- Mesophyll conductance ( g m ) governs CO 2 diffusion to Rubisco and is a key determinant of photosynthetic performance, yet the mechanisms underlying its sensitivity to heat and water stress remain unresolved. - We quantified g m temperature responses across diverse Gossypium species and examined anatomical drivers of g m plasticity in cultivated cotton ( G. hirsutum ) and the wild Australian species G. bickii under elevated temperature and soil water deficit. - Species exhibited contrasting g m strategies: G. hirsutum exhibited high g m and carbon assimilation near thermal optima but showed greater sensitivity under combined heat and water deficit, whereas G. bickii maintained comparatively stable g m and photosynthesis across stress conditions. - Under water deficit, structural adjustments in G. hirsutum (increased leaf porosity, cell wall thickness and mesophyll surface exposure to intercellular airspaces) were insufficient to sustain g m , suggesting that liquid-phase resistances impose dominant constraints on CO 2 diffusion under extreme climatic stress. - These results identify g m as a dynamic, multi-component trait and a key physiological vulnerability in cotton, shaped by coordinated anatomical characteristics and potentially cell wall properties and membrane-associated processes, with major implications for mechanistic photosynthesis modelling and improving climate resilience in cotton and other C 3 species.

BACKGROUND AND AIMS:Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. METHODS:We used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. KEY RESULTS:Optimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for 'light' than 'shaded' leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single 'broadleaf evergreen' functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. CONCLUSIONS:This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

BACKGROUND:The need for rapid in-field measurement of key traits contributing to yield over many thousands of genotypes is a major roadblock in crop breeding. Recently, leaf hyperspectral reflectance data has been used to train machine learning models using partial least squares regression (PLSR) to rapidly predict genetic variation in photosynthetic and leaf traits across wheat populations, among other species. However, the application of published PLSR spectral models is limited by a fixed spectral wavelength range as input and the requirement of separate custom-built models for each trait and wavelength range. In addition, the use of reflectance spectra from the short-wave infrared region requires expensive multiple detector spectrometers. The ability to train a model that can accommodate input from different spectral ranges would potentially make such models extensible to more affordable sensors. Here we compare the accuracy of prediction of PLSR with various deep learning approaches and an ensemble model, each trained and tested using previously published data sets. RESULTS:We demonstrate that the accuracy of PLSR to predict photosynthetic and related leaf traits in wheat can be improved with deep learning-based and ensemble models without overfitting. Additionally, these models can be flexibly applied across spectral ranges without significantly compromising accuracy. CONCLUSION:The method reported provides an improved prediction of wheat leaf and photosynthetic traits from leaf hyperspectral reflectance and do not require a full range, high cost leaf spectrometer. We provide a web service for deploying these algorithms to predict physiological traits in wheat from a variety of spectral data sets, with important implications for wheat yield prediction and crop breeding.

Leaf gas exchange measurements provide an important tool for inferring a plant’s photosynthetic biochemistry. In most cases, the responses of photosynthetic CO assimilation to variable intercellular CO concentrations ( A / C response curves) are used to model the maximum rate of carboxylation by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco, V ) and the rate of electron transport at a given photosynthetically active radiation (PAR; J ). The standard Farquhar-Von Caemmerer-Berry model is typically used with default parameters of Rubisco kinetic values and mesophyll conductance to CO ( g ) derived from tobacco that impairs analytical reliability across species. To study this, here we measured the temperature responses of key in vitro Rubisco catalytic properties and g in cotton ( Gossypium hirsutum cv. Sicot 71) and derived V and J ( J at 2000 µmol m s PAR) from cotton A / C curves incrementally measured at 15°C to 40°C using cotton and tobacco parameters with our new automated fitting R package ‘OptiFitACi’. When applied to cotton, the tobacco parameters produced unrealistic J : V ratio of <1 at 25°C, two- to three-fold higher estimates of V , approximately 50% higher estimates of J and more variable estimates of V and J , compared to model parameterisation with cotton-derived values. We determined that errors arise when using a g of 0.23 mol m s bar or below and Rubisco CO -affinities under ambient O ( K ) outside 461 µbar to 627 µbar to model A / C responses in cotton. We show how the multi- A / C modelling capabilities of ‘OptiFitACi’ serves as a robust, user-friendly extension of ‘plantecophys’ by providing simplified temperature-sensitivity and species-specificity parameterisation capabilities to enable higher accuracy estimates of V and J .

