Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds

ABSTRACT Non-destructive and high performance analyses are highly desirable and important for assessing the quality of forest seeds. The aim of this study was to relate parameters obtained from semi-automated analysis of radiographs of Leucaena leucocephala seeds to their physiological potential by means of multivariate analysis. To do so, seeds from five lots collected from parent trees from the region of Viçosa, MG, Brazil, were used. The study was carried out through analysis of radiographic images of seeds, from which the percentage of damaged seeds (predation and fungi), and measurements of area, perimeter, circularity, relative density, and integrated density of the seeds were obtained. After the X-ray test, the seeds were tested for germination in order to assess variables related to seed physiological quality. Multivariate statistics were applied to the data generated, with use of principal component analysis (PCA). X-ray testing allowed visualization of details of the internal structure of seeds and differences regarding density of seed tissues. Semi-automated analysis of radiographic images of Leucaena leucocephala seeds provides information on seed physical characteristics and generates parameters related to seed physiological quality in a simple, fast, and inexpensive manner.摘要：无损且高效的分析手段对于评估林木种子品质而言至关重要。本研究旨在通过多元统计分析，将银合欢（Leucaena leucocephala）种子X光影像的半自动分析所得参数与其生理潜能建立关联。本研究使用了采自巴西米纳斯吉拉斯州维索萨地区母树的5个批次种子。实验通过分析种子的X光影像，获取了种子的破损率（包括虫害侵害与真菌感染），并测量了种子的面积、周长、圆形度、相对密度以及积分密度。完成X光检测后，对种子开展发芽试验以评估与种子生理品质相关的各项指标。对生成的实验数据采用多元统计方法进行分析，其中主成分分析（Principal Component Analysis，PCA）为核心分析手段。X光检测可清晰呈现种子内部结构细节以及种子组织密度的差异。对银合欢种子的X光影像进行半自动分析，能够以简便、快速且低成本的方式获取种子物理特性信息，并生成与种子生理品质相关的参数。