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      X-ray imaging and digital processing application in non-destructive assessing of melon seed quality Translated title: Aplicação do teste de raios-X e processamento digital na avaliação não-destrutiva da qualidade de sementes de melão

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          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.

          Translated abstract

          Resumo: Métodos não-destrutivos e de alto desempenho têm sido desenvolvidos para avaliação da qualidade de sementes. O objetivo deste estudo foi relacionar parâmetros obtidos a partir da análise gratuita e automatizada de radiografias digitais de sementes de melão híbrido com o seu potencial fisiológico. Foram utilizadas amostras de sementes comerciais de três cultivares híbridas de melão (Cucumis melo L.), cada uma representada por três lotes. Foram obtidas imagens radiográficas das sementes, das quais foram geradas determinações de área, perímetro, circularidade, densidade relativa, densidade integrada e preenchimento da cavidade interna de sementes, por meio de uma macro (PhenoxXray) desenvolvida para o software ImageJ®. Após o teste de raios-X, as sementes foram submetidas ao teste de germinação, a partir do qual foram obtidas variáveis relacionadas à qualidade fisiológica. Observou-se variabilidade entre lotes para as características físicas e fisiológicas. Os resultados demonstraram que o uso da macro PhenoXray permite a fenotipagem em larga escala das radiografias de sementes de maneira simples, rápida, consistente e totalmente gratuita. A metodologia é eficiente na obtenção de dados morfométricos e de integridade tecidual em sementes de melão, e os parâmetros gerados apresentam estreita relação com atributos fisiológicos da qualidade das sementes.

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          Most cited references21

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Seed vigour and crop establishment: extending performance beyond adaptation

            Seeds are central to crop production, human nutrition, and food security. A key component of the performance of crop seeds is the complex trait of seed vigour. Crop yield and resource use efficiency depend on successful plant establishment in the field, and it is the vigour of seeds that defines their ability to germinate and establish seedlings rapidly, uniformly, and robustly across diverse environmental conditions. Improving vigour to enhance the critical and yield-defining stage of crop establishment remains a primary objective of the agricultural industry and the seed/breeding companies that support it. Our knowledge of the regulation of seed germination has developed greatly in recent times, yet understanding of the basis of variation in vigour and therefore seed performance during the establishment of crops remains limited. Here we consider seed vigour at an ecophysiological, molecular, and biomechanical level. We discuss how some seed characteristics that serve as adaptive responses to the natural environment are not suitable for agriculture. Past domestication has provided incremental improvements, but further actively directed change is required to produce seeds with the characteristics required both now and in the future. We discuss ways in which basic plant science could be applied to enhance seed performance in crop production.
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              SmartGrain: high-throughput phenotyping software for measuring seed shape through image analysis.

              Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.
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                Author and article information

                Journal
                jss
                Journal of Seed Science
                J. Seed Sci.
                ABRATES - Associação Brasileira de Tecnologia de Sementes (Londrina, PR, Brazil )
                2317-1537
                2317-1545
                2020
                : 42
                : e202042005
                Affiliations
                [1] Viçosa Minas Gerais orgnameUniversidade Federal de Viçosa orgdiv1Departamento de Agronomia Brazil
                [2] Macaíba Rio Grande do Norte orgnameUniversidade Federal do Rio Grande do Norte orgdiv1Departamento de Agropecuária Brazil
                Article
                S2317-15372020000100108 S2317-1537(20)04200000108
                10.1590/2317-1545v42229761
                39561aab-83f0-4983-8611-202f9f6b9c1e

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 09 October 2019
                : 08 January 2020
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 25, Pages: 0
                Product

                SciELO Brazil

                Self URI: Full text available only in PDF format (EN)
                Categories
                Article

                análise automática de imagens,Cucumis melo L.,radiografia de sementes,densidade relativa,automated image analysis,seed radiography,relative density

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