The rate with which crop yields per hectare increase each year is plateauing at the same time that human population growth and other factors increase food demand. Increasing yield potential ( Yp ) of crops is vital to address these challenges. In this review, we explore a component of Yp that has yet to be optimised - that being improvements in the efficiency with which light energy is converted into biomass ( εc ) via modifications to CO2 fixed per unit quantum of light (α), efficiency of respiratory ATP production ( εprod ) and efficiency of ATP use ( εuse ). For α, targets include changes in photoprotective machinery, ribulose bisphosphate carboxylase/oxygenase kinetics and photorespiratory pathways. There is also potential for εprod to be increased via targeted changes to the expression of the alternative oxidase and mitochondrial uncoupling pathways. Similarly, there are possibilities to improve εuse via changes to the ATP costs of phloem loading, nutrient uptake, futile cycles and/or protein/membrane turnover. Recently developed high-throughput measurements of respiration can serve as a proxy for the cumulative energy cost of these processes. There are thus exciting opportunities to use our growing knowledge of factors influencing the efficiency of photosynthesis and respiration to create a step-change in yield potential of globally important crops.

IntroductionEngineering membrane transporters to achieve desired functionality is reliant on availability of experimental data informing structure-function relationships and intelligent design. Plant aquaporin (AQP) isoforms are capable of transporting diverse substrates such as signaling molecules, nutrients, metalloids, and gases, as well as water. AQPs can act as multifunctional channels and their transport function is reliant on many factors, with few studies having assessed transport function of specific isoforms for multiple substrates.MethodsHigh-throughput yeast assays were developed to screen for transport function of plant AQPs, providing a platform for fast data generation and cataloguing of substrate transport profiles. We applied our high-throughput growth-based yeast assays to screen all 13 Arabidopsis PIPs (AtPIPs) for transport of water and several neutral solutes: hydrogen peroxide (H2O2), boric acid (BA), and urea. Sodium (Na+) transport was assessed using elemental analysis techniques.ResultsAll AtPIPs facilitated water and H2O2 transport, although their growth phenotypes varied, and none were candidates for urea transport. For BA and Na+ transport, AtPIP2;2 and AtPIP2;7 were the top candidates, with yeast expressing these isoforms having the most pronounced toxicity response to BA exposure and accumulating the highest amounts of Na+. Linking putative AtPIP isoform substrate transport profiles with phylogenetics and gene expression data, enabled us to align possible substrate preferences with known and hypothesized biological roles of AtPIPs.DiscussionThis testing framework enables efficient cataloguing of putative transport functionality of diverse AQPs at a scale that can help accelerate our understanding of AQP biology through big data approaches (e.g. association studies). The principles of the individual assays could be further adapted to test additional substrates. Data generated from this framework could inform future testing of AQP physiological roles, and address knowledge gaps in structure-function relationships to improve engineering efforts.

Net photosynthetic CO 2 assimilation rate ( A n ) decreases at leaf temperatures above a relatively mild optimum ( T opt ) in most higher plants. This decline is often attributed to reduced CO 2 conductance, increased CO 2 loss from photorespiration and respiration, reduced chloroplast electron transport rate ( J ), or deactivation of Ribulose-1,5-bisphosphate Carboxylase Oxygenase (Rubisco). However, it is unclear which of these factors can best predict species independent declines in A n at high temperature. We show that independent of species, and on a global scale, the observed decline in A n with rising temperatures can be effectively accounted for by Rubisco deactivation and declines in J . Our finding that A n declines with Rubisco deactivation and J supports a coordinated down-regulation of Rubisco and chloroplast electron transport rates to heat stress. We provide a model that, in the absence of CO 2 supply limitations, can predict the response of photosynthesis to short-term increases in leaf temperature.

Recognition of the untapped potential of photosynthesis to improve crop yields has spurred research to identify targets for breeding. The CO2-fixing enzyme Rubisco is characterized by a number of inefficiencies, and frequently limits carbon assimilation at the top of the canopy, representing a clear target for wheat improvement. Two bread wheat lines with similar genetic backgrounds and contrasting in vivo maximum carboxylation activity of Rubisco per unit leaf nitrogen (Vc,max,25/Narea) determined using high-throughput phenotyping methods were selected for detailed study from a panel of 80 spring wheat lines. Detailed phenotyping of photosynthetic traits in the two lines using glasshouse-grown plants showed no difference in Vc,max,25/Narea determined directly via in vivo and in vitro methods. Detailed phenotyping of glasshouse-grown plants of the 80 wheat lines also showed no correlation between photosynthetic traits measured via high-throughput phenotyping of field-grown plants. Our findings suggest that the complex interplay between traits determining crop productivity and the dynamic environments experienced by field-grown plants needs to be considered in designing strategies for effective wheat crop yield improvement when breeding for particular environments.

