A Global Assessment of the State of Plant Health.

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 (i) provisioning (food, fiber, and material), (ii) regulation (climate, atmosphere, water, and soils), and (iii) cultural (recreation, 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 the greatest risk. The overview of results generated from this work identifies directions for future research to be championed by a new generation of scientists and revived public extension services. Breakthroughs from science are 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.

Revisiting food security in 2021: an overview of the past year.

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.

Mapping disruption and resilience mechanisms in food systems.

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.

Modeling the Impact of Crop Diseases on Global Food Security.

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.

The global burden of pathogens and pests on major food crops.

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.

Multiple-Disease System in Coffee: From Crop Loss Assessment to Sustainable Management.

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.

Multiscale Phenotyping and Decision Strategies in Breeding for Resistance.

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.

Variability in aggressiveness of rice blast (Magnaporthe oryzae) isolates originating from rice leaves and necks: a case of pathogen specialization?

Rice blast, caused by Magnaporthe oryzae, causes yield losses associated with injuries on leaves and necks, the latter being in general far more important than the former. Many questions remain on the relationships between leaf and neck blast, including questions related to the population biology of the pathogen. Our objective was to test the hypothesis of adaptation of M. oryzae isolates to the type of organ they infect. To that aim, the components of aggressiveness of isolates originating from leaves and necks were measured. Infection efficiency, latent period, sporulation intensity, and lesion size were measured on both leaves and necks. Univariate and multivariate analyses indicated that isolates originating from leaves were less aggressive than isolates originating from necks, when aggressiveness components were measured on leaves as well as on necks, indicating that there is no specialization within the pathogen population with respect to the type of organ infected. This result suggests that the more aggressive isolates involved in epidemics on leaves during the vegetative stage of the crop cycle have a higher probability to infect necks, and that a population shift may occur during disease transmission from leaves to necks. Implications for disease management are discussed.

Modeling of Yield Losses Caused by Potato Late Blight on Eight Cultivars with Different Levels of Resistance to Phytophthora infestans.

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.

Quantification of the Components of Resistance to Rice Sheath Blight Using a Detached Tiller Test Under Controlled Conditions.

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.

Analysis of nonlinear relationships in dual epidemics, and its application to the management of grapevine downy and powdery mildews.

Dual epidemics are defined as epidemics developing on two or several plant organs in the course of a cropping season. Agricultural pathosystems where such epidemics develop are often very important, because the harvestable part is one of the organs affected. These epidemics also are often difficult to manage, because the linkage between epidemiological components occurring on different organs is poorly understood, and because prediction of the risk toward the harvestable organs is difficult. In the case of downy mildew (DM) and powdery mildew (PM) of grapevine, nonlinear modeling and logistic regression indicated nonlinearity in the foliage-cluster relationships. Nonlinear modeling enabled the parameterization of a transmission coefficient that numerically links the two components, leaves and clusters, in DM and PM epidemics. Logistic regression analysis yielded a series of probabilistic models that enabled predicting preset levels of cluster infection risks based on DM and PM severities on the foliage at successive crop stages. The usefulness of this framework for tactical decision-making for disease control is discussed.

Quantification and modeling of crop losses: a review of purposes.

This review considers the cascade of events that link injuries caused by plant pathogens on crop stands to possible (quantitative and qualitative) crop losses (damage), and to the resulting economic losses. To date, much research has focused on injury control to prevent this cascade of events from occurring. However, this cascade involves a complex succession of components and processes whereby knowledge on crop loss generates entry points for management. Proposed here is a framework linking different types of knowledge on crop loss to a range of decision categories, from tactical to strategic short- or long-term. Important advances in this field are now under way, including a probabilistic treatment of the injury-damage relationship, or analyses of the sources of uncertainty attached to some components of the decision process. Management of injury profiles, rather than individual injuries, and shifts in dimensionality of crop losses are anticipated to contribute to the design of sustainable agricultural systems, and address global issues concerning food security and food safety.

