Woody breast (WB), one of the major muscular myopathies in poultry, impairs the quality and marketability of poultry products, leading to significant economic losses for poultry industries worldwide due to product downgrading and consumer complaints. WB-affected broiler breast fillets are characterized by abnormal tissue hardness, muscle rigidity, and irregular shape profiles. Manual evaluation based on tactile palpation and visual examination is the current practice for WB assessment at poultry processing facilities, but it is subjective, labor-intensive, and may cause contamination or safety concerns due to physical contact for evaluation. This thesis aimed to investigate the applicability of two emerging optical imaging technologies, i.e., 1) light scattering imaging (LSI) and 2) sinusoidal illumination reflectance imaging (SIRI), under both broadband and multispectral modes, for assessing WB myopathy in broiler breast fillets. The corresponding broadband and multispectral images were collected using custom-assembled imaging platforms from broiler meat samples of varying WB conditions, respectively. Different types of features were extracted from the resultant images (i.e., scattering images and demodulated SIRI images) and then utilized for discriminant modeling to classify samples into two [i.e., “Normal (no WB)” and “Defective”] and three [i.e., “Normal (no WB)”, “Moderate”, “Severe”] categories according to WB conditions. Two imaging technologies, i.e., LSI and SIRI, implemented in both broadband and multispectral modes have shown promising potential for the detection of WB defects in broiler breast fillets. More research is needed to further enhance the performance of WB assessment.
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