The genetic architecture of photosynthesis and plant growth-related traits in tomato

Genome-wide association study of leaf photosynthesis using a high-throughput gas exchange system in rice

Enhancing leaf photosynthetic capacity is essential for improving the yield of rice (Oryza sativa L.). Although the exploitation of natural genetic resources is considered a promising approach to enhance photosynthetic capacity, genomic factors related to the genetic diversity of leaf photosynthetic capacity have yet to be fully elucidated due to the limitation of measurement efficiency. In this study, we aimed to identify novel genomic regions for the net CO2 assimilation rate (A) by combining genome-wide association study (GWAS) and the newly developed rapid closed gas exchange system MIC-100. Using three MIC-100 systems in the field at the vegetative stage, we measured A of 168 temperate japonica rice varieties with six replicates for three years. We found that the modern varieties exhibited higher A than the landraces, while there was no significant relationship between the release year and A among the modern varieties. Our GWAS scan revealed two major peaks located on chromosomes 4 and 8, which were repeatedly detected in the different experiments and in the generalized linear modelling approach. We suggest that high-throughput gas exchange measurements combined with GWAS is a reliable approach for understanding the genetic mechanisms underlying photosynthetic diversities in crop species.

Multitraits evaluation of a Solanum pennellii introgression tomato line challenged by combined abiotic stress

Rising daily temperatures and water shortage are two of the major concerns in agriculture. In this work, we analysed the tolerance traits in a tomato line carrying a small region of the Solanum pennellii wild genome (IL12-4-SL) when grown under prolonged conditions of single and combined high temperature and water stress. When exposed to stress, IL12-4-SL showed higher heat tolerance than the cultivated line M82 at morphological, physiological, and biochemical levels. Moreover, under stress IL12-4-SL produced more flowers than M82, also characterized by higher pollen viability. In both lines, water stress negatively affected photosynthesis more than heat alone, whereas the combined stress did not further exacerbate the negative impacts of drought on this trait. Despite an observed decrease in carbon fixation, the quantum yield of PSII linear electron transport in IL12-4-SL was not affected by stress, thereby indicating that photochemical processes other than CO₂ fixation acted to maintain the electron chain in oxidized state and prevent photodamage. The ability of IL12-4-SL to tolerate abiotic stress was also related to the intrinsic ability of this line to accumulate ascorbic acid. The data collected in this study clearly indicate improved tolerance to single and combined abiotic stress for IL12-4-SL, making this line a promising one for cultivation in a climate scenario characterized by frequent and long-lasting heatwaves and low rainfall.

Research Progress in Improving Photosynthetic Efficiency

Photosynthesis is the largest mass- and energy-conversion process on Earth, and it is the material basis for almost all biological activities. The efficiency of converting absorbed light energy into energy substances during photosynthesis is very low compared to theoretical values. Based on the importance of photosynthesis, this article summarizes the latest progress in improving photosynthesis efficiency from various perspectives. The main way to improve photosynthetic efficiency is to optimize the light reactions, including increasing light absorption and conversion, accelerating the recovery of non-photochemical quenching, modifying enzymes in the Calvin cycle, introducing carbon concentration mechanisms into C₃ plants, rebuilding the photorespiration pathway, de novo synthesis, and changing stomatal conductance. These developments indicate that there is significant room for improvement in photosynthesis, providing support for improving crop yields and mitigating changes in climate conditions.

Opportunity and challenges of phenotyping plant salt tolerance

Salinity is a key factor limiting agricultural production worldwide. Recent advances in field phenotyping have enabled the recording of the environmental history and dynamic response of plants by considering both genotype × environment (G×E) interactions and envirotyping. However, only a few studies have focused on plant salt tolerance phenotyping. Therefore, we analyzed the potential opportunities and major challenges in improving plant salt tolerance using advanced field phenotyping technologies. RGB imaging and spectral and thermal sensors are the most useful and important sensing techniques for assessing key morphological and physiological traits of plant salt tolerance. However, field phenotyping faces challenges owing to its practical applications and high costs, limiting its use in early generation breeding and in developing countries.

