Abstract
Abstract: Non-destructive and high throughput methods have been developed for seed quality evaluation. The aim of this study was to relate parameters obtained from the free and automated analysis of digital radiographs of hybrid melons’ seeds to their seeds’ physiological potential. Seeds of three hybrid melon (Cucumis melo L.) cultivars from commercial lot samples were used. Radiographic images of the seeds were obtained, from which area, perimeter, circularity, relative density, integrated density and seed filling measurements were generated by means of a macro (PhenoXray) developed for ImageJ® software. After the X-ray test, seed samples were submitted to the germination test, from which variables related to the physiological quality of the seeds were obtained. Variability between lots was observed for both physical and physiological characteristics. Results showed that the use of the PhenoXray macro allows large-scale phenotyping of seed radiographs in a simple, fast, consistent and completely free way. The methodology is efficient in obtaining morphometric and tissue integrity data of melon seeds and the generated parameters are closely related to physiological attributes of seed quality.
Highlights
The introduction of modern and high-performance techniques capable of generating consistent and fast results, less subjectively and non-destructively, presents great potential for the safe evaluation of the quality of agricultural products (Mahajan et al, 2015).Among the techniques that reach this proposal is the analysis based on electromagnetic X-ray radiation
The water content of the seeds has a high relation with the optical density of the radiography (Simak, 1991)
The uniformity of seed water content between seed lots is necessary to compare parameters related to tissue density, as gray levels of the radiographs
Summary
Among the techniques that reach this proposal is the analysis based on electromagnetic X-ray radiation. This technique, predominantly used in medical applications, has been used in several areas, including seed quality inspection (Rahman and Cho, 2016). Recent advances in the field of computer-aided digital image processing have contributed to making feasible this type of approach. Public domain software such as ImageJ® has provided promising perspectives to address this purpose and provide automation of analyses related to seed radiographs
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