International Agricultural Research Tackling the Effects of Global and Climate Changes on Plant Diseases in the Developing World

Prevalence of groundnut dry root rot (Macrophomina phaseolina (Tassi) Goid.) and its pathogenic variability in Southern India

Macrophomina phaseolina is the most devastating and emerging threat to groundnut production in India. An increase in average temperature and inconsistent rainfalls resulting from changing climatic conditions are strongly believed to aggravate the disease and cause severe yield losses. The present study aims to conduct a holistic survey to assess the prevalence and incidence of dry root rot of groundnut in major groundnut growing regions of Southern India, viz., Andhra Pradesh, Telangana, Karnataka, and Tamil Nadu. Furthermore, the pathogenic variability was determined using different assays such as morphological, cultural, pathogenic, and molecular assays. Results indicate that disease incidence in surveyed locations ranged from 8.06 to 20.61%. Both temperature and rainfall played a major role in increasing the disease incidence. The pathogenic variability of M. phaseolina isolates differed significantly, based on the percent disease incidence induced on cultivars of JL-24 groundnut and K-6 groundnut. Morphological variations in terms of growth pattern, culture color, sclerotia number, and sclerotia size were observed. The molecular characterization of M. phaseolina isolates done by ITS rDNA region using ITS1 and ITS4 primers yielded approximately 600 bp PCR amplicons, sequenced and deposited in GenBank (NCBI). Molecular variability analysis using SSR primers indicated the genetic variation among the isolates collected from different states. The present investigation revealed significant variations in pathogenic variability among isolates of M. phaseolina and these may be considered important in disease management and the development of resistant cultivars against groundnut dry root rot disease.

Spatial distribution and identification of potential risk regions to rice blast disease in different rice ecosystems of Karnataka

Rice is a globally important crop and highly vulnerable to rice blast disease (RBD). We studied the spatial distribution of RBD by considering the 2-year exploratory data from 120 sampling sites over varied rice ecosystems of Karnataka, India. Point pattern and surface interpolation analyses were performed to identify the spatial distribution of RBD. The spatial clusters of RBD were generated by spatial autocorrelation and Ripley’s K function. Further, inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) approaches were utilized to generate spatial maps by predicting the values at unvisited locations using neighboring observations. Hierarchical cluster analysis using the average linkage method identified two main clusters of RBD severity. From the Local Moran’s I, most of the districts were clustered together (at I > 0), except the coastal and interior districts (at I < 0). Positive spatial dependency was observed in the Coastal, Hilly, Bhadra, and Upper Krishna Project ecosystems (p > 0.05), while Tungabhadra and Kaveri ecosystem districts were clustered together at p < 0.05. From the kriging, Hilly ecosystem, middle and southern parts of Karnataka were found vulnerable to RBD. This is the first intensive study in India on understanding the spatial distribution of RBD using geostatistical approaches, and the findings from this study help in setting up ecosystem-specific management strategies against RBD.

Weather fluctuation can override the effects of integrated nutrient management on fungal disease incidence in the rice fields in Taiwan

Both weather fluctuation and farming system influence the epidemiology of crop diseases. However, short-term experiments are difficult to mechanistically extrapolate into long-term ecological responses. Using a mechanistic model with Bayesian inference, long-term data spanning 10 years were used to construct relationships among weather fluctuation (temperature, relative humidity, wind, and rainfall), farming system (conventional and low-external-input farming), and crop disease in experimental rice fields in Taiwan. Conventional and low-external-input farming had similar influences on the disease incidence of rice blast. Temperature had a positive influence on the disease incidence only under high relative humidity. Rainfall positively affected the disease incidence until an optimum level of rainfall. Low-external-input farming, with a lower application of fertilizers and other sustainable nutrient management, achieved similar effects on the disease incidence to those achieved by conventional farming. This suggests that weather fluctuation may override the effect of the farming systems on fungal disease incidence in rice fields.

