氮素对苹果树的生长发育、苹果的营养及产量等都有着非常重要的作用。近红外光谱作为一种无损检测手段有着方便、快速等方面优势。随着光谱技术和图像处理技术的发展，利用光谱和图像分析等技术可构建植物的生化组分预测模型，从而达到快速无损检测的目的。然而目前多数研究仅获取了苹果叶片近红外光谱数据、矿质元素数据和图像数据的一种或两种，同时测定近红外光谱数据、氮元素及图像数据的数据集较少，因此，构建叶片光谱、图像和矿质元素数据集具有再次开发利用价值，支持科研发现。本研究通过收集辽北地区国家苹果资源圃中4种苹果树以及4个不同树龄“寒富”苹果树的健康标准果树叶片，对叶片进行近红外光谱数据、高清图像和氮含量的联合收集工作，建立苹果树标准叶片近红外光谱、标准图像和氮含量的数据集，以期为使用无损手段测定苹果叶片营养诊断提供数据支撑，并为今后利用高空遥感技术开展精准果业生产提供基础数据。

Nitrogen plays important roles in apple tree growth and development, as well as the apple nutrient content and yield. As a non-destructive testing method, near-infrared spectroscopy has the advantages of convenience and speed. Improved spectroscopy and image-processing technology may be used to construct correlation models of plant biochemical components to achieve rapid non-destructive testing. However, most studies currently only obtain one or two aspects of the near-infrared spectral, mineral element, and imaging data from apple leaves, and there are limited studies in which all three data types have been collected simultaneously. Therefore, here, the leaf spectrum has been constructed, in which the image and mineral element datasets can be re-evaluated and utilized in future research. In this study, the leaves of four types of apple trees and four different ages of ‘Hanfu’ apple trees were collected from the National Apple Resource Nursery in northern Liaoning Province. The leaves were analyzed to obtain near-infrared spectroscopic data, high-definition images, and nitrogen contents, providing data supporting the use of non-destructive methods to determine the nutritional contents of apple leaves. The results provide a foundation for the future use of high-altitude remote-sensing technology in fruit production.