Summary Mesophyll conductance (gm) limits photosynthesis by restricting CO2 diffusion between the substomatal cavities and chloroplasts. Although it is known that gm is determined by both leaf anatomical and biochemical traits, their relative contribution across plant functional types (PFTs) is still unclear. We compiled a dataset of gm measurements and concomitant leaf traits in unstressed plants comprising 563 studies and 617 species from all major PFTs. We investigated to what extent gm limits photosynthesis across PFTs, how gm relates to structural, anatomical, biochemical, and physiological leaf properties, and whether these relationships differ among PFTs. We found that gm imposes a significant limitation to photosynthesis in all C3 PFTs, ranging from 10–30% in most herbaceous annuals to 25–50% in woody evergreens. Anatomical leaf traits explained a significant proportion of the variation in gm (R2 > 0.3) in all PFTs except annual herbs, in which gm is more strongly related to biochemical factors associated with leaf nitrogen and potassium content. Our results underline the need to elucidate mechanisms underlying the global variability of gm. We emphasise the underestimated potential of gm for improving photosynthesis in crops and identify modifications in leaf biochemistry as the most promising pathway for increasing gm in these species.

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (Ac ) and electron transport-limited (Aj ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C3 wheat and C4 sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing Ac alone generate more consistent but smaller yield gains across all water and nitrogen environments, Aj enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both Ac and Aj generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross-scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30–40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

In plants with C3 photosynthesis, increasing the diffusion conductance for CO2 from the substomatal cavity to chloroplast stroma (mesophyll conductance) can improve the efficiencies of both CO2 assimilation and photosynthetic water use. In the diffusion pathway from substomatal cavity to chloroplast stroma, the plasmalemma and chloroplast envelope membranes impose a considerable barrier to CO2 diffusion, limiting photosynthetic efficiency. In an attempt to improve membrane permeability to CO2, and increase photosynthesis in tobacco, we generated transgenic lines in Nicotiana tabacum L. cv Petite Havana carrying either the Arabidopsis PIP1;2 (AtPIP1;2) or PIP1;4 (AtPIP1;4) gene driven by the constitutive dual 2x35S CMV promoter. From a collection of independent T0 transgenics, two T2 lines from each gene were characterized, with western blots confirming increased total aquaporin protein abundance in the AtPIP1;2 tobacco lines. Transient expression of AtPIP1;2-mGFP6 and AtPIP1;4-mGFP6 fusions in Nicotiana benthamiana identified that both AtPIP1;2 and AtPIP1;4 localize to the plasmalemma. Despite achieving ectopic production and correct localization, gas exchange measurements combined with carbon isotope discrimination measurements detected no increase in mesophyll conductance or CO2 assimilation rate in the tobacco lines expressing AtPIP. We discuss the complexities associated with trying to enhance gm through modified aquaporin activity.

Aquaporins (AQPs) are multifunctional membrane proteins which have greatly diversified in number and function in the plant Kingdom. In plants, AQPs have evolved to comprise a dynamic solute transport network occurring in all tissues and facilitating transport of water and vital solutes across various cellular membranes. Plant AQPs are involved in a multitude of plant physiological processes, however a better understanding is required of AQP structure-function relationships, multifunctionality and cell membrane localisation in order to begin to describe putative functional roles for the numerous plant AQP gene isoforms. Using an integrated approach, we characterised nine diverse Nicotiana tabacum (tobacco) aquaporins, spanning the 3 largest AQP subfamilies (PIP, TIP, and NIP) and with varied gene expression profiles. High-throughput yeast-based functional screens identified novel candidates for water, hydrogen peroxide (H 2 O 2 ), boric acid (BA) and urea transport across the 3 AQP subfamilies. Using GFP translational fusions, AQPs observed in planta were localised to the plasma membrane, tonoplast and endoplasmic reticulum. AlphaFold protein models illustrated differences in pore shape and size across subfamilies. Our analysis supports the importance of functional data for deciphering unknown AQP structure-function relationships and uncovering novel candidates for in planta solute transport.

