Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions

Pedicel anatomy and histology in tomato vary according to genotype and water-deficit environment, affecting fruit mass

The growth and composition of fleshy fruits depend on resource acquisition and distribution in the plant. In tomato, the pedicel serves as the final connection between plant and fruit. However, very few quantitative data are available for the conducting tissues of the pedicel, nor is their genetic variability known. In the present study, a histological approach was combined with process-based modeling to evaluate the potential contribution made by the anatomy and histology of the pedicel to variations in fruit mass. Eleven genotypes were characterized and the impact of water deficit was studied for a single genotype using stress intensity and stage of application as variables. The results highlighted extensive variations in the relative proportions of the different pedicel tissues and in the absolute areas of xylem and phloem between genotypes. The model suggests that the variations in the area of the pedicel's vascular tissues induced by differences in genotype and water-deficit environments partly contributed to fruit mass variability. They therefore warrant phenotyping for use in the development of plant strains adapted to future environmental constraints. The results also demonstrated the need to develop non-invasive in vivo measurement methods to establish the number and size of active vessels and the flow rates in these vessels to improve prediction of water fluxes in plant architecture.

Resource Translocation Modelling Highlights Density-Dependence Effects in Fruit Production at Various Levels of Organisation

The size of fruit cells, seeds and fruits depends on their number. Could this density-dependence effect result from sugar resource sharing and, if so, does it involve phloem sugar flow or the intensity of sugar unloading to the sink? A density-dependence model (DDM) describing these processes was designed and parameterised for six species at five levels of organisation: cells and seeds within fruits, fruits within clusters, fruits within plants and plants within plots. Sugar flow was driven by phloem conductance, determined by parameters α, governing the shape of its relationship to population size, and κ, its value for a population size of one. Sugar unloading followed Michaelis-Menten kinetics with parameters V_m (maximal unloading rate) and K_m (Michaelis constant). The DDM effectively reproduced the observed individual mass dynamics, the undercompensating density dependence observed in most species at all sub-plant levels and the undercompensating, exact and overcompensating density dependence observed at the plant level. Conductance (κ) was a scaling factor varying with the level of organisation. V_m was positively correlated with density dependence, and α was negatively correlated with density dependence only if the plant-within-plot level was not considered. Analysis of the model's behaviour indicates that density dependence of fruit growth could be a result of sugar sharing, and that both phloem sugar flow and sugar unloading contribute to these effects.

Integration of Crop Growth Models and Genomic Prediction

Crop growth models (CGMs) consist of multiple equations that represent physiological processes of plants and simulate crop growth dynamically given environmental inputs. Because parameters of CGMs are often genotype-specific, gene effects can be related to environmental inputs through CGMs. Thus, CGMs are attractive tools for predicting genotype by environment (G×E) interactions. This chapter reviews CGMs, genetic analyses using these models, and the status of studies that integrate genomic prediction with CGMs. Examples of CGM analyses are also provided.

A parsimonious mechanistic model of reproductive and vegetative growth in fruit trees predicts consequences of fruit thinning and branch pruning

Productivity of fruit tree crops depends on the interaction between plant physiology, environmental conditions and agricultural practices. We develop a mechanistic model of fruit tree crops that reliable simulates the dynamics of variables of interest for growers and consequences of agricultural practices while relying on a minimal number of inputs and parameters. The temporal dynamics of carbon content in the different organs (i.e., shoots-S, roots-R and fruits-F) are the result of photosynthesis by S, nutrient supply by R, respiration by S, R and F, competition among different organs, photoperiod and initial system conditions partially controlled by cultural practices. We calibrate model parameters and evaluate model predictions using unpublished data from a peach (Prunus persica) experimental orchard with trees subjected to different levels of branch pruning and fruit thinning. Fiinally, we evaluate the consequences of different combinations of pruning and thinning intensities within a multi-criteria analysis. The predictions are in good agreement with the experimental measurements and for the different conditions (pruning and thinning). Our simulations indicate that thinning and pruning practices actually used by growers provide the best compromise between total shoot production, which impacts next year's abundance of shoots and fruits, and current year's fruit production in terms of quantity (yield) and quality (average fruit size). This suggests that growers are not only interested in maximizing current year's yield but also in its quality and its durability. The present work provides for modelers a system of equations based on acknowledged principles of plant science easily modifiable for different purposes. For horticulturists, it gives insights on the potentialities of pruning and thinning. For ecologists, it provides a transparent quantitative framework that can be coupled with biotic and abiotic stressors.

