Bibliographic record
Abstract
Pulses are high in nutritional value but are underutilized as foods due to their undesirable flavor attributes. These include bitterness, which may in part due to their saponin content. In this research, a simple and rapid method using high-performance liquid chromatography-mass spectrometry (HPLC-MS) and requiring the minimum sample preparation was developed for the identification and quantification of saponins. This was applied to 8 common Canadian pulses including 3 pea varieties, 4 faba bean varieties, pinto beans, black bean, kidney beans, chickpeas, and green and red lentils. The method was validated according to linearity, accuracy, detection limit, quantification limit, inter- and intra-day precision. Saponin composition and content varies depending on the pulse type and variety. Four types of group B saponins including DDMP-conjugated soyasaponin g and g, and non- DDMP-conjugated soyasaponin Bb and Ba were identified in several pulse samples by HPLC-MS according to their relative retention times, and their molecular and fragment ions, as compared to standards and literature. All pulses tested contained soyasaponin Bb and g with different amounts and percentile distribution. Amongst all 8 types of pulses, the total saponin content ranged from 30 to 8566 g/g, where the lowest saponin content was found in faba bean variety Fabelle and the highest saponin content was found in black beans. Within the 3 pea varieties, the total saponin content varied from 550 to 2144 g/g, and for the 4 faba bean varieties tested it varied between 30 and 388 g/g. In all pulse samples, either soyasaponin Bb or g was the predominant saponin type. Soyasaponin Ba and g was only present in small amounts, except for black beans and pinto beans where 3145 and 1306 g/g of g was found, respectively. The effects of pulse processing methods (sprouting, drying, baking and pressure cooking) on the saponin profile was investigated. Four cultivars of faba beans were germinated and subjected to a range of sprouting times (0, 48, 54, 60, and 72 h and drying times (0, 24, 36, 48, and 60 h). The saponin profiles of raw and sprouted faba bean seeds were measured, along with those found in baked faba bean flour-based crackers. Soyasaponin Bb and βg were the only two types of saponin found in the faba bean varieties studied. Soyasaponin Bb reaches the highest abundance after 54 h of sprouting in most cultivars, whereas the highest for βg was observed at 60 h in most cases, except for FB9-4 (54 h). A significant reduction of soyasaponin Bb was observed after 24 h of drying the sprouted seeds at 60C. The total saponin content after 72 h of sprouting significantly increased in Snowdrop and Fabelle, decreased in FB9-4 and no change in Snowbird compared to unsprouted seeds. Prolonged drying times of up to 60 h significantly reduced the soyasaponin Bb content of 48 hours sprouted faba beans, whereas a slight increase was observed in the soyasaponin βg content in Snowdrop and Fabelle. Regardless of the sprouting condition, both baking and cooking of faba bean flour led to significant reductions in both total saponin and individual saponin content. In addition, the combination of sprouting and pressure cooking is more effective in reducing saponin content in faba bean comparing to pressure cooking alone. The present research into the saponin profile of pulses and how this is changed by common food processing methods, contributes fundamental knowledge which may be beneficial in the utilization of pulses and pulse flour in food.
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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 | 0.002 |
| 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) | 0.001 | 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".