# Infrared Spectroscopy-Quo Vadis?
## 3 Infrared Spectroscopy: The Present
Therefore, progress towards non-invasive diabetes care based on extended IR spectroscopy will be within reach in the next few of years. Additionally, PAS facilitates the acquisition of depth profiles of organic tissue and thus enables tomographic imaging. Here, screening for skin cancer is an important and emerging field for the application of IR spectroscopy. At present, MIR spectroscopy is strongly connected to the latest developments in imaging technologies such as MIR microscopy. Previously, scanning techniques were realized by coupling an FTIR spectrometer to a movable ATR tip scanner or to a sharp atomic force microscopy (AFM) tip in so-called Nano-FTIR setups that are based on scattering type near field scanning near field optical microscopy (s-SNOM) techniques. With the increasing availability of matrix detectors such as MCT arrays or micro-bolometer arrays in combination with fast scanning lasers, IR hyperspectral imaging has emerged from silicon based NIR techniques further into the MIR and have become a current hot-topic and will still be important in the near future. As rapid image acquisition in reflection and transmission mode has become available, the application of this in medicine, surveillance and even defence is steadily increasing [75]. The combination with label-free and cost-effective detection based on minimal sample volumes makes IR spectroscopy especially suitable for routine clinical laboratory applications [76]. Considerable efforts have been made in recent years in FTIR spectroscopic imaging to study things such as the imaging of biopsy tissues [77], fixed cells [78] and live cells [79; 80], including cancer cells [81]. In particular, synchrotron infrared sources coupled to FT-IR microscopy have immense potential for clinical research [82]. However, the long wavelengths of infrared radiation commonly limit lateral resolution in IR imaging. Very recently, smart concepts have been developed to surpass this limitation by exploiting the optical photothermal effect (O-PTIR) [83]. By using visible light as a probe, higher lateral resolution down to the submicron range is achieved for IR imaging and, as a side-effect, Raman scattering may be acquired in the very same experiment [84]. However, energy input is a major issue that hat to be considered when dealing with sensitive samples, as the ineffective Raman scattering process requires a considerable amount of photon flux. The rich information in the NIR and especially MIR spectra often results in complex spectra. Hence, the interpretation of IR spectra greatly benefits from emerging powerful algorithms and software designed for interpretation and data mining. Tools that have been developed several years ago, such as the partial least squares (PLS) algorithm and principal components (PC) analysis have made their transition from specialized applications to a broad stakeholder community. Together with tools like random forests, K-nearest neighbours (KNN) or support vector machines (SVM), chemometrics with multivariate statistic tools, as well as more advanced extreme learning machines (ELM) [85; 86] have become a main part of an IR spectroscopists tools in a variety of different applications [87; 88; 89; 90; 91; 92; 93; 94]. Consequently, analytical application scenarios that have been dominated by highly sensitive hyphenated instruments like gas chromatography coupled to mass spectroscopy (GC-MS) are increasingly interested in IR spectroscopic alternatives. In application fields such as food monitoring, IR spectroscopy may provide a fast, simple to operate, inexpensive to maintain and non-destructive method with highly reliable results. First emerging applications of IR spectroscopy classifying mycotoxin spoilage based on regulatory limits pave the way for more wide spread application of IR spectroscopy in associated fields of profession such as life sciences, production of pharmaceuticals and polymer research.