Effects Of Different Diets On Digestive Enzyme Activities, Growth Performance, And Survival Rate Of Brandt’s Rice Crab Juvenile (Somanniathelphusa Germaini)
Bibliographic record
Abstract
Brandt’s Rice crab (Somanniathelphusa germaini) is a potential species for aquaculture in the Mekong delta. This study was conducted to determine appropriate diets for growth and survival of rice crab at juvenile stage. The experiment consisted of 5 treatments, all treatments were designed and set up randomly in triplicate in 0.25 m2 tanks. Five different types of feed were evaluated including (1) tubifex, (2) Artemia biomass, (3) tubifex + artificial feed, (4) Artemia biomass+ artificial feed and (5) artificial feed. Key digestive enzymes (trypsin, chymotrypsin, pepsin, lipase, and amylase) were measured. After 28 days of rearing, the results showed that water quality parameters were in appropriate range for crab performance. The digestive enzyme activities were fluctuated baseing on feed compositions, in which, trypsin, pepsin, lipase and amylase were important indicators. Crabs fed tubifex were recorded with the highest survival rate (80.0 %), growth performance (CW = 10 mm and W=0.3 g) and productivity (400 ind./m2), which were significantly higher than other treatments (p<0.05). Besides, the artificial feed was not suitable for crab rearing, leading to low growth and survival. The results suggested that tubifex could be applied for the husbandry practice of rice crab nursery.
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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".