Modelling impacts of climate change on arable crop diseases: progress, challenges and applications

SlLTPg1, a tomato lipid transfer protein, positively regulates in response to biotic stresses

Late blight, caused by Phytophthora infestans (P. infestans), is among the most devastating diseases affecting tomato and other Solanaceae species. Lipid transfer proteins (LTPs) represent a class of small, basic proteins that play a crucial role in combating biotic stresses. Previous studies have shown that SlLTPg1 most strongly responds after P. infestans infestation among the LTPs family in tomato. However, the function of SlLTPg1 in disease resistance remains unclear. Here, we constructed transient overexpression and VIGS-silenced plants of SlLTPg1. Our results revealed that SlLTPg1 plays a regulatory role in enhancing tomato resistance against P. infestans. This enhancement was attributed to the upregulation of defense-related genes and reactive oxygen species (ROS) scavenging genes, as well as increased enzymatic antioxidant activities. Importantly, we found that the SlLTPg1 protein significantly inhibited the growth of Fusarium oxysporum (F. oxysporum) by observing the zone of inhibition. Interestingly, we found smaller lesion diameters and upregulated expression levels of PR genes in transient overexpression SlLTPg1 of tobacco. Therefore, we further constructed transgenic tobacco lines of SlLTPg1, presenting evidence that overexpression of SlLTPg1 could positively regulate the resistance of tobacco to F. oxysporum. These findings revealed the role of SlLTPg1 in tomato resistance to P. infestans and tobacco resistance to F. oxysporum. Moreover, we propose SlLTPg1 as a potential candidate gene for augmenting broad-spectrum plant resistance against pathogens.

Prediction of the global occurrence of maize diseases and estimation of yield loss under climate change

BACKGROUND

Climate change significantly impacts global maize production via yield reduction, posing a threat to global food security. Disease-related crop damage reduces quality and yield and results in economic losses. However, the occurrence of diseases caused by climate change, and thus crop yield loss, has not been given much attention.

RESULTS

This study aims to investigate the potential impact of six major diseases on maize yield loss over the next 20 to 80 years under climate change. To this end, the Maximum Entropy model was implemented, based on Coupled Model Intercomparison Project 6 data. The results indicated that temperature and precipitation are identified as primary limiting factors for disease onset. Southern corn rust was projected to be the most severe disease in the future; with a few of the combined occurrence of all the selected diseases covered in this study were predicted to progressively worsen over time. Yield losses caused by diseases varied per continent, with North America facing the highest loss, followed by Asia, South America, Europe, Africa, and Oceania.

CONCLUSION

This study provides a basis for regional projections and global control of maize diseases under future climate conditions. © 2024 Society of Chemical Industry.

Comparative analysis of different Karnal bunt disease prediction models developed by machine learning techniques for Punjab conditions

Timely prediction of pathogen is important key factor to reduce the quality and yield losses. Wheat is major crop in northern part of India. In Punjab, wheat face challenge by different diseases so the study was conducted for two locations viz. Ludhiana and Bathinda. The information regarding the occurrence of Karnal bunt in 12 consecutive crop seasons (from 2009-10 to 2020-21) in Ludhiana district and in 9 crop seasons (from 2010-11 to 2018-19) in Bathinda district, was collected from the Wheat Section of the Department of Plant Breeding and Genetics at Punjab Agricultural University (PAU), located in Ludhiana. The study aims to investigate the adequacy of various methods of machine learning for prediction of Karnal bunt using meteorological data for different time period viz. February, March, 15 February to 15 March and overall period obtained from Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana. The most intriguing outcome is that for each period, different disease prediction models performed well. The random forest regression (RF) for February month, support vector regression (SVR) for March month, SVR and BLASSO for 15 February to 15 March period and random forest for overall period surpassed the performance than other models. The Taylor diagram was created to assess the effectiveness of intricate models by comparing various metrics such as root mean square error (RMSE), root relative square error (RRSE), correlation coefficient (r), relative mean absolute error (MAE), modified D-index, and modified NSE. It allows for a comprehensive evaluation of these models' performance.

