Using Date Palm (Phoenix dactylifera L.) by-products to Cultivate Lactobacillus reuteri spp.
Bibliographic record
Abstract
Lactic acid bacteria (LAB) are used by industry to produce fermented food products. The standard media used to cultivate LABs is DeMan Rogosa Sharp (MRS). However, it is expensive. Alternative low-cost media must be developed for industrial use. A good source for growth media components are by-products generated during the production of agricultural goods, such as dates. Our objective was to investigate the use of date by-products for cultivating Lactobacillus reuteri. Date palm extract (DPE) was prepared by pressing fresh date fruits for one week and diluting 1:2 with diH2O, centrifuging at 4696 x g and 4°C 25 min, and autoclaving the supernatant at 110°C for 15 min. An MRS-based buffer solution was added to DPE make a date palm medium (DPM). DPM was then enriched with various amounts phytone peptone (0, 0.2, 0.4, 0.6, and 0.8 %, w/v). The enriched DPMs were used to cultivate three strains of Lactobacillus reuteri: DSM 20016, CF2-7F, and SD 2112. Our results showed that in the DPM minus phytone peptone, bacterial counts reached 3.18 ± 0.5 log CFU/mL. Addition of lower amounts of phytone peptone did not improve bacterial growth. However, DPM medium supplemented with 0.8% phytone peptone improved the bacterial counts, which reached 6.94 ± 0.1 log CFU/mL, similar to what was observed with MRS (7.90± 0.24 log CFU/mL). There was no significant difference in the growth of LAB in MRS and phytone peptone enriched media DPM (p > 0.05). Date by-products are potentially alternative low cost components of LAB growth media.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".