Modelling the size and composition of fruit, grain and seed by process-based simulation models

Integrated model simulates bigger, sweeter tomatoes under changing climate under reduced nitrogen and water input

When simulating the response of fruit growth and quality to environmental factors and cultivation practices, the interactions between the mother plant and fruit need to be considered as a whole system. Here, we developed the integrative Tomato plant and fruit Growth and Fruit Sugar metabolism (TGFS) model by coupling equations describing the biophysical processes of leaf gas exchange, water transport, carbon allocation, organ growth and fruit sugar metabolism. The model also accounts for effects of soil nitrogen and atmospheric CO₂ concentration on gaseous exchange of water and carbon by the leaf. With different nitrogen and water input values, TGFS performed well at simulating the dry mass of the tomato leaf, stem, root, and fruit, and the concentrations of soluble sugar and starch in fruit. TGFS simulations showed that increasing air temperature and CO₂ concentration has positive effects on fruit growth, but not on sugar concentrations. Further model-based analyses of cultivation scenarios suggest that, in the context of climate change, decreasing N by 15%-25% and decreasing irrigation by 10%-20% relative to current levels would increase tomato fresh weight by 27.8%-36.4% while increasing soluble sugar concentration by up to 10%. TGFS provides a promising tool to optimise N and water inputs for sustainable high-quality tomatoes.

Carbon supply and water status regulate fatty acid and triacylglycerol biosynthesis at transcriptional level in the olive mesocarp

The relative contribution of carbon sources generated from leaves and fruits photosynthesis for triacylglycerol biosynthesis in the olive mesocarp and their interaction with water stress was investigated. With this aim, altered carbon source treatments were combined with different irrigation conditions. A higher decrease in mesocarp oil content was observed in fruits under girdled and defoliated shoot treatment compared to darkened fruit conditions, indicating that both leaf and fruit photosynthesis participate in carbon supply for oil biosynthesis being leaves the main source. The carbon supply and water status affected oil synthesis in the mesocarp, regulating the expression of DGAT and PDAT genes and implicating DGAT1-1, DGAT2, PDAT1-1, and PDAT1-2 as the principal genes responsible for triacylglycerol biosynthesis. A major role was indicated for DGAT2 and PDAT1-2 in well-watered conditions. Moreover, polyunsaturated fatty acid content together with FAD2-1, FAD2-2 and FAD7-1 expression levels were augmented in response to modified carbon supply in the olive mesocarp. Furthermore, water stress caused an increase in DGAT1-1, DGAT1-2, PDAT1-1, and FAD2-5 gene transcript levels. Overall, these data indicate that oil content and fatty acid composition in olive fruit mesocarp are regulated by carbon supply and water status, affecting the transcription of key genes in both metabolic pathways.

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.

Incorporating genome-wide association into eco-physiological simulation to identify markers for improving rice yields

We explored the use of the eco-physiological crop model GECROS to identify markers for improved rice yield under well-watered (control) and water deficit conditions. Eight model parameters were measured from the control in one season for 267 indica genotypes. The model accounted for 58% of yield variation among genotypes under control and 40% under water deficit conditions. Using 213 randomly selected genotypes as the training set, 90 single nucleotide polymorphism (SNP) loci were identified using a genome-wide association study (GWAS), explaining 42-77% of crop model parameter variation. SNP-based parameter values estimated from the additive loci effects were fed into the model. For the training set, the SNP-based model accounted for 37% (control) and 29% (water deficit) of yield variation, less than the 78% explained by a statistical genomic prediction (GP) model for the control treatment. Both models failed in predicting yields of the 54 testing genotypes. However, compared with the GP model, the SNP-based crop model was advantageous when simulating yields under either control or water stress conditions in an independent season. Crop model sensitivity analysis ranked the SNP loci for their relative importance in accounting for yield variation, and the rank differed greatly between control and water deficit environments. Crop models have the potential to use single-environment information for predicting phenotypes under different environments.

