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The Global Plant Health Assessment (GPHA) is a collective, volunteer-based effort to assemble expert opinions on plant health and disease impacts on ecosystem services based on published scientific evidence. The GPHA considers a range of forest, agricultural, and urban systems worldwide. These are referred to as [Ecoregion × Plant System], i.e., selected case examples involving keystone plants in given parts of the world. The GPHA focuses on infectious plant diseases and plant pathogens, but encompasses the abiotic (e.g., temperature, drought, and floods) and other biotic (e.g., animal pests, and humans) factors associated with plant health. Among the 33 [Ecoregion × Plant System] considered, 18 are assessed as in fair or poor health, and 20 as in declining health. Much of the observed state of plant health and its trends are driven by a combination of forces, including climate change, species invasions, and human management. Healthy plants ensure (1) provisioning (food, fiber, and material), (2) regulation (climate, atmosphere, water, and soils), and (3) cultural (re-creation, inspiration, and spiritual) ecosystem services. All these roles that plants play are threatened by plant diseases. Nearly none of these three ecosystem services are assessed as improving. Results indicate that the poor state of plant health in sub-Saharan Africa gravely contributes to food insecurity and environmental degradation. Results further call for the need to improve crop health to ensure food security in the most populated parts of the world, such as in South Asia, where the poorest of the poor, the landless farmers, are at greatest risk. The overview of results generated from this work enables identifying directions for future research to be championed by a new generation of scientists and revived public extension services. Breakthrough from science is needed to (i) gather more data on plant health and its consequences, (ii) identify collective actions to manage plant systems, (iii) exploit the phytobiome diversity in breeding programs, (iv) breed for plant genotypes with resilience to biotic and abiotic stresses, and (v) design and implement plant systems involving the diversity required to ensure their adaptation to current and growing challenges, including climate change and pathogen invasions.

International audience; Emphasizing connectedness among the many elements of plant-based systems that are collectively addressed in One Health is a logical outcome of debates generated by the International Year of Plant Health. The notion of One Health was implemented through the joint use of the concepts of production situation (PS)-the "rice way of life"-and injury profile (IP)-rice health (pathogens, animal pests, and weeds)-in a population of 1051 rice farmers' fields surveyed from 1987 to 2011. Seven associated PSs and nine IPs are characterized. An ending Green Revolution (Period 1) and a post-Green Revolution (Period 2) are considered. Major changes in PSs and IPs occurred, with increased mineral fertilizer inputs, pesticide applications, and landscape uniformity, along with shortening fallow periods, and dropping labour. Increases or decreases in some injuries lead to shifts in IPs towards more frequent bacterial, flower, and panicle diseases. Yield gain between the two periods was marginal but yield losses to IPs remained unchanged. Yet there was an increase by 77.0%, 21.6%, and 439% for insecticides, herbicides, and fungicides, respectively, along with a 27.9% increase in mineral fertilizer inputs. Total factor productivity in rice production dropped by over 40% during the 24 intervening years, not accounting for the long-term effects of these changes on soil fertility, biodiversity, and scarcer water resource. These results call for urgently required reassessment of public efforts to safeguard these agrosystems that are of critical importance economically, socially, and culturally for roughly half the world's population.

The cultivation of grape varieties with partial resistance to disease may become an important component for disease management in the future. The impact of partial resistance on downy mildew epidemics according to its components have not been explored so far. This work aims to model, understand, and quantitatively analyse the effect of partial resistance against dual disease epidemics (foliage and clusters) caused by Plasmopara viticola, and rank the efficiency of different resistance components in disease suppression. We use an epidemiological simulation model to integrate the effect of four components of partial resistance, expressed as relative resistance parameters, i.e. infection efficiency (RRIE), latency period (RRLP), sporulation (RRSP), and infectious period (RRIP). Both the individual and combined effect of these components of resistance on downy mildew epidemics are evaluated through a sensitivity analysis. A comparison of simulation runs in different scenarios of disease conduciveness using experimental measurements of components of partial resistance for 16 different grapevine varieties is also performed. Increasing values of RR parameters led to a suppression of disease progress on foliage. The strongest reduction of epidemics on foliage is generated by increases in RRIE, followed by RRSP, RRIP, and last by RRLP. The effect of partial resistance on epidemics is more conspicuous in a scenario of limited disease conduciveness. The strongest suppressive effect of simulated epidemics on clusters is associated with RRIE, and the lowest effect with RRLP, with similar effects of increasing values of RRIP and RRSP. The use of experimentally measured relative resistance parameters to run simulated epidemics shows a reduction of the area under the disease progress curve from 4 × 105 (on a susceptible reference grapevine variety) to 4 × 102 (on cv. Bronner), i.e. a reduction of disease by 1000. The simulation of the varietal effect in intermediate and less favourable scenarios of disease conduciveness strongly suppresses the epidemic on foliage and limits disease on clusters to very low levels. Deploying partial host plant resistance in environments that are not strongly conducive to downy mildew epidemics could represent an effective use of partial resistance.

