Development and Physicochemical, Sensory and Microbiological Characterization of Ferment Milk With Addition of Cupuaçu
Bibliographic record
Abstract
The development of dairy products using probiotic microorganisms has been an important focus in the food industry. Thus, the present study aimed to evaluate the physicochemical, sensory and microbiological quality of fermented milk with addition of cupuaçu (Theobroma grandiflorum) flavor. The experimental design used was completely randomized, with five replicates, arranged in a 4 × 2 × 2 factorial scheme, consisting of fermented milk with addition of four different strains of probiotic bacteria (Lactobacillus casei shirota, Lactobacillus casei, Lactobacillus acidophilus and Lactobacillus paracasei), presence and absence of cupuaçu flavor, and two evaluation times (1 and 7 days of storage). The results allowed us to conclude that the bacterial strain B (Lactobacillus casei) led to higher values of L*, b*, %Brix and pH. In the presence of cupuaçu flavor, the values of pH, L*, b* and %Brix were significantly higher, which allows us to infer that cupuaçu pulp contributes to decreasing the values of pH and increasing the acidity, lightness, b* and %Brix of fermented milk. Fermented milk with addition of bacteria A (Lactobacillus casei shirota) in the presence of cupuaçu flavor showed reduction in pH and %Brix and, therefore, better acceptance by consumers and bioconservation. The presence of cupuaçu flavor in fermented milk with bacteria B (Lactobacillus casei) alters L* and b* at seven days of storage. Fermented milk with addition of cupuaçu flavor constitutes an opportunity and possibility for developing new flavors from Amazonian fruits, strongly contributing to the durability of dairy products, since the physicochemical, sensory and microbiological characteristics are enhanced within the standards of food safety.
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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 | 0.001 |
| 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) | 0.000 | 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".