Feeding the world: impacts of elevated [CO2] on nutrient content of greenhouse grown fruit crops and options for future yield gains

Several long-term studies have provided strong support demonstrating that growing crops under elevated [CO2] can increase photosynthesis and result in an increase in yield, flavour and nutritional content (including but not limited to Vitamins C, E and pro-vitamin A). In the case of tomato, increases in yield by as much as 80% are observed when plants are cultivated at 1000 ppm [CO2], which is consistent with current commercial greenhouse production methods in the tomato fruit industry. These results provide a clear demonstration of the potential for elevating [CO2] for improving yield and quality in greenhouse crops. The major focus of this review is to bring together 50 years of observations evaluating the impact of elevated [CO2] on fruit yield and fruit nutritional quality. In the final section, we consider the need to engineer improvements to photosynthesis and nitrogen assimilation to allow plants to take greater advantage of elevated CO2 growth conditions.

Understanding source-sink interactions: Progress in model plants and translational research to crops

Agriculture is facing a massive increase in demand per hectare as a result of an ever-expanding population and environmental deterioration. While we have learned much about how environmental conditions and diseases impact crop yield, until recently considerably less was known concerning endogenous factors, including within-plant nutrient allocation. In this review, we discuss studies of source-sink interactions covering both fundamental research in model systems under controlled growth conditions and how the findings are being translated to crop plants in the field. In this respect we detail efforts aimed at improving and/or combining C₃, C₄, and CAM modes of photosynthesis, altering the chloroplastic electron transport chain, modulating photorespiration, adopting bacterial/algal carbon-concentrating mechanisms, and enhancing nitrogen- and water-use efficiencies. Moreover, we discuss how modulating TCA cycle activities and primary metabolism can result in increased rates of photosynthesis and outline the opportunities that evaluating natural variation in photosynthesis may afford. Although source, transport, and sink functions are all covered in this review, we focus on discussing source functions because the majority of research has been conducted in this field. Nevertheless, considerable recent evidence, alongside the evidence from classical studies, demonstrates that both transport and sink functions are also incredibly important determinants of yield. We thus describe recent evidence supporting this notion and suggest that future strategies for yield improvement should focus on combining improvements in each of these steps to approach yield optimization.

Mining for allelic gold: finding genetic variation in photosynthetic traits in crops and wild relatives

Improvement of photosynthetic traits in crops to increase yield potential and crop resilience has recently become a major breeding target. Synthetic biology and genetic technologies offer unparalleled opportunities to create new genetics for photosynthetic traits driven by existing fundamental knowledge. However, large 'gene bank' collections of germplasm comprising historical collections of crop species and their relatives offer a wealth of opportunities to find novel allelic variation in the key steps of photosynthesis, to identify new mechanisms and to accelerate genetic progress in crop breeding programmes. Here we explore the available genetic resources in food and fibre crops, strategies to selectively target allelic variation in genes underpinning key photosynthetic processes, and deployment of this variation via gene editing in modern elite material.

A Machine Learning Approach for the Non-Destructive Estimation of Leaf Area in Medicinal Orchid Dendrobium nobile L

In this study, leaf area prediction models of Dendrobium nobile, were developed through machine learning (ML) techniques including multiple linear regression (MLR), support vector regression (SVR), gradient boosting regression (GBR), and artificial neural networks (ANNs). The best model was tested using the coefficient of determination (R2), mean absolute errors (MAEs), and root mean square errors (RMSEs) and statistically confirmed through average rank (AR). Leaf images were captured through a smartphone and ImageJ was used to calculate the length (L), width (W), and leaf area (LA). Three orders of L, W, and their combinations were taken for model building. Multicollinearity status was checked using Variance Inflation Factor (VIF) and Tolerance (T). A total of 80% of the dataset and the remaining 20% were used for training and validation, respectively. KFold (K = 10) cross-validation checked the model overfit. GBR (R2, MAE and RMSE values ranged at 0.96, (0.82–0.91) and (1.10–1.11) cm2) in the testing phase was the best among the ML models. AR statistically confirms the outperformance of GBR, securing first rank and a frequency of 80% among the top ten ML models. Thus, GBR is the best model imparting its future utilization to estimate leaf area in D. nobile.

