Visible and Near-Infrared Hyperspectral Imaging for Cooking Loss Classification of Fresh Broiler Breast Fillets  
[PERSON]  
1 College of Engineering, China Agricultural University, Beijing 100083, China;  
[EMAIL_ADDRESS] (H.J. ); [EMAIL_ADDRESS] (Y.Y.) [PERSON]  
1 College of Engineering, China Agricultural University, Beijing 100083, China;  
[EMAIL_ADDRESS] (H.J. ); [EMAIL_ADDRESS] (Y.Y.) [PERSON]  
2 Quality & Safety Assessment Research Unit, U.S. National Poultry Research Center, USDA-ARS, 950 College Station Rd., Athens, GA 30605, USA; [EMAIL_ADDRESS] (H.Z. );  
[EMAIL_ADDRESS] (S.Y.) [PERSON]  
3 State Environmental Protection Engineering Center for Mercury Pollution Prevention and Control, and CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China  
34 Correspondence: [EMAIL_ADDRESS] (W.W. Cooking loss (CL, %), one of the methods for water-holding capacity (WHC) determination, is measured as the weight loss of water and soluble matter from the meat during cooking [2]. From a sensory point of view, CL is important because it is negatively correlated with eating quality, including meat juiciness [2]. Thus, evaluating the CL of meat is of interest not only to optimize the eating quality but also for economic reasons. It is well known that most of the water in living muscle is held within the myofibrils, and the CL is mainly due to weight loss caused by protein denaturation and a series of structural changes that occur in myofibrils during heating in cooking [3]. However, other factors, including ultimate pH and concentration of glycogen, could also influence the CL [4], but it so far this is not quite clear. Traditionally, the CL is measured as the weight difference (as a percentage) before and after cooking [5]. Although it can provide reliable information on CL, this reference method is laborious, time-consuming, invasive, and must be conducted on the basis of cooked meat. Therefore, the development of an efficient, rapid, and non-destructive technique to assess CL, especially with respect to fresh intact chicken meat, is extremely desirable. Near-infrared (NIR) spectroscopy has been successfully tested as an efficient and rapid method for meat quality assessment [6; 7; 8]. However, thus far attempts to assess meat CL are few and have not been very successful [9; 10; 11; 12]. It may be speculated that this conventional NIR spectroscopic method is limited by the small sample area (limited spatial information) which is not representative of the CL of the whole heterogeneous meat sample. Hyperspectral imaging (HSI) is an emerging, rapid, and non-contact analytical method that combines conventional spectroscopy and imaging in a single system to acquire spectral and spatial information simultaneously from the target. Although the HSI was originally developed for remote sensing applications, it has received ample attention in many kinds of agro-foods [13] such as cereals [14; 15; 16], fruits [17; 18], vegetables [19; 20], eggs [21], and many other animal or plant products [22; 23]. Recently, in the meat industry, considerable research endeavors have been conducted with respect to meat and meat products. The reason could be that when the hyperspectral data are appropriately processed, it is possible to automatically identify the location of features that display specific spectral characteristics and to map the gradients or classes to show spatial distribution of specific attributes such as color, texture, water, fat, and protein. In the literature, reports have proved that HSI could be successfully implemented in qualitative or quantitative analysis in evaluating the quality and safety traits of pork [24; 25; 26], beef [27; 28], lamb [29], and fish [30]. For chicken meat in particular, HSI was also attempted for evaluating springiness [31], freshness [32], bacterial load [33; 34], surface contamination [35], and hydroxyproline content [36].