The parameterisation process of a previously developed modelling structure of the grapevine-downy mildew pathosystem is described. The model incorporates primary and secondary infections, host crop growth and development, along with a linkage between disease on foliage and disease on clusters. This process-based model was developed with a main objective of understanding the behaviour of the pathosystem under different, variable, environmental conditions, or under climate change. Six scenarios of disease conduciveness were developed in order to capture the range of environmental conditions under which potential downy mildew of grapevine epidemics can develop. These climate scenarios were based on moisture and temperature factors. The scenarios were translated into vectors of parameters for primary and secondary infections in the model. Model testing was performed in three steps: (i) an analysis of potential epidemics was conducted from the literature on grapevine downy mildew in order to delineate the behaviour of the pathosystem under different scenarios; (ii) a simulation experiment was conducted to investigate the response of the model to different patterns of environmental conditions, corresponding to six scenarios of disease conduciveness; and (iii) expected and simulated epidemics under these scenarios were compared. In scenarios, the model mobilised existing quantitative information on downy mildew of grapevine and generated outputs that are congruent with expected patterns of potential epidemic. This study indicates that the model is a reliable tool for simulating accurate and robust potential epidemics of downy mildew of grapevine in a scenario analysis. This can have many applications, such as the understanding of the behaviour of the pathosystem under climate change or when partial host resistance is involved.

A process-based simulation model for the grapevine-downy mildew pathosystem was developed in order to quantitatively synthesize the literature available and to provide a tool to guide strategic decisions for disease management. The model includes: i) the main processes involved in the disease dual epidemics on leaves and clusters, from inoculum mobilisation to disease multiplication on foliage, and to infection of clusters; and ii) host dynamics, i.e. crop development, growth, and physiological and disease-induced senescence. A numerical evaluation was performed to investigate the response of the model to changes of the main epidemiological parameters, i.e. the basic infection rate corrected for the removals (RcOPT), the duration of latency period (LP), the duration of infectious period (IP), and the rate of primary infections (P). Increasing values of RcOPT and IP, and decreasing values of LP resulted in a faster increase of the epidemic on both foliage and clusters, while decreasing values of P delayed epidemics. The simulated dynamics of epidemics on foliage and clusters conformed to patterns of dual epidemics observed for downy mildew. The model can be useful for investigating the effect of strategic disease management tools such as the use of resistant varieties or to investigate the behaviour of the pathosystem under scenarios of climate change.

International audience

Articles published in Food Security in 2021 are reviewed, showing a wide range of topics covered. Many articles are directly linked with "food" and associated terms such as "nutritive", "nutrition", "dietary", and "health". Another important group is linked with (food) "production" and a range of connected terms including: "irrigation", "cultivated", "organic", "varieties", "crop", "vegetable", and "land". A third group of terms refers to the scales at which food security is considered: "household", "farmer", "farm", "smallholder", "community", "nation" and "region". A few themes of Food Security are considered: (1) food supply and demand, food prices, and global trade; (2) food security in households; (3) food production; (4) value chains and food systems; (5) the evolution of the concept of food security; and (6) global nutrition. In a last section, perspectives for Food Security are discussed along four lines of thoughts: the level of inter-disciplinary research published in Food Security; the importance of the Social Sciences for food security as a collective good underpinned by other collective goods within food systems; the balance between the Global South and the Global North in Food Security; and a warning that urgent global challenges that vitally interact with food security may be left unattended as a result of the current public health emergency.

Plant breeding for host plant resistance to pathogens brings together different disciplinary domains, especially genetics and plant pathology. The strategies underpinning plant breeding have therefore, logically, been influenced by a number of paradigms that have dominated the field of disease management. This chapter provides a brief overview of these paradigms, where the authors link the implications for plant breeding. In doing so, the authors try to follow an approximate (1) linear and (2) chronological order. Yet the authors are aware that, depending on the considered crop and region, (1) there might have been occasional jumps and step-backs leading to non-linear paths, and (2) the chronology of events may have much varied.

International audience

International audience; Plant diseases are major causes of crop yield losses globally, yet their effects represent a poorly documented source of uncertainty in crop modelling. Ignoring the effects of plant diseases in crop models may lead to large overestimations of current and future crop production levels. Simulation modelling must be seen as a necessary instrument to understand systems and predict their behaviours. This instrument is therefore necessary when profound changes in system structures are envisioned in view of, e.g., ecological intensification or climate adaptation, which necessarily will change injury profiles by plant pathogens and pests. Here, damage mechanisms associated with four major diseases of wheat (brown and yellow rust, septoria tritici blotch and powdery mildew) are considered. These diseases and their damage mechanisms are featured in WHEATPEST, a process-based model for wheat growth under disease. The same damage mechanisms were thus incorporated into four wheat growth models (HERMES, WOFOST_GT, SSM_WHEAT, DSSAT-Nwheat), which did not account for yield losses to diseases before. A benchmark experimental data set from the Netherlands was used to perform two calibration steps to simulate disease-free attainable wheat yields (Ya), first by using the experimentally measured crop development and yields as reference, and second by further using the observed leaf area dynamics. A simulation experiment was then conducted with the five models, with three independent factors: (i) each of the four wheat diseases (individually or combined), (ii) the shape of disease progress curves, and (iii) the maximum disease severity. We analysed the simulated crop growth, actual crop yield (Y), and absolute (YL = Ya - Y) and relative (RYL = YL/Ya) yield loss, at different levels of these three factors. In a last stage of analysis, we simulated the effects of Ya on YL and RYL. Maximum severity of disease had the strongest effect on simulated Y and on YL, while there were also significant differences among models in the simulated YL. Powdery mildew and brown rust were generally associated with higher and lower YL, respectively. Simulated RYL increased as the Ya was decreased. Increase of RYL at lower Ya was attributed to a larger reduction of intercepted radiation at low green leaf area index. This work outlines the rationale for implementing damage mechanisms associated with plant diseases into crop models, and provides the necessary first step towards scenario analyses where the consequences of technology shifts, climate change, and changes in disease patterns may influence the magnitude of yield losses to plant diseases.

