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Języki publikacji
Abstrakty
The paper discusses the utilization of hyperspectral imaging in the process of assessing the quality of barley grain intended for brewing purposes. A specialized research setup comprising a spectrophotometer coupled with a CCD camera was employed. During measurements, the spectral distribution of each pixel in the image was recorded within the range of 400 to 1000 nm, enabling the extraction of homogeneous areas on the grain surfaces. Subsequently, surface texture parameters were computed on the designated areas. Prior to engaging in classification analyses, variable reduction was performed utilizing: (a) Fisher's coefficient, (b) classification error coefficient along with the averaged correlation coefficient POE+ACC, and (c) mutual information coefficient MI. The research material consisted of grain categorized into rain-soaked (B), mold -infested (M), and healthy (H). The best classification results were obtained for a wavelength of 800 nm from the extracted homogeneous areas. The classification accuracy reached 100% across all quality groups.
Słowa kluczowe
Rocznik
Tom
Strony
357--375
Opis fizyczny
Bibliogr. 16 poz., il., tab., wykr., zdj.
Twórcy
autor
- Katedra Inżynierii Systemów, Wydział Nauk Technicznych, Uniwersytet Warmińsko-Mazurski, ul. Heweliusza 14, 10-718 Olsztyn
Bibliografia
- BAURIEGEL E., GIEBEL A., GEYER M., SCHMIDT U., HERPPICH W. 2011. Early detection of Fusarium infection in wheat using hyper-spectral imaging. Computer and Electronics in Agriculture, 75(2): 304-312. https://doi.org/10.1016/j.compag.2010.12.006
- COGDILL R.P., HURBURGH C.R., RIPPKE G.R., BAJIC S.J.R., JONES W., MCCLELLAND J.F.T., JENSEN C., LIU J. 2004. Single-kernel maize analysis by near-infrared hyperspectral imaging. Transactions of the ASAE, 47(1): 311-320. https://doi.org/10.13031/2013.15856
- DELWICHE S.R., KIM M.S. 2000. Hyperspectral imaging for detection of scab in wheat. In: Biological Quality and Precision Agriculture II. Eds. J.A. DeShazer, G.E. Meyer. Proceedings Volume, 4203. Environmental and Industrial Sensing. https://doi.org/10.1117/12.411752
- DELWICHE S.R., KIM M.S., DONG Y. 2010. Damage and quality assessment in wheat by NIR hyperspectral imaging. In: Sensing for agriculture and food quality and safety II. Eds. M.S. Kim, S.-I. Tu, K. Chao. Proceedings Volume, 7676. SPIE Defense, Security, and Sensing. https://doi.org/10.1117/12.851150
- DELWICHE S.R., KIM M.S., DONG Y. 2011. Fusarium damage assessment in wheat kernels by Vis/NIR hyperspectral imaging. Sensing and Instrumentation for Food Quality and Safety, 5(2): 63-71. https://doi.org/10.1007/s11694-011-9112-x
- DOWELL F.E., RAM M.S., SEITZ L.M. 1999. Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy. Cereal Chemistry, 76(4): 573-576. https://doi.org/10.1094/CCHEM.1999.76.4.573
- GĄSIOROWSKI H. 1997. Jęczmień. Chemia i technologia. Wyd. I. Państwowe Wydawnictwo Rolnicze i Leśne, Poznań.
- GIROLAMO A. DE, LIPPOLIS V., NORDKVIST E., VISCONTI A. 2009. Rapid and non-invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Near Infrared (FT-NIR) spectroscopy. Food Additives & Contaminants. Part A. Chemistry, Analysis, Control, Exposure and Risk Assessment, 26(6): 907-917. https://doi.org/10.1080/02652030902788946
- NG H.F., WILCKE W.F., MOREY R.V., LANG J.P. 1998. Machine vision evaluation of corn kernel mechanical and mold damage. Transactions of the ASAE, 41(2): 415-420. https://doi.org/10.13031/2013.17166
- PEARSON T.C., WICKLOW D.T. 2006. Detection of corn kernels infected by fungi. Transactions of the ASABE, 49(4): 1235-1245. https://doi.org/10.13031/2013.21723
- POLDER G., HEIJDEN G.W.A.M. VAN DER, WAALWIJK C., YOUNG I.T. 2005. Detection of Fusarium in single wheat kernels using spectral imaging. Seed Science & Technology, 33(3): 655-668. https://doi.org/10.15258/sst.2005.33.3.13
- SINGH C.B., JAYAS D.S., PALIWAL J., WHITE N.D.G. 2012. Fungal damage detection in wheat using short-wave near-infrared hyperspectral and digital colour imaging. International Journal of Food Properties, 15(1): 11-24. https://doi.org/10.1080/10942911003687223
- SINGH C.B., JAYAS D.S., PALIWAL J., WHITE N.D.G. 2007. Fungal detection in wheat using near-infrared hyperspectral imaging. Transactions of the ASABE, 50(6): 2171-2176. https://doi.org/10.13031/2013.24077
- TADEUSIEWICZ R., KOROHODA P. 1997. Komputerowa analiza i przetwarzanie obrazów. Wydawnictwo Fundacji Postępu Telekomunikacji, Kraków.
- THOMAS S., WAHABZADA M., KUSKA M.T., RASCHER U., MAHLEIN A.K. 2017. Observation
- Thomas S., Wahabzada M., Kuska M.T., Rascher U., Mahlein A.K. 2017. Observation of plant–pathogen interaction by simultaneous hyperspectral imaging reflection and transmission measurements. Functional Plant Biology, 44(1): 23-34. https://doi.org/10.1071/FP16127
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4497cabc-d3e8-4a6b-b9be-650222919e94
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