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

MAIN CONCLUSION

By combining hyperspectral signatures of peanut and soybean, we predicted Vcmax and Jmax with 70 and 50% accuracy. The PLS was the model that better predicted these photosynthetic parameters. One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.

Genome wide association study of plant height and tiller number in hulless barley

Hulless barley (Hordeum vulgare L. var. nudum), also called naked barley, is a unique variety of cultivated barley. The genome-wide specific length amplified fragment sequencing (SLAF-seq) method is a rapid deep sequencing technology that is used for the selection and identification of genetic loci or markers. In this study, we collected 300 hulless barley accessions and used the SLAF-seq method to identify candidate genes involved in plant height (PH) and tiller number (TN). We obtained a total of 1407 M paired-end reads, and 228,227 SLAF tags were developed. After filtering using an integrity threshold of >0.8 and a minor allele frequency of >0.05, 14,504,892 single-nucleotide polymorphisms (SNP) loci were screened out. The remaining SNPs were used for the construction of a neighbour-joining phylogenetic tree, and the three subcluster members showed no obvious differentiation among regional varieties. We used a genome wide association study approach to identify 1006 and 113 SNPs associated with TN and PH, respectively. Based on best linear unbiased predictors (BLUP), 41 and 29 SNPs associated with TN and PH, respectively. Thus, several of genes, including Hd3a and CKX5, may be useful candidates for the future genetic breeding of hulless barley. Taken together, our results provide insight into the molecular mechanisms controlling barley architecture, which is important for breeding and yield.

Evaluation of the molecular and physiological response to dehydration of two accessions of the model plant Setaria viridis

Water deficits are responsible for countless agricultural losses. Among the affected crops, C4 plants are of special interest due to their high water and nitrogen use efficiency. Two accessions of Setaria viridis (Ast-1 and A10.1) with contrasting responses to water deficit were used in the current work to better understand the mechanisms behind drought tolerance in C4 species. Our results showed that although the A10.1 accession exhibited a reduced size and lower Rfd values in comparison to Ast-1, it had overall higher Fv/Fm and lower NPQ values in well-watered conditions. The water deficit induction was performed with PEG-8000 at the grain-filling stage using dehydration cycles. Analysis of physiological measurements showed the A10.1 accession as being more tolerant to multiple water deficit exposures. In addition, PCA identified a clear difference in the pattern of drought response of the accessions. Four drought marker genes previously described in the literature were chosen to evaluate the response at the molecular level: SvP5CS2, SvDHN1, SvNAC6, and SvWRKY1. Besides confirming that Ast-1 is a more sensitive accession, the expression analysis revealed that SvNAC1 might better monitor drought stress, while SvWRKY1 was able to differentiate the two accessions. Distinct evolutionary histories of each accession may be behind their differences in response to water deficits.

Physiological, metabolic, and stomatal adjustments in response to salt stress in Jatropha curcas

Salinity is a major issue affecting photosynthesis and crop production worldwide. High salinity induces both osmotic and ionic stress in plant tissues as a result of complex interactions among morphological, physiological, and biochemical processes. Salinity, in turn, can provoke inactivation of some enzymes in the Calvin-Benson cycle and therefore affect the fine adjustment of electron transport in photosystem I and carbon related reactions. Here, we used three contrasting Jatropha curcas genotypes namely CNPAE183 (considered tolerant to salinity), CNPAE218 (sensible), and JCAL171 (intermediate) to understand salinity responses. By performing a long-term (12 months) experiment in land conditions, we investigated distinct mechanisms used by J. curcas to cope with threatening salinity effects by analyzing gas exchange, mineral nutrition and metabolic responses. First, our results highlighted the plasticity of stomatal development and density in J. curcas under salt stress. It also demonstrated that the CNPAE183 presented higher salt-tolerance whereas CNPAE218 displayed a more sensitive salt-tolerance response. Our results also revealed that both tolerance and sensitivity to salinity were connected with an extensive metabolite reprogramming in the Calvin-Benson cycle and Tricarboxylic Acid cycle intermediates with significant changes in amino acids and organic acids. Collectively, these results indicate that the CNPAE183 and CNPAE218 genotypes demonstrated certain characteristics of salt-tolerant-like and salt-sensitive-like genotypes, respectively. Overall, our results highlight the significance of metabolites associated with salt responses and further provide a useful selection criterion in during screening for salt tolerance in J. curcas in breeding programmes.