Trichoderma Isolates Against Abiotic Stresses and Management of Collar rot of Lentil (Lens culinaris L.) Caused by Sclerotium rolfsii

A total of 30 native Trichoderma isolates were collected from the Agricultural Research Station, Ummedganj- Kota, Rajasthan, India. Out of which 9 native isolates were evaluated for bio-efficacy against Sclerotium rolfsii. Isolate ARS K-21 exhibited maximum inhibition (89.26%), followed by ARS K-11 (83.70%) in dual culture. Subsequent evaluations revealed the compatibility of efficient isolate ARS K-21 with various bio botanicals displaying minimum inhibition with Vermiwash (1.11-3.70%) followed by Beejamarat (0.38-15.92%) and Brahmastra (7.78-19.68%), while ARS K-11 displayed compatibility only with Dasparni ark with a minimum inhibition of 1.11-3.70%. Assessment of abiotic stress tolerance of the isolates revealed that most isolates thrived at 200 mM and 400 mM NaCl salt concentrations, with ARS K-21 and ARS K-24 demonstrating moderate growth levels across higher concentrations, except at 1200 mM. Optimal growth of the isolates occurred at 25 and 30 °C, with deviations leading to growth inhibition. Isolates ARS K-1, ARS K-11, ARS K-12 and ARS K-21 exhibited resilience to temperature extremes. ARS K-21 has shown exceptional growth proficiency across a wide pH spectrum (pH 5 to 8.5) followed by ARS K- 24, highlighting their versatility. Mass multiplication of efficient isolate ARS K-21 enriched with vermicompost led to the standardization of a dosage (30 g/kg soil) for managing collar rot in lentil crops at 5 g inoculum per kg soil of S. rolfsii.

ESforRPD2: Expert System for Rice Plant Disease Diagnosis

One of the factors causing rice production disturbance in Indonesia is that farmers lack knowledge of early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make an early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts and uses a Waterfall Paradigm and Unified Modeling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with a sensitivity of 87.5%. The system can also provide recommendations for the treatment of identified diseases. ESforRPD2 is available in Indonesian at http://esforrpd2.blog.unmul.ac.id.

The Challenges and Strategies of Food Security under Global Change

Food insecurity corresponds to a deficit in households' access to appropriate food, either in quantity and/or quality, due to limited financial resources or other factors [...].

Monitoring the phenology of plant pathogenic fungi: why and how?

Phenology is a key adaptive trait of organisms, shaping biotic interactions in response to the environment. It has emerged as a critical topic with implications for societal and economic concerns due to the effects of climate change on species' phenological patterns. Fungi play essential roles in ecosystems, and plant pathogenic fungi have significant impacts on global food security. However, the phenology of plant pathogenic fungi, which form a huge and diverse clade of organisms, has received limited attention in the literature. This diversity may have limited the use of a common language for comparisons and the integration of phenological data for these taxonomic groups. Here, we delve into the concept of 'phenology' as applied to plant pathogenic fungi and explore the potential drivers of their phenology, including environmental factors and the host plant. We present the PhenoFun scale, a phenological scoring system suitable for use with all fungi and fungus-like plant pathogens. It offers a standardised and common tool for scientists studying the presence, absence, or predominance of a particular phase, the speed of phenological phase succession, and the synchronism shift between pathogenic fungi and their host plants, across a wide range of environments and ecosystems. The application of the concept of 'phenology' to plant pathogenic fungi and the use of a phenological scoring system involves focusing on the interacting processes between the pathogenic fungi, their hosts, and their biological, physical, and chemical environment, occurring during the life cycle of the pathogen. The goal is to deconstruct the processes involved according to a pattern orchestrated by the fungus's phenology. Such an approach will improve our understanding of the ecology and evolution of such organisms, help to understand and anticipate plant disease epidemics and their future evolution, and make it possible to optimise management models, and to encourage the adoption of cropping practices designed from this phenological perspective.

