In vivo photoprotection mechanisms observed from leaf spectral absorbance changes showing VIS-NIR slow-induced conformational pigment bed changes

Hyperspectral Imaging Reveals Differential Carotenoid and Chlorophyll Temporal Dynamics and Spatial Patterns in Scots Pine Under Water Stress

Drought-related die-off events have been observed throughout Europe in Scots pine (Pinus sylvestris L.). Such events are exacerbated by carbon starvation that is, an imbalance of photosynthetic productivity and resource usage. Recent evidence suggests that optically measurable photosynthetic pigments such as chlorophylls and carotenoids respond to water stress (WS). However, there is a lack of measurements using imaging spectroscopy, and the mechanisms linking xanthophyll-related changes in reflectance captured by the photochemical reflectance index (PRI) and chlorophyll changes in red edge position (REP) to WS are not understood. To probe this, we conducted a greenhouse experiment where 3-year-old Pinus sylvestris saplings were subjected to water limitation and followed using hyperspectral imaging (HSI) spectroscopy, water status and photosynthetic measurements. Carotenoids (e.g., xanthophyll cycle) and chlorophylls responded to WS, which was observed using the HSI-derived indices PRI and REP respectively. The spatial-temporal response in these two pigment-reflectance groupings differed. The spatial distribution of PRI represented the light intensity around the time of the measurement, whereas REP reflected the daily averaged light intensity over the experimental course. A further difference was noted upon rewatering, where the carotenoid-related PRI partially recovered but the chlorophyll-related REP did not.

In vivo detection of spectral reflectance changes associated with regulated heat dissipation mechanisms complements fluorescence quantum efficiency in early stress diagnosis

Early stress detection of crops requires a thorough understanding of the signals showing the very first symptoms of the alterations in the photosynthetic light reactions. Detection of the activation of the regulated heat dissipation mechanism is crucial to complement passively induced fluorescence to resolve ambuiguities in energy partitioning. Using leaf spectroscopy, we evaluated the capability of pigment spectral unmixing to calculate the fluorescence quantum efficiency (FQE) and simultaneously retrieve fast absorption changes in a drought and nitrogen deficiency experiment with tomato. In addition, active fluorescence measurements and pigment analyses of xanthophylls, carotenes and chlorophylls were conducted. We observed notable responses in noninvasive proximal sensing-retrieved FQE values under stress, but as expected, these alone were not enough to identify the constraints in photosynthetic efficiency. Reflectance-based detection of the 535-nm peak absorption change was able to complement FQE and indicate the activation of regulated heat dissipation for both stress treatments under growing light conditions. However, further complexity in the light harvesting energy regulation needs to be accounted for when considering additional light stress. Our results underscore the potential of complementary in vivo quantitative spectroscopy-based products in the early and nondestructive stress diagnosis of plants, marking the path for further applications.

Estimation of photosynthetic dynamics in forests from daily measured fluorescence and PRI data with adjustment for canopy shadow fraction

We conducted year-long measurements of the photochemical reflectance index (PRI) and solar-induced fluorescence in the O2A oxygen band (SIFA) at a Norway spruce forest and a European beech forest to study relationships of these remote sensing variables to photosynthesis by trees in grown forest stands. Measured PRI and SIFA values were linked to changes in forest gross primary productivity (GPP) and light-use efficiency (LUE). Changes in the shadow fraction (αS) within tree crowns influenced PRI and fluorescence signals. In the spruce forest, the quantum yield of SIFA (FYSIFA) decreased around midday together with photosynthesis and GPP. Such decreases in FYSIFA were accompanied by an increase in the αS. In the beech forest, we detected an increase in FYSIFA together with a decrease in αS in the afternoon hours. The overall sensitivity of PRI to LUE was variable according to the season, presumably influenced by complex changes in photosynthetic pigments. PRI and FYSIFA showed weak correlations with canopy LUE; however, when considered together, the correlation was strengthened (R2 was 0.63 and 0.34 in spruce and beech forest, respectively). Our model predicting LUE dynamics includes a diurnal minimum of PRI and canopy αS to make allowances for seasonal changes in photosynthetic pigments and for diurnal variability of the shadow fraction in forests. The incorporation of these correcting factors allowed us to estimate LUE at R2 = 0.68 (spruce) and 0.53 (beech). The modeling equations appeared sensitive to the absorbed photosynthetically active radiation (APAR), but less sensitive to the GPP of these forests. Substituting pigments correction with introducing differential PRI (ΔPRI) into the model did not significantly improve the LUE estimation across the season. Our results show that the joint use of PRI and fluorescence improves LUE and GPP estimation accuracy in both daily and seasonal observations.

