Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Perspectives on improving photosynthesis to increase crop yield

Improving photosynthesis, the fundamental process by which plants convert light energy into chemical energy, is a key area of research with great potential for enhancing sustainable agricultural productivity and addressing global food security challenges. This perspective delves into the latest advancements and approaches aimed at optimizing photosynthetic efficiency. Our discussion encompasses the entire process, beginning with light harvesting and its regulation and progressing through the bottleneck of electron transfer. We then delve into the carbon reactions of photosynthesis, focusing on strategies targeting the enzymes of the Calvin-Benson-Bassham (CBB) cycle. Additionally, we explore methods to increase carbon dioxide (CO2) concentration near the Rubisco, the enzyme responsible for the first step of CBB cycle, drawing inspiration from various photosynthetic organisms, and conclude this section by examining ways to enhance CO2 delivery into leaves. Moving beyond individual processes, we discuss two approaches to identifying key targets for photosynthesis improvement: systems modeling and the study of natural variation. Finally, we revisit some of the strategies mentioned above to provide a holistic view of the improvements, analyzing their impact on nitrogen use efficiency and on canopy photosynthesis.

The long and tortuous path towards improving photosynthesis by engineering elevated mesophyll conductance

The growing demand for global food production is likely to be a defining issue facing humanity over the next 50 years. To tackle this challenge, there is a desire to bioengineer crops with higher photosynthetic efficiencies, to increase yields. Recently, there has been a growing interest in engineering leaves with higher mesophyll conductance (gm), which would allow CO2 to move more efficiently from the substomatal cavities to the chloroplast stroma. However, if crop yield gains are to be realised through this approach, it is essential that the methodological limitations associated with estimating gm are fully appreciated. In this review, we summarise these limitations, and outline the uncertainties and assumptions that can affect the final estimation of gm. Furthermore, we critically assess the predicted quantitative effect that elevating gm will have on assimilation rates in crop species. We highlight the need for more theoretical modelling to determine whether altering gm is truly a viable route to improve crop performance. Finally, we offer suggestions to guide future research on gm, which will help mitigate the uncertainty inherently associated with estimating this parameter.

Plant microphenotype: from innovative imaging to computational analysis

The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications of microphenotyping in plant science over the past two decades. We then point out several challenges in this field and suggest that cross-scale image acquisition strategies, powerful artificial intelligence algorithms, advanced genetic analysis, and computational phenotyping need to be established and performed to better understand interactions among genotype, environment, and management. Microphenotyping has entered the era of Microphenotyping 3.0 and will largely advance functional genomics and plant science.

Conserved cellular patterning in the mesophyll of rice leaves

The mesophyll cells of grass leaves, such as rice, are traditionally viewed as displaying a relatively uniform pattern, in contrast to the clear distinctions of palisade and spongy layers in typical eudicot leaves. This quantitative analysis of mesophyll cell size and shape in rice leaves reveals that there is an inherent pattern in which cells in the middle layer of the mesophyll are larger and less circular and have a distinct orientation of their long axis compared to mesophyll cells in other layers. Moreover, this pattern was observed in a range of rice cultivars and species. The significance of this pattern with relation to potential photosynthetic function and the implication of the widespread use of middle layer mesophyll cells as typical of the rice leaf have been investigated and discussed.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Is chloroplast size optimal for photosynthetic efficiency?

Improving photosynthetic efficiency has recently emerged as a promising way to increase crop production in a sustainable manner. While chloroplast size may affect photosynthetic efficiency in several ways, we aimed to explore whether chloroplast size manipulation can be a viable approach to improving photosynthetic performance. Several tobacco (Nicotiana tabacum) lines with contrasting chloroplast sizes were generated via manipulation of chloroplast division genes to assess photosynthetic performance under steady-state and fluctuating light. A selection of lines was included in a field trial to explore productivity. Lines with enlarged chloroplasts underperformed in most of the measured traits. Lines with smaller and more numerous chloroplasts showed a similar efficiency compared with wild-type (WT) tobacco. Chloroplast size only weakly affected light absorptance and light profiles within the leaf. Increasing chloroplast size decreased mesophyll conductance (gm ) but decreased chloroplast size did not increase gm . Increasing chloroplast size reduced chloroplast movements and enhanced non-photochemical quenching. The chloroplast smaller than WT appeared to be no better than WT for photosynthetic efficiency and productivity under field conditions. The results indicate that chloroplast size manipulations are therefore unlikely to lead to higher photosynthetic efficiency or growth.

Creating a virtual leaf

When microscopy meets modelling the exciting concept of a 'virtual leaf' is born. The goal of a 'virtual leaf' is to capture complex physiology in a virtual environment, resulting in the capacity to run experiments computationally. One example of a 'virtual leaf' application is capturing 3D anatomy from volume microscopy data and estimating where water evaporates in the leaf and the proportions of apoplastic, symplastic and gas phase water transport. The same 3D anatomy could then be used to improve established 3D reaction-diffusion models, providing a better understanding of the transport of CO₂ across the stomata, through the airspace and across the mesophyll cell wall. This viewpoint discusses recent progress that has been made in transitioning from a bulk leaf approach to a 3D understanding of leaf physiology, in particular, the movement of CO₂ and H₂O within the leaf.