Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture

Abstract

As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning and more available computing power each time. Optical spectroscopy is widely used to evaluate plant tissues, diagnose crops, and study the response of plants to biotic and abiotic stress. Spectral methods can also assist in remote and non-invasive assessment of the physiology of photosynthetic biofilms and the impact of plant species on biodiversity and ecosystem stability. The emergence of high-throughput technologies for plant phenotyping and the accompanying need for methods for rapid and non-contact assessment of plant productivity has generated renewed interest in the application of optical spectroscopy in fundamental plant sciences and agriculture. In this perspective paper, starting with a brief overview of the scientific and technological backgrounds of optical spectroscopy and current mainstream techniques and applications, we foresee the future development of this family of optical spectroscopic methodologies.

Effects of Magnetized, Chelated Iron Foliage Treatments, and Metal Halide Lamps on Plant Water Structure, Water Vapor Dynamics, and Resilience for Legumes under Water Stress

“…Recent research uncovers the effects of near (NIR) and short wave (SWIR) infrared wavelengths on plant physiology, morphology, growth, and yield [26,[47][48][49]. The interactions between IR radiation and plant foliage and tissue are complex [26,47].…”

Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality—A Review

“…Raman spectroscopy is not yet used widely in agriculture and in response to food analysis but has been used recently [ 73 ]. Ramaskie techniques do not require a labor-intensive access service, and they can be tested directly in the environment with pits [ 74 ].…”

Economic-threshold-based classification of soybean aphid, Aphis glycines, infestations in commercial soybean fields using Sentinel-2 satellite data

“…The development of remote sensing associated with computer processing and information technologies contributes to the advancement of agriculture (Mulla, 2013;Cavaco et al, 2022), particularly for the detection, mapping, monitoring, and management of abiotic and biotic plant stresses, including diseases and insects (Abd El-Ghany et al, 2020;Cavaco et al, 2022;Rhodes et al, 2022). Remote sensing for plant stresses involves the use of contactless sensors to detect the electromagnetic radiation reflected or emitted from plant tissues and relate measures of that radiation to changes in plant physicochemical properties (Mulla, 2013;Abd El-Ghany et al, 2020;Cavaco et al, 2022). Numerous studies have documented the effects of insects on the spectral reflectance of crops and forests using ground-, drone-, and satellite-based sensors (Luo et al, 2013;Santos et al, 2017;Vanegas et al, 2018;Iost Filho et al, 2022;Ma et al, 2023).…”