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.

Towards a virtual fruit focusing on quality: modelling features and potential uses

The fruit is a hierarchically organized organ composed of cells from different tissues. Its quality, defined by traits such as fruit size and composition, is the result of a complex chain of biological processes. These processes involve exchanges (transpiration, respiration, photosynthesis, phloem and xylem fluxes, and ethylene emission) between the fruit and its environment (atmosphere or plant), tissue differentiation, and cell functioning (division, endoreduplication, expansion, metabolic transformations, and vacuolar storage). In order to progress in our understanding of quality development, it is necessary to analyse the fruit as a system, in which processes interact. In this case, a process-based modelling approach is particularly powerful. Such a modelling approach is proposed to develop a future 'virtual fruit' model. The value of a virtual fruit for agronomists and geneticists is also discussed.

Analysis of citrate accumulation during peach fruit development via a model approach

Based on the citrate model of Lobit and colleagues and measured data, a new model, which is able to reproduce the variation over time of citrate concentration in two peach cultivars, has been proposed. As in the original one, the new model calculates the rate of citrate synthesis or degradation as the product of a 'synthesis potential' and an 'efficiency level'. While in the old model the 'efficiency level' was a simple linear function of temperature and respiration, in the new one its relationship with respiration is accounted for by a coefficient that decreases throughout fruit development. The differences in model parameters between the two cultivars were investigated: late-maturing cv. Suncrest had significantly lower citrate synthesis potential than mid-maturing cv. Fidelia. The responses of citrate concentration to model parameters, temperature, fruit respiration, and growth curves were studied. The most important parameter in the new model, k(4,2), represented the date when the relationship between respiration and 'efficiency level' changed from positive to negative. Raising mean temperature increased the citrate concentration at the beginning and decreased it near maturity for cv. Suncrest, while citrate concentration increased throughout fruit development and more strongly for cv. Fidelia. An increase in the mesocarp dry weight increased both fruit respiration and citrate concentration at the beginning of fruit development, while near maturity it increased fruit respiration but decreased citrate concentration. The model was also able to reproduce the effect of assimilate supply (leaf:fruit ratio). Further potential uses of the model were discussed.

Analysing the genetic control of peach fruit quality through an ecophysiological model combined with a QTL approach

Ecophysiological models are increasingly expected to include genetic information via genotype-dependent parameters. These parameters could be considered as quantitative traits and submitted to analysis. A pre-existing ecophysiological model of fruit quality was used and the distribution of the genotypic parameters in a second backcross population derived from a clone of a wild peach (Prunus davidiana) and commercial nectarine varieties (P. persica (L.) Batsch) was analysed. The correlations between the two years of experimentation were higher for the genotypic parameters than for the quality traits commonly studied by breeders. The correlations between the genotypic parameters and the quality traits were low. Quantitative trait loci (QTLs) for the genotypic key parameters of the ecophysiological model were detected by linear regression. Co-locations of QTLs for parameters were observed as well as co-locations of QTLs for parameters and quality traits. The ecophysiological model and the results of the QTL analysis were combined by substituting each parameter in the model by the sum of QTL effects. This combined model can simulate the behaviour of genotypes carrying diverse combinations of alleles. The quality of this combined model was moderately suitable, but had some shortcomings. Improvements are suggested and further use of this combined model as a tool for breeders is discussed.

Simulating genotypic variation of fruit quality in an advanced peach x Prunus davidiana cross

Ecophysiological models are increasingly expected to describe genotypic variation within breeding populations. Accordingly, the ability of an ecophysiological model of peach to explain variation in fruit quality among 100 genotypes of a second backcross progeny derived from a clone of wild peach (Prunus davidiana) crossed with two commercial nectarine (Prunus persica) varieties was explored. Experimental measurements were carried out to calibrate the model for each genotype. The predictive quality of the model was tested on several independent datasets. The genotypic variation in dry and fresh growth of the fruit and the stone were effectively described by the model. Prediction of the amount of total sugar in flesh at maturity was accurate, whereas prediction of flesh dry matter content and total sugar concentration was suitable but less accurate. This approach and the results have allowed physiological processes to be ranked according to their contribution to the variation in fruit quality between genotypes. Fruit growth demand and the hydraulic conductance in the fruit were the main processes that explained the fruit quality variation. Shortcomings and further potential uses of the model are discussed.

