On the concepts and correct use of radiometric quantities for assessing the light environment and their application to plant research.

Light is one of the most important factors for photosynthetic organisms to grow. Historically, the amount of light in plant sciences has been referred to as light intensity, irradiance, photosynthetic active radiation, photon flux, photon flux density, etc. On occasion, all these terms are used interchangeably, yet they refer to different physical units and each metric offers distinct information. Even for experts in the fields of plant photobiology, the use of these terms is confusing, and there is a loose implementation of each concept. This makes the use of radiometric units even more confusing to non-experts when looking for ways to measure light, since they could easily feel overwhelmed by the specialized literature. The use of scientific concepts must be accurate, as ambiguity in the use of radiometric quantities can lead to inconsistencies in analysis, thus decreasing the comparability between experiments and to the formulation of incorrect experimental designs. In this review, we provide a simple yet comprehensive view of the use of radiometric quantities in an effort to clarify their meaning and applications. To facilitate understanding, we adopt a minimum amount of mathematical expressions and provide a historical summary of the use of radiometry (with emphasis on plant sciences), examples of uses, and a review of the available instrumentation for radiometric measurements.

Advanced technologies in studying plant photosynthesis: principles and applications.

sion="1.0" encoding="utf-8"?> FP Functional Plant Biology Funct. Plant Biol. 1445-4408 1445-4416 CSIRO Publishing 36 Gardiner Road Clayton VIC 3168 Australia FP22050 10.1071/FP22050 Foreword Advanced technologies in studying plant photosynthesis: principles and applications A. Zavafer et al . https://orcid.org/0000-0002-8905-1618 Zavafer Alonso A Fan Dayong B * https://orcid.org/0000-0001-8150-9535 Murakami Keach C Handling Editor Shabala Sergey Plant Science Division, Research School of Biology, The Australian National University, Canberra, ACT 2001, Australia. Hokkaido Agricultural Research Center (HARC), National Agriculture and Food Research Organization (NARO), 1 Hitsujigaoka, Toyohira, Sapporo 062-8555, Japan. College of Forestry, Beijing Forestry, University, Beijing 100083, China. * Correspondence to: Dayong Fan Hokkaido Agricultural Research Center (HARC), National Agriculture and Food Research Organization (NARO), 1 Hitsujigaoka, Toyohira, Sapporo 062-8555, Japan Email: dayong73fan@163.com 9 May 2022 49 6 Special Issue i iii 9 May 2022 Published: 9 May 2022 © 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing 2022 The Authors The foreword to this special issue on the advanced technologies in studying photosynthesis focuses on the main contributions of Fred Chow, one of the key Australian scientists studying light reactions in plants.

Appropriate time interval of PPFD measurement to estimate daily photosynthetic gain.

Photosynthetic models sometimes incorporate meteorological elements typically recorded at a time interval of 10 min or 1 h. Because these data are calculated by averaging instantaneous values over time, short-term environmental fluctuations are concealed, which may affect outputs of the model. To assess an appropriate time interval of photosynthetic photon flux density (PPFD) measurement for accurate estimation of photosynthetic gain under open field conditions, we simulated the daily integral net photosynthetic gain using photosynthetic models with or without considering induction kinetics in response to changes in PPFD. Compared with the daily gain calculated from 60-min-interval PPFD data using a steady-state model that ignored the induction kinetics (i.e. a baseline gain), the gains simulated using higher-resolution PPFD data (10-s, 1-min, and 10-min intervals) and using a dynamic model that considered slow induction kinetics were both smaller by ~2%. The gain estimated by the slow dynamic model with 10-s-interval PPFD data was smaller than the baseline gain by more than 5% with a probability of 66%. Thus, the use of low-resolution PPFD data causes overestimation of daily photosynthetic gain in open fields. An appropriate time interval for PPFD measurement is 1 min or shorter to ensure accuracy of the estimates.

Prediction of municipality-level winter wheat yield based on meteorological data using machine learning in Hokkaido, Japan.

