Neural Network for AI-Driven Prediction of Larval Protein Yield: Establishing the Protein Conversion Index (PCI) for Sustainable Insect Farming

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 652 - 652

Published: Jan. 16, 2025

The predictive capabilities of artificial intelligence for predicting protein yield from larval biomass present valuable advancements sustainable insect farming, an increasingly relevant alternative source. This study develops a neural network model to predict conversion efficiency based on the nutritional composition feed. utilizes structured two-layer with four neurons in each hidden layer and one output neuron, employing logistic sigmoid functions layers linear function layer. Training is performed via Bayesian regularization backpropagation minimize mean squared error, resulting high regression coefficient (R = 0.9973) low mean-squared error (MSE 0.0072401), confirming precision estimating yields. AI-driven approach serves as robust tool yields, enhancing resource promoting sustainability insect-based production.

Language: Английский

Evaluating the Influence of Nutrient-Rich Substrates on the Growth and Waste Reduction Efficiency of Black Soldier Fly Larvae

Sustainability, Journal Year: 2024, Volume and Issue: 16(22), P. 9730 - 9730

Published: Nov. 8, 2024

Background: The black soldier fly (Hermetia illucens) has emerged as a promising tool in sustainable waste management, owing to its larvae’s ability efficiently convert organic into valuable biomass. Objective: This study investigates the impact of various substrate compositions on growth, reduction efficiency, and bioconversion rate (BSF) larvae illucens). aim is optimize feeding strategies enhance effectiveness BSF management protein production. Methods: A controlled experiment was conducted over 20-day period, using four different types: 100% sludge, 75% sludge + 25% chicken feed, feed. Each treatment had three replicates with 100 each. Larval growth metrics, including weight width, were recorded bi-daily. efficiency calculated based remaining larval biomass, respectively. Elemental analysis performed determine type accumulation elements larvae. Results: Significant differences observed rates across substrates. feed led highest (M = 0.0881 g/day, SD 0.0042) 7.52%, 0.34), while achieved 86.2%, 2.15). ANOVA tests indicated that composition significantly affected these outcomes (p < 0.05). showed substantial variations concentrations calcium, cadmium, nickel among substrates, having 0.2763 ppm, 0.023), from other treatments 0.001). Conclusions: results demonstrate crucial for optimizing efficiency. Nutrient-rich such biomass production, although careful consideration elemental accumulation, especially heavy metals, essential safe application animal

Language: Английский

Black Soldier Fly Larvae’s Optimal Feed Intake and Rearing Density: A Welfare Perspective (Part II)

Insects, Journal Year: 2024, Volume and Issue: 16(1), P. 5 - 5

Published: Dec. 26, 2024

The large-scale insect rearing sector is expected to grow significantly in the next few years, with Hermetia illucens L. (black soldier fly, BSF) playing a pivotal role. As traditional livestock, it essential improve and ensure BSF welfare. A starting point can be an adaptation of Five Freedoms framework. Feed availability must optimized meet larvae nutritional needs (freedom from hunger) while maximizing substrate conversion efficiency. Similarly, density well-being, particularly operations. In this study, Control (commercial laying hen feed) Omnivorous substrates (vegetable meat) were used as dietary regimes. first trial, three feeding rates tested: 50, 100, 200 mg feed/larva/day; second densities evaluated: 5, 10, 15 larvae/cm2. Performance parameters, including final larval weight, frass biomass, growth rate, reduction, feed ratio, length, survival chemical composition, process optimization, studied. Our results show that rate approximately 90 feed/larva/day diet 175 diet, along 5 7.57 larvae/cm2, respectively, diets, produced optimal performances ensuring well-being. This outcome offers valuable insights for implementing good welfare practices farming optimizing management

Language: Английский