## 5 Conclusions and Perspectives
Finally, recent advances in smartphone technologies have opened the door to the development of accessible highly portable HSI systems (Figure 15) capable of accurate, laboratory- and field-based hyperspectral data collection, providing a solid foundation for future developments of customized HSI tools for practical applications (i.e., quality inspection by operators in real-time) [90]. In this case, the authors adopted a linear transmissive diffraction grating which requires a movement system to analyze the entire sample and build the hypercube. Also, in this case, the spectral device is capable of covering the visible range (400-700 nm). Although the used diffraction grating has an efficiency of 20% in the SWNIR region, coupling this component with commercial smartphone cameras reduces the detectable optical range due to the presence of IR filters (used to reduce optical noise due to infrared radiation and improve image quality) commonly mounted in front of the camera detector. However, the possibility to develop cost-effective systems able to cover a wider spectral range (from 400 to 1000) is ongoing, even though the performance of these tools still needs to be carefully evaluated (both in controlled and operative conditions) to demonstrate real applicability within the complex production realities from pre- to postharvest. Indeed, the capability to retrieve visible information (from 400 to 750) is an interesting starting point to solve different issues (raised in Table 4) like color-browning, chilling injuries, shelf life, and chlorophyll content. Figure 14: HSI device proposed by [PERSON] and [PERSON] (2020): (1) Case; (2) Front lens holder; (3) Square aperture; (4) Spacer 1; (5) Spacer 2; (6) Transmissive diffraction grating; (7) Camera holder; (8) Spacer 3; (9) Extension; (10) Lid; (11) Raspberry Pi 3 B+; (12) Raspberry Pi NoIR V2 Camera 8 Megapixels; (13) Power Supply Connector; (14) Power On/Off Switch; (15) +10 Macro 52 mm Lens; (16) Lens 35 mm C Series. Edmund Optics, model 59872. Reprinted with permission from Ref. [89]. 2020, Elsevier. The arrival of this instrumentation in the scientific literature is the basis for the development of further real-time monitoring applications that allow the final introduction of this technology within the Industry 4.0 concept. The development of new, simple, and interconnected optical HSI systems (coupled with fast computing technologies based on parallel computing) would allow for the creation of the remote storage of optical databases, allowing for the continuous updating and refinement of the prediction performance of predictive models with the aim of continuously upgrading the control services at different and crucial steps from pre- to postharvest. S.V. : conceptualization, formal analysis, methodology, investigation, data curation, figure preparation, writing--original draft. A.T.: conceptualization, formal analysis, methodology, software, data curation, figure preparation, writing--review and editing. V.G. : conceptualization, methodology, writing--original draft, writing--review and editing, supervision. A.P. : investigation. A.C.: investigation. R.G. : conceptualization, writing--review and editing. R.B. : conceptualization, methodology, writing--original draft, writing--review and editing, supervision. All authors have read and agreed to the published version of the manuscript. Universita degli Studi di Milano funded this research according to two research projects entitled \"Development of a cost-effective IoT hyperspectral device for distributed and autonomous monitoring of vine crops\" (research program \"Agricolitura e ambiente: sfide e prospective\"), and \"BErires and leaves hyperspectral Imaging Camera on vine (BELCAvine)\" (Azione A-Linea 2-Piano di sostegno alla ricerca 2020). Moreover, this review is part of a PhD project funded by Programa Operativo Nazionale \"Ricerca e Innovazione\" 2014-2020--Action IV.S. \"Doctorates on green topics\" (PON). Not applicable. Figure 15: Schematic diagram proposed by [PERSON] et al.