is in this order: BSH concentration and inoculum size; BSH concentration and fermentation time; and fermentation time and inoculum size. The results of this study indicated breadfruit starch could be hydrolyzed using acid hydrolysis and microwave irradiation in a relatively short time. The BSH obtained could potentially add to other substrates for bioethanol production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".