Wet Fractionation Approaches For Isolating Pulse Proteins And Their Modification Through pH Shifting
Bibliographic record
Abstract
Plant protein extraction involves separating proteins from other plant materials. The extracted proteins are then used in various food and non-food applications depending on their nutritional and functional properties. In the case of food ingredients, markets require consistent and reliable protein ingredients. Pulses are high in proteins, and their extracted proteins exhibit good functionality when used as ingredients, such as foaming or emulsifying agents. However, the processing conditions to which the proteins are subject can impact the protein structure and affect their functionality. The overarching goal of this study was to investigate the impact of extraction conditions, such as flour to water ratio (f:w), particle size of the starting flours and the use of different extraction methods, on the surface and functional properties of four different pulses: yellow peas (YP), green lentils (GL), kabuli chickpeas (CH) and navy beans (NB). Additionally, the effect of a pH shifting method was investigated on a commercial pea protein as a model for a pulse protein, with the aim of enhancing pulse protein solubility, foaming and emulsifying properties.\nThe first study (Chapter 3) examined the effect of reducing water levels used during alkaline extraction, where three different flour:water ratios were tested (1:10, which is the most commonly used ratio, 1:7 and 1:5) on fine pulse flours (sieved through a 0.5 mm mesh size screen, P1) and the resulting extraction, protein yields, and functionality were assessed. The results showed that reducing the water levels used in the extraction process did not result in changes in functionality; however, it led to a significant decrease in the protein yields recovered. Due to these protein losses, a 1:10 f:w ratio was selected to perform extractions with a coarse flour (1.27 mm mesh size screen, P2) to assess extraction yields as well as functionality. Results showed that using a fine flour led to an increase in both extraction (0.4 to 3.2 % increase) and protein yields (7.9 to 10.3 % increase). In terms of the functional properties, P1 and P2 extracted proteins differed in some functional properties, but these differences were not consistent for all the pulses evaluated. Determination of the legumin (L) and vicilin (V) ratios of the pulse types evaluated led to finding differences in functionality between the different pulse types tested: NB exhibited the highest solubility and emulsifying properties, while CH showed the highest foaming capacity (FC). This study highlights the impact of milling and control of the particle size of the starting flours on the extraction of pulse proteins.\nThe second study (Chapter 4) focused on the effect of using different extraction methods, alkaline extraction – isoelectric precipitation - AEIP and salt extraction- SE, on the surface, functional and nutritional properties of protein isolates extracted from the same pulses tested in the first study. The optimum conditions found in the first study were used in this study as well since the 1:10 f:w ratio and P1 flours achieved the highest yields. Results showed that the extraction method influences the type of proteins being extracted, impacting the albumin (A)/ globulin (G) ratios. The SE-extracted proteins extracted a greater proportion of albumins than the AEIP method, and these differences in protein composition had an effect on the nutritional properties as well as on protein functionality, impacting protein solubility, foaming and emulsifying properties. The proteins extracted using an AEIP method showed increased in-vitro protein digestibility (IVPD), while the SE proteins showed overall increased functionality over the AEIP proteins.\nThe last study (Chapter 5) explored the effect of acid (pH 2) and alkaline (pH 10) pH shifting in combination with temperature on a commercial pea protein isolate as a modification method to improve the protein’s solubility, foaming and emulsifying properties. Results from this study indicated that an alkaline pH shifting, as well as in combination with heat, led to increases in protein solubility, while an acidic treatment as well as in combination with heat negatively impacted this functional property. The FC of the samples was increased by an alkaline pH shifting, while FS results were either neutral or negatively impacted by the treated samples. An analysis of the foam structure using a dynamic foam analyzer (DFA) allowed us to explore differences and to monitor the bubble structure of the resulting foams.\nOverall, this research explored the effects of protein extraction methods and conditions on the resulting functionality and nutritional properties of common pulses grown in Canada. Knowledge from these studies can provide further understanding on the impact of changes in protein structure during processing and aid in obtaining consistent ingredients with the expected functionality for food applications.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".