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Understanding the relationships between host range and pathogenicity for parasites, and between the efficiency and scope of immunity for hosts are essential to implement efficient disease control strategies. In the case of plant parasites, most studies have focused on describing qualitative interactions and a variety of genetic and evolutionary models has been proposed in this context. Although plant quantitative resistance benefits from advantages in terms of durability, we presently lack models that account for quantitative interactions between plants and their parasites and the evolution of these interactions. Nestedness and modularity are important features to unravel the overall structure of host-parasite interaction matrices. Here, we analysed these two features on 32 matrices of quantitative pathogenicity trait data gathered from 15 plant-parasite pathosystems consisting of either annual or perennial plants along with fungi or oomycetes, bacteria, nematodes, insects and viruses. The performance of several nestedness and modularity algorithms was evaluated through a simulation approach, which helped interpretation of the results. We observed significant modularity in only six of the 32 matrices, with two or three modules detected. For three of these matrices, modules could be related to resistance quantitative trait loci present in the host. In contrast, we found high and significant nestedness in 30 of the 32 matrices. Nestedness was linked to other properties of plant-parasite interactions. First, pathogenicity trait values were explained in majority by a parasite strain effect and a plant accession effect, with no or minor parasite-plant interaction term. Second, correlations between the efficiency and scope of the resistance of plant genotypes, and between the host range breadth and pathogenicity level of parasite strains were overall positive. This latter result questions the efficiency of strategies based on the deployment of several genetically-differentiated cultivars of a given crop species in the case of quantitative plant immunity.

An amendment to this paper has been published and can be accessed via the original article.

BackgroundAlthough native to North America, the invasion of the aphid-like grape phylloxera Daktulosphaira vitifoliae across the globe altered the course of grape cultivation. For the past 150 years, viticulture relied on grafting-resistant North American Vitis species as rootstocks, thereby limiting genetic stocks tolerant to other stressors such as pathogens and climate change. Limited understanding of the insect genetics resulted in successive outbreaks across the globe when rootstocks failed. Here we report the 294-Mb genome of D. vitifoliae as a basic tool to understand host plant manipulation, nutritional endosymbiosis, and enhance global viticulture.ResultsUsing a combination of genome, RNA, and population resequencing, we found grape phylloxera showed high duplication rates since its common ancestor with aphids, but similarity in most metabolic genes, despite lacking obligate nutritional symbioses and feeding from parenchyma. Similarly, no enrichment occurred in development genes in relation to viviparity. However, phylloxera evolved > 2700 unique genes that resemble putative effectors and are active during feeding. Population sequencing revealed the global invasion began from the upper Mississippi River in North America, spread to Europe and from there to the rest of the world.ConclusionsThe grape phylloxera genome reveals genetic architecture relative to the evolution of nutritional endosymbiosis, viviparity, and herbivory. The extraordinary expansion in effector genes also suggests novel adaptations to plant feeding and how insects induce complex plant phenotypes, for instance galls. Finally, our understanding of the origin of this invasive species and its genome provide genetics resources to alleviate rootstock bottlenecks restricting the advancement of viticulture.

This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the global uniform practical exponential stability for a class of uncertain Takagi-Sugeno fuzzy systems. The uncertainties are supposed uniformly to be bounded by some known integrable functions to obtain an exponential convergence toward a neighborhood of the origin. Therefore, we use common quadratic Lyapunov function (CQLF) and parallel distributed compensation (PDC) controller techniques to show the global uniform practical exponential stability of the closed-loop system. Numeric simulations are given to validate the proposed approach.

In this paper, we introduce the notion of global practical exponential stability for Takagi-Sugeno fuzzy systems in presence of perturbations. The proposed approach for stability analysis is based on the determination of the bounds of perturbations that characterize the asymptotic convergence of the solutions to a small ball centered at the origin. The goal is to study systems whose desired behavior is asymptotic stability about the origin of the state space or a close approximation to this. All state trajectories are bounded and approach a sufficiently small neighborhood of the origin under some perurbations. The effectiveness of the presented criterion is demonstrated by a numerical example. [ABSTRACT FROM AUTHOR]

In this paper, the observer design problem for a T-S fuzzy bilinear control system is investigated. First, an observer of Kalman type is designed to estimate the system states for the linear case. Then, some new sufficient conditions are derived to show the exponential convergence of the solutions of the error equation for fuzzy bilinear systems. Furthermore, we consider some uncertainties of the system that are bounded and satisfy a certain condition where an observer is designed. Moreover, an application to Van de Vusse system is given. [ABSTRACT FROM AUTHOR]

This research focuses on the home health care optimization problem that involves staff routing and scheduling problems. The considered problem is an extension of multiple travelling salesman problem. It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon. Thus, a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint. Nevertheless, when the time horizon become large, practical-sized instances become very difficult to solve in a reasonable computational time. Therefore, a new Learning Genetic Algorithm for mTSP (LGA-mTSP) is proposed to solve the problem. LGA-mTSP is composed of a new genetic algorithm for mTSP, combined with a learning approach, called learning curves. Learning refers to that caregivers' productivity increases as they gain more experience. Learning curves approach is considered as a way to save time and costs. Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of stabilization by an estimated state feedback for a family of nonlinear time-delay Takagi-Sugeno fuzzy parameterized systems. The delay is supposed to be constant where the parameter-dependent controls laws are used to compensate the nonlinearities which are formulated in terms of linear matrix inequalities (LMIs). Based on the LyapunovKrasovskii functionals, global exponential stability of the closed-loop systems is achieved. The controller and observer gains are able to be separately designed even in the presence of modeling uncertainty and state delay. Finally, a numerical example is given to show the applicability of the main result. [ABSTRACT FROM AUTHOR]

Changes in virulence of Plasmopara halstedii populations under different major gene (Pl) management strategies were studied over 5 years continuous cropping of one sunflower hybrid under netting cages. Strategies were monoculture of forms of the hybrid with 1 gene or with combinations of 2 genes, alternation of different genes, and mixtures of several different forms of the hybrid. Monoculture with single resistance genes led to loss of efficient resistance after 3 years, with high levels of disease and increased variability of the pathogen, whatever the Pl gene used. Combinations of genes, alternation and mixtures gave longer term control of downy mildew. In particular, combinations of resistance genes coming from both female and male parents of the hybrid (such that even impurities had a resistance gene) gave the best control and least variation in pathogen virulence. Results are discussed with the object of durable control of downy mildew by all methods available.