锶胁迫条件下生菜光谱效应特征

锶（Sr）胁迫条件下生菜的反射光谱特征会发生明显改变。通过室内生菜水培试验,获取了36个不同生长期、6个不同锶浓度胁迫的生菜叶片400～950 nm波段区间的生化参数信息（叶绿素含量、细胞结构、叶片金属含量）和反射光谱信息,利用光谱技术并结合数学统计方法研究了生菜叶片7个光谱特征参数与实测叶片锶元素含量之间的相关性,优选了较敏感光谱特征参数,建立了其与生菜叶片锶含量的线性回归模型。结果表明,锶胁迫生菜叶片叶绿素含量呈先上升后下降的规律,细胞结构差异不明显。锶胁迫生菜叶片反射光谱直观上无规律,通过采用光谱技术方法分析得出锶胁迫生菜叶片的红边波段位置先“红移”再“蓝移”,红谷波段位置则“红移”,植被指数B4/B3比值先升高后降低,红边归一化植被指数（NDVI）值随着锶浓度的升高而降低。相关性及线性回归模型分析表明红边波段位置与叶片锶含量显著相关。本文为下一步基于光谱特征的叶片重金属含量反演模型的构建提供了较好的数据源和基础理论。

Study on Spectral Effect Characteristics of Lettuce under Strontium Stress

Under Sr stress, the reflective spectral characteristics of lettuce would change significantly. The biochemical parameter information (chlorophyll content, cell structure, leaf metal content) and reflective spectrum information of lettuce leaves in 400~950 nm band of 3 different growth stages and 6 different strontium concentrations were obtained through indoor lettuce hydroponics experiment. The correlation between 7 spectral characteristic parameters of lettuce leaves and measured strontium content of lettuce leaves was explored by spectral technology and mathematical statistics, The more sensitive spectral characteristic parameters were optimized, and the linear regression model between them and strontium content in lettuce leaves was established. The results showed that the chlorophyll content of lettuce leaves under strontium stress increased first and then decreased, and there was no significant difference in cell structure. The reflectance spectrum of strontium stressed lettuce leaves is intuitively irregular. Through spectral analysis, it is concluded that the position of the red edge band of strontium stressed lettuce leaves first "red shift" and then "blue shift", and the position of the red valley band is "red shift". The ratio of vegetation index B4/B3 first increases and then decreases. The normalized vegetation index (NDVI) value of the red edge decreases with the increase of strontium concentration. Correlation and linear regression model analysis showed that the position of red edge band was significantly related to strontium content in leaves. This paper provides a good data source and basic theory for the next step of building the retrieval model of leaf heavy metal content based on spectral characteristics.