机器学习在植物工厂中的研究现状与挑战

Machine Learning in Plant Factory:Current Status and Challenges

为有效缓解来自人口、环境和资源方面的压力,发展植物工厂非常重要。智慧植物工厂是设施农业发展的高级阶段,研究如何将机器学习应用在植物工厂中有效提高生产效率,促使植物工厂向智能化方向发展是一个重要的新课题。通过将机器学习与作物表型研究相结合,建立作物生长模型,并应用到生长环境监测中(病、虫、草、旱涝、营养等),及精准调控植物工厂室内环境及营养液智能调控等方式中,解决好中国植物工厂成本高、作物产量低的问题,助力植物工厂向信息化、自动化、智能化、精准化和个性化方向发展。

To effectively relieve the pressure from population,environment and resources,it is very important to develop plant factory.Intelligent plant factory is an advanced stage in the development of facility agriculture.It is a new topic to study how to apply machine learning in plant factory to effectively improve the production efficiency and promote the intelligent development of plant factory.Combining machine learning with crop phenotype study,a crop growth model is established and applied to plant growth environment monitoring(diseases,insects,grass,drought and water logging,nutrition,etc.),accurate plant factory indoor environment regulation,and intelligent nutrient solution regulation etc.,so as to solve the problem of high cost and low crop yield of plant factories in China.The study can help plant factories develop towards the one with information technology,automation,intelligence,precision and individuation.