Significance of Direct and Indirect Impacts of Temperature Increase Driven by Climate Change on Threat to Oilseed Rape Posed by Sclerotinia sclerotiorum

Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, threatens oilseed rape (Brassica napus) crops internationally. The development of this disease is strongly controlled by the weather, which is why global climate change is likely to influence its spread and impact. Climate change may affect the pathogen directly or indirectly via the host plant. This study investigates the potential impact of climate warming on Sclerotinia stem rot severity in oilseed rape in Poland. The aim of this investigation was to assess the relationship between the direct impact (DI) and indirect impact (II) of climate change on disease severity using the 4.5 and 8.5 representative concentration pathways (RCPs). Under the RCP4.5 scenario, nearly 60% of the simulations performed for 16 regions in four periods (2020-2039, 2040-2059, 2060-2079, 2080-2099) showed reductions in disease severity in comparison to those conducted for 1986-2005, while under RCP 8.5, this reduction was generated for nearly 90% of the cases. The effect of the RCP scenario on clustering the regions according to the value of Sclerotinia stem rot severity was also investigated. The simulations revealed that, for all periods, the lowest disease severities are expected for Zachodniopomorskie and Pomorskie. The results obtained also show the superior effects of the II over the DI on Sclerotinia stem rot severity in the future. Under the RCP4.5 scenario, the rate of IIs was greater than that of DIs for 10 regions, while under RCP8.5, this relationship was registered for 16 regions. These outcomes result from the acceleration of the oilseed rape flowering period triggered by expected temperature increases. The novelty of this study lies in a detailed analysis of the relationships between the DI and II of climate change, expressed numerically, for 16 regions in Poland. The obtained results highlight the role of the indirect impact in shaping disease severity and indicate that it should be incorporated into assessment methods of climate change effects alongside the direct impact.

Climate change impacts on plant pathogens, food security and paths forward

Plant disease outbreaks pose significant risks to global food security and environmental sustainability worldwide, and result in the loss of primary productivity and biodiversity that negatively impact the environmental and socio-economic conditions of affected regions. Climate change further increases outbreak risks by altering pathogen evolution and host-pathogen interactions and facilitating the emergence of new pathogenic strains. Pathogen range can shift, increasing the spread of plant diseases in new areas. In this Review, we examine how plant disease pressures are likely to change under future climate scenarios and how these changes will relate to plant productivity in natural and agricultural ecosystems. We explore current and future impacts of climate change on pathogen biogeography, disease incidence and severity, and their effects on natural ecosystems, agriculture and food production. We propose that amendment of the current conceptual framework and incorporation of eco-evolutionary theories into research could improve our mechanistic understanding and prediction of pathogen spread in future climates, to mitigate the future risk of disease outbreaks. We highlight the need for a science-policy interface that works closely with relevant intergovernmental organizations to provide effective monitoring and management of plant disease under future climate scenarios, to ensure long-term food and nutrient security and sustainability of natural ecosystems.

Tackling Soil ARG-Carrying Pathogens with Global-Scale Metagenomics

Antibiotic overuse and the subsequent environmental contamination of residual antibiotics poses a public health crisis via an acceleration in the spread of antibiotic resistance genes (ARGs) through horizontal gene transfer. Although the occurrence, distribution, and driving factors of ARGs in soils have been widely investigated, little is known about the antibiotic resistance of soilborne pathogens at a global scale. To explore this gap, contigs from 1643 globally sourced metagnomes are assembled, yielding 407 ARG-carrying pathogens (APs) with at least one ARG; APs are detected in 1443 samples (sample detection rate of 87.8%). The richness of APs is greater in agricultural soils (with a median of 20) than in non-agricultural ecosystems. Agricultural soils possess a high prevalence of clinical APs affiliated with Escherichia, Enterobacter, Streptococcus, and Enterococcus. The APs detected in agricultural soils tend to coexist with multidrug resistance genes and bacA. A global map of soil AP richness is generated, where anthropogenic and climatic factors explained AP hot spots in East Asia, South Asia, and the eastern United States. The results herein advance this understanding of the global distribution of soil APs and determine regions prioritized to control soilborne APs worldwide.

