Mealworm protein for animal feed: Automating and optimising production.

用于动物饲料的黄粉虫蛋白：自动化和优化生产。

• 批准号: 10053146
• 金额: $ 32.86万
• 依托单位: MR BUG LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10053146
• 关键词: Mealworm; protein; animal; feed; Automating

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.

我们迫切需要生产更可持续的蛋白质，其中一种方法就是养殖昆虫。昆虫的蛋白质含量高，比传统的谷物生产对环境的影响小得多。通常作为动物饲料饲养的一种昆虫是粉虫，即黄粉虫。目前阻碍粉虫蛋白用于动物饲料的瓶颈是生产成本。遇到的主要成本是原料和劳动力，因此该项目通过开发农业过程自动化和测试不同的原料，重点关注这两个领域。我们将研究粉虫的行为，并使用摄像机和热传感器来确定进食时间，以及疾病或害虫问题的早期预警。将围绕昆虫的自然行为设计物联网传感器和机器视觉分析的组合，使用摄像头和热传感器来支持繁殖，饲料和健康标记。我们将使用机器视觉分析昆虫饲养托盘的高分辨率图像和视频，以确定甲虫向繁殖托盘移动时的性别，估计生长，计数和量化运动模式。这些将确定最佳条件和幼虫的自然运动行为，当食物稀缺时减慢，将用于确定饲料的时机。成像还将用作早期预警系统，以识别潜在的病虫害问题。虽然昆虫蛋白比其他动物蛋白更具可持续性，但仍有改进的空间，特别是在饲养它们的饲料方面，以避免使用可用于人类消费或饲料制造商的饲料，我们将测试来自作物生产的副产品，以及来自餐饮业的水果和蔬菜废料，以确定最适合粉虫生长和蛋白质含量的最佳饲料。