This study analyzed meteorological constraints on winter wheat yield in the northern Japanese island, Hokkaido, and developed a machine learning model to predict municipality-level yields from meteorological data. Compared to most wheat producing areas, this island is characterized by wet climate owing to greater annual precipitation and abundant snowmelt water supply in spring. Based on yield statistics collected from 119 municipalities for 14 years (N = 1,516) and high-resolution surface meteorological data, correlation analyses showed that precipitation, daily minimum air temperature, and irradiance during the grain-filling period had significant effects on the yield throughout the island while the effect of snow depth in early winter and spring was dependent on sites. Using 10-d mean meteorological data within a certain period between seeding and harvest as predictor variables and one-year-leave-out cross-validation procedure, performance of machine learning models based on neural network (NN), random forest (RF), support vector machine regression (SVR), partial least squares regression (PLS), and cubist regression (CB) were compared to a multiple linear regression model (MLR) and a null model that returns an average yield of the municipality. The root mean square errors of PLS, SVR, and RF were 872, 982, and 1,024 kg ha-1 and were smaller than those of MLR (1,068 kg ha-1) and null model (1,035 kg ha-1). These models outperformed the controls in other metrics including Pearson's correlation coefficient and Nash-Sutcliffe efficiency. Variable importance analysis on PLS indicated that minimum air temperature and precipitation during the grain-filling period had major roles in the prediction and excluding predictors in this period (i.e. yield forecast with a longer lead-time) decreased forecast performance of the models. These results were consistent with our understanding of meteorological impacts on wheat yield, suggesting usefulness of explainable machine learning in meteorological crop yield prediction under wet climate.

Partially Dissecting Electron Fluxes in Both Photosystems in Spinach Leaf Disks during Photosynthetic Induction.

Photosynthetic induction, a gradual increase in photosynthetic rate on a transition from darkness or low light to high light, has ecological significance, impact on biomass accumulation in fluctuating light and relevance to photoprotection in strong light. However, the experimental quantification of the component electron fluxes in and around both photosystems during induction has been rare. Combining optimized chlorophyll fluorescence, the redox kinetics of P700 [primary electron donor in Photosystem I (PSI)] and membrane inlet mass spectrometry in the absence/presence of inhibitors/mediator, we partially estimated the components of electron fluxes in spinach leaf disks on transition from darkness to 1,000 �mol photons�m-2�s-1 for up to 10 min, obtaining the following findings: (i) the partitioning of energy between both photosystems did not change noticeably; (ii) in Photosystem II (PSII), the combined cyclic electron flow (CEF2) and charge recombination (CR2) to the ground state decreased gradually toward 0 in steady state; (iii) oxygen reduction by electrons from PSII, partly bypassing PSI, was small but measurable; (iv) cyclic electron flow around PSI (CEF1) peaked before becoming somewhat steady; (v) peak magnitudes of some of the electron fluxes, all probably photoprotective, were in the descending order: CEF1 > CEF2 + CR2 > chloroplast O2 uptake; and (vi) the chloroplast NADH dehydrogenase-like complex appeared to aid the antimycin A-sensitive CEF1. The results are important for fine-tuning in silico simulation of in vivo photosynthetic electron transport processes; such simulation is, in turn, necessary to probe partial processes in a complex network of interactions in response to environmental changes.

Time course of the photochemical reflectance index during photosynthetic induction: its relationship with the photochemical yield of photosystem II.

Time courses of photochemical reflectance index (PRI) of an attached cucumber leaf during a dark-light transition were compared with those of photochemical yields of photosystem II (YII ) to discuss the feasibility of PRI imaging for estimating the efficiency of photosynthetic light use. YII and PRI were simultaneously evaluated with a pulse-amplitude modulation chlorophyll fluorometer and a low-cost imaging system consisting of digital cameras and band-pass filters, respectively. YII decreased immediately after the transition and then increased under various photon flux densities. Although PRI exhibited delayed time courses with respect to YII under low light conditions, PRI decreased monotonically under high light conditions. There was no correlation between YII and the changes in PRI (ΔPRI) immediately after the transition but YII was correlated with ΔPRI under the steady-state photosynthesis. These results indicate that the use of PRI to estimate YII under fluctuating light based on the regression obtained at steady state can overestimate YII . The imaging system was also applied to evaluate the spatial PRI distribution within a leaf. While PRI of leaf areas that remained untreated, or had been treated with H2 O again, first dropped and then rose under low light and monotonically decreased under high light conditions, leaf areas treated with inhibitor (dichlorophenyl dimethylurea) did not exhibit any changes. It is likely that the inhibitor suppressed lumen acidification, which triggers a decrease in PRI. It was suggested that YII of leaves with malfunctions in the photosynthetic electron transport can be overestimated by the PRI-based estimation.