An epidemiological simulation model with three scales of spatial hierarchy.

ABSTRACT An epidemiological model integrating three organizational scales of host plant populations (e.g., sites, leaves, and plants) is presented. At the lowest (site) scale, the model simulates the dynamics of vacant, latent, infectious, and removed sites. Three types of vacant sites are distinguished, depending on presence of infections at higher scales (leaf or plant). The rate of infection of each type of vacant site is computed according to ratios of autodeposition, allo-leaf-deposition, and allo-plantdeposition. At the leaf and plant scales, the rate of victimization is a function of the rate of infection of vacant sites. Sensitivity analyses showed that deposition patterns (the relative proportions of auto-, allo-leaf-, and allo-plant-depositions) and host structure (leaf size and number of leaves per plant) affected the speed of epidemics at the different scales. Model outputs conformed with results from other approaches in the case of random distribution of the disease. The model hypotheses concerning infection from autodeposited propagules, and their implications for disease epidemics, are discussed. The model can be used to derive relationships between allo-deposition ratios and disease incidences at the three scales. These relationships become simple when disease intensity is low. These relationships may be useful, e.g., to assess the potential efficiency of cultivar mixture to control epidemics. Integration of different organization scales and allo-deposition parameters enables the model to capture important features of epidemics developing in space without using explicitly spatialized variables. Such an approach could be useful to analyze other ecological processes that involve a variety of scales.

Research priorities for rice pest management in tropical Asia: a simulation analysis of yield losses and management efficiencies.

ABSTRACT A simulation study was conducted to assess the current and prospective efficiency of rice pest management and develop research priorities for lowland production situations in tropical Asia. Simulation modeling with the RICEPEST model provided the flexibility required to address varying production situations and diverse pest profiles (bacterial leaf blight, sheath blight, brown spot, leaf blast, neck blast, sheath rot, white heads, dead hearts, brown plant-hoppers, insect defoliators, and weeds). Operational definitions for management efficacy (injury reduction) and management efficiency (yield gain) were developed. This approach enabled the modeling of scenarios pertaining to different pest management strategies within the agroecological contexts of rice production and their associated pest injuries. Rice pests could be classified into two broad research priority-setting categories with respect to simulated yield losses and management efficiencies. One group, including weeds, sheath blight, and brown spot, consists of pests for which effective pest management tools need to be developed. The second group consists of leaf blast, neck blast, bacterial leaf blight, and brown plant-hoppers, for which the efficiency of current management methods is to be maintained. Simulated yield losses in future production situations indicated that a new type of rice plant with high-harvest index and high-biomass production ("New Plant Type") was more vulnerable to pests than hybrid rice. Simulations also indicated that the impact of deployment of host resistance (e.g., through genetic engineering) was much larger when targeted against sheath blight than when targeted against stem borers. Simulated yield losses for combinations of production situations and injury profiles that dominate current lowland rice production in tropical Asia ranged from 140 to 230 g m(-2). For these combinations, the simulated efficiency of current pest management methods, expressed in terms of relative yield gains, ranged from 0.38 to 0.74. Overall, the analyses indicated that 120 to 200 x 10(6) tons of grain yield are lost yearly to pests over the 87 x 10(6) ha of lowland rice in tropical Asia. This also amounts to the potential gain that future pest management strategies could achieve, if deployed.

Rice Pest Constraints in Tropical Asia: Characterization of Injury Profiles in Relation to Production Situations.

