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Título: Digital image processing and spectral data source in seed analysis
Palavras-chave: Image analysis
Image processing
Seed quality
Processamento digital de imagens
Análise de imagem
Sementes - Análise
Sementes - Qualidade
Data do documento: 2020
Editor: CABI
Citação: SCHNEIDER, B. de O.; ALVES, M. de C. Digital image processing and spectral data source in seed analysis. CAB Reviews, Wallingford, n. 40, p. 1-6, 2020. DOI: 10.1079/PAVSNNR202015040.
Resumo: Image processing is currently gaining lots of attention at seed quality labs as well as grain quality labs for being nondestructive, faster, and more objective than traditional seed or grain analysis methods. While seed analysts focus on quality parameters that will ensure vigorous plants, grain analysts focus on parameters related to safety or grading of the grain using roughly the same methods. We observed that few techniques on image processing have been used and that image data source roughly shapes research work done. The main data sources are visible light, hyperspectral imaging in the infrared section, and X-ray. Laser speckle is not so common but was also included. We have also noted that ultrasound imaging and magnetic resonance are also used for analysis, but these data sources were left out because of little work found.
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