Physiological and Biochemical Responses of Tomato Plants Grafted onto Solanum pennellii and Solanum peruvianum under Water-Deficit Conditions

Grafting using suitable rootstocks mitigates the adverse effects caused by environmental stresses such as water deficit in the tomato crop. Solanum pennellii and Solanum peruvianum, the wild relatives of tomato, are used as rootstocks due to their tolerance to water deficit and soil-borne diseases. This study focused on evaluating physiological and biochemical responses of tomato plants grafted onto S. pennellii and S. peruvianum rootstocks during water deficit. The commercial tomato cultivar 'HM 1823' (HM) either self-grafted (HM/HM) or grafted onto S. pennellii (HM/PN), S. peruvianum (HM/PR), and 'Multifort' (HM/MU) rootstocks were subjected to water-deficit stress by withholding irrigation for eight days. The performance of the grafted plants under water deficit was evaluated using physiological and biochemical parameters in vegetative tissues of the grafted plants. Plants grafted using S. pennellii (PN) and S. peruvianum (PR) rootstocks showed higher values of water potential (Ψw), relative water content (RWC), net photosynthetic rate (A), and leaf water use efficiencies (WUE) compared to HM, HM/HM, and HM/MU. Plants grafted onto tomato wild relatives showed the lowest malondialdehyde (MDA) and proline content. This study demonstrated that the rootstocks of wild tomato relatives reduced the effect of water deficit to a greater extent through better physiological, metabolic, and biochemical adjustments than self-grafting plants.

Integrating multi-omics data for crop improvement

Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.

Metabolomic Analysis of Natural Variation in Arabidopsis

Methodological advances in coupled-mass spectrometry (gas chromatography and liquid chromatography; GC-MS and LC-MS) have rendered the profiling of highly complex plant extracts relatively facile and allowed that their high-throughput use aids the investigation of a range of biological questions. Among these is the elucidation of the genetic factors underlying metabolite abundance. For this purpose genome-wide association studies (GWAS) are being widely adopted in Arabidopsis with the resultant quantitative trait loci being subjected to cross-validation by the use of recombinant inbred lines, introgression lines, and T-DNA insertional knockout lines.

Evaluation of anatomical and physiological traits of Solanum pennellii Cor. associated with plant yield in tomato plants under water-limited conditions

Although intensively studied, few works had looked into S. pennellii’s ability to cope with water-deficit conditions from a breeding point of view. In this study, we assessed potential traits of S. pennellii, that had previously been linked to high yields in other plant species, under long-term water-limited conditions and made a parallel with plant yield. For this purpose, the drought-resistant tomato genotypes IL 3–5 and IL 10–1, and the drought-sensitive IL 2–5 and IL 7–1 at seed level, together with both parents the S. pennellii accession LA 716 and the cultivar M82 were kept at 50 and 100% ASW throughout the growing season. Our findings confirm the superiority of LA 716 under water-limited conditions compared to the other S. lycopersicum genotypes in terms of plant water status maintenance. Percentual reduction on plant yield was higher in IL 3–5 and IL 10–1 than in M82 plants, indicating no correlation between drought resistance on germination and plant productive stages. A strong positive correlation was found between fruit yield and A, g_s, and Ψ_leaf at 50% ASW, suggesting these traits as important selection criteria. LT and g_min, LA 716’s most promising traits, did not show a linear correlation with fruit yield under low water regimes. This study unravels traits behind tomato performance under water-limited conditions and should work as guidance for breeders aiming at developing drought-resistant tomato cultivars.

Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops

Photosynthesis is the major process leading to primary production in the Biosphere. There is a total of 7000bn tons of CO2 in the atmosphere and photosynthesis fixes more than 100bn tons annually. The CO2 assimilated by the photosynthetic apparatus is the basis of crop production and, therefore, of animal and human food. This has led to a renewed interest in photosynthesis as a target to increase plant production and there is now increasing evidence showing that the strategy of improving photosynthetic traits can increase plant yield. However, photosynthesis and the photosynthetic apparatus are both conditioned by environmental variables such as water availability, temperature, [CO2], salinity, and ozone. The "omics" revolution has allowed a better understanding of the genetic mechanisms regulating stress responses including the identification of genes and proteins involved in the regulation, acclimation, and adaptation of processes that impact photosynthesis. The development of novel non-destructive high-throughput phenotyping techniques has been important to monitor crop photosynthetic responses to changing environmental conditions. This wealth of data is being incorporated into new modeling algorithms to predict plant growth and development under specific environmental constraints. This review gives a multi-perspective description of the impact of changing environmental conditions on photosynthetic performance and consequently plant growth by briefly highlighting how major technological advances including omics, high-throughput photosynthetic measurements, metabolic engineering, and whole plant photosynthetic modeling have helped to improve our understanding of how the photosynthetic machinery can be modified by different abiotic stresses and thus impact crop production.

High Photosynthetic Rates in a Solanum pennellii Chromosome 2 QTL Is Explained by Biochemical and Photochemical Changes

Enhanced photosynthesis is strictly associated with to productivity and it can be accomplished by genetic approaches through identification of genetic variation. By using a Solanum pennellii introgression lines (ILs) population, it was previously verified that, under normal (CO2), IL 2-5 and 2-6 display increased photosynthetic rates by up to 20% in comparison with their parental background (M82). However, the physiological mechanisms involved in the enhanced CO2 assimilation exhibited by these lines remained unknown, precluding their use for further biotechnological applications. Thereby, here we attempted to uncover the physiological factors involved in the upregulation of photosynthesis in ILs 2-5 and 2-6 under normal (CO2) as well as under elevated (CO2). The results provide evidence for increased biochemical capacity (higher maximum carboxylation velocity and maximum electron transport rate) in plants from IL 2-5 and 2-6, whereas the diffusive components (stomatal and mesophyll conductances) were unaltered in these ILs in comparison to M82. Our analyses revealed that the higher photosynthetic rate observed in these ILs was associated with higher levels of starch as well as total protein levels, specially increased RuBisCO content. Further analyses performed in plants under high (CO2) confirmed that biochemical properties are involved in genetic variation on chromosome 2 related to enhanced photosynthesis.

GWAS reveals two novel loci for photosynthesis-related traits in soybean

Photosynthesis plays an extremely important role throughout the life cycle of plants. Improving the photosynthetic rate is a major target for increasing crop productivity. This study was conducted to identify single nucleotide polymorphisms (SNPs) associated with the net photosynthetic rate (Pn), stomatal conductance (Cond), intercellular carbon dioxide concentration (Ci) and transpiration rate (Trmmol) through genome-wide association study (GWAS) and to inspect the relationships among these traits in soybean (Glycine max (L.) Merr.). A population of 219 soybean accessions was used in this research. A total of 12 quantitative trait loci (QTLs) associated with Pn, Cond, Ci and Trmmol were detected and distributed on chromosomes 1, 2, 6, 7, 9, 11, 12, 13, 15, 16, 18, and 19, and some of these QTL overlapped with previously reported QTLs. Furthermore, four candidate genes were identified, and there were significantly different expression levels between the high-light-efficiency accessions and low-light-efficiency accessions. These putative genes may participate in the regulation of photosynthesis through different metabolic pathways. Therefore, the associated novel QTLs and candidate genes detected in this study will provide a theoretical basis for genetic studies of photosynthesis and provide new avenues for crop improvement.

Phenotyping: New Windows into the Plant for Breeders

Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.

Engineering Improved Photosynthesis in the Era of Synthetic Biology

Much attention has been given to the enhancement of photosynthesis as a strategy for the optimization of crop productivity. As traditional plant breeding is most likely reaching a plateau, there is a timely need to accelerate improvements in photosynthetic efficiency by means of novel tools and biotechnological solutions. The emerging field of synthetic biology offers the potential for building completely novel pathways in predictable directions and, thus, addresses the global requirements for higher yields expected to occur in the 21st century. Here, we discuss recent advances and current challenges of engineering improved photosynthesis in the era of synthetic biology toward optimized utilization of solar energy and carbon sources to optimize the production of food, fiber, and fuel.