Temperature contributes to host specialization of coffee wilt disease (Fusarium xylarioides) on arabica and robusta coffee crops

Coffee wilt disease, caused by the fungus Fusarium xylarioides, is a vascular wilt disease that has affected coffee production in sub-Saharan Africa over the past century. Today, the disease has two host-specific populations specialising on arabica and robusta coffee crops, which grow at high and low altitude, respectively. Here we test whether adaptation to different temperatures contributes to specialisation of the fungi on each crop. Firstly, climate models show that the severity of the arabica and robusta populations of coffee wilt disease correlates with temperature. The robusta population shows higher peak severity than the arabica population overall, but the latter has greater cold tolerance. Secondly, growth assays of thermal performance of fungal strains in vitro show that, while robusta strains grow faster than arabicas at intermediate temperatures, the arabica strains have higher sporulation and spore germination rates at temperatures below 15ºC. The match between environmental patterns of severity in nature with thermal performance of fungal cultures in the laboratory supports a role for temperature adaptation in specialisation on arabica and robusta coffee. Extrapolating our temperature-models to future climate change predicts that disease severity could decline on average due to increased temperature but could increase in some coffee-growing regions.

Process-Based Crop Modeling for High Applicability with Attention Mechanism and Multitask Decoders

Crop models have been developed for wide research purposes and scales, but they have low compatibility due to the diversity of current modeling studies. Improving model adaptability can lead to model integration. Since deep neural networks have no conventional modeling parameters, diverse input and output combinations are possible depending on model training. Despite these advantages, no process-based crop model has been tested in full deep neural network complexes. The objective of this study was to develop a process-based deep learning model for hydroponic sweet peppers. Attention mechanism and multitask learning were selected to process distinct growth factors from the environment sequence. The algorithms were modified to be suitable for the regression task of growth simulation. Cultivations were conducted twice a year for 2 years in greenhouses. The developed crop model, DeepCrop, recorded the highest modeling efficiency (= 0.76) and the lowest normalized mean squared error (= 0.18) compared to accessible crop models in the evaluation with unseen data. The t-distributed stochastic neighbor embedding distribution and the attention weights supported that DeepCrop could be analyzed in terms of cognitive ability. With the high adaptability of DeepCrop, the developed model can replace the existing crop models as a versatile tool that would reveal entangled agricultural systems with analysis of complicated information.

Targeted mutagenesis with sequence-specific nucleases for accelerated improvement of polyploid crops: Progress, challenges, and prospects

Many of the world's most important crops are polyploid. The presence of more than two sets of chromosomes within their nuclei and frequently aberrant reproductive biology in polyploids present obstacles to conventional breeding. The presence of a larger number of homoeologous copies of each gene makes random mutation breeding a daunting task for polyploids. Genome editing has revolutionized improvement of polyploid crops as multiple gene copies and/or alleles can be edited simultaneously while preserving the key attributes of elite cultivars. Most genome-editing platforms employ sequence-specific nucleases (SSNs) to generate DNA double-stranded breaks at their target gene. Such DNA breaks are typically repaired via the error-prone nonhomologous end-joining process, which often leads to frame shift mutations, causing loss of gene function. Genome editing has enhanced the disease resistance, yield components, and end-use quality of polyploid crops. However, identification of candidate targets, genotyping, and requirement of high mutagenesis efficiency remain bottlenecks for targeted mutagenesis in polyploids. In this review, we will survey the tremendous progress of SSN-mediated targeted mutagenesis in polyploid crop improvement, discuss its challenges, and identify optimizations needed to sustain further progress.

