Near infrared imaging to detect Aspergillus flavus infection in three varieties of dates

Abdel Moitte, 2010, Sorption isotherms behaviour of some egyptian date fruit varieties, World J. Dairy Food Sci., 8, 74 Al-Janobi, 2010 Al-Jasser, 2010, Effect of storage temperatures on microbial load of some dates palm fruit sold in Saudi Arabia market, Afr. J. Food Sci., 4, 359 Al-Mezeini, 2015, X-ray imaging of stored dates to detect infestation by saw-toothed beetles, Int. J. Fruit Sci., 16, 42, 10.1080/15538362.2015.1044692 Al-Ohali, 2011, Computer vision based date fruit grading system: design and implementation, J. King Saud Univ. Comp. Inform. Sci., 23, 29 Al-Rahbi, 2015, Back propagation neural network (bpnn) to detect surface crack on dates using RGB images, J. Med. Bioeng., 4, 67 Al-Rahbi, 2013, Detecting surface cracks on dates using color imaging technique, Food Sci. Technol. Res., 19, 795, 10.3136/fstr.19.795 Dull, 1991, The near infrared determination of moisture in whole dates, Am. Soc. Horticult. Sci., 26, 1303 Fadel, 2006, Fruit color properties of different cultivars of dates (Phoenix dactylifera, L.,), Agric. Eng. Int. CIGR Ejournal, VIII, 1 Gabriel, 2015, Bit plane slicing technique to classify date varieties, AgricEngInt : CIGR J., 17, 267 Gonzalez, 2011 Gowen, 2010, Applications of thermal imaging in food quality and safety assessment, Trends Food Sci. Technol., 21, 190, 10.1016/j.tifs.2009.12.002 Hahn, 2004, Spectral detection and neural network discrimination of Rhizopus stolonifer spores on red tomatoes, Biosyst. Eng., 89, 93, 10.1016/j.biosystemseng.2004.02.012 Hamad, 2012, The microbial quality of processed date fruits collected from a factory in Al-Hofuf city, Kingdom of Saudi Arabia, Emir. J. Food Agric., 24, 105 Hasnaoui, 2010, Chemical composition and microbial quality of dates grown in figuig oasis of Morocco, Int. J. Agric. Biol., 12, 311 Hasnaoui, 2011, Physicochemical characterization, classification and quality evaluation of date palm fruits of some of date palm fruits of some Moroccan cultivars, J. Sci. Res., 3, 139, 10.3329/jsr.v3i1.6062 Hedayati, 2007, Aspergillus flavus: human pathogen, allergen and mycotoxin producer, Microbiology, 153, 1677, 10.1099/mic.0.2007/007641-0 Hosseini, 2012, Some major mycotoxin and their mycotoxicosis in nuts and dried fruits, Int. J. Agron. Plant Prod., 3, 179 Ibrahim, 2009, Isolation and identification of fungi associated with date fruits (Phoenix dactylifera, LINN.) sold at Bayero University, Kano, Nigeria, Bayero J. Pure Appl. Sci., 2, 127 Lee, 2008, Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging, J. Food Eng., 86, 388, 10.1016/j.jfoodeng.2007.10.021 Mahesh, 2008, Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes, Biosyst. Eng., 101, 50, 10.1016/j.biosystemseng.2008.05.017 Manickavasagan, 2008, Wheat class identification using monochrome images, J. Cereal. Sci., 47, 518, 10.1016/j.jcs.2007.06.008 Manickavasagan, 2014, RGB color imaging technique for grading of dates, Sci. Hortic., 175, 87, 10.1016/j.scienta.2014.06.003 Manickavasagan, 2014, Edge detection features to evaluate hardness of dates using monochrome images, Food Bioprocess Technol., 7, 2251, 10.1007/s11947-013-1219-0 Manickavasagan, 2014, Non-destructive measurement of total soluble solid (TSS) content of dates using NIR imaging, Emir. J. Food Agric., 26, 970, 10.9755/ejfa.v26i11.18102 Manickavasagan, 2015, Computer vision techniques for quality assessment of dates, Int. Res. J. Elect. Comp. Eng., 1, 7, 10.24178/irjece.2015.1.2.07 Manickavasagn, 2012, Quality assessment of dates by computer vision technology, 217 Mireei, 2010, Non-destructive measurement of moisture and soluble solids content of mazafati date fruit by NIR spectroscopy, Aust. J. Crop. Sci., 4, 175 Mohana, 2014, A novel technique for grading of dates using shape and texture features, Machine Learning Appl.: Int. J., 1, 15 Mousa, 2011, Modelling the effect of water activity and temperature on growth rate and aflatoxin production by two isolates of Aspergillus flavus on paddy, J. Appl. Microbiol., 111, 1262, 10.1111/j.1365-2672.2011.05134.x Muhammed, 2015, Date fruits classification using texture descriptors and shape-size features, Eng. Appl. Artif. Intell., 37, 361, 10.1016/j.engappai.2014.10.001 Pourdarbani, 2015, Study on an automatic sorting system for Date fruits, Journal of the Saudi Society of Agricultural Sciences, 14, 83, 10.1016/j.jssas.2013.08.006 Rahman, 2004, Susceptibility of some varieties of date fruits to support the production of aflatoxins: analysis by high performance liquid chromatography, Pakistan J. Biol. Sci., 7, 1937, 10.3923/pjbs.2004.1937.1941 Schmilovitch, 1999, Maturity determination of fresh dates by near infrared spectroscopy, J. Sci. Food Agric., 79, 86, 10.1002/(SICI)1097-0010(199901)79:1<86::AID-JSFA175>3.0.CO;2-R Senthilkumar, 2012, Detection of fungal infection in canola using near-infrared hyperspectral imaging, J. Agri. Eng., 49, 21 Shenasi, 2002, Microflora of date fruits and production of aflatoxins at various stages of maturation, Int. J. Food Microbiol., 79, 113, 10.1016/S0168-1605(02)00185-X Singh, 2007, Fungal detection in wheat using near-infrared hyperspectral imaging, Trans. ASABE, 50, 2171, 10.13031/2013.24077 Teena, 2013, Potential of machine vision techniques for detecting fecal and microbial contamination of food products: a review, Food Bioprocess Technol., 6, 1621, 10.1007/s11947-013-1079-7 Teena, 2014, Near infrared (NIR) hyperspectral imaging to classify fungal infected date fruits, J. Stored Prod. Res., 59, 306, 10.1016/j.jspr.2014.09.005 Teena, 2016, RGB color imaging to detect Aspergillus flavus infection in dates, Emir. J. Food Agric., 28, 683, 10.9755/ejfa.2016-01-070