重金属对水稻根-茎-叶胁迫响应机理及其LIBS快速检测方法研究

Heavy metal pollution and stress are expanding rapidly, which causes plant toxic effect, metabolism disorder, growth damage and even the plant death. These factors restrict the high-yield, high-quality, efficient, ecological and safety and sustainable agriculture. This project is focused on the growth and physiological features of rice under heavy metal stress, and using the “root-stem-leaf” trinity research strategies. The theoretical contents are exploring the rules of metal absorption, transportation, distribution in rice root-stem-leaf, and the functional mechanism of root morphologic changes, development traits and physiological regulation. The methodological contents are using hyper-spectral imaging, microscopy Imaging and laser-induced breakdown spectroscopy (LIBS) to develop fast detection methods and models, including the root morphology and metal absorption, stem development and metal transportation, and metal leaf physiological index and metal visual distribution model. This project will realize the fast detection of stress growth, physiological and heavy metals, which is helpful for the stress dynamic monitoring, prevention and restoration and precise management, and meaningful for the crop yield and quality safety.

重金属污染对农作物胁迫效应日趋严重，造成植物毒害效应、代谢过程紊乱、生长发育伤害，乃至植株死亡，大大制约了农作物高产、优质、高效、生态、安全生产和可持续发展。本项目围绕重金属胁迫下水稻生长生理响应特性，提出水稻“根-茎-叶”三位一体化研究策略，系统地研究镉、铬、铜三种重金属在水稻根部吸收、茎部运移和叶面分布规律，探明重金属对水稻根系形态变化、茎杆发育特性和叶片生理调控的胁迫响应机理；应用高光谱成像、显微成像和激光诱导击穿光谱（LIBS）等技术，建立胁迫下水稻根系形态微结构和重金属吸收互作机理及快速检测方法、茎杆发育生态和重金属运移规律及快速测定模型、叶片生理参量和重金属分布调控机理及可视化方法，实现水稻重金属元素和逆境生理参量的快速检测，对作物逆境的动态监测、及时有效的防治与修复和精准化管理决策，保障作物产量和品质安全具有重要意义。

土壤-植物生产系统中重金属污染对农作物胁迫效应日趋严重，探明作物重金属胁迫与逆境生理的互作规律，研究逆境生理与重金属元素快速检测方法，对于保障作物产量和品质安全具有重要意义。本项目以水稻、烟草、生菜为研究对象，从“根-茎-叶”三个维度研究重金属胁迫下作物形态特征、逆境生理信息和重金属元素的快速定量检测机理、方法和模型，取得多项进展，主要成果包括：探究了重金属胁迫下作物“根-茎-叶”形态参数与微观结构的变化规律及互作机理；探明了多种重金属（镉、铬、铜）胁迫下作物“根-茎-叶”逆境生理信息（还原型抗坏血酸、还原型谷胱甘肽、游离脯氨酸、丙二醛与可溶性蛋白）动态变化规律及互作机理，建立了生理参量高光谱图谱快速检测模型，研究了逆境生理信息分布可视化表达方法，实现了重金属胁迫下作物逆境生理指标快速检测；研究了重金属LIBS检测参数优化和信号增强方法，建立了基于化学计量学的作物重金属快速检测模型，探究了LIBS检测植物鲜叶样本水效益去除方法，研究了重金属元素在叶片叶脉和叶面的分布规律，建立了重金属分布可视化方法和模型，为田间重金属及时有效防治与作物精准化管理决策提供了重要支撑。项目执行期间，发表SCI收录论文7篇；申请国家发明专利5项，其中授权发明专利2项；获2019年教育部科技进步一等奖。