Abstract
New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.
Highlights
Food security is one of the biggest current challenges faced by the world (Godfray et al 2010)
Considering that combined use of multiple technologies of image analysis for description of traits of interest in seeds is a key point for modernization of agriculture, the aim of this study was to propose a method of highthroughput phenotyping, using free access tools for processing of 2D X-ray images of brachiaria seeds, as well as to relate the parameters obtained with seed physiological quality
According to Berry et al (2018), a big challenge associated with automated image analysis is variation in image quality, which may inadvertently affect the results
Summary
Food security is one of the biggest current challenges faced by the world (Godfray et al 2010). Non-invasive optical technologies based on electromagnetic radiation have been adapted to the large area of plant sciences and have provided a range of possibilities for applications in seed studies (Hughes et al 2017, Rolletschek et al 2015, Rousseau et al 2015). Among these technologies, the X-ray test has been successfully applied for non-destructive evaluation of indicators that are not visible in seeds (Huang et al 2015, Kotwaliwale et al 2014, Rahman & Cho 2016).
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