This chapter reviews approaches taken to assessing the impact of diseases on rice crops, primarily in tropical Asia, compared with insect pests and weeds. Published estimates of yield loss show great variation between and within reports. This reflects the diversity of metrics used and differences in method, location, scale, crop ecosystem etc., exposing the inconsistency of the estimates as representative of rice production. Results are then summarised of >1000 surveys of farmers’ fields conducted over 25 years to a standardised protocol. Estimates were made of the levels of injury to the growing crop attributed to each disease or pest species present, and of the crop yield. Records of physical, biological, and socio-economic characteristics showed the importance of the influence of the crop’s “production situation” on the impact of pathogen and pest species. These surveys were complemented by the results of yield-loss experiments, and by epidemic modelling (based on EPIRICE) and yield-loss modelling (based on RICEPEST). An overview of the results of this research programme is presented, together with a summary of recent trends in rice crop health in Asia. In contrast with views widely held in the 1980s, plant diseases now appear to have a much greater impact on rice production than insect pests.

International audience; Stem rust, or black rust, of wheat, caused by Puccinia graminis f. sp. tritici, has recently re-emerged in several parts of the world, with epidemics occurring in eastern Africa, as well as northern and southern Europe. Damage mechanisms from disease dynamically affect the physiology of the crop as it grows and develops, and as the epidemic progresses, leading to yield losses in the stem rust-diseased wheat stand. Process-based agrophysiological models that include disease-induced damage mechanisms can help to better understand the physiological processes leading to yield losses, and to inform strategic decisions such as breeding strategies. Such models have not been developed for wheat stem rust so far. Two damage mechanisms for stem rust, light stealing and assimilate diversion, were incorporated in the agrophysiological simulation model WHEATPEST. The model, tested from experimental field data retrieved from the literature, provides a satisfactory representation of the system, although consistently underestimates relative yield losses by about 6.9%, resulting in relative yield losses between 17% and 56%. Analyses highlight the importance of the diversion of assimilates toward the pathogen in the magnitude of yield loss. Considering only the reduction of green leaf area would underestimate damage from stem rust by at least threefold. The analysis also shows the importance of the dynamic interplay between disease and crop growth, especially the dynamics of leaf area, on yield loss. Directions to consider additional damage mechanisms are proposed, and perspectives for future research, especially in relation to plant breeding strategies under climate change, are offered.

International audience

This opinion article results from a collective analysis by the Editorial Board of Food Security. It is motivated by the ongoing covid-19 global epidemic, but expands to a broader view on the crises that disrupt food systems and threaten food security, locally to globally. Beyond the public health crisis it is causing, the current global pandemic is impacting food systems, locally and globally. Crises such as the present one can, and do, affect the stability of food production. One of the worst fears is the impacts that crises could have on the potential to produce food, that is, on the primary production of food itself, for example, if material and non-material infrastructure on which agriculture depends were to be damaged, weakened, or fall in disarray. Looking beyond the present, and not minimising its importance, the covid-19 crisis may turn out to be the trigger for overdue fundamental transformations of agriculture and the global food system. This is because the global food system does not work well today: the number of hungry people in the world has increased substantially, with the World Food Programme warning of the possibility of a "hunger pandemic". Food also must be nutritious, yet unhealthy diets are a leading cause of death. Deepening crises impoverish the poorest, disrupt food systems, and expand "food deserts". A focus on healthy diets for all is all the more relevant when everyone's immune system must react to infection during a global pandemic. There is also accumulating and compelling evidence that the global food system is pushing the Earth system beyond the boundaries of sustainability. In the past twenty years, the growing demand for food has increasingly been met through the destruction of Earth's natural environment, and much less through progress in agricultural productivity generated by scientific research, as was the case during the two previous decades. There is an urgent need to reduce the environmental footprint of the global food system: if its performances are not improved rapidly, the food system could itself be one main cause for food crises in the near future. The article concludes with a series of recommendations intended for policy makers and science leaders to improve the resilience of the food system, global to local, and in the short, medium and long term.

International audience

International audience; Plant pathology must contribute to improving food security in a safe operating space, which is shrinking as a result of declining natural resources, climate change, and the growing world population. This review analyzes the position of plant pathology in a nexus of relationships, which is mapped and where the coupled dynamics of crop growth, disease, and yield losses are modeled. We derive a hierarchy of pathogens, whereby pathogens reducing radiation interception (RI), radiation use efficiency (RUE), and harvest index increasingly impact crop yields in the approximate proportions: 1:4.5:4,700. Since the dawn of agriculture, plant breeding has targeted the harvest index as a main objective for domesticated plants. Surprisingly, the literature suggests that pathogens that reduce yields by directly damaging harvestable plant tissues have received much less attention than those that reduce RI or RUE. Ecological disease management needs to target diverse production situations and therefore must consider variation in attainable yields; this can be achieved through the reengineering of agrosystems to incorporate built-in dynamic diversity of genes, plants, and crop stands.

Plant disease emergences have dramatically increased recently as a result of global changes, especially with respect to trade, host genetic uniformity, and climate change. A better understanding of the conditions and processes determining epidemic outbreaks caused by the emergence of a new pathogen, or pathogen strain, is needed to develop strategies and inform decisions to manage emerging diseases. A polyetic process-based model is developed to analyse conditions of disease emergence. This model simulates polycyclic epidemics during successive growing seasons, the yield losses they cause, and the pathogen survival between growing seasons. This framework considers one immigrant strain coming in a single event into a system where a resident strain is already established. Outcomes are formulated as probability of emergence, time to emergence, and yield loss, resulting from deterministic and stochastic simulations. An analytical solution to determine a threshold for emergence is also derived. Analyses focus on the effects of two fitness parameters on emergence: the relative rate of reproduction (epidemic speed), and the relative rate of mortality (decay of population between seasons). Analyses revealed that stochasticity is a critical feature of disease emergence. The simulations suggest that: (a) emergence may require a series of independent immigration events before a successful invasion takes place; (b) an explosion in the population size of the new pathogen (or strain) may be preceded by many successive growing seasons of cryptic presence following an immigration event; and (c) survival between growing seasons is as important as reproduction during the growing season in determining disease emergence. © 2020 British Society for Plant Pathology ISSN:0032-0862 ISSN:1365-3059

