Abstract:Recently is growing the need for non-invasive, fast, and accurate technologies that can predict seed quality. Between these technologies, X-ray image analysis stand out for evaluation of the internal morphology of the seeds. Thus, the aim of the present study was to evaluate the efficiency of a specialized software for analyzing digital radiographs of Urochloa decumbens seeds called SARS (Sistema de Análise de Radiografias de Sementes - Seed Radiograph Analysis System). Five comercial seed lots of U. decumbens… Show more
“…Unlike what was observed in this study, Ramos et al (2022) observed that U. decumbens seeds with higher germination potential and vigor showed significant correlations with some of the physical variables obtained by the X-ray test, such as area, perimeter, and tissue density. Furthermore, as already mentioned, several other studies have demonstrated the benefit of osmopriming when compared to unprimed seeds.…”
Section: Resultscontrasting
confidence: 99%
“…Medeiros et al (2020) evaluated the analysis of X-ray images on U. ruziziensis seeds and observed that physical attributes obtained by the X-ray test such as tissue density and seed filling were highly correlated with physiological quality, efficiently helping to carry out their large-scale phenotyping. The physical attributes obtained by the X-ray technique in U. decumbens seeds were highly correlated with germination and vigor, showing the potential of the technique for this species (Ramos et al, 2022).…”
The use of high-quality Urochloa decumbens seeds is an essential factor for the establishment of pastures, and osmopriming under stress conditions may improve seed performance. This study was conducted at the Universidade Federal de Viçosa in a completely randomized design and aimed to evaluate the effects of osmopriming and its relationship with physical and physiological attributes of U. decumbens seeds subjected to water deficit. Seeds from ten lots were primed in H2O (0 MPa) and PEG (−0.8 MPa), KNO3 (0.2%), and SNP (0.10 mmol L−1) solutions for 24 hours. Unprimed seeds were used as control. The seeds were evaluated in two trials after osmopriming. Trial I consisted of the X-ray test to evaluate physical attributes and germination and vigor tests. In Trial II, the seeds were placed to germinate under favorable (0 MPa) and water deficit conditions (−0.2 MPa) to evaluate physiological attributes. In general, osmopriming of U. decumbens seeds assisted in increasing physical attributes such as area, gray scale, perimeter, and tissue density. Osmopriming does not contribute to the best physiological performance of U. decumbens seeds under ideal germination conditions (0 MPa). However, osmopriming with SNP (0.10 mmol L−1) and PEG (−0.8 MPa) for 24 hours contributes to the better physiological performance of seeds under water deficit.
“…Unlike what was observed in this study, Ramos et al (2022) observed that U. decumbens seeds with higher germination potential and vigor showed significant correlations with some of the physical variables obtained by the X-ray test, such as area, perimeter, and tissue density. Furthermore, as already mentioned, several other studies have demonstrated the benefit of osmopriming when compared to unprimed seeds.…”
Section: Resultscontrasting
confidence: 99%
“…Medeiros et al (2020) evaluated the analysis of X-ray images on U. ruziziensis seeds and observed that physical attributes obtained by the X-ray test such as tissue density and seed filling were highly correlated with physiological quality, efficiently helping to carry out their large-scale phenotyping. The physical attributes obtained by the X-ray technique in U. decumbens seeds were highly correlated with germination and vigor, showing the potential of the technique for this species (Ramos et al, 2022).…”
The use of high-quality Urochloa decumbens seeds is an essential factor for the establishment of pastures, and osmopriming under stress conditions may improve seed performance. This study was conducted at the Universidade Federal de Viçosa in a completely randomized design and aimed to evaluate the effects of osmopriming and its relationship with physical and physiological attributes of U. decumbens seeds subjected to water deficit. Seeds from ten lots were primed in H2O (0 MPa) and PEG (−0.8 MPa), KNO3 (0.2%), and SNP (0.10 mmol L−1) solutions for 24 hours. Unprimed seeds were used as control. The seeds were evaluated in two trials after osmopriming. Trial I consisted of the X-ray test to evaluate physical attributes and germination and vigor tests. In Trial II, the seeds were placed to germinate under favorable (0 MPa) and water deficit conditions (−0.2 MPa) to evaluate physiological attributes. In general, osmopriming of U. decumbens seeds assisted in increasing physical attributes such as area, gray scale, perimeter, and tissue density. Osmopriming does not contribute to the best physiological performance of U. decumbens seeds under ideal germination conditions (0 MPa). However, osmopriming with SNP (0.10 mmol L−1) and PEG (−0.8 MPa) for 24 hours contributes to the better physiological performance of seeds under water deficit.
“…The study in [66] used the Ilastik tool to categorize voids, fractures, and mineral grains in sandstone samples from Antarctica's McMurdo Dry Valleys. In [67] Ilastik was used to analyze seedling images, efficiently classify seed vigor, and demonstrate its capability to assess physiological potential within a short 7-day germination period. The researchers demonstrated in [68] that cisTEM's GPU-accelerated 2D template matching provides computational efficiency and scalability, enabling precise ribosome identification in Mycoplasma pneumoniae cells.…”
Accurate measurement of the microspores, mesopores, and macropores on the surface of the activated carbon is essential due to its direct influence on the material's adsorption capacity, surface area, and overall performance in various applications like water purification, air filtration, and gas separation. Traditionally, Scanning Electron Microscopy (SEM) images of activated carbons are collected and manually annotated by a human expert to differentiate and measure different pores in the surface. However, manual analysis of such surfaces is costly, time-consuming, and resource-intensive as requires supervision from experts. In this paper, we propose an automatic Deep-learning-based solution to address this challenge of activated carbon surface segmentation. We introduce a novel SEM Image segmentation dataset for activated carbon. We then evaluate the state-of-the-art deep learning models on the novel semantic segmentation task that shows promising results. Finally, we outline the key research challenges and discuss potential research directions to address these challenges.
“…Neste contexto, sementes do gênero Urochloa tem sido objeto de estudos recentes com processamento de imagens, através do qual dados biométricos das sementes são relacionados a suas informac ¸ões fisiológicas, e.g. porcentagem de germinac ¸ão, velocidade de emergência [Ramos et al 2022, de Freitas et al 2021. Em particular, imagens de raios X de Urochloa brizantha tem sido utilizadas para verificar a ocorrência de danos nas sementes durante seu beneficiamento [Silva et al 2022, Jeromini et al 2019.…”
A qualidade das sementes é essencial na agricultura. A busca por testes rápidos para aferir com acurácia o vigor das sementes é uma preocupação de empresas produtoras, para as quais o tempo de execução dos testes é um fator limitante. Este artigo aplica a arquitetura YOLOv8 para avaliar a qualidade de sementes de forma rápida, automatizada e não destrutiva. O método proposto utiliza imagens radiográficas de sementes braquiárias (Urochloa brizantha) para identificar e classificá-las com base em sua qualidade fisiológica. A rede YOLOv8 foi treinada com um conjunto de dados de imagens de sementes e os resultados mostraram uma alta precisão na identificação e classificação das mesmas, com métricas mAP50 e mAP50-95, respectivamente, 90.6% e 90.1% em relação a todas as classes.
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