Identifying best sensor technologies to deliver verifiable health & welfare, environment and processing quality benefits for dairy production.

乳制品生产和加工是英国西部许多农村地区的关键产业，将人类不可食用的饲料转化为各种健康饮食的宝贵成分，并有助于农村社区的可持续发展。乳制品生产在所有可以利用英国草原进行食品生产的反刍动物生产系统中碳足迹最低，因此我们专注于提高乳制品生产和加工的技术效率。该项目解决了牛奶和乳制品消费者和零售商的一些关键问题，他们需要对乳制品生产系统的环境足迹和动物福利标准感到放心。它将开发新的工具，为消费者、零售商和加工商提供有关乳制品生产系统中环境足迹和动物福利标准的可验证信息。我们将使用监测技术，包括环境传感器、动物传感器和摄像技术，农民已经在使用这些技术来管理其系统的技术方面，如喂养和生育。我们将避免预先判断不同技术的潜力，并从已经商业化或即将商业化的任何设备开始工作。通过使用先进的机器学习技术将这些信息与手动记录的信息相关联，我们将能够开发新的算法，以更容易，更便宜和更可靠的方式提供环境排放和奶牛福利的指数。我们的目标是确定环境和福利方面的几个关键共同指标的预测因子，这些指标有助于制定公认的农场保证标准，并使消费者放心。我们将与英国主要乳制品地区的先进奶牛场合作，以确保关系稳固，并为其他农民提供示范和推广平台。脱欧后，英国可能有新的机会出口或取代进口高价值乳制品;这些产品的开发建立在环境足迹和奶牛福利等方面可验证质量的坚实基础上。

Dairy production and processing are key industries for many rural areas in western Britain, converting human inedible feeds into valuable components of healthy varied diets and contributing to the sustainability of rural communities. Dairy production has the lowest carbon footprint of all of the ruminant production systems that can utilise the UK's grasslands for food production and so we focus on improving technical efficiency in dairy production and processing. The project addresses some of the key concerns of consumers and retailers of milk and dairy products, who need to be reassured about the environmental footprint and animal welfare standards of dairy production systems. It will develop new tools to provide consumers, retailers and processors with verifiable information about the environmental footprint and animal welfare standards in dairy production systems. We will use monitoring technologies, including environmental sensors, animal-mounted sensors and camera technologies that are already being used by farmers to manage technical aspects of their systems, such as feeding and fertility. We will avoid prejudging the potential of different technologies and start out by working with any equipment that is already being used commercially, or is about to be commercialised. By relating this information to manually recorded information, using advanced machine learning techniques, we will be able to develop new algorithms to provide indexes of environmental emissions and cow welfare in ways that are both easier, cheaper and more reliable. Our objective is to identify predictors of a few key common indicators for both environment and welfare aspects that can contribute to accepted farm assurance standards and reassure consumers. We will work with progressive dairy farms across the main UK dairying regions to ensure that relationships are robust and to provide a platform for demonstration and extension to other farmers. After BREXIT, the UK may have new opportunities to export or replace imports of high-value dairy products; development of such products is built on a solid foundation of verifiable quality in aspects such as environmental footprint and cow welfare.