title: Feasibility study on nondestructively sensing meat's freshness using light scattering imaging technique.
abstract: Rich nutrient matrix meat is the first-choice source of animal protein for many people all over the world, but it is also highly susceptible to spoilage due to chemical and microbiological activities. In this work, we attempted the feasibility study of rapidly and nondestructively sensing meat's freshness using a light scattering technique. First, we developed the light scattering system for image acquisition. Next, texture analysis was used for extracting characteristic variables from the region of interest (ROI) of a scattering image. Finally, a novel classification algorithm adaptive boosting orthogonal linear discriminant analysis (AdaBoost-OLDA) was proposed for modeling, and compared with two classical classification algorithms linear discriminant analysis (LDA) and support vector machine (SVM). Experimental results showed that classification results by AdaBoost-OLDA algorithm are superior to LDA and SVM algorithms, and eventually achieved 100% classification rate in the calibration and prediction sets. This work demonstrates that the developed light scattering technique has the potential in noninvasively sensing meat's freshness.
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Huanhuan
authors.initials: H
authors.lastname: Li
authors.affiliation: Animal Science Department, North Dakota State University, Fargo, North Dakota, United States.
authors.forename: Xin
authors.initials: X
authors.lastname: Sun
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Wenxiu
authors.initials: W
authors.lastname: Pan
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Felix
authors.initials: F
authors.lastname: Kutsanedzie
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Jiewen
authors.initials: J
authors.lastname: Zhao
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China. Electronic address: q.s.chen@hotmail.com.
authors.forename: Quansheng
authors.initials: Q
authors.lastname: Chen
mesh_terms: D000818:Animals; D002138:Calibration; D004044:Dietary Proteins / Q000032:analysis; D016002:Discriminant Analysis; D000067493:Dynamic Light Scattering / Q000379:methods*; D005240:Feasibility Studies; D005506:Food Contamination; D005516:Food Microbiology; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008460:Meat / Q000032:analysis* / Q000382:microbiology; D015999:Multivariate Analysis; D060388:Support Vector Machine
chemical_list: D004044:Dietary Proteins
keywords: AdaBoost–OLDA; Freshness; Light scattering; Meat; Nondestructively sensing