A Mathematical Model of Photosynthetic Electron Transport in Response to the Light Spectrum Based on Excitation Energy Distributed to Photosystems.

To enable us to analyze more systematically the effects of the spectral distribution of light (i.e. light quality) on photosynthetic electron transport, we propose a simple mathematical model which describes electron transport reactions under light-limited conditions based on the excitation energy distributed to the photosystems. The model assumes that the rate-limiting photosystem performs the photochemical reaction at its maximum yield, while the yield in the other photosystem is passively down-regulated to equalize the rates of linear electron transport through the photosystems. Using intact cucumber leaves, we tested the model by comparing actual and estimated photosynthetic parameters under several combinations of photon flux densities of red and far-red lights (R and FR, respectively). Simultaneously provided R and FR yielded greater gross photosynthetic rates than the sums of the rates under only R and only FR, which is known as the 'enhancement effect'. The present model reproduced these non-additive increases in the gross photosynthetic rates in response to supplemental FR to R and provided more accurate estimates than an existing method that did not take the enhancement effect into account (root mean square errors: 0.11 and 0.21 µmol m-2 s-1, respectively). Using the present model, the photon flux density of the supplemental FR which gives the changing point of rate-limiting photosystem and the photochemical yields of the non-rate-limiting photosystems were estimated reasonably well. The present study has therefore formulated a simplified quantitative electron transport model in response to the light spectrum based on generally accepted concepts and demonstrated its validity experimentally.

Quantification of excitation energy distribution between photosystems based on a mechanistic model of photosynthetic electron transport.

Absorbed light energy is converted into excitation energy. The excitation energy is distributed to photosystems depending on the wavelength and drives photochemical reactions. A non-destructive, mechanistic and quantitative method for estimating the fraction of the excitation energy distributed to photosystem II (f) was developed. For the f values for two simultaneously provided actinic lights (ALs) with different spectral distributions to be estimated, photochemical yields of the photosystems were measured under the ALs and were then fitted to an electron transport model assuming the balance between the electron transport rates through the photosystems. For the method to be tested using leaves with different properties in terms of the long-term and short-term acclimation (adjustment of photosystem stoichiometry and state transition, respectively), the f values for red and far-red light (R and FR) were estimated in leaves grown (~1 week) under white light without and with supplemental FR and adapted (~10 min) to R without and with supplemental FR. The f values for R were clearly greater than those for FR and those of leaves grown with and adapted to supplemental FR tended to be higher than the controls. These results are consistent with previous studies and therefore support the validity of the proposed method.

Interaction between the spectral photon flux density distributions of light during growth and for measurements in net photosynthetic rates of cucumber leaves.

The net photosynthetic rate of a leaf becomes acclimated to the plant's environment during growth. These rates are often measured, evaluated and compared among leaves of plants grown under different light conditions. In this study, we compared net photosynthetic rates of cucumber leaves grown under white light-emitting diode (LED) light without and with supplemental far-red (FR) LED light (W- and WFR-leaves, respectively) under three different measuring light (ML) conditions: their respective growth light (GL), artificial sunlight (AS) and blue and red (BR) light. The difference in the measured photosynthetic rates between W- and WFR-leaves was greater under BR than under GL and AS. In other words, an interaction between supplemental FR light during growth and the spectral photon flux density distribution (SPD) of ML affected the measured net photosynthetic rates. We showed that the comparison and evaluation of leaf photosynthetic rates and characteristics can be biased depending on the SPD of ML, especially for plants grown under different photon flux densities in the FR waveband. We also investigated the mechanism of the interaction. We confirmed that the distribution of excitation energy between the two photosystems (PSs) changed in response to the SPD of GL, and that this change resulted in the interaction, as suggested in previous reports. However, changes in PS stoichiometry could not completely explain the adjustment in excitation energy distribution observed in this study, suggesting that other mechanisms may be involved in the interaction.