Techno-Economic Analysis of the Multiple-Pass Ultrasonication with Mechanical Homogenization (MPUMH) Processing of Processed Carrot Discards to Puree
Bibliographic record
Abstract
A sustainable valorization process for puree processing from processed carrot discards (PDCs) was proposed by using multiple-pass ultrasonication with mechanical homogenization (MPUMH), optimized at 9 min ultrasonication followed by mechanical homogenization for 1 min, subjected to three passes. Techno-economic analysis of the puree processing plant was studied for two process models using SuperPro Designer for a plant with a capacity of 17.4 MT/day, operational for 26 weeks, with a 20-year lifetime. The two scenarios were (i) base case (PDCs processed without peels and crowns) and (ii) case 2 (PDCs and carrots (50:50, w/w) processed with peels and crowns). Both scenarios were economically feasible with an internal rate of return (IRR) and return on investment (ROI) at 24.71% and 31.04% (base case) and 86.11% and 119.87% (case 2), respectively. Case 2 had a higher total capital investment (Can$13.7 million) but a lower annual operating cost (Can$8.9 million), resulting in greater revenue generation (Can$29.7 million), thus offering a higher ROI. Sensitivity analysis related to the number of passes on puree quality and price is suggested to lower the capital investment. For the base case, a lower ROI was due to the high labor cost incurred for manual peeling of PDCs, indicating the critical need for developing a commercial peeler equipped to cut labor costs and increase profitability. The study casts insights into the techno-economic performance of a sustainable process for the valorization of PDCs.
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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 | 0.002 |
| 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".