Dare to be resilient: the key to future pesticide-free orchards?

Considering the urgent need for more sustainable fruit tree production, it is high time to find durable alternatives to the systematic use of phytosanitary products in orchards. To this end, resilience can deliver a number of benefits. Relying on a combination of tolerance, resistance, and recovery traits, disease resilience appears as a cornerstone to cope with the multiple pest and disease challenges over an orchard's lifetime. Here, we describe resilience as the capacity of a tree to be minimally affected by external disturbances or to rapidly bounce back to normal functioning after being exposed to these disturbances. Based on a literature survey largely inspired from research on livestock, we highlight different approaches for dissecting phenotypic and genotypic components of resilience. In particular, multisite experimental designs and longitudinal measures of so-called 'resilience biomarkers' are required. We identified a list of promising biomarkers relying on ecophysiological and digital measurements. Recent advances in high-throughput phenotyping and genomics tools will likely facilitate fine scale temporal monitoring of tree health, allowing identification of resilient genotypes with the calculation of specific resilience indicators. Although resilience could be considered as a 'black box' trait, we demonstrate how it could become a realistic breeding goal.

Virtual profiling: a new way to analyse phenotypes.

Simulation models can be used to perform virtual profiling in order to analyse eco-physiological processes controlling plant phenotype. To illustrate this, an eco-physiological model has been used to compare and contrast the status of a virtual fruit system under two situations of carbon supply. The model simulates fruit growth, accumulation of sugar, citric acid and water, transpiration, respiration and ethylene emission, and was successfully tested on peach (Prunus persica L. Batsch) for two leaf-to-fruit ratios (6 and 18 leaves per fruit). The development stage and the variation in leaf number had large effects of the fruit model variables dealing with growth, metabolism and fruit quality. A sensitivity analysis showed that changing a single parameter value, which could correspond to a genotypic change induced by a mutation, either strongly affects most of the processes, or affects a specific process or none. Correlation analysis showed that, in a complex system such as fruit, the intensity of many physiological processes and quality traits co-varies. It also showed unexpected co-variations resulting from emergent properties of the system. This virtual profiling approach opens a new route to explore the impact of mutations, or naturally occurring genetic variations, under differing environmental conditions.

Under what circumstances can process-based simulation models link genotype to phenotype for complex traits? Case-study of fruit and grain quality traits.

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.

Local adaptation in European populations of Arabidopsis lyrata (Brassicaceae).

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.

Is competition between mesocarp cells of peach fruits affected by the percentage of wild species genome?

The number of cells and the mean cell volume in the mesocarps of fruits from peach genotypes with different percentages of the genome of Prunus davidiana, a wild, related, species, were evaluated. The mesocarp mass varied greatly between the four groups of genotypes. The mean cell volume and the number of cells were negatively correlated within each group. This correlation can be interpreted as a relationship of competition between cells. In order to describe the type of competition in the different groups, we tried to adjust a model of competition for resources proposed by Lescourret and Génard (Ecoscience 10:334-341, 2003). To estimate the values of the three parameters of the model for the different groups, we applied model selection. Within nested models, we identified a single best model with six parameter values. This model was roughly accurate, but it allowed us to describe the general relationship for each group. The parameter values revealed a strong and under-compensating density-dependence effect for all groups. The percentage of P. davidiana genome appeared to influence the maximal number of cells and the strength of the competition, but no effect was found on the maximal mean volume of cells.