Apparent digestibility of different microalgae dried biomass in rainbow trout (Oncorhynchus mykiss)
Bibliographic record
Abstract
Despite a growing interest in microalgae as sustainable sources of nutrients in complete aquafeeds, little information is presently available on the nutritive value of these novel potential feed ingredients for carnivorous fish species. The aim of this study was to estimate energy and the apparent macronutrient digestibility of a panel of cultivated microalgae, using rainbow trout as a fish model. From a basal reference diet mash, 8 test diets were obtained including finely ground dried biomass of Arthrospira platensis (ART), Chlorella sorokiniana (CHL), Nannochloropsis oceanic (NAN), Nostoc sphaeroides (NOS), Tisochrysis lutea (TISO), Phaeodactylum tricornutum (PHAE), Porphyridium purpureum (POR) and Tetraselmis suecica (TETR) at a 12:88 w:w microalgae to reference diet ratio. All diets were added with acid insoluble ash (1.0%) as an inert marker before being extruded and dried into 3mm pellet. The apparent digestibility coefficients (ADCs) of dry matter, protein, organic matter and energy for reference and test diets were estimated in vivo with juvenile rainbow trout using 9 units of three 50-L tanks, each stocked with 15 fish (52.4 ± 1.5 g), fitted with a settling column for fecal collection (Guelph system). Each diet, offered to visual satiety in two daily meals, was evaluated over three independent 10-day fecal collection periods preceded by 7 days adaptation to a new diet. ADCs were calculated by difference relative to those measured with the reference diet. The various microalgal biomasses showed significantly different apparent digestibility values (p<.05). Dry matter ADCs ranged from 90.4% for TISO to 53.3% for CHL. Protein ADCs varied from 94.4% for POR to 63.9% for CHL. Organic matter ADCs ranged from 94.6 for TISO to 58.3% for CHL while gross energy ADCs varied from 93.7 for POR to 53.1% for NAN. The results obtained here using the rainbow trout as a carnivorous fish model for digestibility, provide a useful indication of the nutritive value of different microalgae to assist in the formulation of environmental friendly fish diets. They also showed that, due to poor digestibility of certain microalgae biomass, just a few of them can tackle the sustainability challenge of the aquafeed industry as a potential and cost-effective source of nutrients and the adoption of suitable physical or enzymatic rupture treatments in some species will be needed to improve their digestibility.
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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) | 0.000 | 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 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".