From the Ground to Space: Using Solar-Induced Chlorophyll Fluorescence to Estimate Crop Productivity

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar‐induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower‐level observations and process‐based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30–50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower‐derived GPP and county‐level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R² = 0.89). Spatially, county‐level TROPOMI SIF correlates with crop productivity (R² = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring

NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Field-based high throughput plant phenotyping has recently gained increased interest in the efforts to bridge the genotyping and phenotyping gap and accelerate plant breeding for crop improvement. In this paper, we introduce a large-scale, integrated robotic cable-driven sensing system developed at University of Nebraska for field phenotyping research. It is constructed to collect data from a 0.4ha field. The system has a sensor payload of 30kg and offers the flexibility to integrate user defined sensing modules. Currently it integrates a four-band multispectral camera, a thermal infrared camera, a 3D scanning LiDAR, and a portable visible near-infrared spectrometer for plant measurements. Software is designed and developed for instrument control, task planning, and motion control, which enables precise and flexible phenotypic data collection at the plot level. The system also includes a variable-rate subsurface drip irrigation to control water application rates, and an automated weather station to log environmental variables. The system has been in operation for the 2017 and 2018 growing seasons. We demonstrate that the system is reliable and robust, and that fully automated data collection is feasible. Sensor and image data are of high quality in comparison to the ground truth measurements, and capture various aspects of plant traits such as height, ground cover and spectral reflectance. We present two novel datasets enabled by the system, including a plot-level thermal infrared image time-series during a day, and the signal of solar induced chlorophyll fluorescence from canopy reflectance. It is anticipated that the availability of this automated phenotyping system will benefit research in field phenotyping, remote sensing, agronomy, and related disciplines.ISSN:0168-1699ISSN:1872-710

High-throughput phenotyping of plant leaf morphological, physiological, and biochemical traits on multiple scales using optical sensing

Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth, health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, physiological, and biochemical traits of plant leaves on multiple scales. We summarize the characteristics, advantages and limitations of optical sensing and data-processing methods applied in various plant phenotyping scenarios. Finally, we discuss the future prospects of plant leaf phenotyping research. This review aims to help researchers choose appropriate optical sensors and data processing methods to acquire plant leaf phenotypes rapidly, accurately, and cost-effectively

Emerging approaches to measure photosynthesis from the leaf to the ecosystem

Measuring photosynthesis is critical for quantifying and modeling leaf to regional scale productivity of managed and natural ecosystems. This review explores existing and novel advances in photosynthesis measurements that are certain to provide innovative directions in plant science research. First, we address gas exchange approaches from leaf to ecosystem scales. Leaf level gas exchange is a mature method but recent improvements to the user interface and environmental controls of commercial systems have resulted in faster and higher quality data collection. Canopy chamber and micrometeorological methods have also become more standardized tools and have an advanced understanding of ecosystem functioning under a changing environment and through long time series data coupled with community data sharing. Second, we review proximal and remote sensing approaches to measure photosynthesis, including hyperspectral reflectance- A nd fluorescence-based techniques. These techniques have long been used with aircraft and orbiting satellites, but lower-cost sensors and improved statistical analyses are allowing these techniques to become applicable at smaller scales to quantify changes in the underlying biochemistry of photosynthesis. Within the past decade measurements of chlorophyll fluorescence from earth-orbiting satellites have measured Solar Induced Fluorescence (SIF) enabling estimates of global ecosystem productivity. Finally, we highlight that stronger interactions of scientists across disciplines will benefit our capacity to accurately estimate productivity at regional and global scales. Applying the multiple techniques outlined in this review at scales from the leaf to the globe are likely to advance understanding of plant functioning from the organelle to the ecosystem

