Abstract: In order to achieve rapid and non⁃destructive detection of pigment content and photosynthetic performance in leaves of three different colors of Physocarpus,in the growing season,the pigment content,color parameters and hyperspectral reflectance of the leaves of the three test materials at different leaf positions were determined,and the leaf pigment content estimation model was established by multiple stepwise regression and partial least squares regression analysis,and the accuracy was tested.The results showed that the spectral reflection characteristics of Physocarpus amurensis and Physocarpus opulifolius var.luteus were similar,and Physocarpus opulifolius‘Summer Wine’was different from the other two at the green light peak and near infrared light.The spectral reflectance of the three was Physocarpus opulifolius var.luteus>Physocarpus amurensis>Physocarpus opulifolius‘Summer Wine’.The pigment estimation model based on partial least squares had the highest accuracy,among which,the modeling and testing R² values of leaf color parameters and the contents of total chlorophyll,anthocyanin in Physocarpus amurensis and anthocyanin in Physocarpus opulifolius‘Summer Wine’were all above 0.68 and the highest was 0.89.The modeling R2 values of the hyperspectral parameters and the contents of chlorophyll a，chlorophyll b,total chlorophyll,carotenoid and anthocyanin in Physocarpus amurensis and Physocarpus opulifolius var.luteus were all above 0.79 and the highest was 0.98,while the testing R² values were above 0.64 and the highest was 0.91.The accuracy of leaf pigment estimation model based on hyperspectral parameters was higher than that based on leaf color parameters.The advantages of partial least squares regression model in the estimation of pigment content in leaves of three color systems of Physocarpus were verified,and a high⁃precision estimation model for leaf pigment was established.

Key words: Physocarpus, Leaf pigment, Color parameter, Hyperspectral parameter, Partial least squares

摘要： 为快速、无损检测3种（品种）不同色系风箱果叶片色素含量及光合性能，在生长季内分别测定3种试材不同叶位叶片的色素含量、色彩参数、高光谱反射率，通过多元逐步回归、偏最小二乘回归分析建立叶片色素含量估算模型，并进行精度检验。结果表明，风箱果、金叶风箱果叶片光谱反射特性相似，紫叶风箱果在绿光峰值及近红外光处区别于前两者，三者光谱反射率表现为金叶风箱果>风箱果>紫叶风箱果。基于偏最小二乘构建的色素估算模型精度最高，其中，叶片色彩参数与风箱果总叶绿素、花色素苷及紫叶风箱果花色素苷含量建模和检验R²均在0.68以上，最高为0.89；高光谱参数与风箱果及金叶风箱果的叶绿素a、叶绿素b、总叶绿素、类胡萝卜素、花色素苷含量建模R²均在0.79以上，最高为0.98，检验R²均在0.64以上，最高为0.91。基于高光谱参数建立的叶片色素估算模型精度高于基于色彩参数所建模型；证实了偏最小二乘回归模型在3种（品种）色系风箱果叶片色素含量估算中的优越性，并构建了高精度的叶片色素估算模型。

关键词: 风箱果, 叶片色素, 色彩参数, 高光谱参数, 偏最小二乘