Cadmium contamination in food crops: Risk assessment and control in smart age

With mankind entering the smart age, Cd contamination risk control in food crop revolution has been put on the agenda. Based on the theoretical basis, technical methods and developing trends, this review look back and forward the age of Cd contamination risk control driven by ‘genotype (G)+ envirotype (E)’ dual-engines. Focusing on G, an inter-specific Cd contamination risk assessment meta-analysis was carried, in which a higher Cd contamination risk in rice and wheat than maize was observed. So different strategies are recommended to be taken considering inter-specific difference. To control the risk in crops with high accumulating characteristic, smart creation of low-Cd crops can be applied by two methods: 1) Excavating and pyramiding natural variations in natural population and 2) designing and implementing artificial variations which do not exist in natural population. Focusing on E, the influence of environmental factors to food crop Cd accumulation was discussed and the strategy using Envirotype-to-phenotype (E2P) models to predict and implement safety threshold were offered. In the foreseeable future, with the support of environmental science, biology, big data, artificial intelligence and other interdisciplinary and multi-technology, Cd contamination risk control will move toward intelligent, efficient and directional, ultimately realizing the revolutionary transformation from ‘experience’ to ‘smart’.

随着人类步入智能时代，粮食作物产业革命背景下的镉（Cadmium, Cd）污染风险管控已被提上议事日程。本综述基于理论基础、技术方法与发展趋势，回溯并展望了以‘基因型（G）+环境型（E）’双引擎驱动的镉污染风险管控时代。聚焦基因型维度，本研究开展了种间镉污染风险评估的荟萃分析，结果显示水稻与小麦的镉污染风险显著高于玉米。因此，需结合作物种间差异制定差异化管控策略。针对具备高积累特性的作物，可通过两种路径实现低镉作物的智能创制：一是挖掘并聚合自然群体中的天然变异；二是设计并引入自然群体中不存在的人工变异。聚焦环境型维度，本综述探讨了环境因子对粮食作物镉积累的影响，并提出了利用环境型-表型（Envirotype-to-phenotype, E2P）模型开展预测并制定安全阈值的管控策略。在可预见的未来，在环境科学、生物学、大数据、人工智能等多学科与多技术的支撑下，镉污染风险管控将朝着智能化、高效化与定向化方向发展，最终实现从‘经验导向’到‘智能导向’的革命性转变。