International audience; Food Security has a multidisciplinary vision which addresses all the dimensions of food security at all its scales, from the individual to global. The journal involves a large Editorial Board and an extended network of Reviewers. Nevertheless, because of the many dimensions of the food security problem, because of the large size of the submissions that are commonly submitted to the journal, and because of our aim to excellence, publication may sometimes be slow. We shall do better in 2020. This editorial highlights some of the diversity, relevance, and importance of Food Security as an international scientific journal in different fields: the importance of sociology and social capital; the physical access to food; agriculture - what it is supposed to deliver as a system and its sustainability; gender and the inequality of gender towards food; and the environmental constraints to achieving food security. Some Food Security submissions involve up to three Editors and ten Reviewers to achieve publication: This Editorial is also meant to thank the very large, volunteer, community involved in Food Security: Authors, Editors, and Reviewers.

International audience; Yield loss analysis is critical to inform tactical and strategic decisions in crop health management, and requires quantification of three elements: the levels of injury caused by disease or pest, the actual (injured) yield, and the attainable (uninjured) yield. Reverse modelling allows reconstruction of an object or a process from limited information combined with a mathematical model. This approach is applied to estimate yield losses caused by diseases in winter wheat using a process-based simulation model (WHEATPEST), in combination with field data generated by a network of experiments across France, where multiple disease injuries and actual yields, but not attainable yields, were measured. The analysis covers 70 [year 9 region 9 variety 9 crop management] combinations encompassing five years (2004–2008), four French regions, two winter wheat varieties (one high-yielding and one hardy variety), and two levels of crop management corresponding to two levels of chemical intensification. The analysis involved three main successive modelling steps where actual yield, attainable yield and yield losses associated with individual diseases were simulated. Overall, simulated yield losses to combined diseases ranged from 0 to 4.2 t ha1, and averaged 0.80 t ha1. Septoria tritici blotch caused the highest mean yield loss of 0.66 t ha1. The results highlight the contribution of varietal improvement to agricultural sustainability and performances. Reverse modelling can be applied to other crops and diseases or pests, in order to estimate individual and combined disease yield losses.

International audience

International audience

International audience; Wheat disease management in Europe is mainly based on the use of fungicides and the cultivation of resistant cultivars. Improving disease management implies the formal comparison of disease management methods in terms of both crop health and yield levels (attainable yield, actual yield), thus enabling an assessment of yield losses and yield gains. Such an assessment is not available for wheat in Europe. The objective of the analysis reported here is to provide an overview of wheat health and yield performance in field experiments in Europe. Data from field experiments in six European countries (Belgium, France, Germany, Italy, Norway, and Sweden) conducted between 2013 and 2017 were analysed to that aim. Relationships between multiple disease levels, yield, level of cultivar resistance, level of fungicide protection, and weather patterns were assessed. The analyses included 73 field experiments, corresponding to a total of 447 [fungicide protection level x cultivar] combinations. Analyses across the six countries led to ranking the importance of foliar wheat diseases as follows, in decreasing order: leaf blotch (septoria tritici blotch, septoria nodorum blotch, and tan spot), leaf rust, yellow rust, and powdery mildew. Fusarium head blight was observed in France and Italy, and stem rust was sporadically observed in Italy. Disease patterns, crop inputs (fertiliser, fungicides), and yields widely varied within and across countries. Disease levels were affected by the level of fungicide use, by cultivar resistance, as well as by weather patterns. While this analysis enables a better documentation of the status of wheat health in Europe, it also highlights the critical need for policies in Europe enabling a more judicious use of pesticides. First, common standards for field experiments are needed (experimental designs and protocols; disease assessment procedures and scales; references, including reference-susceptible cultivars); second, assessments in farmers' fields – and not in research stations – are necessary; and third, there is a need to use available process-based crop models to estimate attainable yields, and so, yield losses.

The representativeness of information on yield losses due to rice diseases in tropical Asia was studied. Published studies involving different groups of diseases (viral, bacterial, and fungal) and conducted in different rice production ecosystems were compared to help identify research gaps, the filling of which could improve current disease management in rice and help in developing strategies that fit the management needs of fast-evolving rice production systems in the future. Four criteria of representativeness of yield loss information were used: representativeness over time (the proportion of studies conducted over more than one crop cycle), representativeness over space (the proportion of studies conducted in more than one location), representativeness of scale (the proportion of studies conducted on the scale of plots or fields), and representativeness of injury (the standard deviation of the proportion of studies using inoculation, spontaneous infection, or chemical control). A strong imbalance in both the number and the representativeness of studies dealing with fungal, viral, and bacterial diseases was found. Most of the few studies of yield loss due to viral diseases (mainly rice tungro disease) were conducted on the scale of individual (potted) plants or were based on one-year data sets, often reflecting strong epidemics only. Studies of bacterial diseases were conducted in single locations only, and whether such results can be extrapolated still needs to be addressed. There is an acute need to better document yield losses in rice ecosystems other than the irrigated ecosystem. While studies conducted in the upland, rain-fed lowland, and deep-water rice ecosystems seem to have a high degree of representativeness, this cannot compensate for their small number in view of the great diversity of these environments. Studies of irrigated rice tend to concentrate on one year and one location. This approach may be based on the erroneous view that the irrigated ecosystem is homogeneous, and possible extrapolation of data from these studies needs to be examined.

