Development and Process Optimization of a Novel Method (Multiple-pass Ultrasonication with Mechanical Homogenization) for Processing Puree from Carrot Rejects
Bibliographic record
Abstract
Carrots (Daucus carota. L) are among the top five vegetables grown in Canada. In 2020, 386,486 MT of carrots were produced worth $131.783 M. It is estimated that 20-30% of the total production is removed as carrot rejects and waste (CRW) during primary processing. These are either anaerobically digested for biogas production or utilized for animal feed with the remaining being sent to landfills releasing methane and causing a detrimental effect on the environment. Since CRW are generated from carrots, rich in nutrients, they potentially have a high valorization potential. A part of the research study deals with the assessment of CRW for their use as a biofuel, extraction of beta-carotene and food product development. Studies are documented on the utilization of CRW as biofuel and extraction of bioactive compounds but limited to no studies are reported on their usage in product development. A research gap was identified, emphasizing the need for the assessment of raw material, accounting for its variability and the potential hurdles for its utilization in food processing. Carrot puree was considered a potential product, since it could be sold commercially, both as a product and as an ingredient in the food industry. The conventional carrot puree processing methods involve multiple unit operations, longer processing time, high energy consumption and significant loss of naturally present bioactive components. This study was focused on the development and optimization of the novel method “Multiple-pass ultrasonication and mechanical homogenization” (MPUMH) for the processing of carrot puree. The optimized experimental conditions were used for processing processed carrot discards (PCD’s) to puree and the developed product was evaluated for its physicochemical and nutraceutical properties. MPUMH process is energy efficient, capable of handling non-uniformity in the raw material and allows significant retention of bioactive components in carrot puree. A proof-of-concept suggests that there is a valorization potential of CRW to carrot puree. However, before making efforts for scale-up, the techno-economic analysis (TEA) of the process was performed to understand the commercial feasibility and economic competitiveness of this process. The preliminary study is showing encouraging results and should be considered for pilot-scale processing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".