Nondestructive Quality Evaluation Techniques

Abstract Food quality and safety are directly related to human nutrition and health. The need for accurate, quick, and objective determination of various quality affecting factors, such as external factors (appearance—size, shape, color, or gloss and texture) and internal factors (physical, chemical, and biological), is expected to rise with the increase in demand for healthy foods. Food quality can be assessed, evaluated, and controlled using destructive and nondestructive methods. Generally, the food sample is lost after evaluation by the destructive methods. Using nondestructive quality evaluation techniques, food samples can be analyzed without affecting the food system. These instrumental methods are categorized under the objective measuring techniques. In recent years, these nondestructive quality evaluation methods have become a powerful tool, particularly due to the recent developments in computer hardware systems. This article presents the fundamentals of nondestructive quality evaluation techniques and highlights the different methods of nondestructive quality evaluation techniques, namely X-rays, hyperspectral imaging, and near-infrared imaging.

[1]  Peter Meinlschmidt,et al.  Thermographic techniques and adapted algorithms for automatic detection of foreign bodies in food , 2003, SPIE Defense + Commercial Sensing.

[2]  P. Zerbini Emerging technologies for non-destructive quality evaluation of fruit , 2006 .

[3]  Colm P. O'Donnell,et al.  Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .

[4]  Lembe S. Magwaza,et al.  Non-destructive characterization and volume estimation of pomegranate fruit external and internal morphological fractions using X-ray computed tomography , 2016 .

[5]  D. Jayas,et al.  Detection of fungal infection in five different pulses using near-infrared hyperspectral imaging , 2016 .

[6]  Gamal ElMasry,et al.  Principles of Hyperspectral Imaging Technology , 2010 .

[7]  Digvir S. Jayas,et al.  Classification of vitreousness in durum wheat using soft X-rays and transmitted light images , 2006 .

[8]  Gamal ElMasry,et al.  Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging , 2011 .

[9]  Anton du Plessis,et al.  Non-destructive Estimation of Maize (Zea mays L.) Kernel Hardness by Means of an X-ray Micro-computed Tomography (μCT) Density Calibration , 2015, Food and Bioprocess Technology.

[10]  Sunil K Mathanker,et al.  X-Ray Applications in Food and Agriculture: A Review , 2013 .

[11]  Christoph Reh An Overview of Nondestructive Sensor Technology in Practice: The User's View , 2008 .

[12]  Noel D.G. White,et al.  Assessment of soft X-ray imaging for detection of fungal infection in wheat , 2009 .

[13]  R. C. Murry,et al.  Christensen's physics of diagnostic radiology , 1990 .

[14]  Rafael Font,et al.  Quantification of glucosinolates in leaves of leaf rape (Brassica napus ssp. pabularia) by near-infrared spectroscopy. , 2005, Phytochemistry.

[15]  Xiwei Wang,et al.  Structuring Image Templates for Identification of Foreign Object in Food in Shielding Packages Based On Wavelet Transforms , 2010 .

[16]  Natsuko Toyofuku,et al.  X-ray detection of defects and contaminants in the food industry , 2008 .

[17]  Aldo Cipriano,et al.  Automated fish bone detection using X-ray imaging , 2011 .

[18]  Irwin R. Donis-González,et al.  Internal characterisation of fresh agricultural products using traditional and ultrafast electron beam X-ray computed tomography imaging☆ , 2014 .

[19]  Jan Sijbers,et al.  A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs , 2016 .

[20]  Franz Pfeiffer,et al.  Novelty detection of foreign objects in food using multi-modal X-ray imaging , 2016 .

[21]  J. Abbott Quality measurement of fruits and vegetables , 1999 .

[22]  F. J. García-Ramos,et al.  Non-destructive technologies for fruit and vegetable size determination - a review , 2009 .

[23]  Shyam Narayan Jha,et al.  Nondestructive Evaluation of Food Quality , 2010 .

[24]  Di Wu,et al.  Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications , 2013 .

[25]  Noel D.G. White,et al.  Detection techniques for stored-product insects in grain , 2007 .

[26]  Nachiket Kotwaliwale,et al.  Radiography, CT and MRI , 2010 .

[27]  Guang Li,et al.  Tea Classification Based on Artificial Olfaction Using Bionic Olfactory Neural Network , 2006, ISNN.

[28]  E A Navajas,et al.  Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. , 2010, Meat science.

[29]  Efstathios Z. Panagou,et al.  Data mining derived from food analyses using non-invasive/non-destructive analytical techniques; determination of food authenticity, quality & safety in tandem with computer science disciplines , 2016 .

[30]  A. Peirs,et al.  Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .

[31]  Assessment of intramuscular fat level and distribution in beef muscles using X-ray microcomputed tomography. , 2010, Meat science.

[32]  Hanna Piekarska-Boniecka,et al.  Detection of the granary weevil based on X-ray images of damaged wheat kernels , 2014 .

[33]  Behrouz Tousi,et al.  Usage of Fruit Response to Both Force and Forced Vibration Applied to Assess Fruit Firmness-a Review , 2011 .

[34]  Martine Wevers,et al.  Comparison of X-ray CT and MRI of watercore disorder of different apple cultivars , 2014 .

[35]  Sundaram Gunasekaran,et al.  Computer Vision Systems , 2010 .

[36]  K. Alagusundaram,et al.  Quality analysis of mango fruit with fruit fly insect by non-destructive soft X-ray method. , 2015 .

[37]  Yibin Ying,et al.  Food Safety Evaluation Based on Near Infrared Spectroscopy and Imaging: A Review , 2016, Critical reviews in food science and nutrition.

[38]  Noel D.G. White,et al.  Detection of fungal infection and Ochratoxin A contamination in stored barley using near-infrared hyperspectral imaging , 2016 .

[39]  Da-Wen Sun,et al.  Improving quality inspection of food products by computer vision: a review , 2004 .

[40]  S. Jha Near Infrared Spectroscopy , 2010 .

[41]  Yong He,et al.  Theory and application of near infrared reflectance spectroscopy in determination of food quality , 2007 .

[42]  Andrew Webb,et al.  Introduction to Medical Imaging: Physics, Engineering and Clinical Applications , 2010 .

[43]  Neeraj Seth,et al.  X-ray imaging methods for internal quality evaluation of agricultural produce , 2011, Journal of Food Science and Technology.

[44]  Quansheng Chen,et al.  Recent advances in emerging imaging techniques for non-destructive detection of food quality and safety , 2013 .

[45]  Marcelo Blanco,et al.  NIR spectroscopy: a rapid-response analytical tool , 2002 .