Marginal Lands to Grow Novel Bio-Based Crops: A Plant Breeding Perspective

The biomass demand to fuel a growing global bio-based economy is expected to tremendously increase over the next decades, and projections indicate that dedicated biomass crops will satisfy a large portion of it. The establishment of dedicated biomass crops raises huge concerns, as they can subtract land that is required for food production, undermining food security. In this context, perennial biomass crops suitable for cultivation on marginal lands (MALs) raise attraction, as they could supply biomass without competing for land with food supply. While these crops withstand marginal conditions well, their biomass yield and quality do not ensure acceptable economic returns to farmers and cost-effective biomass conversion into bio-based products, claiming genetic improvement. However, this is constrained by the lack of genetic resources for most of these crops. Here we first review the advantages of cultivating novel perennial biomass crops on MALs, highlighting management practices to enhance the environmental and economic sustainability of these agro-systems. Subsequently, we discuss the preeminent breeding targets to improve the yield and quality of the biomass obtainable from these crops, as well as the stability of biomass production under MALs conditions. These targets include crop architecture and phenology, efficiency in the use of resources, lignocellulose composition in relation to bio-based applications, and tolerance to abiotic stresses. For each target trait, we outline optimal ideotypes, discuss the available breeding resources in the context of (orphan) biomass crops, and provide meaningful examples of genetic improvement. Finally, we discuss the available tools to breed novel perennial biomass crops. These comprise conventional breeding methods (recurrent selection and hybridization), molecular techniques to dissect the genetics of complex traits, speed up selection, and perform transgenic modification (genetic mapping, QTL and GWAS analysis, marker-assisted selection, genomic selection, transformation protocols), and novel high-throughput phenotyping platforms. Furthermore, novel tools to transfer genetic knowledge from model to orphan crops (i.e., universal markers) are also conceptualized, with the belief that their development will enhance the efficiency of plant breeding in orphan biomass crops, enabling a sustainable use of MALs for biomass provision.

Variations in Growth, Physiology, and Antioxidative Defense Responses of Two Tomato (Solanum lycopersicum L.) Cultivars after Co-Infection of Fusarium oxysporum and Meloidogyne incognita

The soil-borne fungus Fusarium oxysporum (Fo) and the nematode Meloidogyne incognita (Mi) are destructive pathogens that cause substantial yield losses to tomato (Solanum lycopersicum L.) crops worldwide. The present study sought to elucidate the physiological, biochemical, and cytological responses of tomato cultivars (Gailing maofen 802 and Zhongza 09) by root invasion of Fo (1 × 105 CFUmL−1) and Mi (1500 second-stage juveniles (J2) alone and in combination after 14 days. Results revealed that combined inoculation of Fo and Mi significantly increased disease intensity, electrolyte leakage, and hydrogen peroxide and malondialdehyde contents; and decreased photosynthetic capacity and enzyme activity in both cultivars as compared to their solo inoculation. Increasing the disease intensity reduced the maximum morphological traits, such as shoot length, total dry weight, and total chlorophyll contents, in G. maofen 802 (by 32%, 54.2%, and 52.3%, respectively) and Zhongza 09 (by 18%, 32%, and 21%, respectively) as compared to the control. Others factors were also reduced in G. maofen 802 and Zhongza 09, such as photosynthetic capacity (by 70% and 57%, respectively), stomatal conductance (by 86% and 70%, respectively), photochemical quantum yield of photosystem II (YII) (by 36.6% and 29%, respectively), and electron transport rate (by 17.7% and 10%, respectively), after combined inoculation of Fo and Mi. Furthermore, the combined infestation of Fo and Mi resulted in reduced activity of plant-defense-related antioxidants in G. maofen 802 compared with their single application or control. However, these antioxidants were highly up-regulated in Zhongza 09 (by 59%–93%), revealing the induction of tolerance against studied pathogens. The transmission electron microscopy (TEM) results further demonstrated that root cells of Zhongza 09 had unique tetrahedral crystal-like structures in the membrane close to mitochondria under all treatments except control. Therefore, it is concluded that Mi caused severe root damage, suppressed plant growth, depleted antioxidants, and caused high generation of ROS in the presence of Fo as compared to its solo inoculation. Tolerant cultivars adopted different mechanistic strategies at the structural and cellular levels to tolerate the Mi and Fo stresses.