QTL analysis of quality traits in an advanced backcross between Prunus persica cultivars and the wild relative species P. davidiana

Genetic control of the different attributes involved in peach quality has been investigated in an advanced backcross population derived from a cross between Prunus davidiana clone P1908, a wild parent with poor agronomic performance, and a commercial variety, Summergrand. A total of 24 physical and biochemical traits were investigated. Quantitative trait loci (QTLs) were detected for all the traits studied. We identified alleles from P. davidiana with agronomically favorable effects regarding fruit and stone sizes, sugar and acid concentrations and red flesh coloration, in clear contrast to its phenotype. We identified three main regions of the genome where alleles from P. davidiana had negative effects on multiple traits. In other regions, co-locations of QTLs with opposite effects on quality traits were also detected. We discuss the nature of these co-locations in the light of the probable physiological mechanisms involved. Strategies to cope with negative correlations between favorable traits and co-locations of P. davidiana alleles with negative effects on quality traits and positive effects regarding resistance to powdery mildew are discussed from a breeding point of view.

Analysis of genotypic variation in fruit flesh total sugar content via an ecophysiological model applied to peach

A simulation model of the evolution of total sugar content ( C(TS)) in fruit was developed in order to describe the within- and between-genotype variation of C(TS) observed in a peach ( Prunus persica (L.) Batsch) breeding population. The parameter k defines the ratio of carbon used for synthesizing compounds other than sugars for each genotype. Model input variables are dry flesh growth rate and fresh flesh mass of fruit. We estimated k for 137 peach and nectarine genotypes derived from a clone of a wild peach ( Prunus davidiana) by three generations of crosses with commercial nectarine varieties. We tested the predictive quality of the model on independent datasets. Despite an underestimation of the observed C(TS), the correlation between observations and predictions was suitable (0.72). Spearman correlation coefficients between 2001 and 2002 for model input variables and parameter k were higher than for C(TS). None of the three components assimilation supply to the fruit, metabolism, or dilution, seemed to have a greater relative effect on C(TS) variation than the others. Indeed, C(TS) variation seemed to result from the balance between the three components. The interest of this approach, which consists of dissecting traits into components via an ecophysiological model, for breeding strategy and for sugar accumulation studies are discussed.

Does variability in shoot carbon assimilation within the tree crown explain variability in peach fruit growth?

A three-dimensional model of radiative transfer and leaf gas exchange was used to quantify daily carbon (C) assimilation of all fruit-bearing shoots (FBS) in an early maturing 6-year-old peach tree (Prunus persica L. Batsch) with a heavy crop load. For a sample of FBS (n=36), growth of fruit and leafy shoots was measured every 1-2 weeks from 24 days after bloom (DAB) until harvest, between 93-101 DAB. The objective was to relate shoot C assimilation with harvested fruit mass for each shoot to test the hypothesis that variation in C supply contributes significantly to variation in fruit growth within and among FBS. Mean C assimilation of the sampled shoots was 0.07 g C fruit(-1) day(-1), but varied between 0.014 and 0.32 g C fruit(-1) day(-1). This indicates that C availability for fruit growth would have varied significantly among individual FBS if they were autonomous. Mean fruit dry mass on each FBS varied between 0.716 and 7.68 g C at harvest, and most of the variation originated among, not within, individual FBS. However, there were no correlations between the mean and standard deviation of fruit mass and fruit relative growth rate when each was plotted against shoot C assimilation, indicating that factors such as those regulating C demand of fruit, or C transfer among individual FBS, may be more important in controlling variability in fruit growth than intra-crown variability in shoot C assimilation. Under the study conditions, FBS were non-autonomous for C, because a model of fruit and leafy shoot growth was unable to reproduce the observed growth without supplementary contribution of C from shoots without fruit.

