Compositional Profiling for the Quality Assessment of Canadian Honeys and Their Biotransformation into Functional Sweeteners
Bibliographic record
Abstract
Honey has been cherished for centuries as a natural sweetener and continues to hold a significant place in the food industry due to its unique taste, nutritional properties, and health benefits.With monofloral honeys attracting increased consumer attention, there is a growing need to develop novel methods for authenticating honeys.It is crucial not only to detect adulteration, such as the addition of syrups, but also to identify the botanical origins of honey, which has become an industrial demand.The most widely adopted technique for authenticating floral type is pollen analysis, which is highly sophisticated.Recent advances in honey authentication methods have primarily focused on identifying biomarkers, such as phenolic compounds.However, previous studies have suggested that both the carbohydrate composition and enzymes in honey have correlations with its botanical sources.Few studies have been conducted on the authentication of Canadian honeys, and no comprehensive profiling for sugars and enzymes were established.Therefore, this study aims to provide insight into the sugar and enzyme composition of four types of monofloral honey commonly found in the Canadian market.The first objective was to conduct the carbohydrate and enzymatic profiling of 163 selected Canadian monofloral honeys, namely buckwheat, clover, blueberry, and goldenrod, and to establish a robust authentication method for botanical origin differentiation, while focusing on identifying potential biomarkers.The activities of five enzymes, namely diastase, invertase, acid phosphatase, glucose oxidase, and catalase, were examined.2 monosaccharides (fructose and glucose), 6 disaccharides (trehalose, isomaltose, sucrose, maltose, nigerose, and gentiobiose), and 1 trisaccharide (erlose) were successfully identified and quantified among all honey samples using high performance anion exchange chromatography with pulse amperometric detection (HPAEC-PAD) and liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC/MS-QToF).Results showed the average enzymatic activity and sugar content varies across the four floral types.Multivariate analysis revealed the potentiality of acid phosphatase and catalase activities as markers for identifying botanical sources.Statistically significant (p<0.0001)negative correlations were observed between glucose content and Isomaltose, gentiobiose, or nigerose content, and between 5-hydroxymethylfurfural (HMF) content and diastase or invertase activities.Additionally, prediction models were generated based on the variables quantified with accuracy scores varing between 80-90%.Agreeing with the previous results, the model suggested
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".