Nitrogen differentially modulates photosynthesis, carbon allocation and yield related traits in two contrasting Capsicum chinense cultivars

Yield-related traits of Capsicum chinense are highly dependent on coordination between vegetative and reproductive growth, since the formation of reproductive tissues occurs iteratively in new sympodial bifurcations. In this study, we used two C. chinense cultivars (Biquinho and Habanero), contrasting for fruit size and fruit set, to investigate the responses of nitrogen (N) deficiency and excess on growth, photosynthesis, carbon (C) and N metabolisms as well as yield-related traits. Both cultivars increased biomass allocation to leaves in conditions of higher N supply and exhibited a parabolic behavior for fruit biomass allocation. Plants growing under N-deficiency produced a lower number of flowers and heavier fruits. Contrarily, plants under high N condition tended to decrease their CO₂ assimilation rate, harvest index and fruit weight. Biquinho, the cultivar with lower fruit size and higher fruit set, was initially less affected by excess of N due to its continuous formation of new reproductive sinks in relation to Habanero (which has lower fruit set and higher fruit size). The results suggest that N amount influences sucrose supply to different organs and can differentially affect yield-related traits between Capsicum cultivars with contrasting source-sink relations.

Using natural variation to understand the evolutionary pressures on plant photosynthesis

Photosynthesis is the gateway of the Sun's energy into the biosphere and the source of the ozone layer; thus it is both provider and protector of life as we know it. Despite its pivotal role we know surprisingly little about the genetic basis of variation in photosynthesis and the selective pressures giving rise to or maintaining this variation. In this review, I will briefly summarise our current knowledge of intraspecific and interspecific variation in photosynthesis to understand the main selective constraints on photosynthesis and what this means for the future of nature and agriculture in a changing world.

Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

INTRODUCTION

To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.

OBJECTIVE

This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.

METHODS

The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.

RESULTS

Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.

CONCLUSIONS

Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.

Using Plant Phenomics to Exploit the Gains of Genomics

Agricultural scientists face the dual challenge of breeding input-responsive, widely adoptable and climate-resilient varieties of crop plants and developing such varieties at a faster pace. Integrating the gains of genomics with modern-day phenomics will lead to increased breeding efficiency which in turn offers great promise to develop such varieties rapidly. Plant phenotyping techniques have impressively evolved during the last two decades. The low-cost, automated and semi-automated methods for data acquisition, storage and analysis are now available which allow precise quantitative analysis of plant structure and function; and genetic dissection of complex traits. Appropriate plant types can now be quickly developed that respond favorably to low input and resource-limited environments and address the challenges of subsistence agriculture. The present review focuses on the need of systematic, rapid, minimal invasive and low-cost plant phenotyping. It also discusses its evolution to modern day high throughput phenotyping (HTP), traits amenable to HTP, integration of HTP with genomics and the scope of utilizing these tools for crop improvement.