Plant aquaporins have many more functions than just transporting water. Within the diversity of plant aquaporins are isoforms capable of transporting signaling molecules, nutrients, metalloids and gases. It is established that aquaporin substrate discrimination depends on combinations of factors such as solute size, pore size and polarity, and post-translational protein modifications. But our understanding of the relationships between variation in aquaporin structures and the implications for permeability is limited. High-throughput yeast-based assays were developed to assess diverse substrate permeabilities to water, H 2 O 2 , boric acid, urea and Na + . All 13 plasma membrane intrinsic proteins (PIPs) from Arabidopsis (AtPIPs) were permeable to both water and H 2 O 2 , although their effectiveness varied, and none were permeable to urea. AtPIP2 isoforms were more permeable to water than AtPIP1s, while AtPIP1s were more efficient at transporting H 2 O 2 with AtPIP1;3 and AtPIP1;4 being the most permeable. Among the AtPIP2s, AtPIP2;2 and AtPIP2;7 were also permeable to boric acid and Na + . Linking AtPIP substrate profiles with phylogenetics and gene expression data enabled us to align substrate preferences with known biological roles of AtPIPs and importantly guide towards unidentified roles hidden by functional redundancy at key developmental stages and within tissue types. This analysis positions us to more strategically test in planta physiological roles of AtPIPs in order to unravel their complex contributions to the transport of important substrates, and secondly, to resolve links between aquaporin protein structure, substrate discrimination, and transport efficiency. One sentence summary Yeast based high throughput assays were developed to assess the permeability of each Arabidopsis PIP aquaporin isoform to water, H 2 O 2 , boric acid, urea and sodium.

To finish this special issue, some friends, colleagues and students of Prof. Chow (Emeritus Professor, the Research School of Biology, the Australian National University) have written small tributes to acknowledge not only his eminent career but to describe his wonderful personality.

Abstract Aquaporins (AQPs) are membrane‐spanning channel proteins with exciting applications for plant engineering and industrial applications. Translational outcomes will be improved by better understanding the extensive diversity of plant AQPs. However, AQP gene families are complex, making exhaustive identification difficult, especially in polyploid species. The allotetraploid species of Nicotiana tabacum (Nt; tobacco) plays a significant role in modern biological research and is closely related to several crops of economic interest, making it a valuable platform for AQP research. Recently, De Rosa et al., (2020) and Ahmed et al., (2020), concurrently reported on the AQP gene family in tobacco, establishing family sizes of 76 and 88 members, respectively. The discrepancy highlights the difficulties of characterizing large complex gene families. Here, we identify and resolve the differences between the two studies, clarify gene models, and yield a consolidated collection of 84 members that more accurately represents the complete NtAQP family. Importantly, this consensus NtAQP collection will reduce confusion and ambiguity that would inevitably arise from having two different descriptive studies and sets of NtAQP gene names. This report also serves as a case study, highlighting and discussing variables to be considered and refinements required to ensure comprehensive gene family characterizations, which become valuable resources for examining the evolution and biological functions of genes.

The dynamics of leaf photosynthesis in fluctuating light affects carbon gain by plants. Mesophyll conductance (gm) limits CO2 assimilation rate (A) under the steady state, but the extent of this limitation under non-steady-state conditions is unknown. In the present study, we aimed to characterize the dynamics of gm and the limitations to A imposed by gas diffusional and biochemical processes under fluctuating light. The induction responses of A, stomatal conductance (gs), gm, and the maximum rate of RuBP carboxylation (Vcmax) or electron transport (J) were investigated in Arabidopsis (Arabidopsis thaliana (L.)) and tobacco (Nicotiana tabacum L.). We first characterized gm induction after a change from darkness to light. Each limitation to A imposed by gm, gs and Vcmax or J was significant during induction, indicating that gas diffusional and biochemical processes limit photosynthesis. Initially, gs imposed the greatest limitation to A, showing the slowest response under high light after long and short periods of darkness, assuming RuBP-carboxylation limitation. However, if RuBP-regeneration limitation was assumed, then J imposed the greatest limitation. gm did not vary much following short interruptions to light. The limitation to A imposed by gm was the smallest of all the limitations for most of the induction phase. This suggests that altering induction kinetics of mesophyll conductance would have little impact on A following a change in light. To enhance the carbon gain by plants under naturally dynamic light environments, attention should therefore be focused on faster stomatal opening or activation of electron transport.

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

To feed an ever-increasing population we must leverage advances in genomics and phenotyping to harness the variation in wheat breeding populations for traits like photosynthetic capacity which remains unoptimized. Here we survey a diverse set of wheat germplasm containing elite, introgression and synthetic derivative lines uncovering previously uncharacterized variation. We demonstrate how strategic integration of exotic material alleviates the D genome genetic bottleneck in wheat, increasing SNP rate by 62% largely due to Ae. tauschii synthetic wheat donors. Across the panel, 67% of the Ae. tauschii donor genome is represented as introgressions in elite backgrounds. We show how observed genetic variation together with hyperspectral reflectance data can be used to identify candidate genes for traits relating to photosynthetic capacity using association analysis. This demonstrates the value of genomic methods in uncovering hidden variation in wheat and how that variation can assist breeding efforts and increase our understanding of complex traits.