中文摘要：

为了快速、准确估测番茄叶片叶绿素含量,利用光谱分析技术研究了玻璃温室环境下番茄叶绿素含量敏感光谱波段提取及其估测模型。番茄以基质方式栽培,在结果期使用ASD FieldSpecTM HH型便携式光谱辐射仪采集叶片光谱,并采用752型紫外-可见分光光度计测定其叶绿素含量。从原始光谱、吸光度光谱、一阶微分光谱、去除包络线光谱出发,进行光谱预处理,分析了净化图谱信息、突出作物叶绿素含量光谱特征的有效性。其中,吸光度光谱在可见光部分增强了光谱响应特征,去除包络线光谱和一阶微分光谱均具有较强的蓝光、红光吸收谷和绿光反射峰。又结合波段间自相关分析和多重共线性诊断提取了番茄叶绿素含量敏感光谱波段,原始光谱特征波段为639,672,696,750,768nm;吸光度光谱特征波段为638,663,750,763nm;去包络线光谱特征波段为436,564,591,612,635,683,760nm;一阶微分光谱特征波段为516,559,778nm。最后,应用4种预处理下的番茄叶绿素含量敏感光谱波段分别建立多元线性回归模型,模型精度由高至低分别为去包络线、吸光度、原始、一阶微分,其中去包络线模型校正集决定系数R2c为0.88,验证集决定系数R2v达到0.82,具有较好的预测能力。

英文摘要：

In order to predict the content of chlorophyll in tomato rapidly and accurately,this study,with spectrum technology,focused on the extraction of sensitive spectral bands of tomato chlorophyll in glass greenhouse environment and created an effective estimation model.During the period of cultivating tomatoes,leaf spectra were measured with an ASD FieldSpec HH spectrophotometer and chlorophyll content was measured with Type 752UV-Vis spectrophotometer.Based on the original spectra,absorbance spectra,first derivative spectra and continuum removal spectra,spectral data was preprocessed,in which the effectiveness of spectral features of chlorophyll content of tomato was highlighted and spectral response characteristics of the absorbance spectra in the visible part was enhanced.It was shown that both the continuum removal spectra and the first derivative spectra have strong blue and red absorption valley and green reflection peak.In this paper,the original spectrum,absorbance spectrum,first derivative spectrum and continuum removal spectrum were analyzed and compared,and then optimal spectral feature parameters were extracted with methods of Inter-Correlation analysis and multivariate collinearity diagnosis.Sensitive bands from original spectrum are 639,672,696,750 and 768nm.Sensitive bands from absorbance spectrum are 638,663,750and763 nm.Sensitive bands from first derivative spectrum are 516,559 and 778nm.Sensitive bands from continuum removal spectrum are 436,564,591,612,635,683 and 760nm.The stepwise multiple regressions were used to develop the prediction models of the chlorophyll content of tomato leaf.The result showed that the prediction model,which used the values from continuum removal spectrum at 436,564,591,612,635,683,760 nm as input variables,had the best predictive ability.The calibrationR-Square was 0.88 and the validation R-Square was 0.82.