Journal of Seed Science (Dec 2020)
Seed quality analysis of Senna siamea Lam. using image analysis techniques
Abstract
Abstract: The inclusion of image analysis techniques for the accurate and rapid assessment of the quality of forest seeds is highly desirable. The use of digital radiographic images of seeds and the analysis of seedling images, still little used in determining the quality of forest seeds, are among the available imaging techniques. This study aimed to assess the feasibility of using the analysis of images of seeds and seedlings in the assessment of the physical and physiological quality of Senna siamea seeds. Radiographic images of seeds were obtained from five seed lots, allowing generating morphological and tissue integrity descriptors. These seeds were then subjected to germination and seedling growth tests, which allowed obtaining variables related to physiological quality. The generated seedlings were scanned and analyzed using the software ImageJ. The data were analyzed using analysis of variance, correlation, and principal component analysis. The results showed differences between seed lots in terms of physiological quality and physical integrity of internal tissues. Significant correlations were observed between the variables obtained with the radiographic analysis and seed physiological characterization tests. The use of techniques to analyze seed radiographs and seedling images allows access to information on the physical and physiological integrity of S. siamea seeds.
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