A protocol for characterizing patterns of rice cropping practices and injuries due to pathogens, insects, and weeds was developed and used in six sites in tropical Asia covering a wide range of environments where lowland rice is cultivated. The data collected in a total population of 456 individual farmers' fields were combined to site-specific weather data and analyzed using non-parametric multivariate techniques: cluster analyses with chi-square distance and correspondence analyses. The main results are: (i) patterns of cropping practices that are common across sites can be identified; (ii) conversely, injury profiles that are common across sites can be determined; (iii) patterns of cropping practices and injury profiles are strongly associated at the regional scale; (iv) weather patterns are strongly associated with patterns of cropping practices and injury profiles; (v) patterns of cropping practices and injury profiles allow for a good description of the variation in actual yield; and (vi) patterns of cropping practices and injury profiles provide a framework that accurately reflects weather variation and site diversity, and reliably accounts for variation in yield. The mean estimated yield across sites (4.12 t ha-1) corresponds to commonly cited averages in the region and indicates the potential for increased productivity with better management practices, especially an improved water supply. Injuries due to pests are secondary compared with other yield-limiting factors. Injury profiles were dominated by stem rot and sheath blight (IN1); bacterial leaf blight, plant hoppers, and leaf folder (IN2); and sheath rot, brown spot, leaf blast, and neck blast (IN3). IN1 was associated with high (mineral) fertilizer inputs, long fallow periods, low pesticide use, and good water management in (mostly) transplanted rice crops of a rice-rice rotation. IN2 was associated with direct-seeded rice crops in an intensive rice-rice rotation, where fertilizer and pesticide inputs are low and water management is poor, or where fertilizer and pesticide inputs are high and water management is adequate. IN3 corresponds to low input, labor intensive (hand weeding and transplanting) rice crops in a diverse rotation system with uncertain water supply. Weed infestation was an omnipresent constraint. This study shows the potential for developing pest management strategies that can be adapted throughout the region, rather than being site-specific.

Rice Pest Constraints in Tropical Asia: Quantification of Yield Losses Due to Rice Pests in a Range of Production Situations.

A series of experiments was conducted where a range of injuries due to rice pests (pathogens, insects, and weeds) was manipulated simultaneously with a range of production factors (fertilizer input, water supply, crop establishment method, variety) in different seasons and years. These factors were chosen to represent lowland rice production situations characterized in surveys conducted in tropical Asia and their corresponding range of attainable yield. Experiments complemented one another in exploring the response surface of rice yields to yield-limiting and yield-reducing factors. The resulting experimental data base consisted of 445 individual plots and involved 11 manipulated injuries in a range of attainable yields of 2 to 11 t ha-1. A first, nonparametric, multivariate analysis led to a hierarchy of potential injuries, from marginally (e.g., bacterial leaf blight) to extremely harmful (e.g., rice tungro disease). A second, parametric, multivariate approach resulted in a multiple regression model involving factors generated by principal component analysis on injuries that adequately described the variation in actual yield. One major finding was that some (attainable yield × injury factors) interactions significantly contributed to the description of variation in actual yield, indicating that some injuries (or their combinations) had a stronger or weaker yield-reducing effect, depending on the level of attainable yield. For instance, yield losses due to sheath blight, weed infestation, and rice tungro disease tend to increase, remain stable, and decrease, respectively, with increasing attainable yields. Back-computations using the principal component regression model estimated yield losses caused by individual injuries, using the mean injury levels in a population of farmers' fields surveyed across tropical Asia. The results indicate that sheath blight, brown spot, and leaf blast are diseases that cause important losses (between 1 and 10%) regionally. Among the insect injuries, only white heads caused by stem borers appear of relevance (2.3% yield losses). These injuries, however, do not match in importance those caused by weeds, whether outgrowing the rice crop canopy (WA) or not (WB), both types of injuries causing about 20% yield losses when considered individually. When all mean injuries were combined into one mean injury profile occurring at a regional attainable yield of 5.5 t ha-1, a mean yield loss of 37.2% was estimated, indicating that injuries were less than additive in their yield-reducing effects. Scenario analyses were conducted in a set of (production situations × injury profiles) combinations characterized from surveys in farmers' fields in tropical Asia. Depending on the scenario chosen, losses ranging from 24 to 41% were found.

Assessing the Representativeness of Data on Yield Losses Due to Rice Diseases in Tropical Asia.

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.