Insights into the Host-Pathogen Interaction Pathways through RNA-Seq Analysis of Lens culinaris Medik. in Response to Rhizoctonia bataticola Infection

Dry root rot (Rhizoctonia bataticola) is an important disease of lentils (Lens culinaris Medik.).To gain an insight into the molecular aspects of host-pathogen interactions, the RNA-seq approach was used in lentils following inoculation with R.bataticola. The RNA-Seq has generated >450 million high-quality reads (HQRs) and nearly 96.97% were properly aligned to the reference genome. Very high similarity in FPKM (fragments per kilobase of exon per million mapped fragments) values (R > 0.9) among biological replicates showed the consistency of the RNA-Seq results. The study revealed various DEGs (differentially expressed genes) that were associated with changes in phenolic compounds, transcription factors (TFs), antioxidants, receptor kinases, hormone signals which corresponded to the cell wall modification enzymes, defense-related metabolites, and jasmonic acid (JA)/ethylene (ET) pathways. Gene ontology (GO) categorization also showed similar kinds of significantly enriched similar GO terms. Interestingly, of the total unigenes (42,606), 12,648 got assembled and showed significant hit with Rhizoctonia species. String analysis also revealed the role of various disease responsive proteins viz., LRR family proteins, LRR-RLKs, protein kinases, etc. in the host-pathogen interaction. Insilico validation analysis was performed using Genevestigator^® and DEGs belonging to six major defense-response groups viz., defense-related enzymes, disease responsive genes, hormones, kinases, PR (pathogenesis related) proteins, and TFs were validated. For the first time some key miRNA targets viz. miR156, miR159, miR167, miR169, and miR482 were identified from the studied transcriptome, which may have some vital role in Rhizoctonia-based responses in lentils. The study has revealed the molecular mechanisms of the lentil/R.bataticola interactions and also provided a theoretical approach for the development of lentil genotypes resistant to R.bataticola.

Spatiotemporal Survey of Multiple Rice Diseases in Irrigated Areas Compared to Rainfed Lowlands in the Western Burkina Faso

Multiple constraints affect rice yields in West Africa. Among these constraints are viral, bacterial, and fungal pathogens. We aimed to describe the spatiotemporal patterns of occurrence and incidence of multiple rice diseases in farmers' fields in contrasting rice growing systems in the western Burkina Faso. For this purpose, we selected a set of three pairs of sites, each comprising an irrigated area and a neighboring rainfed lowland, and studied them over four consecutive years. We first performed interviews with the rice farmers to better characterize the management practices at the different sites. This study revealed that the transplanting of rice and the possibility of growing rice twice a year are restricted to irrigated areas, while other practices, such as the use of registered rice cultivars, fertilization, and pesticides, are not specific but differ between the two rice growing systems. Then, we performed symptom observations at these study sites to monitor the following four diseases: yellow mottle disease, Bacterial Leaf Streak (BLS), rice leaf blast, and brown spot. The infection rates were found to be higher in irrigated areas than in rainfed lowlands, both when analyzing all observed symptoms together (any of the four diseases) and when specifically considering each of the two diseases: BLS and rice leaf blast. Brown spot was particularly prevalent in all six study sites, while yellow mottle disease was particularly structured geographically. Various diseases were frequently found together in the same field (co-occurrence) or even on the same plant (coinfection), especially in irrigated areas.

From Lab to Farm: Elucidating the Beneficial Roles of Photosynthetic Bacteria in Sustainable Agriculture

Photosynthetic bacteria (PSB) possess versatile metabolic abilities and are widely applied in environmental bioremediation, bioenergy production and agriculture. In this review, we summarize examples of purple non-sulfur bacteria (PNSB) through biofertilization, biostimulation and biocontrol mechanisms to promote plant growth. They include improvement of nutrient acquisition, production of phytohormones, induction of immune system responses, interaction with resident microbial community. It has also been reported that PNSB can produce an endogenous 5-aminolevulinic acid (5-ALA) to alleviate abiotic stress in plants. Under biotic stress, these bacteria can trigger induced systemic resistance (ISR) of plants against pathogens. The nutrient elements in soil are significantly increased by PNSB inoculation, thus improving fertility. We share experiences of researching and developing an elite PNSB inoculant (Rhodopseudomonas palustris PS3), including strategies for screening and verifying beneficial bacteria as well as the establishment of optimal fermentation and formulation processes for commercialization. The effectiveness of PS3 inoculants for various crops under field conditions, including conventional and organic farming, is presented. We also discuss the underlying plant growth-promoting mechanisms of this bacterium from both microbial and plant viewpoints. This review improves our understanding of the application of PNSB in sustainable crop production and could inspire the development of diverse inoculants to overcome the changes in agricultural environments created by climate change.

