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.

We studied local adaptation to contrasting environments using an organism that is emerging as a model for evolutionary plant biology-the outcrossing, perennial herb Arabidopsis lyrata subsp. petraea (Brassicaceae). With reciprocal transplant experiments, we found variation in cumulative fitness, indicating adaptive differentiation among populations. Nonlocal populations did not have significantly higher fitness than the local population. Experimental sites were located in Norway (alpine), Sweden (coastal), and Germany (continental). At all sites after one year, the local population had higher cumulative fitness, as quantified by survival combined with rosette area, than at least one of the nonlocal populations. At the Norwegian site, measurements were done for two additional years, and fitness differences persisted. The fitness components that contributed most to differences in cumulative fitness varied among sites. Relatively small rosette area combined with a large number of inflorescences produced by German plants may reflect differentiation in life history. The results of the current study demonstrate adaptive population differentiation in A. lyrata along a climatic gradient in Europe. The studied populations harbor considerable variation in several characters contributing to adaptive population differentiation. The wealth of genetic information available makes A. lyrata a highly attractive system also for examining the functional and genetic basis of local adaptation in plants.

Detailed information has arisen from research at gene and cell levels, but it is still incomplete in the context of a quantitative understanding of whole plant physiology. Because of their integrative nature, process-based simulation models can help to bridge the gap between genotype and phenotype and assist in deconvoluting genotype-by-environment (GxE) interactions for complex traits. Indeed, GxE interactions are emergent properties of simulation models, i.e. unexpected properties generated by complex interconnections between subsystem components and biological processes. They co-occur in the system with synergistic or antagonistic effects. In this work, different kinds of GxE interactions are illustrated. Approaches to link model parameters to genes or quantitative trait loci (QTL) are briefly reviewed. Then the analysis of GxE interactions through simulation models is illustrated with an integrated model simulation of peach (Prunus persica (L.) Batsch) fruit mass and sweetness, and with a model of wheat (Triticum aestivum L.) grain yield and protein concentration. This paper suggests that the management of complex traits such as fruit and grain quality may become possible, thanks to the increasing knowledge concerning the genetic and environmental regulation of organ size and composition and to the development of models simulating the complex aspects of metabolism and biophysical behaviours at the plant and organ levels.

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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.

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.

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.

As molecular biologists are realising the importance of physiology in understanding functional genomics of quantitative traits, and as physiologists are realising the formidable prospects for improving their phenotypic models with information on the underlying gene networks, researchers worldwide are working on linked physiological–genetic models. These efforts are in their early methodological stage despite, or because of, the availability of many different types of models, the problem being to bring together the different ways that scientists see the plant. This paper describes some current efforts to adapt phenotype models to the objective of simulating gene-phene processes at the plant or crop scale. Particular emphasis is given to the models' capacity to simulate genotype × environment interaction and the resulting phenotypic plasticity, assuming that this permits the defining of model parameters that are closer to specific gene action. Three different types of approaches are presented: (1) a generic, mathematical-architectural model called GREENLAB that simulates resource-modulated morphogenesis; (2) an ecophysiological model of peach tree fruit development and filling, parameterised for a mapping population to evaluate the potential of plugging quantitative trait locus (QTL) effects into the model; and (3) the new model Ecomeristem that constructs plant architecture and its phenotypic plasticity from meristem behaviour, the principal hypothesis being that resource limitations and stresses feed back on the meristems. This latter choice is based on the fact that gene expression happens to a large extent in the meristems. The model is evaluated on the basis of preliminary studies on vegetative-stage rice. The different modelling concepts are critically discussed with respect to their ability to simulate phenotypic plasticity and to operate with parameters that approximate specific gene action, particularly in the area of morphogenesi