In aquaculture, the food costs represent approximately 45% of the operating costs. Thus, the reduction of food costs is essential to achieve the sustainability of such industry, existing great potential both in the reduction of food costs per unit and through the adoption of appropriate food management strategies. The present invention solves typical technical problems in estimating biomass (variable fish speed, low resolution or measurement errors in the calculation of the weight and height of the fish) through the use of new high-resolution optical systems, low-cost electronics and algorithms with neural networks.
Researchers from a Spanish university working in electronic engineering provide a novel biomass estimation system in aquaculture based on optical sensors and neural networks comprising two identical optical barriers. Each of these barriers comprises a first emitter block of photoemitters in the infrared spectrum and a second receiving block of photoreceptors in the infrared spectrum and also means for identifying the fish by radiofrequency, in such a way that a unique identification of each fish occurs when passing through the optical barriers thanks to a radiofrequency identifier. A subsequent classification of the fish identified will be done through neural networks.
The researchers would like to reach license agreements with companies operating in the aquaculture field with the aim to develop applications of the described technology.