日光诱导叶绿素荧光探测小麦氮素营养状况的机理与方法研究

In order to realize precision nitrogen management, it is critical to monitor crop nitrogen status accurately and non-destructively at different fertility levels. By unitizing the technology of solar-induced chlorophyll fluorescence (SIF), crop physiological and nutrient status can be directly detected sensitively at the levels of leaf, canopy and field during the early crop growth stage. On the basis of SIF theory and remote sensing, and adopting physiological and biochemical measurements and statistical analysis through combing the nondestructive monitoring technology with synchronously destructive sampling tests in wheat, this research concentrates on: (1) to reveal the spatial and temporal dynamic patterns and the quantitative relationships between chlorophyll fluorescence spectra (parameters), nitrogen, pigments, photosynthetic characters, fluorescence induction kinetic parameters at different leaf positions and canopy scales under varied nitrogen levels; (2) to clarify the responses of wheat chlorophyll fluorescence spectra (parameters) and underlying mechanisms at different nitrogen levels; (3) to extract the corresponding SIF parameters which are explanatory and sensitive to high and low nitrogen levels; (4) to identify specific SIF indices for early detection and diagnosis of the plant nitrogen stress; (5) to track the changes and dynamic characters for determining the physiological threshold of SIF parameters at the key stages under different nitrogen levels in wheat. The expected results will provide a theoretical and technological foundation for crop nitrogen status under varied nitrogen levels with SIF technology, which would support the satellite-unmanned aerial vehicle-ground platforms for accurate diagnosis of plant nitrogen status and scientific management of nitrogen fertilization, thus facilitating intelligent growth diagnosis and enhancing grain production capacity.

快速无损准确监测作物氮素营养状况是精确农业中氮肥精确管理的前提与核心。日光诱导叶绿素荧光(Solar-induced chlorophyll fluorescence, SIF)能够直接、快速并灵敏的探测作物生理动态状况。本研究针对作物氮素营养监测精准的技术难题，将叶绿素荧光遥感探测原理与作物生理生态机制相结合，深入揭示不同氮素水平下小麦单叶和冠层2个尺度的SIF与氮素、色素、光合和叶绿素荧光动力学参数等的时空动态变化特征，着重阐明小麦SIF对氮素的光谱响应规律和机理关系，构建解释性和可靠性兼具的小麦氮素敏感SIF参数，并筛选能早期探测氮胁迫的最佳SIF参数，明确其动态特征和变化轨迹，最终确定最佳SIF参数在关键生育时期的生理阈值。预期结果为基于星-机-地平台叶绿素荧光的作物氮素精准探测和氮肥科学运筹提供理论基础和技术途径，对实现作物生长智能诊断和提升我国粮食生产能力具有重要意义。

小麦氮素营养的精准、无损、实时监测对指导田间氮肥管理、保障作物产量和品质、减少环境污染以及提高经济效益有重要意义。叶片氮含量（LNC）是与植株光合特性密切相关的重要叶片氮相关参数，该参数的精准监测有助于促进植物功能、植物表型和精确农业研究的发展。传统的光学遥感技术已被广泛用于监测小麦LNC，但是反射率信号提取于植被与土壤等背景的混合像元，易受土壤背景，且对氮素胁迫不敏感。因此，探寻一种能够实时、便捷并精准监测小麦氮素营养状况、光合生理状态的遥感技术是非常必要的。植物生长过程中施氮量的高低会影响植株LNC的多少，进而影响植株的光合能力和非光化学猝灭系数，也就影响到了荧光的发射，这为日光诱导叶绿素荧光（SIF）监测小麦LNC提供了理论基础和原理支撑。.本研究利用高光谱传感器获取小麦关键生育期的SIF信号，同步测试光合生理参数和农学参数，以开展基于SIF信号的小麦叶片氮素营养监测研究。（1）通过比较两个观测尺度上各个指标的生育期变化规律和监测精度发现，研究发现在基于面积和重量的两种LNC指标中，SIF信号与基于面积的LNC更相关，尤其在冠层尺度上；基于↑SIFR2和↑SIFN构建的监测LNC的模型最佳。（2）通过比较单叶尺度不同基于面积LNC（LNCarea）水平的小麦叶片上下行SIF产率光谱，研究探明由于叶绿素的重吸收效应和叶片内部结构的散射效应，下行SIF信号弱于上行SIF信号，红光区域SIF峰小于远红光区域SIF峰值。下行SIF指数监测LNCarea的表现要优于上行SIF指数，且SIF双峰比值指数监测LNCarea的精度要高于单波段指数，尤其是↓SIFR1的表现最佳。且相应的LNCarea监测模型在不同数据集中表现稳定。（3）通过比较SIF指数、植被指数以及农学参数随氮素处理的时序性响应规律，筛选出对氮素胁迫最敏感的SIF指数为↑SIFR2，并构建了相应的NNI监测模型。这些研究结果为SIF信号精准监测小麦叶片氮含量以及及时监测和诊断小麦氮素胁迫提供了技术支撑和理论基础，促进了小麦田间氮素的运筹管理。