Comparative transcriptomics and metabolomics reveal specialized metabolite drought stress responses in switchgrass (Panicum virgatum)

Switchgrass (Panicum virgatum) is a bioenergy model crop valued for its energy efficiency and drought tolerance. The related monocot species rice (Oryza sativa) and maize (Zea mays) deploy species-specific, specialized metabolites as core stress defenses. By contrast, specialized chemical defenses in switchgrass are largely unknown. To investigate specialized metabolic drought responses in switchgrass, we integrated tissue-specific transcriptome and metabolite analyses of the genotypes Alamo and Cave-in-Rock that feature different drought tolerance. The more drought-susceptible Cave-in-Rock featured an earlier onset of transcriptomic changes and significantly more differentially expressed genes in response to drought compared to Alamo. Specialized pathways showed moderate differential expression compared to pronounced transcriptomic alterations in carbohydrate and amino acid metabolism. However, diterpenoid-biosynthetic genes showed drought-inducible expression in Alamo roots, contrasting largely unaltered triterpenoid and phenylpropanoid pathways. Metabolomic analyses identified common and genotype-specific flavonoids and terpenoids. Consistent with transcriptomic alterations, several root diterpenoids showed significant drought-induced accumulation, whereas triterpenoid abundance remained predominantly unchanged. Structural analysis verified select drought-responsive diterpenoids as oxygenated furanoditerpenoids. Drought-dependent transcriptome and metabolite profiles provide the foundation to understand the molecular mechanisms underlying switchgrass drought responses. Accumulation of specialized root diterpenoids and corresponding pathway transcripts supports a role in drought stress tolerance.

Fungal Endophytes to Combat Biotic and Abiotic Stresses for Climate-Smart and Sustainable Agriculture

The agricultural sustainability concept considers higher food production combating biotic and abiotic stresses, socio-economic well-being, and environmental conservation. On the contrary, global warming-led climatic changes have appalling consequences on agriculture, generating shifting rainfall patterns, high temperature, CO2, drought, etc., prompting abiotic stress conditions for plants. Such stresses abandon the plants to thrive, demoting food productivity and ultimately hampering food security. Though environmental issues are natural and cannot be regulated, plants can still be enabled to endure these abnormal abiotic conditions, reinforcing the stress resilience in an eco-friendly fashion by incorporating fungal endophytes. Endophytic fungi are a group of subtle, non-pathogenic microorganisms establishing a mutualistic association with diverse plant species. Their varied association with the host plant under dynamic environments boosts the endogenic tolerance mechanism of the host plant against various stresses via overall modulations of local and systemic mechanisms accompanied by higher antioxidants secretion, ample enough to scavenge Reactive Oxygen Species (ROS) hence, coping over-expression of defensive redox regulatory system of host plant as an aversion to stressed condition. They are also reported to ameliorate plants toward biotic stress mitigation and elevate phytohormone levels forging them worthy enough to be used as biocontrol agents and as biofertilizers against various pathogens, promoting crop improvement and soil improvement, respectively. This review summarizes the present-day conception of the endophytic fungi, their diversity in various crops, and the molecular mechanism behind abiotic and biotic resistance prompting climate-resilient aided sustainable agriculture.

