Effect of barrel temperature and feed moisture on the physical properties of chickpea–sorghum and chickpea–maize extrudates, and the functionality and nutritional value of their resultant flours—Part II
Bibliographic record
Abstract
Abstract Background and objectives The effect of barrel temperature (120 and 150°C, held constant in zones 4–6) and feed moisture (20% and 24%) on the physical properties of chickpea–sorghum (CS) and chickpea–maize (CM) extrudates, and the functional and nutritional properties (protein quality) of their flours were examined. Findings Temperature had a greater effect on the physical properties than moisture for both blends, where, in general, extrusion at 150°C resulted in greater expansion, less hardness, and lower bulk density than at 120°C. Extrusion also increased the water‐holding capacity relative to the raw CS and CM blends, but had an adverse effect on oil‐holding capacity, foaming, and emulsifying properties. Pasting viscosities of precooked flours were also lowered by 8 to 37 times due to the pregelatinization of the starch. Although in vitro protein digestibility increased after extrusion, the in vitro protein digestibility‐corrected amino acid score (PDCAAS) showed an overall reduction relative to the raw blended flours due to the reduction of the primary limiting amino acid lysine during extrusion. Conclusions Only the chickpea–maize blend extruded at 120°C at either 20% or 24% moisture had higher in vitro PDCAAS than the raw blend, with only the one with 24% moisture having a value >0.70. Significance and novelty A balance between functionality and protein quality needs to be considered when using extruded pulse–cereal blends.
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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 | 0.000 | 0.001 |
| 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".