Modelling citrate metabolism in fruits: responses to growth and temperature

Citrate production and degradation during the last stage of fruit development were modelled by representing the fluxes through the enzymes of the citrate cycle and the malic enzyme, the transport of metabolites between the cytosol and the mitochondria, and the stoichiometry equations that relate these reactions. After solving the corresponding system of equations, the rate of citrate synthesis (or degradation) was expressed as a simple function of temperature, mesocarp weight, and respiration. The model was applied to peach fruit, and its parameters were estimated from the data of a 2-year field experiment. The predictions of the model were in agreement with experimental data. Simulations were made to analyse the responses to variations of temperature and fruit growth. Increasing fruit growth before stone hardening stimulated citrate production, while increasing fruit growth after stone hardening reduced it. Delaying the date at which the maximum growth rate was reached enhanced citrate production during most of the period. In the last weeks before harvest, increasing temperature depressed citrate production, while, at the beginning of the period studied, it enhanced it.

Changes in fruit sugar concentrations in response to assimilate supply, metabolism and dilution: a modeling approach applied to peach fruit (Prunus persica)

The influence of assimilate supply, metabolism and dilution on sugar concentrations in the mesocarp of peach (Prunus persica (L.) Batsch) fruit during the main stage of fruit enlargement was analyzed with the SUGAR model of Génard and Souty (1996). The model predicts the partitioning of carbon into sucrose, sorbitol, glucose and fructose in the mesocarp of peach fruit. Based on measured data and the model, we determined values for the relative rates of sugar transformation. These rates were constant, varied with time or varied with relative fruit growth rate, depending on the type of sugar. Equations were derived to describe these rates and incorporated into the SUGAR model. The model simulated the effects of changing assimilate supply and fruit volume on sugar concentrations. The set of equations for the SUGAR model was rewritten to include the three components influencing sugar concentrations: assimilate supply, metabolism and dilution. The sugar types differed in sensitivity to these components. Sucrose was highly sensitive to changes in assimilate supply and to the dilution effect; it was not subject to intense metabolic transformation. Sorbitol was the most important carbohydrate in fruit metabolism, which explains why the sorbitol concentration was always low despite the strong positive effect of assimilate supply. The reducing sugars constituted a transitory storage pool and their concentrations were closely related to metabolism.

Ecophysiological analysis of genotypic variation in peach fruit growth

Cultivated varieties generally differ greatly from wild genotypes of the same closely related species. However, the processes responsible for these differences have not been elucidated. To analyse variations in fruit mass, fruit growth was characterized in a peach cultivar, a wild related species non-cultivated, and four hybrids derived by crossing them. These genotypes offer a wide range of agronomic values. An ecophysiological model of peach fruit growth in dry mass was used. This model simulates carbon partitioning at the 'shoot-bearing fruit' level by considering three compartments: fruits, 1-year-old stems and leafy shoots. The experimental measurements showed considerable variation between genotypes for fruit mass at maturity, fruit growth and source activity. The parameters of the ecophysiological model for each genotype were estimated from experimental data,. The model made it possible to account for genotypic variations in fruit growth and for genotype x fruit load interactions. Using the model, it was shown that the main processes explaining fruit growth variations among the genotypes studied were differences in potential fruit growth.

Theoretical analysis of systematic errors introduced by a pedicel-girdling technique used to estimate separately the xylem and phloem flows

The water budget of fruits was analysed by means of a biophysical model of fruit growth, built and calibrated recently for peaches [Prunus persica (L.) Batsch]. This analysis was applied to the evaluation of systematic errors introduced by a pedicel-girdling method (with the observations being treated by means of a subtractive technique) used to separate the contributions of xylem and phloem flow to the total water inflow to the fruit. The flows were considered as solution transport through composite membranes and were calculated by means of equations drawn from non-equilibrium thermodynamics. The total inflow of water was simulated as dependent on the water status in the tree. The hourly time step was used for the simulation. The flows obtained by simulation of the pedicel-girdled fruit were compared with those found by simulation of the intact-pedicel fruit. The error introduced by the pedicel-girdling technique was evaluated theoretically and was shown to vary during the day, ranging from very small (relative error of 3-7%) at the period when the rate of fruit growth is maximal to 100% when the fruit volume does not change. The vascular flows obtained from the "girdling experiments" are discussed in relation to the possible theoretically estimated errors.