Nonhomologous end joining as key to CRISPR/Cas-mediated plant chromosome engineering

Although clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas)-mediated gene editing has revolutionized biology and plant breeding, large-scale, heritable restructuring of plant chromosomes is still in its infancy. Duplications and inversions within a chromosome, and also translocations between chromosomes, can now be achieved. Subsequently, genetic linkages can be broken or can be newly created. Also, the order of genes on a chromosome can be changed. While natural chromosomal recombination occurs by homologous recombination during meiosis, CRISPR/Cas-mediated chromosomal rearrangements can be obtained best by harnessing nonhomologous end joining (NHEJ) pathways in somatic cells. NHEJ can be subdivided into the classical (cNHEJ) and alternative NHEJ (aNHEJ) pathways, which partially operate antagonistically. The cNHEJ pathway not only protects broken DNA ends from degradation but also suppresses the joining of previously unlinked broken ends. Hence, in the absence of cNHEJ, more inversions or translocations can be obtained which can be ascribed to the unrestricted use of the aNHEJ pathway for double-strand break (DSB) repair. In contrast to inversions or translocations, short tandem duplications can be produced by paired single-strand breaks via a Cas9 nickase. Interestingly, the cNHEJ pathway is essential for these kinds of duplications, whereas aNHEJ is required for patch insertions that can also be formed during DSB repair. As chromosome engineering has not only been accomplished in the model plant Arabidopsis (Arabidopsis thaliana) but also in the crop maize (Zea mays), we expect that this technology will soon transform the breeding process.

Precipitation increases the abundance of fungal plant pathogens in Eucalyptus phyllosphere

Understanding the current and future distributions of plant pathogens is critical to predict the plant performance and related economic benefits in the changing environment. Yet, little is known about the roles of environmental drivers in shaping the profiles of fungal plant pathogens in phyllosphere, an important habitat of microbiomes on Earth. Here, using a large-scale investigation of Eucalyptus phyllospheric microbiomes in Australia and the multiple linear regression model, we show that precipitation is the most important predictor of fungal taxonomic diversity and abundance. The abundance of fungal plant pathogens in phyllosphere exhibited a positive linear relationship with precipitation. With this empirical dataset, we constructed current and future atlases of phyllosphere plant pathogens to estimate their spatial distributions under different climate change scenarios. Our atlases indicate that the abundance of fungal plant pathogens would increase especially in the coastal regions with up to 100-fold increase compared with the current abundance. These findings advance our understanding of the distributions of fungal plant pathogens in phyllospheric microbiomes under the climate change, which can improve our ability to predict and mitigate their impacts on plant productivity and economic losses.

Exploring Smallholder Farmers’ Preferences for Climate-Smart Seed Innovations: Empirical Evidence from Southern Ethiopia

Rapid plant breeding is essential to overcome low productivity problems in the face of climatic challenges. Despite considerable efforts to improve breeding practices in Ethiopia, increasing varietal release does not necessarily imply that farmers have access to innovative varietal choices. Prior research did not adequately address whether varietal attributes are compatible with farmers’ preferences in harsh environmental conditions. With an agricultural policy mainly aiming to achieve productivity maximization, existing breeding programs prioritize varietal development based on yield superiority. Against this background, we estimated a multinomial logit (MNL) model based on choice-experiment data from 167 bean growers in southern Ethiopia to explore whether farmers’ attribute preferences significantly diverge from those of breeders’ priorities. Four important bean attributes identified through participatory research methods were used. The results demonstrate that farmers have a higher propensity toward drought-tolerant capability than any of the attributes considered. The model estimates further show the existence of significant preference heterogeneity across farmers. These findings provide important insight to design breeding profiles compatible with specific producer segments. We suggest demand-driven breeding innovations and dissemination strategies in order to accelerate the adoption of climate-smart and higher-yielding bean innovations that contribute to achieve the national and global sustainability goals in Ethiopia.

