# Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture
## 6 Conclusions  
Fostering the progress in plant sciences is undoubtedly a strategic goal for the forthcoming decades in order to comply with the increasing demand for agricultural products, fueled by a growing world population. Numerous biotic and abiotic environmental stresses impair crop productivity and lead to significant losses in agricultural yield worldwide. Additionally, many strains caused by global warming and human-intensive use of natural resources on the various ecosystems across the planet have already had a clear negative impact on the biodiversity of many species, starting with plants. Against this backdrop, there has been an increasing demand for more and high-throughput phenotyping on the plants' physiological responses and regulatory mechanisms under unfavorable conditions, which will allow early and effective intervention to avoid crop loss. Furthermore, the agro-food industry warrants new and smart tools that allow sustainable agriculture practices and smart management to produce crops with higher yield and quality required by the highly demanding markets and consumers and significantly reduce the current food loss. Numerous spectroscopic techniques, used in situ or remotely, have been proved to comply with these requests, and seem to become more and more helpful towards the major challenges comprised in plant sciences fundamental and applied research, as well as in various applications already claimed by precision agriculture. They have already granted the development of effective tools capable of studying plant physiology and reporting stress events, and provided many devices used in the management of various crops supply chains. However, there is still much to investigate regarding these systems' accuracy and robustness and their resulting cost-benefit to make their access by end users easier and to grant significant advances in high-throughput phenomics. The latter need to occur across scales of phenotyping platforms to sustain and improve crop yields from greenhouses to natural settings, accounting for the unavoidable constraining imposed by seasonal growing conditions. There is also space for the combination of some of these techniques, as well as with others of electronic nature in a sensors-fusion approach, that can reach farther and provide more insight into plant structure, responses and behavior under various conditions. In some cases, the improvement of the current spectroscopic techniques, aside from their reliance on more powerful and effective data analysis techniques, may further depend on the signal amplification emitted by plant structures and pathways through the inclusion in situ nanosensors, such as fluorescence or carbon dots that provide specific spectral signatures and can be monitored in real-time, even remotely, and allow, for instance, the field-based phenotyping platforms to collect high-throughput trait measurements over large areas. Satellite imaging can detect pests, diseases, and weed infestations on a larger scale with less complexity, but the frequency of data updates and cost to retrieve them is still a bottleneck. The major challenges with drones are the reliability issues and accuracy of the mosaic image. Now, they comprise sophisticated software for auto flight and automatic image stitching of the whole field and reasonably low-cost, which will, in the near future, help new researchers to explore more drone-based multi-view stereopsis (MVS) methods in agriculture. The spectral response of the remote sensing data can be affected by variable soil backgrounds and residue covers, which will affect the detection accuracy, and more attention must be given to this issue. Widespread commercialization of MVS in agriculture is possible only with robust, low-cost, automated, unified detection systems (pest, weed, and diseases). The future research focus must be on MVS capable of detecting all yield affecting factors of a particular crop. A multi-crop detection variant is preferable since farmers use the same field for different crops in different seasons in a year.