Resistance of rice (Oryza sativa) to sheath blight, caused by Rhizoctonia solani, is quantitative and involves two mechanisms: physiological resistance and disease escape. The epidemiological concept of components of resistance was applied using a detached tiller method under controlled conditions, to specifically address physiological resistance to sheath blight in rice. A sclerotium was inserted below the leaf collar of individual rice tillers maintained in tubes filled with water. Different variables were measured after incubation: number of lesions, lesion length, vertical sheath colonization, presence or absence of dark margin at the edge of lesions, and survival duration of the leaf blade. Several rice varieties reported to have different levels of susceptibility to sheath blight were assessed, together with varieties that are cultivated over large areas. Although numerical differences between rice varieties were observed for all disease variables, only the number of lesions significantly differed among varieties tested in this study. The varieties Pecos and IR64 had the consistently lowest and highest disease intensities, respectively. This methodology may allow the detection of sources of resistance that specifically involve defense mechanisms. When combined with field assessment, this methodology should also enable to quantitatively assess the relative role of both mechanisms of resistance to sheath blight.

Climate change has a number of observed, anticipated, or possible consequences on crop health worldwide. Global change, on the other hand, incorporates a number of drivers of change, including global population increase, natural resource evolution, and supply–demand shifts in markets, from local to global. Global and climate changes interact in their effects on global ecosystems. Identifying and quantifying the impacts of global and climate changes on plant diseases is complex. A number of nonlinear relationships, such as the injury (epidemic)–damage (crop loss) relationship, are superimposed on the interplay among the three summits of the disease triangle (host, pathogen, environment). Work on a range of pathosystems involving rice, peanut, wheat, and coffee has shown the direct linkage and feedback between production situations and crop health. Global and climate changes influence the effects of system components on crop health. The combined effects of global and climate changes on diseases vary from one pathosystem to another within the tetrahedron framework (humans, pathogens, crops, environment) where human beings, from individual farmers to consumers to entire societies, interact with hosts, pathogens, and the environment. This article highlights international phytopathological research addressing the effects of global and climate changes on plant diseases in a range of crops and pathosystems.

This Position Paper was prepared by members of the Task Force on Global Food Security of the International Society for Plant Pathology. An objective approach is proposed to the assessment of the potential of genetic modification (GM) to reduce the impact of crop diseases. \ud \ud The addition of GM to the plant breeder’s conventional toolbox facilitates gene-by-gene introduction into breeding programmes of well defined characters, while also allowing access to genes from a greatly extended range of organisms. The current status of GM crops is outlined. GM could make an additional contribution to food security but its potential has been controversial, sometimes because of fixed views that GM is unnatural and risky. These have no factual basis: GM technology, where adopted, is widely regulated and no evidence has been reported of adverse consequences for human health. \ud \ud The potential benefits of GM could be particularly valuable for the developing world but there are numerous constraints. These include cost, inadequate seed supply systems, reluctance to adopt unfamiliar technology, concern about markets, inadequacy of local regulatory systems, mismatch between research and growers’ needs, and limited technical resources. The lower cost of new gene-editing methods should open the practice of GM beyond multinational corporations. As yet there are few examples of utilization of GM-based resistance to plant diseases.\ud \ud Two cases, papaya ringspot virus and banana xanthomonas wilt, are outlined. In the developing world there are many more potential cases whose progress is prevented by the absence of adequate biosafety regulation. \ud \ud It is concluded that there is untapped potential for using GM to introduce disease resistance. An objective approach to mobilizing this potential is recommended, to address the severe impact of plant disease on food security.

International audience; A large network of field experiments has been conducted over several years across France to identify combinations of winter wheat cultivars and management practices in which partial resistances under limited chemical protection would achieve adequate disease management, while leading to satisfactory yield performance, and so achieve the double objective of ecological sustainability and economic viability. Little information is available to document the variation in multiple disease levels, a n ecessary step towards a chemical extensification process, in wheat networked experiments. This article provides a description of dis- ease intensities in a set of 101 experiments totalling 3525 individual wheat plots over eight successive years (2003 – 2010). The diseases considered are brown rust (BR, Puccinia triticina ), yellow rust (YR, Puccinia striiformis ), fusarium head blight (FHB, Fusarium graminearum , F. culmorum ,and F. avenaceum ), pow- dery mildew (PM, Blumeria graminis ), and septoria tritici blotch (STB, Zymoseptoria tritici ). Hierarchical cluster analysis led to the identification of three variety groups associated with (1) moderate-low disease levels in general, except for YR (moderate levels) – 16 varie- ties; (2) moderate-low BR, YR, and FHB levels, and moderate PM and STB levels – 12 varieties; (3) com- paratively higher BR, YR, FHB, and STB levels, and moderate PM levels – 17 varieties. The association of disease levels represented as binary categories (i.e., epidemics vs. non-epidemics) with climatic years corresponded to chi-square values ( χ 2 =87.0 – 1402) that were one to two orders of magnitude larger than the values corresponding to the associations of diseases with variety groups ( χ 2 =6.41 – 321) or with levels of crop management ( χ 2 =21.2 – 82.1). Multivariate non parametric analyses indicated the existence of three disease syndromes, two of which being dominated by BR or STB, and a third associated with diverse diseases and frequent FHB. This suggests that STB and BR might each be considered as key-stone species dominat- ing specific wheat disease syndromes. Multiple corre- spondence analysis highlighted the linkages between multiple epidemic occurrence and the three character- ized variety groups. Risk factors analyses conducted through logistic regressions provided quantitative estimates of the contribution of climatic years, variety groups, and crop management, to the likelihood of epidemic occurrence for each of the five diseases considered. The results indicate that climatic years, wheat varieties, and crop management, in this decreasing order, define disease epidemic risk in the multiple wheat-diseases pathosystem.

