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Weber C, Dai Pra AL, Passoni LI, et al. Determination of maize hardness by biospeckle and fuzzy granularity. Food Sci Nutr. 2014;2(5):557-64doi: 10.1002/fsn3.130.
Weber, C., Dai Pra, A. L., Passoni, L. I., Rabal, H. J., Trivi, M., & Poggio Aguerre, G. J. (2014). Determination of maize hardness by biospeckle and fuzzy granularity. Food science & nutrition, 2(5), 557-64. https://doi.org/10.1002/fsn3.130
Weber, Christian, et al. "Determination of maize hardness by biospeckle and fuzzy granularity." Food science & nutrition vol. 2,5 (2014): 557-64. doi: https://doi.org/10.1002/fsn3.130
Weber C, Dai Pra AL, Passoni LI, Rabal HJ, Trivi M, Poggio Aguerre GJ. Determination of maize hardness by biospeckle and fuzzy granularity. Food Sci Nutr. 2014 Sep;2(5):557-64. doi: 10.1002/fsn3.130. Epub 2014 Jun 02. PMID: 25473513; PMCID: PMC4237485.
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Food Sci Nutr. 2014 Sep;2(5):557-64. doi: 10.1002/fsn3.130. Epub 2014 Jun 02.

Determination of maize hardness by biospeckle and fuzzy granularity.

Food science & nutrition

Christian Weber, Ana L Dai Pra, Lucía I Passoni, Héctor J Rabal, Marcelo Trivi, Guillermo J Poggio Aguerre

Affiliations

  1. Facultad de Ciencias Agrarias y Forestales, Universidad Nacional de La Plata CC31 Correo Argentino, La Plata, 1900, Argentina ; Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC-PBA), Centro de Investigaciones Ópticas (CONICET La Plata-CIC) P.O. Box 3, Gonnet, La Plata, 1897, Argentina.
  2. Grupo de Inteligencia Artificial aplicada a Ingeniería, Departamento Matemática, Facultad de Ingeniería, Universidad Nacional de Mar del Plata Juan B. Justo 4302, Mar del Plata, 7600, Argentina.
  3. Laboratorio de Bioingeniería, Departamento Electrónica, Facultad de Ingeniería, Universidad Nacional de Mar del Plata Juan B. Justo 4302, Mar del Plata, 7600, Argentina.
  4. Centro de Investigaciones Ópticas (CONICET La Plata-CIC) and UID Optimo, Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de la Plata P.O. Box 3, Gonnet, La Plata, 1897, Argentina.
  5. Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC-PBA), Centro de Investigaciones Ópticas (CONICET La Plata-CIC) P.O. Box 3, Gonnet, La Plata, 1897, Argentina.

PMID: 25473513 PMCID: PMC4237485 DOI: 10.1002/fsn3.130

Abstract

In recent years there has been renewed interest in the development of novel grain classification methods that could complement traditional empirical tests. A speckle pattern occurs when a laser beam illuminates an optically rough surface that flickers when the object is active and is called biospeckle. In this work, we use laser biospeckle to classify maize (Zea mays L.) kernel hardness. A series of grains of three types of maize were cut and illuminated by a laser. A series of images were then registered, stored, and processed. These were compared with results obtained by floating test. The laser speckle technique was effective in discriminating the grains based on the presence of floury or vitreous endosperm and could be considered a feasible alternative to traditional floating methods. The results indicate that this methodology can distinguish floury and vitreous grains. Moreover, the assay showed higher discrimination capability than traditional tests. It could be potentially useful for maize classification and to increase the efficiency of processing dry milling corn.

Keywords: Biospeckle; dry milling; laser; maize hardness

References

  1. Eur Biophys J. 2004 Dec;33(8):694-9 - PubMed
  2. J Anim Sci. 2010 Apr;88(13 Suppl):E143-50 - PubMed
  3. J Sci Food Agric. 2010 Aug 30;90(11):1870-8 - PubMed

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