Climate change: how it impacts the emergence, transmission, resistance and consequences of viral infections in animals and plants

The ongoing COVID-19 pandemic has made us wonder what led to its occurrence and what can be done to avoid such events in the future. As we document, one changing circumstance that is resulting in the emergence and changing the expression of viral diseases in both plants and animals is climate change. Of note, the rapidly changing environment and weather conditions such as excessive flooding, droughts, and forest fires have raised concerns about the global ecosystem's security, sustainability, and balance. In this review, we discuss the main consequences of climate change and link these to how they impact the appearance of new viral pathogens, how they may facilitate transmission between usual and novel hosts, and how they may also affect the host's ability to manage the infection. We emphasize how changes in temperature and humidity and other events associated with climate change influence the reservoirs of viral infections, their transmission by insects and other intermediates, their survival outside the host as well the success of infection in plants and animals. We conclude that climate change has mainly detrimental consequences for the emergence, transmission, and outcome of viral infections and plead the case for halting and hopefully reversing this dangerous event.

Forecasting Plant and Crop Disease: An Explorative Study on Current Algorithms

Every year, plant diseases cause a significant loss of valuable food crops around the world. The plant and crop disease management practice implemented in order to mitigate damages have changed considerably. Today, through the application of new information and communication technologies, it is possible to predict the onset or change in the severity of diseases using modern big data analysis techniques. In this paper, we present an analysis and classification of research studies conducted over the past decade that forecast the onset of disease at a pre-symptomatic stage (i.e., symptoms not visible to the naked eye) or at an early stage. We examine the specific approaches and methods adopted, pre-processing techniques and data used, performance metrics, and expected results, highlighting the issues encountered. The results of the study reveal that this practice is still in its infancy and that many barriers need to be overcome.

A Review on Prediction Models for Pesticide Use, Transmission, and Its Impacts

The lure of increased productivity and crop yield has caused the imprudent use of pesticides in great quantity that has unfavorably affected environmental health. Pesticides are chemicals intended for avoiding, eliminating, and mitigating any pests that affect the crop. Lack of awareness, improper management, and negligent disposal of pesticide containers have led to the permeation of pesticide residues into the food chain and other environmental pathways, leading to environmental degradation. Sufficient steps must be undertaken at various levels to monitor and ensure judicious use of pesticides. Development of prediction models for optimum use of pesticides, pesticide management, and their impact would be of great help in monitoring and controlling the ill effects of excessive use of pesticides. This paper aims to present an exhaustive review of the prediction models developed and modeling strategies used to optimize the use of pesticides.

Engineering crops of the future: CRISPR approaches to develop climate-resilient and disease-resistant plants

To meet increasing global food demand, breeders and scientists aim to improve the yield and quality of major food crops. Plant diseases threaten food security and are expected to increase because of climate change. CRISPR genome-editing technology opens new opportunities to engineer disease resistance traits. With precise genome engineering and transgene-free applications, CRISPR is expected to resolve the major challenges to crop improvement. Here, we discuss the latest developments in CRISPR technologies for engineering resistance to viruses, bacteria, fungi, and pests. We conclude by highlighting current concerns and gaps in technology, as well as outstanding questions for future research.

Potato virus Y and Potato leafroll virus management under climate change in sub-Saharan Africa

Potato has increased in importance as a staple food in sub-Saharan Africa, where its production is faced with a multitude of challenges, including plant disease development and spread under changing climatic conditions. The economically most important plant viruses affecting potatoes globally are Potato virus Y (PVY) and Potato leafroll virus (PLRV). Disease management relies mostly on the use of insecticides, cultural control and seed certification schemes. A major obstacle in many sub-Saharan Africa countries is the availability of disease-free quality seed potatoes. Establishment and implementation of quality control through specialised seed production systems and certification schemes is critical to improve seed potato quality and reduce PVY and PLRV sources. Seed could be further improved by breeding virus-resistant varieties adapted to different environmental conditions combined with management measures tailored for smallholder or commercial farmers to specific agricultural requirements. Innovative technologies – including more sensitive testing, remote sensing, machine learning and predictive models – provide new tools for the management of PVY and PLRV, but require support for adoption and implementation in sub-Saharan Africa.

