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.