Optimization of diffuse reflectance spectroscopy measurements for direct and rapid screening of pesticides: A case study of spinach

Although diffuse reflectance spectroscopy (DRS) measurements can be collected rapidly and simultaneously, the resulting datasets are imbalanced and redundant due to the highly correlated spectral features collected on relatively few samples. Consequently, modelling these datasets using machine learning (ML) techniques is challenging and necessitates longer training times and more computational resources. Furthermore, models developed with such data are frequently prone to overfitting, resulting in promising but often non-reproducible results. We demonstrate the advantage of using an eigenvector decomposition principal component analysis (PCA) in reducing the dimensionality and data mining of DRS measurements in the short near-infrared region (750-900 nm). A total of 547 DRS measurements consisting of 151 wavelengths were acquired from spinach samples sprayed with two different pesticides and control samples. The measurements were later preprocessed with a Savitzky-Golay filter and multiplicative scatter analysis. After performing PCA on the preprocessed data, two principal components (PCs) that explained 77% of the cumulative variance and maximized the interclass variation were extracted and used as inputs to three ML models namely; artificial neural networks, support vector machine and random forest, to classify the samples. Re-sampling was used to tune the models and avoid overfitting. The performance of the models was compared using raw DRS data, pre-processed (PP) DRS data, and PCs data. The results show that pesticide classification using PCs data requires the least amount of training time (average 2.4 s) for all the models, and achieves 100% classification accuracy. In addition, it was observed that spectral data pre-processing improves accuracy and training time when compared to using raw spectral data. These findings are particularly encouraging since they demonstrate the possibility of developing rapid and accurate classification models for screening pesticide residues in fresh produce based on DRS measurements with minimal computational resources.

Insights on the regulation of photosynthesis in pea leaves exposed to oscillating light

Plants growing in nature often experience fluctuating irradiance. However, in the laboratory, the dynamics of photosynthesis are usually explored by instantaneously exposing dark-adapted plants to constant light and examining the dark-to-light transition, which is a poor approximation of natural phenomena. With the aim creating a better approximation, we exposed leaves of pea (Pisum sativum) to oscillating light and measured changes in the functioning of PSI and PSII, and of the proton motive force at the thylakoid membrane. We found that the dynamics depended on the oscillation period, revealing information about the underlying regulatory networks. As demonstrated for a selected oscillation period of 60 s, the regulation tries to keep the reaction centers of PSI and PSII open. We present an evaluation of the data obtained, and discuss the involvement of particular processes in the regulation of photosynthesis. The forced oscillations provided an information-rich fingerprint of complex regulatory networks. We expect future progress in understanding these networks from experiments involving chemical interventions and plant mutants, and by using mathematical modeling and systems identification and control tools.

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under shortterm, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.

Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.