Water transport in fleshy fruits: Research advances, methodologies, and future directions

Fruits are reproductive organs in flowering plants and the harvested products of many agricultural crops. They play an increasingly important role in the human diet due to their nutritional values. Water is the most abundant component of most fleshy fruits, and it is essential for fruit growth and quality formation. Water is transported to the fruit via the vascular system (xylem and phloem) and lost to the air through the fruit surface due to transpiration. This minireview presents a framework for understanding water transport in fleshy fruits along with brief introductions of key methodologies used in this research field. We summarize the advances in the research on the patterns of water flow into and out of the fruit over development and under different environmental conditions and cultural practices. We review the key findings on fruit transpiration, xylem transport, phloem transport, and the coordination of water flows in maintaining fruit water balance. We also summarize research on post-vascular water transport mediated by aquaporins in fruits. More efforts are needed to elucidate the mechanisms by which different environmental conditions impact fruit water transport at the micro-level and to better understand the physiological implications of the coordination of water flows. Incorporating fruit water transport into the research area of plant hydraulics will provide new insights into water transport in the soil-plant-atmosphere continuum.

Modelling predicts tomatoes can be bigger and sweeter if biophysical factors and transmembrane transports are fine-tuned during fruit development

The trade-off between yield and quality, a major problem for the production of fleshy fruits, involves fruit expansive growth and sugar metabolism. Here we developed an integrative model by coupling a biophysical model of fleshy fruit growth processes, including water and carbon fluxes and organ expansion, with an enzyme-based kinetic model of sugar metabolism to better understand the interactions between these two processes. The integrative model was initially tested on tomato fruit, a model system for fleshy fruit. The integrative model closely simulated the biomass and major carbon metabolites of tomato fruit developing under optimal or stress conditions. The model also performed robustly when simulating the fruit size and sugar concentrations of different tomato genotypes including wild species. The validated model was used to explore ways of uncoupling the size-sweetness trade-off in fruit. Model-based virtual experiments suggested that larger sweeter tomatoes could be obtained by simultaneously manipulating certain biophysical factors and transmembrane transports. The integrative fleshy fruit model provides a promising tool to facilitate the targeted bioengineering and breeding of tomatoes and other fruits.

Integration of QTL, Transcriptome and Polymorphism Studies Reveals Candidate Genes for Water Stress Response in Tomato

Water deficit (WD) leads to significant phenotypic changes in crops resulting from complex stress regulation mechanisms involving responses at the physiological, biochemical and molecular levels. Tomato growth and fruit quality have been shown to be significantly affected by WD stress. Understanding the molecular mechanism underlying response to WD is crucial to develop tomato cultivars with relatively high performance under low watering conditions. Transcriptome response to WD was investigated through the RNA sequencing of fruit and leaves in eight accessions grown under two irrigation conditions, in order to get insight into the complex genetic regulation of WD response in tomato. Significant differences in genotype WD response were first observed at the phenotypic level for fruit composition and plant development traits. At the transcriptome level, a total of 14,065 differentially expressed genes (DEGs) in response to WD were detected, among which 7393 (53%) and 11,059 (79%) were genotype- and organ-specific, respectively. Water deficit induced transcriptome variations much stronger in leaves than in fruit. A significant effect of the genetic background on expression variation was observed compared to the WD effect, along with the presence of a set of genes showing a significant genotype × watering regime interaction. Integrating the DEGs with previously identified WD response quantitative trait loci (QTLs) mapped in a multi-parental population derived from the crossing of the eight genotypes narrowed the candidate gene lists to within the confidence intervals surrounding the QTLs. The results present valuable resources for further study to decipher the genetic determinants of tomato response to WD.

Responses of water accumulation and solute metabolism in tomato fruit to water scarcity and implications for main fruit quality variables

Fruit is important for human health, and applying deficit irrigation in fruit production is a strategy to regulate fruit quality and support environmental sustainability. Responses of different fruit quality variables to deficit irrigation have been widely documented, and much progress has been made in understanding the mechanisms of these responses. We review the effects of water shortage on fruit water accumulation considering water transport from the parent plant into the fruit determined by hydraulic properties of the pathway (including xylem water transport and transmembrane water transport regulated by aquaporins) and the driving force for water movement. We discuss water relations and solute metabolism that affect the main fruit quality variables (e.g. size, flavour, nutrition, and firmness) at the cellular level under water shortage. We also summarize the most recent advances in the understanding of responses of the main fruit quality variables to water shortage, considering the effects of variety, the severity of water deficit imposed, and the developmental stage of the fruit. We finally identify knowledge gaps and suggest avenues for future research. This review provides new insights into the stress physiology of fleshy fruit, which will be beneficial for the sustainable production of high-quality fruit under deficit irrigation.

Organ-wide and ploidy-dependent regulation both contribute to cell-size determination: evidence from a computational model of tomato fruit

The development of a new organ is the result of coordinated events of cell division and expansion, in strong interaction with each other. This study presents a dynamic model of tomato fruit development that includes cell division, endoreduplication, and expansion processes. The model is used to investigate the potential interactions among these developmental processes within the context of the neo-cellular theory. In particular, different control schemes (either cell-autonomous or organ-controlled) are tested and compared to experimental data from two contrasting genotypes. The model shows that a pure cell-autonomous control fails to reproduce the observed cell-size distribution, and that an organ-wide control is required in order to get realistic cell-size variations. The model also supports the role of endoreduplication as an important determinant of the final cell size and suggests that a direct effect of endoreduplication on cell expansion is needed in order to obtain a significant correlation between size and ploidy, as observed in real data.