New Methods for Measurements of Photosynthesis from Space

Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate depends critically on knowing where, when, and how carbon dioxide (CO2) is exchanged between the land and atmosphere. In particular, determining the rate of carbon fixation by the Earth's biosphere (commonly referred to as gross primary productivity, or GPP) and the dependence of this productivity on climate is a central goal. Historically, GPP has been inferred from spectral imagery of the land and ocean. Assessment of GPP from the color of the land and ocean requires, however, additional knowledge of the types of plants in the scene, their regulatory mechanisms, and climate variables such as soil moisture—just the independent variables of interest! Sunlight absorbed by chlorophyll in photosynthetic organisms is mostly used to drive photosynthesis, but some can also be dissipated as heat or re‐radiated at longer wavelengths (660–800 nm). This near‐infrared light re‐emitted from illuminated plants is termed solarinduced fluorescence (SIF), and it has been found to strongly correlate with GPP. To advance our understanding of SIF and its relation to GPP and environmental stress at the planetary scale, the Keck Institute for Space Studies (KISS) convened a workshop—held in Pasadena, California, in August 2012—to focus on a newly developed capacity to monitor chlorophyll fluorescence from terrestrial vegetation by satellite. This revolutionary approach for retrieving global observations of SIF promises to provide direct and spatially resolved information on GPP, an ideal bottom‐up complement to the atmospheric net CO2 exchange inversions. Workshop participants leveraged our efforts on previous studies and workshops related to the European Space Agency’s FLuorescence EXplorer (FLEX) mission concept, which had already targeted SIF for a possible satellite mission and had developed a vibrant research community with many important publications. These studies, mostly focused on landscape, canopy, and leaf‐level interpretation, provided the ground‐work for the workshop, which focused on the global carbon cycle and synergies with atmospheric net flux inversions. Workshop participants included key members of several communities: plant physiologists with experience using active fluorescence methods to quantify photosynthesis; ecologists and radiative transfer experts who are studying the challenge of scaling from the leaf to regional scales; atmospheric scientists with experience retrieving photometric information from space‐borne spectrometers; and carbon cycle experts who are integrating new observations into models that describe the exchange of carbon between the atmosphere, land and ocean. Together, the participants examined the link between “passive” fluorescence observed from orbiting spacecraft and the underlying photochemistry, plant physiology and biogeochemistry of the land and ocean. This report details the opportunity for forging a deep connection between scientists doing basic research in photosynthetic mechanisms and the more applied community doing research on the Earth System. Too often these connections have gotten lost in empiricism associated with the coarse scale of global models. Chlorophyll fluorescence has been a major tool for basic research in photosynthesis for nearly a century. SIF observations from space, although sensing a large footprint, probe molecular events occurring in the leaves below. This offers an opportunity for direct mechanistic insight that is unparalleled for studies of biology in the Earth System. A major focus of the workshop was to review the basic mechanisms that underlie this phenomenon, and to explore modeling tools that have been developed to link the biophysical and biochemical knowledge of photosynthesis with the observable—in this case, the radiance of SIF—seen by the satellite. Discussions led to the identification of areas where knowledge is still lacking. For example, the inability to do controlled illumination observations from space limits the ability to fully constrain the variables that link fluorescence and photosynthesis. Another focus of the workshop explored a “top‐down” view of the SIF signal from space. Early studies clearly identified a strong correlation between the strength of this signal and our best estimate of the rate of photosynthesis (GPP) over the globe. New studies show that this observation provides improvements over conventional reflectance‐based remote sensing in detecting seasonal and environmental (particularly drought related) modulation of photosynthesis. Apparently SIF responds much more quickly and with greater dynamic range than typical greenness indices when GPP is perturbed. However, discussions at the workshop also identified areas where top‐down analysis seemed to be “out in front” of mechanistic studies. For example, changes in SIF based on changes in canopy light interception and the light use efficiency of the canopy, both of which occur in response to drought, are assumed equivalent in the top‐down analysis, but the mechanistic justification for this is still lacking from the bottom‐up side. Workshop participants considered implications of these mechanistic and empirical insights for large‐scale models of the carbon cycle and biogeochemistry, and also made progress toward incorporating SIF as a simulated output in land surface models used in global and regional‐scale analysis of the