Proximal Imaging of Changes in Photochemical Reflectance Index in Leaves Based on Using Pulses of Green-Yellow Light

Plants are affected by numerous environmental factors that influence their physiological processes and productivity. Early revealing of their action based on measuring spectra of reflected light and calculating reflectance indices is an important stage in the protection of agricultural plants. Photochemical reflectance index (PRI) is a widely used parameter related to photosynthetic changes in plants under action of stressors. We developed a new system for proximal imaging of PRI based on using short pulses of measuring light detected simultaneously in green (530 nm) and yellow (570 nm) spectral bands. The system has several advances compared to those reported in literature. Active light illumination and subtraction of the ambient light allow for PRI measurements without periodic calibrations. Short duration of measuring pulses (18 ms) minimizes their influence on plants. Measurements in two spectral bands operated by separate cameras with aligned fields of visualization allow one to exclude mechanically switchable parts like filter wheels thus minimizing acquisition time and increasing durability of the setup. Absolute values of PRI and light-induced changes in PRI (ΔPRI) in pea leaves and changes of these parameters under action of light with different intensities, water shortage, and heating have been investigated using the developed setup. Changes in ΔPRI are shown to be more robust than the changes in the absolute value of PRI which is in a good agreement with our previous studies. Values of PRI and, especially, ΔPRI are strongly linearly related to the energy-dependent component of the non-photochemical quenching and can be potentially used for estimation of this component. Additionally, we demonstrate that the developed system can also measure fast changes in PRI (hundreds of milliseconds and seconds) under leaf illumination by the pulsed green-yellow measuring light. Thus, the developed system of proximal PRI imaging can be used for PRI measurements (including fast changes in PRI) and estimation of stressors-induced photosynthetic changes.

Modification of a gas exchange system to measure active and passive chlorophyll fluorescence simultaneously under field conditions

Solar-induced fluorescence (SIF) is a promising tool to estimate photosynthesis across scales; however, there has been limited research done at the leaf level to investigate the relationship between SIF and photosynthesis. To help bridge this gap, a LI-COR LI-6800 gas exchange instrument was modified with a visible-near-infrared (VIS-NIR) spectrometer to measure active and passive fluorescence simultaneously. The system was adapted by drilling a hole into the bottom plate of the leaf chamber and inserting a fibre-optic to measure passive steady-state fluorescence (F _t , _λ , analogous to SIF) from the abaxial surface of a leaf. This new modification can concurrently measure gas exchange, passive fluorescence and active fluorescence over the same leaf area and will allow researchers to measure leaf-level F _t , _λ in the field to validate tower-based and satellite measurements. To test the modified instrument, measurements were performed on leaves of well-watered and water-stressed walnut plants at three light levels and a constant air temperature. Measurements on these same plants were also conducted using a similarly modified Walz GFS-3000 gas exchange instrument to compare results. We found a positive linear correlation between F _t , _λ measurements from the modified LI-6800 and GFS-3000 instruments. We also report a positive linear relationship between F _t , _λ and normalized steady-state chlorophyll fluorescence (F _t /F _o ) from the pulse-amplitude modulation (PAM) fluorometer of the LI-6800 system. Accordingly, this modification will inform the link between spectrally resolved F _t , _λ and gas exchange-leading to improved interpretation of how remotely sensed SIF tracks changes in the light reactions of photosynthesis.

Diurnal dynamics of nonphotochemical quenching in Arabidopsis npq mutants assessed by solar-induced fluorescence and reflectance measurements in the field

Solar-induced fluorescence (SIF) is highly relevant in mapping photosynthesis from remote-sensing platforms. This requires linking SIF to photosynthesis and understanding the role of nonphotochemical quenching (NPQ) mechanisms under field conditions. Hence, active and passive fluorescence were measured in Arabidopsis with altered NPQ in outdoor conditions. Plants with mutations in either violaxanthin de-epoxidase (npq1) or PsbS protein (npq4) exhibited reduced NPQ capacity. Parallel measurements of NPQ, photosystem II efficiency, SIF and spectral reflectance (ρ) were conducted diurnally on one sunny summer day and two consecutive days during a simulated cold spell. Results showed that both npq mutants exhibited higher levels of SIF compared to wild-type plants. Changes in reflectance were related to changes in the violaxanthin-antheraxanthin-zeaxanthin cycle and not to PsbS-mediated conformational changes. When plants were exposed to cold temperatures, rapid onset of photoinhibition strongly quenched SIF in all lines. Using well-characterized Arabidopsis npq mutants, we showed for the first time the quantitative link between SIF, photosynthetic efficiency, NPQ components and leaf reflectance. We discuss the functional potential and limitations of SIF and reflectance measurements for estimating photosynthetic efficiency and NPQ in the field.