Modelling carbon sources and sinks in terrestrial vegetation

Contents Summary 652 I. Introduction 652 II. Discrepancy in predicting the effects of rising [CO₂ ] on the terrestrial C sink 655 III. Carbon and nutrient storage in plants and its modelling 656 IV. Modelling the source and the sink: a plant perspective 657 V. Plant-scale water and Carbon flux models 660 VI. Challenges for the future 662 Acknowledgements 663 Authors contributions 663 References 663 SUMMARY: The increase in atmospheric CO₂ in the future is one of the most certain projections in environmental sciences. Understanding whether vegetation carbon assimilation, growth, and changes in vegetation carbon stocks are affected by higher atmospheric CO₂ and translating this understanding in mechanistic vegetation models is of utmost importance. This is highlighted by inconsistencies between global-scale studies that attribute terrestrial carbon sinks to CO₂ stimulation of gross and net primary production on the one hand, and forest inventories, tree-scale studies, and plant physiological evidence showing a much less pronounced CO₂ fertilization effect on the other hand. Here, we review how plant carbon sources and sinks are currently described in terrestrial biosphere models. We highlight an uneven representation of complexity between the modelling of photosynthesis and other processes, such as plant respiration, direct carbon sinks, and carbon allocation, largely driven by available observations. Despite a general lack of data on carbon sink dynamics to drive model improvements, ways forward toward a mechanistic representation of plant carbon sinks are discussed, leveraging on results obtained from plant-scale models and on observations geared toward model developments.

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.

Disentangling the Effects of Water Stress on Carbon Acquisition, Vegetative Growth, and Fruit Quality of Peach Trees by Means of the QualiTree Model

Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree) was adapted for describing the water stress effects on peach (Prunus persica L. Batsch) vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar ("Elberta") under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on its sink strength, and; secondly, through an indirect reducing effect on photosynthesis. Fruit composition was moderately affected by water stress. The enhancements performed in the model broadened its predictive capabilities and proved that QualiTree allows for a better understanding of the water stress effects on fruit-tree functioning and might be useful for designing innovative horticultural practices in a changing climate scenario.

Surfing parameter hyperspaces under climate change scenarios to design future rice ideotypes

Growing food crops to meet global demand and the search for more sustainable cropping systems are increasing the need for new cultivars in key production areas. This study presents the identification of rice traits putatively producing the largest yield benefits in five areas that markedly differ in terms of environmental conditions in the Philippines, India, China, Japan and Italy. The ecophysiological model WARM and sensitivity analysis techniques were used to evaluate phenotypic traits involved with light interception, photosynthetic efficiency, tolerance to abiotic stressors, resistance to fungal pathogens and grain quality. The analysis involved only model parameters that have a close relationship with phenotypic traits breeders are working on, to increase the in vivo feasibility of selected ideotypes. Current climate and future projections were considered, in the light of the resources required by breeding programs and of the role of weather variables in the identification of promising traits. Results suggest that breeding for traits involved with disease resistance, and tolerance to cold- and heat-induced spikelet sterility could provide benefits similar to those obtained from the improvement of traits involved with canopy structure and photosynthetic efficiency. In contrast, potential benefits deriving from improved grain quality traits are restricted by weather variability and markedly affected by G × E interactions. For this reason, district-specific ideotypes were identified using a new index accounting for both their productivity and feasibility.

Contribution of Crop Models to Adaptation in Wheat

With world population growing quickly, agriculture needs to produce more with fewer inputs while being environmentally friendly. In a context of changing environments, crop models are useful tools to simulate crop yields. Wheat (Triticum spp.) crop models have been evolving since the 1960s to translate processes related to crop growth and development into mathematical equations. These have been used over decades for agronomic purposes, and have more recently incorporated advances in the modeling of environmental footprints, biotic constraints, trait and gene effects, climate change impact, and the upscaling of global change impacts. This review outlines the potential and limitations of modern wheat crop models in assisting agronomists, breeders, and policymakers to address the current and future challenges facing agriculture.

Modeling Allometric Relationships in Leaves of Young Rapeseed (Brassica napus L.) Grown at Different Temperature Treatments

Functional-structural plant modeling (FSPM) is a fast and dynamic method to predict plant growth under varying environmental conditions. Temperature is a primary factor affecting the rate of plant development. In the present study, we used three different temperature treatments (10/14°C, 18/22°C, and 26/30°C) to test the effect of temperature on growth and development of rapeseed (Brassica napus L.) seedlings. Plants were sampled at regular intervals (every 3 days) to obtain growth data during the length of the experiment (1 month in total). Total leaf dry mass, leaf area, leaf mass per area (LMA), width-length ratio, and the ratio of petiole length to leaf blade length (PBR), were determined and statistically analyzed, and contributed to a morphometric database. LMA under high temperature was significantly smaller than LMA under medium and low temperature, while leaves at high temperature were significantly broader. An FSPM of rapeseed seedlings featuring a growth function used for leaf extension and biomass accumulation was implemented by combining measurement with literature data. The model delivered new insights into growth and development dynamics of winter oilseed rape seedlings. The present version of the model mainly focuses on the growth of plant leaves. However, future extensions of the model could be used in practice to better predict plant growth in spring and potential cold damage of the crop.