Modelling tiller growth and mortality as a sink-driven process using Ecomeristem: implications for biomass sorghum ideotyping

BACKGROUND AND AIMS

Plant modelling can efficiently support ideotype conception, particularly in multi-criteria selection contexts. This is the case for biomass sorghum, implying the need to consider traits related to biomass production and quality. This study evaluated three modelling approaches for their ability to predict tiller growth, mortality and their impact, together with other morphological and physiological traits, on biomass sorghum ideotype prediction.

METHODS

Three Ecomeristem model versions were compared to evaluate whether tillering cessation and mortality were source (access to light) or sink (age-based hierarchical access to C supply) driven. They were tested using a field data set considering two biomass sorghum genotypes at two planting densities. An additional data set comparing eight genotypes was used to validate the best approach for its ability to predict the genotypic and environmental control of biomass production. A sensitivity analysis was performed to explore the impact of key genotypic parameters and define optimal parameter combinations depending on planting density and targeted production (sugar and fibre).

KEY RESULTS

The sink-driven control of tillering cessation and mortality was the most accurate, and represented the phenotypic variability of studied sorghum genotypes in terms of biomass production and partitioning between structural and non-structural carbohydrates. Model sensitivity analysis revealed that light conversion efficiency and stem diameter are key traits to target for improving sorghum biomass within existing genetic diversity. Tillering contribution to biomass production appeared highly genotype and environment dependent, making it a challenging trait for designing ideotypes.

CONCLUSIONS

By modelling tiller growth and mortality as sink-driven processes, Ecomeristem could predict and explore the genotypic and environmental variability of biomass sorghum production. Its application to larger sorghum genetic diversity considering water deficit regulations and its coupling to a genetic model will make it a powerful tool to assist ideotyping for current and future climatic scenario.

Model-based QTL detection is sensitive to slight modifications in model formulation

Classical crop models have been developed to predict crop yield and quality, and they are based on physiological and environmental inputs. After molecular discoveries, models should integrate genetic variation to allow predictions that are more genotype-dependent. An interesting approach, Quantitative Trait Locus (QTL)-based ecophysiological modeling, has shown promising results for the design of ideotypes that are adapted to biotic and abiotic stresses, but there are still limitations to attaining a fully integrated model. The aim of this case study is to clarify the impact of choosing different model equations (closely related and with different numbers of parameters) and optimization methods on the detection of QTLs controlling the parameters of crop growth. Different growth equations were parameterized based on a genetic population by following different approaches. The correlations between parameters were analyzed, and two different strategies were adopted to address the correlation issue. QTL analysis was performed on the optimized values of the parameters of the growth equations and on the observed dry mass (DM) data to validate the QTLs detected. Overall, models and strategies resulted in different QTLs being detected. Similar LOD profiles but with peaks of different heights were observed, some of which were significant, resulting in different numbers of QTLs. In some cases, peaks had slightly different positions or were absent. Even closely related growth models led to the detection of different QTLs. The goodness of fit and complexity of the growth models were found to be insufficient to select the best model. Calculating parameters independently of observed data may not be a good strategy, whereas setting parameters independent of the genotype is recommended. Given the large-scale global optimization problem and the strong correlations between parameters, the two algorithms tested showed poor performance. Currently, the lack of effective algorithms is the main obstacle to answering the question posed. The authors therefore suggest testing different model formulations and comparing the QTLs detected before choosing the best formulation to use in an ecophysiological modeling approach based on QTLs.

Putting primary metabolism into perspective to obtain better fruits

Background

One of the key goals of fruit biology is to understand the factors that influence fruit growth and quality, ultimately with a view to manipulating them for improvement of fruit traits.

Scope

Primary metabolism, which is not only essential for growth but is also a major component of fruit quality, is an obvious target for improvement. However, metabolism is a moving target that undergoes marked changes throughout fruit growth and ripening.

Conclusions

Agricultural practice and breeding have successfully improved fruit metabolic traits, but both face the complexity of the interplay between development, metabolism and the environment. Thus, more fundamental knowledge is needed to identify further strategies for the manipulation of fruit metabolism. Nearly two decades of post-genomics approaches involving transcriptomics, proteomics and/or metabolomics have generated a lot of information about the behaviour of fruit metabolic networks. Today, the emergence of modelling tools is providing the opportunity to turn this information into a mechanistic understanding of fruits, and ultimately to design better fruits. Since high-quality data are a key requirement in modelling, a range of must-have parameters and variables is proposed.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.