Sustainable Valorization of Whey by Electroactivation Technology for <i>In Situ</i> Isomerization of Lactose into Lactulose: Comparison between Electroactivation and Chemical Processes at Equivalent Solution Alkalinity
Bibliographic record
Abstract
The demand for production of prebiotics at a commercial scale is rising due to the consumers’ growing health awareness. Whey, a coproduct of the dairy industries, is a suitable feed medium to produce a prebiotic lactulose through the isomerization of lactose under alkaline conditions. The aim of the present study was to compare the isomerization of lactose into lactulose in situ of whey by using electroactivation technology with the chemical isomerization method using KOH as catalysis under equivalent solution alkalinity. Electroisomerization of lactose into lactulose was performed by using whey solutions of 7, 14, and 21% (w/v) dry matter under current intensities of 300, 600, and 900 mA, respectively, during 60 min with a sampling interval of 5 min. The conventional chemical method was carried out using KOH powder as catalyst at the alkalinity that corresponded to that measured in the electroactivated whey at each 5 min interval. The results showed that lactulose production was dependent on the whey concentration, current intensity, and EA time. The highest lactulose yield of 32% was achieved under a 900 mA current intensity at 60 min for a 7% whey solution. Thereafter, the EA conditions were compared to those of a conventional chemical isomerization process by maintaining similar alkalinity in the feed solutions. However, no lactulose was produced by the chemical process for the equivalent solution alkalinity as in the EA technique. These results were correlated with the solution pH, which reached the required values in a 7% whey solution with values of up to pH 11.50, whereas the maximum pH values that were obtained at higher whey concentrations were around 10–10.50, which was not enough to initiate the lactose isomerization reaction. The outcomes of this study suggest that EA is an efficient technology to produce lactulose using whey lactose.
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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 | 0.001 |
| 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) | 0.000 | 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".