Crop pathogens and pests reduce the yield and quality of agricultural production. They cause substantial economic losses and reduce food security at household, national and global levels. Quantitative, standardized information on crop losses is difficult to compile and compare across crops, agroecosystems and regions. Here, we report on an expert-based assessment of crop health, and provide numerical estimates of yield losses on an individual pathogen and pest basis for five major crops globally and in food security hotspots. Our results document losses associated with 137 pathogens and pests associated with wheat, rice, maize, potato and soybean worldwide. Our yield loss (range) estimates at a global level and per hotspot for wheat (21.5% (10.1–28.1%)), rice (30.0% (24.6–40.9%)), maize (22.5% (19.5–41.1%)), potato (17.2% (8.1–21.0%)) and soybean (21.4% (11.0–32.4%)) suggest that the highest losses are associated with food-deficit regions with fast-growing populations, and frequently with emerging or re-emerging pests and diseases. Our assessment highlights differences in impacts among crop pathogens and pests and among food security hotspots. This analysis contributes critical information to prioritize crop health management to improve the sustainability of agroecosystems in delivering services to societies. An expert elicitation survey estimates yield losses for the five major food crops worldwide, suggesting that the highest losses are associated with food-deficit regions with fast-growing populations and frequently with emerging or re-emerging pests and diseases.

International audience; AbstractIntensive agriculture has led to several drawbacks such as biodiversity loss, climate change, erosion, and pollution of air and water. A potential solution is to implement management practices that increase the level of provision of ecosystem services such as soil fertility and biological regulation. There is a lot of literature on the principles of agroecology. However, there is a gap of knowledge between agroecological principles and practical applications. Therefore, we review here agroecological and management sciences to identify two facts that explain the lack of practical applications: (1) the occurrence of high uncertainties about relations between agricultural practices, ecological processes, and ecosystem services, and (2) the site-specific character of agroecological practices required to deliver expected ecosystem services. We also show that an adaptive-management approach, focusing on planning and monitoring, can serve as a framework for developing and implementing learning tools tailored for biodiversity-based agriculture. Among the current learning tools developed by researchers, we identify two main types of emergent support tools likely to help design diversified farming systems and landscapes: (1) knowledge bases containing scientific supports and experiential knowledge and (2) model-based games. These tools have to be coupled with well-tailored field or management indicators that allow monitoring effects of practices on biodiversity and ecosystem services. Finally, we propose a research agenda that requires bringing together contributions from agricultural, ecological, management, and knowledge management sciences, and asserts that researchers have to take the position of “integration and implementation sciences.”

International audience; A process-based model was developed to simulate the dynamics of grapevine growth within and over years. The model was designed so that it could be used in a later stage to incorporate damage mechanisms of grape diseases, and to analyse their effects on growth and yield over consecutive seasons. The development stage is modelled according to temperature. The within season-dynamics includes (1) the production of assimilates from photosynthesis, (2) the reallocation of assimilates from roots and trunk during the vegetative phase of the crop cycle, (3) the partitioning of assimilates towards leaves, stems, grapes, roots, and trunk, (4) the accumulation of assimilates in roots and trunk after maturity, and (5) leaf senescence. Winter and within-season pruning are also included. The model was parameterised for Vitis labrusca using literature and experimental data. The model was tested with data collected from a 5-year-old vineyard of V. labrusca cv. Niagara Rosada, and evaluated by comparing outputs with data from the literature. The model satisfactorily reproduced the general dynamics of plant growth within year and over successive seasons. Simulation over 20 years indicated that biomass of leaf, stem, grape, and trunk at grapevine maturity increased according to a sigmoid dynamics, while a near-linear increase in roots dry biomass was simulated.

This article addresses the modelling of crop health and its impact on crop losses, with a special emphasis on plant diseases. Plant disease epidemiological models have many different shapes. We propose a summary of modelling structures for plant disease epidemics, which stem from the concepts of infection rate, of site, of basic infection rate corrected for removals (Rc), and of basic reproductive number (R0). Crop losses, the quantitative and qualitative impacts of diseases and pests on crop performances, can be expressed along many different dimensions. We focus on yield loss, defined as the difference between the attainable yield and the actual yield, in a production situation. The modelling of yield loss stems from the concept of damage mechanism, which can be applied to the wide range of organisms (including pathogens, weeds, arthropods, or nematodes) that may negatively affect crop growth and performances. Damage mechanisms are incorporated in crop growth models to simulate yield losses. In both fields, epidemiology and crop loss, we discuss the process of model development, including model simplification. We emphasize model simplification as a main avenue towards model genericity. This is especially relevant to enable addressing the diversity of crop pathogens and pests. We also discuss the usefulness of considering differing evaluation criteria depending on the stage of model development, and thus, depending on modelling objectives. We illustrate progress made on two global key crops where model simplification has been critical; rice and wheat. Modelling pests and diseases, and of the yield losses they cause on these two crops, lead us to propose the concept of crop health syndrome as a set of injury functions, each representing the dynamics of an injury (such as, for example, the time-course of an epidemic). Crop health in a given context can be represented by the set of such injury functions, which in turn can be used as drivers for crop loss models.