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public-private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

Temperature and Soil Moisture Stress Modulate the Host Defense Response in Chickpea During Dry Root Rot Incidence

Dry root rot caused by the necrotrophic phytopathogenic fungus Rhizoctonia bataticola is an emerging threat to chickpea production in India. In the near future, the expected increase in average temperature and inconsistent rainfall patterns resultant of changing climatic scenarios are strongly believed to exacerbate the disease to epidemic proportions. The present study aims to quantify the collective role of temperature and soil moisture content (SMC) on disease progression in chickpea under controlled environmental conditions. In our study, we could find that both temperature and soil moisture played a decisive role in influencing the dry root rot disease scenario. As per the disease susceptibility index (DSI), a combination of high temperature (35°C) and low SMC (60%) was found to elicit the highest disease susceptibility in chickpea. High pathogen colonization was realized in chickpea root tissue at all time-points irrespective of genotype, temperature, and SMC. Interestingly, this was in contrast to the DSI where no visible symptoms were recorded in the roots or foliage during the initial time-points. For each time-point, the colonization was slightly higher at 35°C than 25°C, while the same did not vary significantly with respect to SMC. Furthermore, the differential expression study revealed the involvement of host defense-related genes like endochitinase and PR-3-type chitinase (CHI III) genes in delaying the dry root rot (DRR) disease progression in chickpea. Such genes were found to be highly active during the early stages of infection especially under low SMC.

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.

BLIGHTSIM: A New Potato Late Blight Model Simulating the Response of Phytophthora infestans to Diurnal Temperature and Humidity Fluctuations in Relation to Climate Change

Temperature response curves under diurnal oscillating temperatures differ from those under constant conditions for all stages of the Phytophthora infestans infection cycle on potatoes. We developed a mechanistic model (BLIGHTSIM) with an hourly time step to simulate late blight under fluctuating environmental conditions and predict late blight epidemics in potato fields. BLIGHTSIM is a modified susceptible (S), latent (L), infectious (I) and removed (R) compartmental model with hourly temperature and relative humidity as driving variables. The model was calibrated with growth chamber data covering one infection cycle and validated with field data from Ecuador. The model provided a good fit to all data sets evaluated. There was a significant interaction between average temperature and amplitude in their effects on the area under the disease progress curve (AUDPC) as predicted from growth chamber data on a single infection cycle. BLIGHTSIM can be incorporated in a potato growth model to study effects of diurnal temperature range on late blight impact under climate change scenarios.

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.

Spatial Analysis of Rice Blast in China at Three Different Scales

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At the regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from 10 June to 10 September during 2009 to 2014, and surveyed in 143 fields in September 2016; at the county scale, three surveys were done covering one to five counties in 2015 to 2016; and, at the field scale, blast was evaluated in six fields in 2015 to 2016. Spatial cluster and hot spot analyses were conducted in the geographic information system on the geographical pattern of the disease at regional scale, and geostatistical analysis was performed at all three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1,080 km at regional scale and 5 to 10 m at field scale but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Modelling the impacts of pests and diseases on agricultural systems

The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

QTLs for Resistance to Major Rice Diseases Exacerbated by Global Warming: Brown Spot, Bacterial Seedling Rot, and Bacterial Grain Rot

In rice (Oryza sativa L.), damage from diseases such as brown spot, caused by Bipolaris oryzae, and bacterial seedling rot and bacterial grain rot, caused by Burkholderia glumae, has increased under global warming because the optimal temperature ranges for growth of these pathogens are relatively high (around 30 °C). Therefore, the need for cultivars carrying genes for resistance to these diseases is increasing to ensure sustainable rice production. In contrast to the situation for other important rice diseases such as blast and bacterial blight, no genes for complete resistance to brown spot, bacterial seedling rot or bacterial grain rot have yet been discovered. Thus, rice breeders have to use partial resistance, which is largely influenced by environmental conditions. Recent progress in molecular genetics and improvement of evaluation methods for disease resistance have facilitated detection of quantitative trait loci (QTLs) associated with resistance. In this review, we summarize the results of worldwide screening for cultivars with resistance to brown spot, bacterial seedling rot and bacterial grain rot and we discuss the identification of QTLs conferring resistance to these diseases in order to provide useful information for rice breeding programs.

