植物的波谱特征主要取决于它的叶子，叶片的生长状态决定了不同的特征光谱信息。不同植物叶片的色素含量、细胞结构、含水量、营养物质不同，光谱响应与图像呈现均不相同。利用光谱和图像分析等技术，可以识别植物类型、反演植物营养元素含量、监测植物生长状态。目前多数研究集中在某一时期光谱或图像的研究，同时连续获取光谱和图像的研究较少。本研究通过收集国家苹果资源圃中的富士、华红、嘎啦三种苹果叶片8-10月每周一次的苹果健康标准叶片，并进行近红外光谱和图像的获取，以期为今后利用无损手段进行品种识别、测定苹果健康情况等积累基础数据。

The spectral characteristics of a plant mainly depend on its leaves, and the growth state of leaves determines different characteristic spectral information. Different plant leaves have different pigment content, cell structure, water content and nutrients, and the spectra response and image presentation are different. Using spectra and image analysis techniques, we can identify plant types, retrieve plant nutrient content and monitor plant growth status. At present, most studies focus on the study of spectra or image in a certain period, and there are few studies obtaining spectra and images simultaneously and continuously. In this study, healthy and standard apple leaves of Fuji, Huahong and Gala in the National Apple Resource Nursery were collected once a week from August to October, and the near-infrared spectra and images were obtained, in order to accumulate basic data for variety identification and determination of apple health by nondestructive means in the future.