Assessment of crop loss due to multiple diseases and pests (D&P) is a necessary step in designing sustainable crop management systems. Understanding the drivers of D&P development and yield loss helps identify leverage points for crop health management. Crop loss assessment is also necessary for the quantification of D&P regulation service to identify promising systems where ecosystem service provision is optimized. In perennial crops, assessment of crop losses due to D&P is difficult, as injuries can affect yield over years. In coffee, one of the first perennials in which crop loss trials were implemented, crop losses concurrent with injuries were found to be approximately 50% lower than lagged losses that originated following the death of productive branches due to D&P. Crop losses can be assessed by field trials and surveys, where yield reduction factors such as the number of productive branches that have died are quantified, and by modeling, where damage mechanisms for each injury are considered over several years.

The literature on the importance of plant pathogens sometimes emphasizes their possible role in historical foodshortages and even in famines. Aside from such major crises, plant pathogens should also be seen as important reducers of crop performances, with impacts on system sustainability, from the ecological, agronomical, social, and economic standpoints – all contributing ultimately to affecting food security. These views need reconciliation in order to produce a clearer picture of the multidimensional effects of plant disease epidemics. Such a picture is needed for disease management today, but would also be useful for future policies. This article attempts to develop a framework that would enable assessment of the impacts of plant diseases, referred collectively to as crop health, on food security via its components. We have combined three different existing definitions of food security in order to develop a framework consisting of the following six components: (1) Availability. Primary production; (2) Availability. Import - Stockpiles; (3) Access. Physical and supply chain; (4) Access. Economic; (5) Stability of food availability; (6) Utility-Safety-Quality- Nutritive value. In this framework, components of food security are combined with three attributes of production situations: the nature of the considered crop (i.e. food- or non- food), the structure of farms (i.e. subsistence or commercial), and the structure of markets (i.e. weakly organized and local, to strongly organized and globalized). The resulting matrix: [Food security components] × [Attributes of production situations] provides a framework where the impacts of chronic, acute, and emerging plant disease epidemics on food security can be examined. We propose that, given the number of components and interactions at play, a systems modelling approach is required to address the functioning of food systems exposed to plant disease risks. This approach would have application in both the management of the current attrition of crop performances by plant diseases, and also of possible disease-induced shocks. Such an approach would also enable quantifying shifts in disease vulnerability of production situations, and therefore, of food systems, as a result of climate change, globalization, and evolving crop health.

Advances in biotechnology have rendered tracking of quantitative trait loci (QTLs) a much easier task, making phenotyping, and not genotyping, the main bottleneck to integrating quantitative host plant resistance into breeding programs. The relevance of phenotyping methods is conditioned by their ability to predict the performance of a genotype at the field scale. Components of resistance represent the keystone hierarchy level between resistance expression in the field (the breeder's scale) and QTLs (the geneticist's scale). We describe approaches for upscaling processes to identify components of resistance that best predict field resistance, and for decision making for selection in breeding programs. We further highlight avenues for future research considering specific processes: disease transmission, defoliation, disease escape, polyetic processes, and interactions between components of resistance.

International audience; Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology.

We witness unprecedented changes in Earth’s natural and man-made ecosystems. These changes are generated by a number of drivers – human population growth, global trade, climate change, and technology shifts – which are often linked in their evolutions, and compounded in their impacts (Vitousek et al., 1986; Rosen, 2000). Importantly, these drivers of change are not linear in their dynamics, evolve at different speeds, and act upon the diversity of the biosphere through different mechanisms, resulting in heterogeneous impacts (Cassman et al., 2005; Garrett et al., 2011). Agriculture may be seen both as a recipient of these effects as well as a cause of changes in the biosphere. As with any of the interactions at play in an ecosystem, plant disease displays responses to these changes.

The status of global food security, i.e., the balance between the growing food demand of the world population and global agricultural output, combined with discrepancies between supply and demand at the regional, national, and local scales (Smil 2000; UN Department of Economic and Social Affairs 2011; Ingram 2011), is alarming. This imbalance is not new (Dyson 1999) but has dramatically worsened during the recent decades, culminating recently in the 2008 food crisis. It is important to note that in mid-2011, food prices were back to their heights of the middle of the 2008 crisis (FAO 2011). Plant protection in general and the protection of crops against plant diseases in particular, have an obvious role to play in meeting the growing demand for food quality and quantity (Strange and Scott 2005). Roughly, direct yield losses caused by pathogens, animals, and weeds, are altogether responsible for losses ranging between 20 and 40 % of global agricultural productivity (Teng and Krupa 1980; Teng 1987; Oerke et al. 1994; Oerke 2006). Crop losses due to pests and pathogens are direct, as well as indirect; they have a number of facets, some with short-, and others with long-term consequences (Zadoks 1967). The phrase “losses between 20 and 40 %” therefore inadequately reflects the true costs of crop losses to consumers, public health, societies, environments, economic fabrics and farmers. The components of food security include food availability (production, import, reserves), physical and economic access to food, and food utilisation (e.g., nutritive value, safety), as has been recently reviewed by Ingram (2011). Although crop losses caused by plant disease directly affect the first of these components, they also affect others (e.g., the food utilisation component) directly or indirectly through the fabrics of trade, policies and societies (Zadoks 2008). Most of the agricultural research conducted in the 20th century focused on increasing crop productivity as the world population and its food needs grew (Evans 1998; Smil 2000; Nellemann et al. 2009). Plant protection then primarily focused on protecting crops from yield losses due to biological and non-biological causes. The problem remains as challenging today as in the 20th century, with additional complexity generated by the reduced room for manoeuvre available environmentally, economically, and socially (FAO 2011; Brown 2011). This results from shrinking natural resources that are available to agriculture: these include water, agricultural land, arable soil, biodiversity, the availability of non-renewable energy, human labour, fertilizers (Smil 2000), and the deployment of some key inputs, such as high quality seeds and planting material (Evans 1998). In addition to yield losses caused by diseases, these new elements of complexity also include post harvest quality losses and the possible accumulation of toxins during and after the S. Savary (*) : J.-N. Aubertot INRA, UMR1248 AGIR, 24 Chemin de Borde Rouge, Auzeville, CS52627, 31326 Castanet-Tolosan Cedex, France e-mail: Serge.Savary@toulouse.inra.fr

