Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Abstract

Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

Bridging the Gap Between Remote Sensing and Plant Phenotyping—Challenges and Opportunities for the Next Generation of Sustainable Agriculture

“…In remote sensing, standards for metadata collection by scientists often mainly regard information on sensor performance or geolocation, while auxiliary data about vegetation is often limited to the traits in focus. But, plant status is only a small function of just one individual co-variable and requires additional information on the biotic and abiotic environment and genetic makeup of the plant, thus, such an approach may result in an oversimplified interpretation of the remote sensing signal (Galieni et al, 2021 ). In contrast, explicit geolocation is essential to link the signal to the field observation and needs to be considered in field phenotyping data collection.…”

“…Thanks to the flexibility of remote sensing systems, the dynamic developments of plant traits can be assessed by standardized measurements with little effort. However, for more complex traits, such as the identification of biotic and abiotic crop stress, the selection of the most suitable sensor combination is challenging (Galieni et al, 2021 ; Berger et al, (in prep)). Nevertheless, remote sensing platforms such as UAVs and micro-satellites are overcoming traditional trade-offs between spatial, temporal, and spectral resolutions.…”

Drought Early Warning in Agri-Food Systems

“…The remote sensing literature offers numerous examples proposing earth observation techniques to support assessment of drought conditions [23]. Increasing access to open data, high-resolution remote sensors, and enhanced computing facilities have led to a new set of sophisticated techniques for DEWS in agriculture experiencing drought stress conditions [24], which monitor evapotranspiration [25], soil moisture [26], ground water fluxes [26,27], and precipitation.…”

Stress Detection Using Proximal Sensing of Chlorophyll Fluorescence on the Canopy Level

“…However, much research has been carried out in the area of optical sensors [3] for measuring the reflected and fluorescent light from the canopy as a mean for non-distruptive remote sensing of stress. Even though many methods have been suggested, sensor-based phenotyping is still at an early stage of development and not yet commonly applied in the field [3,4]. Thus, there is still a need for more research to develop reliable and cost-effective sensors for stress detection [2].…”

“…There is a great deal of ongoing research on advanced optical sensors for stress detection (see review articles [2,4,15]). A wide range of spectral and spatial resolutions on the sensors are used; fluorescence spectroscopy [16,17] and multicolour fluorescence imaging [18] as well as hyperspectral imaging [19][20][21][22].…”