Rheological profile of diets produced using agro-industrial wastes for rearing codling moth larvae for baculovirus biopesticides
Bibliographic record
Abstract
A rheological study of diets using the agro-industrial wastes (brewery wastewater and pomace waste) was carried out in order to obtain a diet most adapted to supply nutrients for growth of codling moth (CM) larvae. Nutritive capacity (g/L) of brewery wastewater (BWW) (25.5 ± 5.5 carbohydrates; 16.9 ± 2.1 proteins; 6 ± 1.6 lipids) and pomace waste (POM) (22.0 ± 0.03 carbohydrates; 11.3 ± 1.3 proteins; 2 ± 0.2 lipids) were essential and important as replacement or in association with other ingredients [soya flour (SF), wheat germ (WG), yeast extract (YE)] of the standard diet for the breeding of codling moth larvae. These diet additives also contributed to the preservation of texture and nutritive content of larvae diet. The eggs and CM larvae were grown on alternate diets under industrial conditions (16:8 h photoperiod; 25 ± 1 °C and 50 ± 0.5 % of humidity). The higher assimilation of nutrients of the diets in BWW and control diet was observed by calculating the rate of hatching of eggs (0.48 to 0.71); larvae growth (0.23 to 0.4) and fertility (1.33 to 3 for control diet). The excellent growth and fertility rates of codling moth larvae were attributed to variations in viscosity (varying from 50 to 266 mPa.s⁻¹), particle size (varying 24.3 μm in 88.05 μm with regard to 110 μm the control diet) and total solids (145.88 g/L POM + YE; 162.08 g/L BWW + YE; 162.2 g/L POM + WG; 173 g/L control; 174.3 g/L BWW + WG) diets. Lower viscosity favored improved diet due to ease of assimilation of nutrients. Thus, rheology is an important parameter during preparation of diets for growth of codling moth larvae as it will dictate the nutrient assimilation which is an important parameter of larvae growth.
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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".