## 2 Materials and Methods
### Data Acquisition and Data Set for Model Development  
The 12 broiler breast fillet samples were split randomly into two fillet sets with six fillets in each set. Each fillet was placed on a sample plate covered with a food-grade conveyor belt piece (blue color). The fillets were used as clean/normal samples first and then contaminated/abnormal samples. The difference between two fillet sets was on the size of FMs when contaminating the fillets: large (\(5\times 5\) mm\({}^{2}\)) versus small (\(2\times 2\) mm\({}^{2}\)). Both sides (bone-side and skin-side) of a fillet were imaged without and with FMs using VNIR and SWIR imaging systems, sequentially one by one.  
First, both sides of each clean fillet were scanned without FMs. Then, all 12 fillets were contaminated with FMs and scanned again. If a fillet belonged to the fillet set for the large FMs, the fillet was contaminated with \(5\times 5\) mm\({}^{2}\) FM samples, as shown in Figure 1a. Otherwise, the fillet was contaminated with \(2\times 2\) mm\({}^{2}\) FM samples, as shown in Figure 1b. The large FM samples in Figure 1a were placed set by set (Set 1-6) on both sides (one at a time) of a fillet in five different locations, as shown in Figure 2a such that different FM samples were spatially grouped in each location (far left, far right, top, bottom, and middle)without touching each other. The small FM samples in Figure 1b were placed set by set (Set 1-6) on both sides (one at a time) of a filled randomly without touching each other. Each fillet within the fillet set for the large FMs had 25 FM samples on its surface, whereas each fillet within the fillet set for the small FMs had 50 FM samples on its surface. Note that the FM pieces were firmly pressed down on the fillet surface so that the FMs did not fall off. This sample preparation protocol was designed for a worst-case scenario of the surface FMs because the spectral signals of the meat right beneath the surface FMs could be easily mixed with the reflectance spectra of the pure FMs. The above experimental design resulted in a total of 96 hyperspectral images from two fillet sets \(\times\) six fillets per fillet set \(\times\) (clean and contaminated surfaces) \(\times\) two sides per fillet \(\times\) (VNIR and SWIR imaging modalities). The 48 hyperspectral images (24 VNIR and 24 SWIR images) obtained from the fillet set for the large FMs were used as a training set for model development and validation to create pure spectral data reliably from the large FM areas. The other 48 hyperspectral images (24 VNIR and 24 SWIR images) obtained from the fillet set for the small FMs were set aside as a separate test set for evaluation of model performance and determination of detection limit. The chicken samples for training and test sets were selected by random sampling whereas the FM samples were selected by stratified sampling. The total number of FMs in each of FM Groups (see Table 1 for the Groups) was 40 (metal), 20 (wood), and 170 (polymer) for the training set, and 80 (metal), 40 (wood), and 340 (polymer) for the test set, respectively.  
Spectral data of the fillet and large FM samples for the training set were measured with the spectrometer. Each sample was measured in three different locations within the sample. Muscle tissue surfaces at bone and skin sides and fatty areas were probed with each fillet sample. Thus, we obtained 54 spectra from the six breast fillets (six fillets \(\times\) (two sides for muscle + skin-side for fat) \(\times\) three repeats) and 90 spectra from the 30 FM samples (30 large FMs \(\times\) three repeats).