carbon cycle. Comparison of remotely sensed SIF with modelsimulated SIF may open new possibilities for model evaluation and data assimilation, perhaps leading to better modeling tools for analysis of the other retrieval from GOSAT satellite, atmospheric CO2 concentration. Participants also identified another application for SIF: a linkage to the physical climate system arising from the ability to better identify regional development of plant water stress. Decreases in transpiration over large areas of a continent are implicated in the development and “locking‐in” of drought conditions. These discussions also identified areas where current land surface models need to be improved in order to enable this research. Specifically, the radiation transport treatments need dramatic overhauls to correctly simulate SIF. Finally, workshop participants explored approaches for retrieval of SIF from satellite and ground‐based sensors. The difficulty of resolving SIF from the overwhelming flux of reflected sunlight in the spectral region where fluorescence occurs was once a major impediment to making this measurement. Placement of very high spectral resolution spectrometers on GOSAT (and other greenhouse gas–sensing satellites) has enabled retrievals based on infilling of solar Fraunhofer lines, enabling accurate fluorescence measurements even in the presence of moderately thick clouds. Perhaps the most interesting challenge here is that there is no readily portable ground‐based instrumentation that even approaches the capability of GOSAT and other planned greenhouse gas satellites. This strongly limits scientists’ ability to conduct ground‐based studies to characterize the footprint of the GOSAT measurement and to conduct studies of radiation transport needed to interpret SIF measurement. The workshop results represent a snapshot of the state of knowledge in this area. New research activities have sprung from the deliberations during the workshop, with publications to follow. The introduction of this new measurement technology to a wide slice of the community of Earth System Scientists will help them understand how this new technology could help solve problems in their research, address concerns about the interpretation, identify future research needs, and elicit support of the wider community for research needed to support this observation. Somewhat analogous to the original discovery that vegetation indices could be derived from satellite measurements originally intended to detect clouds, the GOSAT observations are a rare case in which a (fortuitous) global satellite dataset becomes available before the research community had a consolidated understanding on how (beyond an empirical correlation) it could be applied to understanding the underlying processes. Vegetation indices have since changed the way we see the global biosphere, and the workshop participants envision that fluorescence can perform the next indispensable step by complementing these measurements with independent estimates that are more indicative of actual (as opposed to potential) photosynthesis. Apart from the potential FLEX mission, no dedicated satellite missions are currently planned. OCO‐2 and ‐3 will provide much more data than GOSAT, but will still not allow for regional studies due to the lack of mapping capabilities. Geostationary observations may even prove most useful, as they could track fluorescence over the course of the day and clearly identify stress‐related down‐regulation of photosynthesis. Retrieval of fluorescence on the global scale should be recognized as a valuable tool; it can bring the same quantum leap in our understanding of the global carbon cycle as vegetation indices once did

Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy

Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZ

Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus

There remains limited information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (ΦF), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships

Investigation on data fusion of sun-induced chlorophyll fluorescence and reflectance for photosynthetic capacity of rice

Studying crop photosynthesis is crucial for improving yield, but current methods are labor-intensive. This research aims to enhance accuracy by combining leaf reflectance and sun-induced chlorophyll fluorescence (SIF) signals to estimate key photosynthetic traits in rice. The study analyzes 149 leaf samples from two rice cultivars, considering reflectance, SIF, chlorophyll, carotenoids, and CO2 response curves. After noise removal, SIF and reflectance spectra are used for data fusion at different levels (raw, feature, and decision). Competitive adaptive reweighted sampling (CARS) extracts features, and partial least squares regression (PLSR) builds regression models. Results indicate that using either reflectance or SIF alone provides modest estimations for photosynthetic traits. However, combining these data sources through measurement-level data fusion significantly improves accuracy, with mid-level and decision-level fusion also showing positive outcomes. In particular, decision-level fusion enhances predictive capabilities, suggesting the potential for efficient crop phenotyping. Overall, sun-induced chlorophyll fluorescence spectra effectively predict rice's photosynthetic capacity, and data fusion methods contribute to increased accuracy, paving the way for high-throughput crop phenotyping