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; The Shtienberg model for predicting yield loss caused by Phytophthora infestans in potato was developed and parameterized in the 1990s in North America. The predictive quality of this model was evaluated in France for a wide range of epidemics under different soil and weather conditions and on cultivars different than those used to estimate its parameters. A field experiment was carried out in 2006, 2007, 2008, and 2009 in Brittany, western France to assess late blight severity and yield losses. The dynamics of late blight were monitored on eight cultivars with varying types and levels of resistance. The model correctly predicted relative yield losses (efficiency = 0.80, root mean square error of prediction = 13.25%, and bias = 0.36%) as a function of weather and the observed disease dynamics for a wide range of late blight epidemics. In addition to the evaluation of the predictive quality of the model, this article provides a dataset that describes the development of various late blight epidemics on potato as a function of weather conditions, fungicide regimes, and cultivar susceptibility. Following this evaluation, the Shtienberg model can be used with confidence in research and development programs to better manage potato late blight in France.

International audience; A sample of 200 accessions was selected from IRRI’s rice (Oryza sativa) germplasm bank, that represents rice diversity in terms of genetic groups (aus, indica, tropical japonica, temperate japonica, and aromatic) and crop duration cycles of the accessions. The sample also captured the diversity of rice germplasm in terms of morphological traits. The accessions were assessed for their level of susceptibility to sheath blight in a field experiment, by inoculating hills at the centre of microfields and measuring disease intensity. Morphological traits of all accessions were also measured. Analyses of variance indicated significant effects of genetic groups and genotypes on sheath blight intensity, measured by different variables (lesion height, relative lesion height, leaf severity, sheath severity, and disease incidence on tillers). Results from multivariate analyses (canonical correlation, hierarchical cluster analyses, correspondence analysis, and discriminant analysis), and logistic regressions indicated that morphological traits were strongly associated with disease intensity, and that their effect was larger than that of genetic groups. In particular, plant height was associated with low sheath blight intensity. Effects of genetic groups could however also be detected, and the combination of results suggested a ranking of genetic groups with increasing level of susceptibility to sheath blight as: aus\indica\japonica.

The impacts of climate change on ecosystem services are complex in the sense that effective prediction requires consideration of a wide range of factors. Useful analysis of climate-change impacts on crops and native plant systems will often require consideration of the wide array of other biota that interact with plants, including plant diseases, animal herbivores, and weeds. We present a framework for analysis of complexity in climate-change effects mediated by plant disease. This framework can support evaluation of the level of model complexity likely to be required for analysing climate-change impacts mediated by disease. Our analysis incorporates consideration of the following set of questions for a particular host, pathogen, host–pathogen combination, or geographic region. 1. Are multiple biological interactions important? 2. Are there environmental thresholds for population responses? 3. Are there indirect effects of global change factors on disease development? 4. Are spatial components of epidemic processes affected by climate? 5. Are there feedback loops for management? 6. Are networks for intervention technologies slower than epidemic networks? 7. Are there effects of plant disease on multiple ecosystem services? 8. Are there feedback loops from plant disease to climate change? Evaluation of these questions will help in gauging system complexity, as illustrated for fusarium head blight and potato late blight. In practice, it may be necessary to expand models to include more components, identify those components that are the most important, and synthesize such models to include the optimal level of complexity for planning and research prioritization.

In recent years, a rice panicle disease—rice spikelet rot, occurred seriously in large rice-growing area in China, causing the rice grains discolor, unfilled and deform. It does not only influence the rice yield, because of the colored pathogens and toxigenic, but also changes the appearance of the rice and reduces its quality. Spikelet rot disease influences on the rice production and market price, and causes harm to the safety and health of human and livestock. This paper makes effort to elucidate the occurrence, epidemic regularity of the disease, the pathogenicity of isolates. Fungicides to control the disease were preliminarily selected in lab and control efficiency test were conducted in field. The investigation results indicate that japonica varieties and their hybrid combination, tighten panicle varieties are easier to be infected by the disease than that of the indica rice varieties with loosen panicles. It was propitious to the disease occurrence and epidemic when rice late booting to flowering period met the overcast, rainy (high humidity) and warm (25–33 °C) climate. Indoor selection results showed that ketotriazole shows very good restraint effect on the pathogens. Seed treating with fungicide, spraying ketotriazole, carbendazim + thiram mixture or tricyclazole at later booting and/or flowering stage can reached over 70% control efficiency to the disease.

Rice spikelet rot disease (SRD) is an emerging disease of rice panicle in China, which affects both rice yield and grain quality. Four fungal pathogens were isolated from diseased rice grains. Morphological observation, biological testing and molecular characterization led to identify these fungi as Fusarium proliferatum , Bipolaris australiensis , Curvularia lunata and Alternaria tenuis . The four fungi can grow from 10 °C to 40 °C, and from pH 5 to pH 10. The most suitable temperature range is 25 °C–30 °C, however the optimal pH for sporulation of these fungi varies greatly. The four fungi can grow on media supplemented with different carbon and nitrogen sources. These differences in carbon and nitrogen requirements suggest differences in trophism, and have large effects on hyphal growth and spore production. The results suggest that rice SRD is caused by various fungi with diverse physiological characteristics.