Mealworm protein for animal feed: Automating and optimising production.

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There is a strong need to produce more sustainable protein and one way of doing this is by farming insects. Insects have a high protein content and a much lower environmental footprint than traditional meet production. One of the insect species that is commonly farmed for animal feed are the mealworms, _Tenebrio molitor_. Current bottlenecks for mealworm protein being affordable for use for animal feed is the cost of production. The key costs encountered are feedstock and labour, hence this project focuses on those two areas by developing automation for the farming process and testing different feedstocks. We will work with the mealworm behaviour and use cameras and heat sensors to identify time to feed as well as an early warning of any issues with disease or pests.Combination of IoT sensors and machine vision analysis will be designed around the insects' natural behaviour, using cameras and heat sensors to support breeding, feed and health markers. We will use machine vision analysis on high resolution images and video of insect rearing trays to identify the sex of the beetles as they move towards breeding trays, estimate growth, count and quantify movement patterns. These will determine optimum conditions and the larvae natural movement behaviour which slows down when food is scarce will be used to identify timing of feeds. Imaging will also be used as an early warning system to identify potential issues with pests and diseases.Although insect protein is more sustainable than other animal protein, there are still improvements that can be made, especially in the feedstock they are reared on to avoid using feed that could be used for human consumption or by the feed manufacturers and we will test co-products from crop production, and fruit and vegetable based waste from the catering industry, identifying the best feed for optimum mealworm growth and protein content.