Combined dynamics of the 500-600 nm leaf absorption and chlorophyll fluorescence changes in vivo: Evidence for the multifunctional energy quenching role of xanthophylls

Carotenoids (Cars) regulate the energy flow towards the reaction centres in a versatile way whereby the switch between energy harvesting and dissipation is strongly modulated by the operation of the xanthophyll cycles. However, the cascade of molecular mechanisms during the change from light harvesting to energy dissipation remains spectrally poorly understood. By characterizing the in vivo absorbance changes (ΔA) of leaves from four species in the 500-600 nm range through a Gaussian decomposition, while measuring passively simultaneous Chla fluorescence (F) changes, we present a direct observation of the quick antenna adjustments during a 3-min dark-to-high-light induction. Underlying spectral behaviours of the 500-600 nm ΔA feature can be characterized by a minimum set of three Gaussians distinguishing very quick dynamics during the first minute. Our results show the parallel trend of two Gaussian components and the prompt Chla F quenching. Further, we observe similar quick kinetics between the relative behaviour of these components and the in vivo formations of antheraxanthin (Ant) and zeaxanthin (Zea), in parallel with the dynamic quenching of singlet excited chlorophyll a (¹Chla*) states. After these simultaneous quick kinetical behaviours of ΔA and F during the first minute, the 500-600 nm feature continues to increase, indicating a further enhanced absorption driven by the centrally located Gaussian until 3 min after sudden light exposure. Observing these precise underlying kinetic trends of the spectral behaviour in the 500-600 nm region shows the large potential of in vivo leaf spectroscopy to bring new insights on the quick redistribution and relaxation of excitation energy, indicating a key role for both Ant and Zea.

A light-induced decrease in the photochemical reflectance index (PRI) can be used to estimate the energy-dependent component of non-photochemical quenching under heat stress and soil drought in pea, wheat, and pumpkin

The remote sensing of a plant's physiological state is a key problem of precision agriculture. The photochemical reflectance index (PRI), which is based on the intensities of the reflected light at 531 and 570 nm, is an important tool for the remote sensing of photosynthetic processes in plants. In particular, the PRI can be strongly connected with the non-photochemical quenching of chlorophyll fluorescence (NPQ) and the quantum yield of photosystem II (ФPSII); however, this connection is dependent on illumination, the intensity of stressor actions, the time scale of measurements, etc. The aim of the present work was to analyze the connection of PRI with the energy-dependent component of NPQ (NPQF) and ФPSII under heating and soil drought conditions. Pea, wheat, and pumpkin seedlings, which were grown under controlled conditions, were investigated. A PAM fluorometer Dual-PAM-100 and spectrometer S-100 were used for measurements of photosynthetic parameters and PRI, respectively. It was shown that heat stress increased the NPQF and the magnitude of light-induced changes in PRI (ΔPRI) and decreased ФPSII in pea seedlings. The decreased ФPSII and increased ΔPRI were observed in wheat after heating, but significant changes in NPQF were absent; the significant decrease in ФPSII was observed in pumpkin seedlings, while there were no significant changes in the other parameters. ΔPRI and NPQF after heating were significantly correlated. However, a significant correlation of the absolute values of PRI with photosynthetic parameters was absent. The soil drought increased NPQF and the magnitude of ΔPRI and decreased ФPSII in peas. ΔPRI was strongly correlated with photosynthetic parameters, but this correlation was absent for the absolute value of PRI. Thus, ΔPRI is strongly connected with the magnitude of NPQF and can be used as an estimator of this parameter.