Spectroscopy offers several advantages for metabolic flux analysis, such as high sensitivity and specificity, non-invasive and non-destructive measurements, and multiplexing and parallelization capabilities. However, spectroscopy also has some limitations, such as high cost and complexity, low spatial and temporal resolution, and interference and noise. Spectroscopy can detect and distinguish very low concentrations of labeled metabolites, and discriminate between different isotopes and molecular structures without requiring any chemical or physical modification of the sample. It can also measure multiple metabolites and pathways simultaneously to perform high-throughput analysis of many samples. On the flip side, spectroscopy requires expensive and sophisticated instruments and software, as well as skilled operators and analysts. Additionally, it cannot capture the spatial distribution and temporal dynamics of metabolic flux at the cellular or subcellular level, often requiring long sampling times and large sample volumes. Furthermore, it may be affected by the background signal, the matrix effect, or the overlapping spectra of different metabolites, necessitating calibration and normalization.