Chemical Characterization and Acceptability of Eight Cassava Varieties Introduced in Rwanda
Bibliographic record
Abstract
Cassava is a staple food and an important and cheap source of carbohydrate in Rwanda. However, the nature and chemical composition of cassava roots limit its proper use as food due to its toxicity and short shelf life. The cyanogenic glucosides found in the cassava roots are responsible for the toxicity. The aim of the study was to characterize the chemical profile and consumer acceptability of paste from eight cassava varieties processed into flour using four processing methods. The cassava samples were harvested from trials conducted at Rubona Station of Rwanda Agriculture and Animal Resources Development Board. Four processing methods were used, namely, Cassava grated fermented, Cassava roots fermented, Cassava grated no fermented and Cassava roots no fermented. Pressing was done before drying the products to obtain the flour. At each stage of processing, the samples were prepared for laboratory analysis of dry mater, titratable acidity, cyanhydric acid and crude fiber by Rwanda Standards Board laboratory. Cassava flour was made into paste and sensory evaluation was conducted to evaluate the acceptability of the eight cassava varieties. The sensory attributes for the Ugali tested was significantly different (P<0.05). The method of grating before fermentation gave the most tasty Ugali than cassava root fermented. The more prefered varieties were GAHENE/2 and SEMAK 150/452 followed by BULK 13, MH95/0091 and NASE 14. The chemical analysis done for the 8 cassava varieties flour from the 4 processing methods exhibited the acceptable acidity and the NASE 14, Gahene/2 and Bulk 13 had the lowest cyanide hydrogen.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".