Preliminary microbiological and chemical characterisation of edible goat’s rennet, a unique product of Sardinian food tradition
Bibliographic record
Abstract
The edible goat rennet (EGR) namely Caggiu de crabittu, is a traditional Sardinian foodstuff deriving from the stomach of a weaned (breastfed) kid whose edible part is represented by the milk coagulated inside the abomasum that, before consumption, is subjected to a suitable ripening time. In this study, a preliminary investigation into the microbiological characteristics and physicochemical parameters of different EGRs manufactured by distinct Sardinian farms was conducted. Results showed that the edible goat rennet was free of spoilage/pathogenic bacteria and was characterised by a significant presence (6–7 log cfu/g) of mesophilic lactic acid bacteria (i.e. Lactococcus lactis, Lactobacillus plantarum, Lactobacillus paracasei, Lactobacillus brevis) and Enterococci. Oleic, linolenic, palmitic and myristic acids were the most abundant free fatty acids (FFA) in all samples, while both caprylic and butyric acid contents resulted the lowest. Long chain FFA (≥C18:0) represented about 50% of total FFA. Among the polyunsaturated FFA, high content of linoleic (C18:2n-6) and alpha-linolenic (C18:3n-3) acids have been detected. In this study, EGR is shown to be microbiologically safe, with a high number of live lactic bacteria and an FFA content that is attractive from a nutritional point of view.HighlightsEdible goat’s rennet (EGR) resulted microbiologically safe with a high number of viable mesophilic lactic acid bacteria.In the EGR an intense process of lipolysis has occurred.EGR had a high content of linolenic acid.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".