## 4 Conclusions  
In summary, FT-IR and Raman techniques fingerprinted maple syrup products based on their unique chemical composition, allowing for BBL and traditional maple syrup authentication. Both FT-IR and Raman systems combined with SIMCA provided non-destructive, fast, and accurate determination of quality traits in BBL and traditional maple  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Approach**} & \multirow{2}{*}{**Sugar**} & \multicolumn{6}{c}{**Training Model**} & \multicolumn{6}{c}{**External Validation Model**} \\ \cline{3-10}  & & **Range** & **N \({}^{\text{a}}\)** & **Factor** & **SECV \({}^{\text{b}}\)** & **Rcal** & **Range** & **N \({}^{\text{c}}\)** & **SEP \({}^{\text{d}}\)** & **Rval** \\ \hline \multirow{2}{*}{**FT-IR**} & \({}^{\circ}\)Brix & 39.3-78.7 & 30 & 5 & 0.56 & 0.99 & 65.2–78.4 & 7 & 0.88 & 0.98 \\  & **Sucrose** & 3.3–66.2 & 30 & 4 & 1.68 & 0.99 & 18.4–65.3 & 7 & 1.66 & 0.99 \\ \hline \multirow{2}{*}{**Raman**} & \({}^{\circ}\)Brix & 39.9–78.5 & 29 & 5 & 1.00 & 0.98 & 65.0–78.7 & 7 & 1.23 & 0.96 \\  & **Sucrose** & 3.5–66.6 & 30 & 3 & 1.69 & 0.99 & 17.5–65.1 & 7 & 1.67 & 0.99 \\ \hline \hline \end{tabular}  
* \({}^{\text{a}}\) Sample number in the training models. \({}^{\text{b}}\) Standard error of cross validation. \({}^{\text{c}}\) Sample number in the external validation models. \({}^{\text{d}}\) Standard error of prediction.  
\end{table}
Table 2: Statistics of partial least square regression (PLSR) models developed using a training (\(n=30\)) and an external validation (\(n=7\)) data set based on FT-IR and Raman spectral data for estimating Brix and sucrose contents in traditional maple syrups, BBL maple syrups, and table syrup samples.  
sgroups and detected potential maple syrup adulterants. Our results showed that 15% of commercial maple syrup (traditional and/or BBL) samples that were tested and labeled as \"pure\" exhibited unusual sugar and/or volatile profiles, and both FT-IR and Raman equipment discriminated these suspicious samples from the pure ones. Furthermore, both FT-IR and Raman, combined with PLSR, showed good predictions for all samples' total \"Brix and sucrose contents.  
K.Z.: methodology, validation, formal analysis, investigation, writing--original draft, visualization; D.P.A.: methodology, validation, writing--review and editing, supervision, project administration; L.E.R.-S.: conceptualization, validation, resources, writing--review and editing, supervision. All authors have read and agreed to the published version of the manuscript.  
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.  
Not applicable.  
The data used to support the findings of this study can be made available by the corresponding author upon request.  
We would like to thank Bissell Maple Farm, Jefferson, Ohio, for kindly providing maple syrup and BBL samples for our research.  
The authors declare no conflict of interest.  
Figure 11: Soft independent modeling of class analogy (SIMCA) projection plots of classification of authentic BBL samples from suspicious BBL and traditional maple syrup samples by GC-MS.