类胡萝卜素探测作物养分胁迫的光谱诊断机理与方法研究

The present methods of crop nutrient detection are mostly focused on chlorophyll or nutrient as monitoring indexes, which cannot meet the demand of early detection of nutrient status of agricultural production. Thus, it is in urgent need to establish diagnostic methods of nutrient deficiency in regional scale which could eliminate the effect of crop types and foliar colors to assure timely supply of nutrient in the critical growth periods of crops. (1) Carotenoid and xanthophyll are crucial physiological indexes which reflect nutrient status of crops. When crops are in nutrient deficiency, ratio between carotenoid and chlorophyll content varies. To find out the mechanism of spectral response of carotenoid and the regularity of nutrient stress, comparative experiments in field plots were performed and ratio between carotenoid and chlorophyll content, which could eliminate the effect of crop types and foliar colors, would be used as monitoring index to analyze whether crops are in nutrient stress or not. (2) Establishing diagnostic models of nutrient stress of corps both in leaf and canopy scale, and proposing methods to early detection and monitoring of nitrogen stress of crops through remote sensing based on ratio between carotenoid and chlorophyll content. (3) Aiming at the challenge that nutrient stress could not be easily distinguished from other stresses, experiments of various treatments were conducted to analyze the difference in multidimensional features such as spectral, spatial and temporal dimensions amongst nutrient, water and plant diseases and insect pests’ stresses of crops, thereby distinguishing different stresses combined with spectral, spatial and temporal information. The results would be significant in achieving early and rapid detection of nutrient stress in regional scale, guiding timely variable rate fertilization, reducing environmental contamination of croplands, preserving ecological environment and guaranteeing national food security.

当前作物养分光谱探测主要以叶绿素含量等作为监测指标，无法满足农业生产对作物养分状况及时诊断的需求，迫切需要建立消除作物品种和叶色影响的养分亏缺大面积快速诊断方法。本项目通过大田控制实验，开展以下研究：(1)作物养分亏缺时，体内类胡萝卜素和叶绿素含量及两者间比值会发生变化，选取类胡萝卜素与叶绿素比值作为判定小麦是否发生养分胁迫的指标，解析类胡萝卜素光谱探测机理与养分胁迫响应规律；(2)作物养分诊断需要解决不同胁迫类型区分的难题，通过解析小麦养分、水分和病害等胁迫在“光谱-空间-时相”等多维特征上的差异，提出综合光谱、空间与时相信息的不同胁迫区分方法；(3)建立叶片和冠层尺度的养分胁迫诊断模型，提出基于类胡萝卜素与叶绿素含量比值的氮素养分胁迫遥感监测与诊断方法，消除不同品种类型和叶色差异的影响。研究成果对实现大面积快速养分缺乏诊断，指导适时变量施肥、保护生态环境和保障国家粮食安全具有重要意义。

作物发生养分胁迫时会造成体内生化参数含量变化，进而使叶色发生变化，建立以作物体内生化参数含量等作为监测指标进行作物养分亏缺早期诊断对大面积农田作物长势监测及精准农业实施具有十分重要的作用。本项目以小麦和玉米为研究对象，通过开展田间控制实验和野外调查实验，选取类胡萝卜素、叶绿素、类胡萝卜素和叶绿素的比值、氮素作为养分亏缺的指标，开展了基于不同诊断指标尤其是类胡萝卜素的作物养分胁迫光谱诊断机理与方法研究。取得的主要研究结果包括：（1）针对可见光波段类胡萝卜素与叶绿素吸收特征重叠，作物类胡萝卜素含量估算较为困难这一问题，利用PROSAIL植被辐射传输模型模拟数据和田间实测数据，阐明了类胡萝卜素光谱探测机理与养分胁迫响应规律。（2）针对作物早期养分缺乏往往下部叶片首先表现出缺素症状的特点，提出了作物养分垂直分布多角度遥感监测方法，明确了多角度遥感用于监测不同垂直层叶片叶绿素和氮素含量的最佳观测角度，筛选出了多角度遥感监测冠层各层养分的最适观测角度和植被指数，建立了作物叶绿素和氮素垂直分布遥感监测模型，阐明了不同株型对作物养分垂直分布遥感探测的影响；（3）提出了作物类胡萝卜素与叶绿素比值的养分诊断指标，明确了养分胁迫条件下类胡萝卜素、叶绿素色素及其比值与养分胁迫梯度之间的定量关系，建立基于类胡萝卜素与叶绿素含量比值的养分胁迫光谱诊断模型；（4）阐明了作物肥水胁迫与白粉病、条锈病等病害胁迫下的作物光谱响应特征差异，提出了养分与病害等不同胁迫类型的遥感识别方法，实现不同胁迫类型的遥感区分。通过本项目研究，建立了作物养分早期亏缺的光谱诊断方法与模型，研究成果对实现大面积快速养分缺乏诊断，指导适时变量施肥、保护生态环境和保障国家粮食安全具有重要意义。项目资助下共发表学术论文和专著14篇/部，其中，SCI/EI论文12篇；编著专著2部，其中，作为主编出版专著《作物理化参数遥感定量反演》，合著（章节主编）出版英文专著《Progress in Carotenoid Research》；授权国家发明专利3项；获软件著作权登记5项。