Climate change may have limited effect on global risk of potato late blight

Weather affects the severity of many plant diseases, and climate change is likely to alter the patterns of crop disease severity. Evaluating possible future patterns can help focus crop breeding and disease management research. We examined the global effect of climate change on potato late blight, the disease that caused the Irish potato famine and still is a common potato disease around the world. We used a metamodel and considered three global climate models for the A2 greenhouse gas emission scenario for three 20-year time-slices: 2000-2019, 2040-2059 and 2080-2099. In addition to global analyses, five regions were evaluated where potato is an important crop: the Andean Highlands, Indo-Gangetic Plain and Himalayan Highlands, Southeast Asian Highlands, Ethiopian Highlands, and Lake Kivu Highlands in Sub-Saharan Africa. We found that the average global risk of potato late blight increases initially, when compared with historic climate data, and then declines as planting dates shift to cooler seasons. Risk in the agro-ecosystems analyzed, varied from a large increase in risk in the Lake Kivu Highlands in Rwanda to decreases in the Southeast Asian Highlands of Indonesia.

Migrate or evolve: options for plant pathogens under climate change

Findings on climate change influence on plant pathogens are often inconsistent and context dependent. Knowledge of pathogens affecting agricultural crops and natural plant communities remains fragmented along disciplinary lines. By broadening the perspective beyond agriculture, this review integrates cross-disciplinary knowledge to show that at scales relevant to climate change, accelerated evolution and changing geographic distribution will be the main implications for pathogens. New races may evolve rapidly under elevated temperature and CO2 , as evolutionary forces act on massive pathogen populations boosted by a combination of increased fecundity and infection cycles under favourable microclimate within enlarged canopy. Changing geographic distribution will bring together diverse lineages/genotypes that do not share common ecological niche, potentially increasing pathogen diversity. However, the uncertainty of model predictions and a lack of synthesis of fragmented knowledge remain as major deficiencies in knowledge. The review contends that the failure to consider scale and human intervention through new technology are major sources of uncertainty. Recognizing that improved biophysical models alone will not reduce uncertainty, it proposes a generic framework to increase focus and outlines ways to integrate biophysical elements and technology change with human intervention scenarios to minimize uncertainty. To synthesize knowledge of pathogen biology and life history, the review borrows the concept of 'fitness' from population biology as a comprehensive measure of pathogen strengths and vulnerabilities, and explores the implications of pathogen mode of nutrition to fitness and its interactions with plants suffering chronic abiotic stress under climate change. Current and future disease management options can then be judged for their ability to impair pathogenic and saprophytic fitness. The review pinpoints improving confidence in model prediction by minimizing uncertainty, developing management strategies to reduce overall pathogen fitness, and finding new sources of data to trawl for climate signatures on pathogens as important challenges for future research.

Species tree estimation for the late blight pathogen, Phytophthora infestans, and close relatives

To better understand the evolutionary history of a group of organisms, an accurate estimate of the species phylogeny must be known. Traditionally, gene trees have served as a proxy for the species tree, although it was acknowledged early on that these trees represented different evolutionary processes. Discordances among gene trees and between the gene trees and the species tree are also expected in closely related species that have rapidly diverged, due to processes such as the incomplete sorting of ancestral polymorphisms. Recently, methods have been developed for the explicit estimation of species trees, using information from multilocus gene trees while accommodating heterogeneity among them. Here we have used three distinct approaches to estimate the species tree for five Phytophthora pathogens, including P. infestans, the causal agent of late blight disease in potato and tomato. Our concatenation-based "supergene" approach was unable to resolve relationships even with data from both the nuclear and mitochondrial genomes, and from multiple isolates per species. Our multispecies coalescent approach using both Bayesian and maximum likelihood methods was able to estimate a moderately supported species tree showing a close relationship among P. infestans, P. andina, and P. ipomoeae. The topology of the species tree was also identical to the dominant phylogenetic history estimated in our third approach, Bayesian concordance analysis. Our results support previous suggestions that P. andina is a hybrid species, with P. infestans representing one parental lineage. The other parental lineage is not known, but represents an independent evolutionary lineage more closely related to P. ipomoeae. While all five species likely originated in the New World, further study is needed to determine when and under what conditions this hybridization event may have occurred.