## 5 Conclusions and Perspectives

Table 4: _Cont._data, the application of only one device (in some cases) is not enough to cover all the critical points (after each processing step), the whole sample surface (big samples and/or stacked products), and detect foreign substances covered by the mass of a product (as in leafy fresh-cut samples, Section 4.1). In these circumstances, considering the application of several hyperspectral devices, the costs become prohibitive for most companies. Currently, cost reduction is challenging and one of the main topics in HSI research studies. The first solution has been to build low-cost multispectral systems based on selected wavelengths identified by preliminary studies. Such an approach, although effective, extremely reduces the versatility of the instrument (which needs a recustomization if applied on different products and/or parameters) and the capability to refine the model. For these reasons, further studies have to continue in order to develop compact and cost-effective HSI devices to exponentially increase the versatility of applications. In the last ten years, thanks to technological advancement and the development of silicon detectors used for the mass production of photographic instruments (i.e., commercial cameras and smartphones), researchers started to develop snapshot-based systems since they own a high optical throughput associated with an absence of artefacts due to scanning motion and an increased compactness due to no moving components. Since the optical range covered by silicon detectors (about 400-1000 nm) is the most used in the literature (Table 4) for fresh-cut production purposes, this technique offers a very promising solution to pre- and postharvest real-time imaging. However, the lower spatial and spectral resolution provided is still a key element to be studied. One of the first works was proposed by [PERSON] et al. (2012). The authors proposed a low-cost and compact spectral imaging Vis/NIR camera (design based on an unmodified consumer camera, Figure 13) with a mid-resolution hyperspectral mode that allows the spectral measurement of a whole image, with up to 5 nm spectral resolution and 120 \(\times\) 120 spatial resolution. This \"snapshot\" system is based on the principles used in computed tomography. Computed tomography imaging spectrometers (CTISs) use a transmissive diffraction grating to split the incoming light into a number of spectral projections onto a single image plane. Then, spectra are recovered by solving an underdetermined linear system [88]. On the same wave, [PERSON] and [PERSON] in 2020 took advantage of modern small-size high-resolution cameras (Raspberry PI NoIR camera), electronics, and optics to develop a robust low-cost HSI device (Figure 14), which weighs up to 300 g, detects wavelengths from 400 nm-1052 nm, and generates up to 315 different wavebands with a spectral resolution up to 2 nm and a spatial resolution of 116 \(\times\) 110 pixels. Figure 13: HSI device proposed by [PERSON] et al. (2012): (**a**) assembled CTIS camera objective; (**b**) prototype camera objective (**top**) and principal optical path (**bottom**). Reprinted with permission from Ref. [88]. 2012, Elsevier. Although the authors proposed a very interesting plug-and-play HSI solution combined with a user-friendly GUI, the system shows a low-spectral outcome in the SWNIR region (750-1000 nm), suggesting a reduced analytical capability in food quality inspection. The use of this type of transmissive holographic double-axis diffraction grating (Figure 14) guarantees a significant cost reduction with a consistent loss of information in the SWNIR region. However, such devices could be used to develop new applicative solutions using a fleet of distributed HSI sensors able to collect hyperspectral information from different checking spots [89].