Integrating Physiology and Architecture in Models of Fruit Expansion

Architectural properties of a fruit, such as its shape, vascular patterns, and skin morphology, play a significant role in determining the distributions of water, carbohydrates, and nutrients inside the fruit. Understanding the impact of these properties on fruit quality is difficult because they develop over time and are highly dependent on both genetic and environmental controls. We present a 3D functional-structural fruit model that can be used to investigate effects of the principle architectural properties on fruit quality. We use a three step modeling pipeline in the OpenAlea platform: (1) creating a 3D volumetric mesh representation of the internal and external fruit structure, (2) generating a complex network of vasculature that is embedded within this mesh, and (3) integrating aspects of the fruit's function, such as water and dry matter transport, with the fruit's structure. We restrict our approach to the phase where fruit growth is mostly due to cell expansion and the fruit has already differentiated into different tissue types. We show how fruit shape affects vascular patterns and, as a consequence, the distribution of sugar/water in tomato fruit. Furthermore, we show that strong interaction between tomato fruit shape and vessel density induces, independently of size, an important and contrasted gradient of water supply from the pedicel to the blossom end of the fruit. We also demonstrate how skin morphology related to microcracking distribution affects the distribution of water and sugars inside nectarine fruit. Our results show that such a generic model permits detailed studies of various, unexplored architectural features affecting fruit quality development.

Simulation of carbon allocation and organ growth variability in apple tree by connecting architectural and source-sink models

BACKGROUND AND AIMS

Plant growth depends on carbon availability and allocation among organs. QualiTree has been designed to simulate carbon allocation and partitioning in the peach tree (Prunus persica), whereas MappleT is dedicated to the simulation of apple tree (Malus × domestica) architecture. The objective of this study was to couple both models and adapt QualiTree to apple trees to simulate organ growth traits and their within-tree variability.

METHODS

MappleT was used to generate architectures corresponding to the 'Fuji' cultivar, accounting for the variability within and among individuals. These architectures were input into QualiTree to simulate shoot and fruit growth during a growth cycle. We modified QualiTree to account for the observed shoot polymorphism in apple trees, i.e. different classes (long, medium and short) that were characterized by different growth function parameters. Model outputs were compared with observed 3D tree geometries, considering shoot and final fruit size and growth dynamics.

KEY RESULTS

The modelling approach connecting MappleT and QualiTree was appropriate to the simulation of growth and architectural characteristics at the tree scale (plant leaf area, shoot number and types, fruit weight at harvest). At the shoot scale, mean fruit weight and its variability within trees was accurately simulated, whereas the model tended to overestimate individual shoot leaf area and underestimate its variability for each shoot type. Varying the parameter related to the intensity of carbon exchange between shoots revealed that behaviour intermediate between shoot autonomy and a common assimilate pool was required to properly simulate within-tree fruit growth variability. Moreover, the model correctly dealt with the crop load effect on organ growth.

CONCLUSIONS

This study provides understanding of the integration of shoot ontogenetic properties, carbon supply and transport between entities for simulating organ growth in trees. Further improvements regarding the integration of retroaction loops between carbon allocation and the resulting plant architecture are expected to allow multi-year simulations.

Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis

Grain growth and oil biosynthesis are complex processes that involve various enzymes placed in different sub-cellular compartments of the grain. In order to understand the mechanisms controlling grain weight and composition, we need mathematical models capable of simulating the dynamic behavior of the main components of the grain during the grain filling stage. In this paper, we present a non-structured mechanistic kinetic model developed for sunflower grains. The model was first calibrated for sunflower hybrid ACA855. The calibrated model was able to predict the theoretical amount of carbohydrate equivalents allocated to the grain, grain growth and the dynamics of the oil and non-oil fraction, while considering maintenance requirements and leaf senescence. Incorporating into the model the serial-parallel nature of fatty acid biosynthesis permitted a good representation of the kinetics of palmitic, stearic, oleic, and linoleic acids production. A sensitivity analysis showed that the relative influence of input parameters changed along grain development. Grain growth was mostly affected by the specific growth parameter (μ') while fatty acid composition strongly depended on their own maximum specific rate parameters. The model was successfully applied to two additional hybrids (MG2 and DK3820). The proposed model can be the first building block toward the development of a more sophisticated model, capable of predicting the effects of environmental conditions on grain weight and composition, in a comprehensive and quantitative way.