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data

Leaf attribute estimation is crucial for understanding photosynthesis, respiration, transpiration, and carbon and nutrient cycling in vegetation and evaluating the biological parameters of plants or forests. Terrestrial laser scanning (TLS) has the capability to provide detailed characterisations of individual trees at both the branch and leaf scales and to extract accurate structural parameters of stems and crowns. In this paper, we developed a computer graphic-based 3D point cloud segmentation approach for accurately and efficiently detecting tree leaves and their morphological features (i.e., leaf area and leaf angle distributions (leaf azimuthal angle and leaf inclination angle)) from single leaves. To this end, we adopted a sphere neighbourhood model with an adaptive radius to extract the central area points of individual leaves with different morphological structures and complex spatial distributions; meanwhile, four auxiliary criteria were defined to ensure the accuracy of the extracted central area points of individual leaf surfaces. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to cluster the central area points of leaves and to obtain the centre point corresponding to each leaf surface. We also achieved segmentation of individual leaf blades using an advanced 3D watershed algorithm based on the extracted centre point of each leaf surface and two morphology-related parameters. Finally, the leaf attributes (leaf area and leaf angle distributions) were calculated and assessed by analysing the segmented single-leaf point cloud. To validate the final results, the actual leaf area, leaf inclination and azimuthal angle data of designated leaves on the experimental trees were manually measured during field activities. In addition, a sensitivity analysis investigated the effect of the parameters in our segmentation algorithm. The results demonstrated that the segmentation accuracy of Ehretia macrophylla (94.0%) was higher than that of crape myrtle (90.6%) and Fatsia japonica (88.8%). The segmentation accuracy of Fatsia japonica was the lowest of the three experimental trees. In addition, the single-leaf area estimation accuracy for Ehretia macrophylla (95.39%) was still the highest among the three experimental trees, and the single-leaf area estimation accuracy for crape myrtle (91.92%) was lower than that for Ehretia macrophylla (95.39%) and Fatsia japonica (92.48%). Third, the method proposed in this paper provided accurate leaf inclination and azimuthal angles for the three experimental trees (Ehretia macrophylla: leaf inclination angle: R 2 = 0.908, RMSE = 6.806° and leaf azimuth angle: R 2 = 0.981, RMSE = 7.680°; crape myrtle: leaf inclination angle: R 2 = 0.901, RMSE = 8.365° and leaf azimuth angle: R 2 = 0.938, RMSE = 7.573°; Fatsia japonica: leaf inclination angle: R 2 = 0.849, RMSE = 6.158° and leaf azimuth angle: R 2 = 0.947, RMSE = 3.946°). The results indicate that the proposed method is effective and operational for providing accurate, detailed information on single leaves and vegetation structure from scanned data. This capability facilitates improvements in applications such as the estimation of leaf area, leaf angle distribution and biomass.

The ratio of trichomes to stomata is associated with water use efficiency in Solanum lycopersicum (tomato)

Trichomes are specialised structures that originate from the aerial epidermis of plants, and play key roles in the interaction between the plant and the environment. In this study we investigated the trichome phenotypes of four lines selected from the Solanum lycopersicum × Solanum pennellii introgression line (IL) population for differences in trichome density, and their impact on plant performance under water-deficit conditions. We performed comparative analyses at morphological and photosynthetic levels of plants grown under well-watered (WW) and also under water-deficit (WD) conditions in the field. Under WD conditions, we observed higher trichome density in ILs 11-3 and 4-1, and lower stomatal size in IL 4-1 compared with plants grown under WW conditions. The intrinsic water use efficiency (WUEi ) was higher under WD conditions in IL 11-3, and the plant-level water use efficiency (WUEb ) was also higher in IL 11-3 and in M82 for WD plants. The ratio of trichomes to stomata (T/S) was positively correlated with WUEi and WUEb , indicating an important role for both trichomes and stomata in drought tolerance in tomato, and offering a promising way to select for improved water use efficiency of major crops.

Next-generation strategies for understanding and influencing source-sink relations in crop plants

Whether plants are source or sink limited, that is, whether carbon assimilation or rather assimilate usage is ultimately responsible for crop yield, has been the subject of intense debate over several decades. Here we provide a short review of this debate before focusing on the use of transgenic intervention as a means to influence yield by modifying either source or sink function (or both). Given the relatively low success rates of strategies targeting single genes we highlight the success of multi-target transformations. The emergence of whole plant models and the potential impact that these will have in aiding yield improvement strategies are then discussed. We end by providing our perspective for next generation strategies for improving crop plants by means of manipulating their source-sink relations.

Metabolic regulation of photosynthesis

Photosynthesis is fundamental to biomass production, but is a dynamic process sensitive to environmental constraints. In recent years, approaches to increase biomass and grain yield by altering photosynthetically related processes in the plant have received considerable attention. However, improving biomass yield requires a predictive understanding of the molecular mechanisms that allow photosynthesis to be adjusted. The important roles of metabolic reactions external to those directly involved in photosynthesis are highlighted in this review; however, our major focus is on the routes taken to improve photosynthetic carbon assimilation and to increase photosynthetic efficiency and consequently biomass yield.