## 3 Results
### Method Validation  
Matrix effects are common in complicated matrix samples and can negatively impact the accuracy and precision of a method. Matrix effects occur when co-extracted matrix components interfere with ionization, leading to signal suppression or enhancement, which can cause inaccurate quantification [42]. Matrix effects were assessed by comparing the calibration curve slopes of real samples (\(\text{K}_{1}\)) to those of standard solutions (\(\text{K}_{2}\)), using the equation Matrix effects = (\(1-\text{K}_{1}/\text{K}_{2}\)) \(\times\) 100%. Matrix effects values ranging from \(-\)20% to 20% indicate slight signal suppression or enhancement, while values between \(-\)50% and 50% indicate moderate effects and values below \(-\)50% or greater than 50% indicate strong effects [26]. The matrix effects for the five target analytes ranged from 51.3% to 69.9%, indicating severe matrix effects in the milk and chicken samples. Therefore, matrix-matched calibration curves were employed to compensate for these matrix effects, which are common in complex food samples. By preparing calibration standards in the same matrix as the samples, this method accounts for matrix-induced variations in analyte response, ensuring accurate and reliable quantification [43]. This approach improves precision and accuracy, maintaining consistent sensitivity across batches and preventing over- or underestimation of analyte concentrations. Although using an internal standard is a widely recommended approach to further enhance precision and accuracy, it was not incorporated in this study because selecting  
Figure 7: SEM images of (**a,b**) the new SBA-15-SPME Arrow and (**c,d**) the SBA-15-SPME Arrow used for 50 cycles; (**e**) macro-photos of the new SBA-15-SPME Arrow and the SBA-15-SPME Arrow used for 50 cycles; (**f**) reusability of SBA-15-SPME Arrow. a single internal standard that can effectively compensate for the matrix effects and extraction efficiency of all five target analytes poses a challenge, as each compound has unique chemical properties. Instead, matrix-matched calibration was chosen as a more reliable and straightforward approach, effectively correcting for matrix-related biases and ensuring robust quantification. As shown in Table 2, the intra-day and inter-day RSDs were within acceptable ranges, demonstrating that the method achieves high reproducibility and precision without an internal standard. Future work will aim to investigate and incorporate appropriate internal standards for each class of veterinary drugs to further enhance the method's analytical performance. The linear range, correlation coefficient (R), limit of quantification (LOQ), limit of quantification (LOQ), and reproducibility of the SBA-15-SPME Arrow-PMS method obtained using the matrix-matched calibration strategy were evaluated, as shown in Table 2. The correlation coefficients (R) for all five targets were greater than 0.995. The LOD and LOQ, calculated based on signal-to-noise ratios of 3 and 10, respectively, ranged from 2.8 to 9.3 \(\upmu\) kg\({}^{-1}\) and from 10 to 28 \(\upmu\) kg\({}^{-1}\), respectively, in milk. The LOD and LOQ ranged from 3.5 to 11.7 \(\upmu\) kg\({}^{-1}\) and from 12 to 35 \(\upmu\) kg\({}^{-1}\), respectively, in chicken. All these results meet the requirements of the regulations of the European Union, the United States, and China (Table 3) [7; 8; 9]. Intraday and interday RSDs ranged from 3.2% to 10.3% and from 8.5% to 13.4%, respectively, indicating good precision.