A Process-Based Model of TCA Cycle Functioning to Analyze Citrate Accumulation in Pre- and Post-Harvest Fruits

Citrate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. The regulation of citrate accumulation throughout fruit development, and the origins of the phenotypic variability of the citrate concentration within fruit species remain to be clarified. In the present study, we developed a process-based model of citrate accumulation based on a simplified representation of the TCA cycle to predict citrate concentration in fruit pulp during the pre- and post-harvest stages. Banana fruit was taken as a reference because it has the particularity of having post-harvest ripening, during which citrate concentration undergoes substantial changes. The model was calibrated and validated on the two stages, using data sets from three contrasting cultivars in terms of citrate accumulation, and incorporated different fruit load, potassium supply, and harvest dates. The model predicted the pre and post-harvest dynamics of citrate concentration with fairly good accuracy for the three cultivars. The model suggested major differences in TCA cycle functioning among cultivars during post-harvest ripening of banana, and pointed to a potential role for NAD-malic enzyme and mitochondrial malate carriers in the genotypic variability of citrate concentration. The sensitivity of citrate accumulation to growth parameters and temperature differed among cultivars during post-harvest ripening. Finally, the model can be used as a conceptual basis to study citrate accumulation in fleshy fruits and may be a powerful tool to improve our understanding of fruit acidity.

Application of metabolic flux analysis to plants

This volume compiles a series of chapters that cover the major aspects of plant metabolic flux analysis, such as but not limited to labeling of plant material, acquisition of labeling data, mathematical modeling of metabolic network at the cell, tissue, and plant level. A short revue, including methodological points and applications of flux analysis to plants, is presented in this introductory chapter.

A dynamic model of tomato fruit growth integrating cell division, cell growth and endoreduplication

In this study, we developed a model of tomato (Solanum lycopersicum L.) fruit growth integrating cell division, cell growth and endoreduplication. The fruit was considered as a population of cells grouped in cell classes differing in their initial cell age and cell mass. The model describes fruit growth from anthesis until maturation and covers the stages of cell division, endoreduplication and cell growth. The transition from one stage to the next was determined by predefined cell ages expressed in thermal time. Cell growth is the consequence of sugar import from a common pool of assimilates according to the source-sink concept. During most parts of fruit growth, potential cell growth rate increases with increasing cell ploidy and follows the Richards growth function. Cell division or endoreduplication occurs when cells exceed a critical threshold cell mass:ploidy ratio. The model was parameterised and calibrated for low fruit load conditions and was validated for high fruit load and various temperature conditions. Model sensitivity analysis showed that variations in final fruit size are associated with variations in parameters involved in the dynamics of cell growth and cell division. The model was able to accurately predict final cell number, cell mass and pericarp mass under various contrasting fruit load and most of the temperature conditions. The framework developed in this model opens the perspective to integrate information on molecular control of fruit cellular processes into the fruit model and to analyse gene-by-environment interaction effects on fruit growth.

What controls fleshy fruit acidity? A review of malate and citrate accumulation in fruit cells

Fleshy fruit acidity is an important component of fruit organoleptic quality and is mainly due to the presence of malic and citric acids, the main organic acids found in most ripe fruits. The accumulation of these two acids in fruit cells is the result of several interlinked processes that take place in different compartments of the cell and appear to be under the control of many factors. This review combines analyses of transcriptomic, metabolomic, and proteomic data, and fruit process-based simulation models of the accumulation of citric and malic acids, to further our understanding of the physiological mechanisms likely to control the accumulation of these two acids during fruit development. The effects of agro-environmental factors, such as the source:sink ratio, water supply, mineral nutrition, and temperature, on citric and malic acid accumulation in fruit cells have been reported in several agronomic studies. This review sheds light on the interactions between these factors and the metabolism and storage of organic acids in the cell.

Coming of leaf age: control of growth by hydraulics and metabolics during leaf ontogeny

Leaf growth is the central process facilitating energy capture and plant performance. This is also one of the most sensitive processes to a wide range of abiotic stresses. Because hydraulics and metabolics are two major determinants of expansive growth (volumetric increase) and structural growth (dry matter increase), we review the interaction nodes between water and carbon. We detail the crosstalks between water and carbon transports, including the dual role of stomata and aquaporins in regulating water and carbon fluxes, the coupling between phloem and xylem, the interactions between leaf water relations and photosynthetic capacity, the links between Lockhart's hydromechanical model and carbon metabolism, and the central regulatory role of abscisic acid. Then, we argue that during leaf ontogeny, these interactions change dramatically because of uncoupled modifications between several anatomical and physiological features of the leaf. We conclude that the control of leaf growth switches from a metabolic to a hydromechanical limitation during the course of leaf ontogeny. Finally, we illustrate how taking leaf ontogeny into account provides insights into the mechanisms underlying leaf growth responses to abiotic stresses that affect water and carbon relations, such as elevated CO2, low light, high temperature and drought.