Variation in surface conductance to water vapor diffusion in peach fruit and its effects on fruit growth assessed by a simulation model

Surface conductance to water vapor diffusion was measured in individual peach fruits (Prunus persica (L.) Batsch) and plotted as a function of fresh fruit mass for four cultivars. Surface conductance increased with fresh fruit mass, but the pattern differed with cultivar, and fruit-to-fruit variation occurred. Relationships between fruit mass and surface conductance were modeled by fitting mathematical equations to the data. The simulation model of Fishman and Génard (1998) was used to study dry mass and water components of fruit growth (1) when surface conductance varied with fruit size or was constant, and (2) when surface conductance values were high, moderate or low with respect to fruit mass. Increased surface conductance with fresh fruit mass resulted in fruit growth cessation. Fruits differing in surface conductance had similar dry mass. However, under well-watered conditions (stem water potential between -1 and -0.2 MPa), the water balance components of growth (osmotic and hydrostatic pressure, water potential and water balance) differed greatly and, as a result, the lower the surface conductance the greater the fresh fruit mass. These differences were buffered under drought conditions (stem water potential between -2.4 and -0.6 MPa).

A biophysical analysis of stem and root diameter variations in woody plants

A comprehensive model of stem and root diameter variation was developed. The stem (or root) was represented using two coaxial cylinders corresponding with the mature xylem and the extensible tissues. The extensible tissues were assumed to behave as a single cell separated from the mature xylem by a virtual membrane. The mature xylem and the extensible tissues are able to dilate with temperature and grow. Moreover, the extensible tissues are able to shrink and swell according to water flow intensity. The model is mainly based on the calculation of water volume flows in the "single cell" that are described using the principles of irreversible thermodynamics. The elastic response to storage volume and plastic extension accompanying growth are described. The model simulates diameter variation due to temperature, solute accumulation, and xylem, water potential. The model was applied to the peach (Prunus persica) stem and to the plum (Prunus domestica x Prunus spinosa) root. The simulation outputs corresponded well with the diameter variation observed. The model predicts that variations of turgor pressure and osmotic potential are smaller than the variations of xylem water potential. It also demonstrates correlations between the xylem water potential, the turgor pressure, the elastic modulus, and the osmotic potential. The relationship between the diameter and the xylem water potential exhibits a substantial hysteresis, as observed in field data. A sensitivity analysis using the model parameters showed that growth and shrinkage were highly sensitive to the initial values of the turgor pressure and to the reflection coefficient of solutes. Shrinkage and growth were sensitive to elastic modulus and wall-yielding threshold pressure, respectively. The model was not sensitive to changes in temperature.

Effects of timing of nitrogen fertilization on shoot development in peach (Prunus persica) trees

Shoot development was studied for two consecutive years in peach trees fertilized with N either in the previous fall or in the middle of the growing season. During the first year, two additional treatments were studied: no N supply and nitrate supplied in the irrigation water throughout the growing season. The number of shoots that developed depended on nitrogen availability in the period following bud break. During shoot development, leaf emergence occurred in one, two, or three stages, which ended at about 500 to 600 degree days, 1,000 to 1,200 degree days, and 1,500 to 2,000 degree days after bloom, respectively. The proportion of shoots exhibiting a second or third developmental stage depended on nitrogen availability at the beginning of that stage. Increasing nitrogen availability during a developmental stage prolonged the stage and increased the number of leaves produced.

Modeling the response of peach fruit growth to water stress

We applied a semi-mechanistic model of fresh matter accumulation to peach fruit during the stage of rapid mesocarp development. The model, which is based on simple hypotheses of fluid flows into and out of the fruit, assumes that solution flow into the fruit increases with fruit weight and transpiration per unit weight, and decreases with the maximum daily shrinkage of the trunk, which was used as an indicator of water stress. Fruit transpiration was assumed to increase with fruit size and with radiation. Fruit respiration was considered to be related to fruit growth and to temperature. The model simulates variability in growth among fruits according to climatic conditions, degree of water stress and weight of the fruit at the beginning of the simulation. We used data obtained from well-watered and water-stressed trees grown in containers to estimate model parameters and to test the model. There was close agreement between the simulated and measured values. A sensitivity analysis showed that initial fruit weight partly determined the variation in growth among fruits. The analysis also indicated that there was an optimal irradiance for fruit growth and that the effect of high global radiation on growth varied according to the stage of fruit development. Water stress, which was the most important factor influencing fruit growth, rapidly depressed growth, particularly when applied late in the season.