Vegetation indices (VIs) are mainly associated with plant yield, and yield-related physiological traits can assist in breeding selection. Tree breeding programs require a rapid assessment of a large number of individual trees across multiple regions. Unmanned aerial vehicle (UAV) multispectral platforms combined with high spatial, temporal and spectral resolutions can readily assess the VIs at various plant growth phases, which has been deeply detailed for evaluating the physiological status of agricultural crops and forest stands. However, the underlying genetics of foliar spectral bands, VIs and growth traits from a large scale of samples, especially in the case of forest trees, have been less investigated. In this paper, two sites of slash pine breeding populations were completely investigated to monitor the spectral bands, VIs, and tree growth traits. This allows us to determine the genotypic variation of these traits and to estimate the heritability (h²). The results show that the estimated h² ranges from 0.04 to 0.36, and the site may affect tree growth because the traits between two sites come to different h² values. At the two sites, the h² values of the green red difference vegetation index (GNDVI) and anthocyanin reflectance index (ARI) at Site 1 and the red edge chlorophyll index (RECI), leaf chlorophyll index (LCI), red green blue vegetation index (RGBVI), normalized difference red edge index (NDRE), NIR and red edge at Site 2 were less than 0.1. However, breeding selection is still possible for most VIs and growth traits at both sites based on different breeding targets and families (families 3, 5, 10, 11, 14 and 17 at Site 1 and 4, 6, 8, 19 and 13 at Site 2 for optimal spectral bands; families 2, 8, 7, 13, 16, and 18 at Site 1 and 6, 7, 11, 14, 15, 18, and 20 at Site 2 for optimal VIs; families 8 and 16 at Site 1 and families 7 and 18 at Site 2 for optimal growth traits) with a variety of optimal traits are selected. This paper demonstrates the potential use of UAV-based imagery technologies in the breeding selection of slash pine trees.

植被指数（VIs）主要与植物产量相关，产量相关的生理性状可以辅助育种选择。树木育种计划需要对跨多​​个地区的大量单株树木进行快速评估。无人机 (UAV) 多光谱平台结合高空间、时间和光谱分辨率，可以轻松评估不同植物生长阶段的 VI，这对于评估农作物和林分的生理状态已经非常详细。然而，来自大规模样本的叶谱带、VI 和生长性状的潜在遗传学研究较少，尤其是在林木的情况下。在本文中，对两个西洋参繁殖种群进行了全面调查，以监测光谱带、VI、和树的生长特性。这使我们能够确定这些性状的基因型变异并估计遗传力（ħ ²）。结果表明，估计的h ²范围从0.04到0.36，并且该站点可能会影响树木的生长，因为两个站点之间的性状具有不同的h ²值。在这两个站点，h ²Site 1的绿红差异植被指数（GNDVI）和花青素反射指数（ARI）值以及红边叶绿素指数（RECI）、叶片叶绿素指数（LCI）、红绿蓝植被指数（RGBVI）、归一化差异红边缘指数 (NDRE)、NIR 和站点 2 的红色边缘小于 0.1。然而，基于不同的育种目标和科（家 3、5、10、11、14 和 17 在站点 1 和 4、6、8、19 和 13 在站点站点 2 以获得最佳光谱带；站点 1 的第 2、8、7、13、16 和 18 族和站点 2 的第 6、7、11、14、15、18 和 20 族以获得最佳 VI；第 8 和 16 族在站点选择具有多种最佳性状的站点 1 和站点 2 的家族 7 和 18，以获得最佳生长性状。