Effect of variety and malting conditions on proteolytic activity, free amino nitrogen, and soluble protein contents of two maize varieties (Atp-Y and Coca-sr): amylolytic activity and physico-chemical and functional properties of optimal sample
Bibliographic record
Abstract
Introduction The utilization of sprouted meals in beer production and enhancing the physicochemical properties of supplementary foods is widespread in Africa. This work aimed to determine the influence of soaking, germination, maturation and variety conditions on the physicochemical properties, proteolytic activity, free amino nitrogen (FAN) and soluble protein contents of Coca-sr and Atp-Y maize varieties. Methods To achieve this, the central composite design (CCD) was used for the optimization of five parameters, namely soaking time (18–42 h), plant salt concentration (0.5–1.2%), soaking temperature (25–41°C), sprouting time (80–195 h) and ripening time (17.50–42 h), and following dependent variables were investigated: proteolytic activity, FAN content and soluble protein. Optimal samples flours obtained were then subsequently subjected to physicochemical and functional analysis. Results The analysis of results showed that the linear, interactive and quadratic effects of the factors significantly ( p <0.05) affected the proteolytic activity, FAN and soluble protein contents of both varieties. The direction of each factor's variation and its effects were not similar in the two varieties. The optimal malting conditions were 7.31 h soaking with 1.678% vegetable salt at a temperature of 34.65°C followed by sprouting for 245.59 h and maturation for 0.765 h for the Atp-Y variety. For the Coca-sr variety, it requires 1.608 h of soaking with 1.678% vegetable salt at a temperature of 51.93°C followed by 273.94 h and 58.73 h for sprouting and ripening time respectively. The meals of Coca-sr produces using these optimal conditions showed a significantly ( p <0.05) higher proteolytic activity, FAN and soluble protein content. The amylolytic activity was more pronounced in the Atp-Y variety, as was the content of essential amino acids. The above optimal conditions reduced the content of anti-nutrients (phytates, saponins, oxalates, condensed and hydrolysable tannins), improved the availability of minerals (Ca and Mg), reduced the pH, mass density, water retention capacity and swelling rate. Conclusion As a result, the optimal flours of these two maize varieties could be applied in the formulation of supplementary foods, bakery products and beer by industrialists.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".