## 1 Introduction  
The global breakfast cereal market was valued at more than USD 37 billion in 2016 and is estimated to reach USD 51 billion value in 2023 [1; 2; 3]. Breakfast cereals are widely consumed worldwide because they are easy to prepare while also providing essential micronutrients, including folic acid, vitamin C, iron, zinc, fibers, and, potentially, antioxidants and phytoestrogens [4]. On the other hand, the large amount of sugar added to some products can increase the risk of obesity and diabetes [4; 5] while reducing the overall nutritional quality of breakfast cereal [6]. According to the FDA, the difference between the laboratory analysis and the amount declared on the nutrition facts panel must be within \(\pm 20\%\) range to comply with regulations [7], and many store-bought breakfast cereals are reported to have significantly higher or lower sugar content than the label indicates [8]. Therefore, it is important to monitor and control the product's sugar content in every production step and at the end-product. Traditionally, sugar content analysis has been carried out using enzymes (invertase) [9], gas chromatography (GC) [10; 11], capillary electrophoresis [12], high-performance anion-exchange chromatography coupled with a pulsed amperometric detection (HPAEC-PAD) [13], or high-performance liquid chromatography (HPLC) [14; 15]. However, these techniques require lengthy sample preparation procedures and analysis time, use relatively expensive analytical equipment, generate hazardous waste, and produce results with varying accuracy, depending on personnel or operating conditions. Optical spectroscopy offers an alternative to the aforementioned methods for measuring the nutritional content of cereals. Spectroscopic methods enable simple, fast, high-throughput, and non-destructive analysis with high specificity. Vibrational spectroscopy, specifically mid-infrared (MIR) and near-infrared (NIR) spectroscopy, has demonstrated accurate quantification of a variety of compounds, including sugar, salt, _trans_-fat, total fat, and moisture content, fatty acid composition, free fatty acids, peroxide value, and \(p\)-anisidine value in breakfast cereals, infant cereals, snack foods, cake mixes, bakery products, and potato chips [16; 17; 18; 19; 20; 21; 22; 23; 24]. In recent years, advancements in optoelectronics and micro-electromechanical systems (MEMS) have enabled the development of miniaturized infrared spectrometers that can be used in the field and/or in-line to meet requirements for continuous quality control and process monitoring in industrial applications [25]. Sensor technologies based on handheld [26; 27; 28], portable [29; 30], pocket-size [31; 32] spectrometers have become more mainstream and have the potential to replace bulky benchtop systems. Currently, most handheld spectrometers on the market use silicon-based Charge Coupled Device (CCD) detectors, which provide readily available, low-cost instruments but are constrained to operating between 780 to 1400 nm. However, recent efforts to integrate on-chip MEMS-based Fourier Transform (FT) spectrometers with reliable light sources and extended indium gallium arsenide (InGaAs) photodetector arrays provide reliable performance for NIR signals out to 2600 nm [25]. Si-Ware Systems introduced the first miniaturized FT-NIR instrument utilizing a MEMS-based Michaelson interferometer operating between 1350 and 2560 nm built on a Si chip using lithographic techniques. This longer-wave spectral range offers more valuable spectroscopic signatures (first or second overtones and combination vibrations) and stronger absorptivity that enables a more highly accurate characterization of food quality traits than the shorter-wave spectral range [33; 34]. The combination of handheld, ruggedized NIR spectrometer technology with advanced chemometric algorithms enables handheld, accurate, and specific quantification of the nutritional content of food products.