Climate change and disease in plant communities

Climate change is triggering similar effects on the incidence and severity of disease for crops in agriculture and wild plants in natural communities. The complexity of natural ecosystems, however, generates a complex array of interactions between wild plants and pathogens in marked contrast to those generated in the structural and species simplicity of most agricultural crops. Understanding the different impacts of climate change on agricultural and natural ecosystems requires accounting for the specific interactions between an individual pathogen and its host(s) and their subsequent effects on the interplay between the host and other species in the community. Ultimately, progress will require looking past short-term fluctuations to multiyear trends to understand the nature and extent of plant and pathogen evolutionary adaptation and determine the fate of plants under future climate change.

Climate change is triggering similar effects on the incidence and severity of disease for crops in agriculture and wild plants in natural communities. However, this Essay maintains that accounting for the complexity of wild systems is a vital part of fully understanding the potential impact of climate change, not only on individual pathogen species but, more importantly, on entire natural communities.

Diversity in susceptibility reactions of winter wheat genotypes to obligate pathogens under fluctuating climatic conditions

To date, studies have usually focused on the impact of abiotic factors on the distribution of plant pathogens and have built forecast models for the prediction of pathogen outbreaks. However, the impact of the combined effects of biotic and abiotic factors on the prevalence of economically important pathogens has usually been neglected. The objective of this study was to determine the relationship between powdery mildew and rusts of wheat and to examine how the combined effects of abiotic and biotic factors influence their prevalence. The study was conducted in the period 2016-2019 using the collection of 2158 genotypes of winter wheat. The most influential factors on disease indices and relationships among obligate pathogens were determined using multiple regression models and principal component analysis. The possibility of the coexistence of different rust species in the same growing season and in the same field was shown. The significant influence of fluctuations in winter temperatures on changes in the prevalence of obligate pathogens was determined. The strong impact of genotypes and their reaction on climatic elements in certain phenological stages were shown to be significant factors influencing the interactions among obligate pathogens and the predominance of one pathogen over another.

Fighting Fusarium Pathogens in the Era of Climate Change: A Conceptual Approach

Fusarium head blight (FHB) caused by Fusarium pathogens is one of the most devastating fungal diseases of small grain cereals worldwide, substantially reducing yield quality and food safety. Its severity is increasing due to the climate change caused by weather fluctuations. Intensive research on FHB control methods has been initiated more than a decade ago. Since then, the environment has been rapidly changing at regional to global scales due to increasing anthropogenic emissions enhanced fertilizer application and substantial changes in land use. It is known that environmental factors affect both the pathogen virulence as well as plant resistance mechanisms. Changes in CO2 concentration, temperature, and water availability can have positive, neutral, or negative effects on pathogen spread depending on the environmental optima of the pathosystem. Hence, there is a need for studies of plant-pathogen interactions in current and future environmental context. Long-term monitoring data are needed in order to understand the complex nature of plants and its microbiome interactions. We suggest an holobiotic approach, integrating plant phyllosphere microbiome research on the ecological background. This will enable the development of efficient strategies based on ecological know-how to fight Fusarium pathogens and maintain sustainable agricultural systems.

Eating our way through the Anthropocene

This paper examines the complex interactions between food systems, diets, and the environment. We discuss the challenges facing the food system as a result of environmental degradation and climate change. We review the state of current diets and their effects on human health outcomes. As we consider paths forward, we examine holistic solutions that align nutrition, health, and environmental goals. Finally, we identify ethical questions relevant to the changing global food system. We consider our moral obligations to other people - both now and in the future - and the planet, and we posit that eating is an ethical act requiring reflection at all scales.

Forecasting severe grape downy mildew attacks using machine learning

Grape downy mildew (GDM) is a major disease of grapevine that has an impact on both the yields of the vines and the quality of the harvested fruits. The disease is currently controlled by repetitive fungicide treatments throughout the season, especially in the Bordeaux vineyards where the average number of fungicide treatments against GDM was equal to 10.1 in 2013. Reducing the number of treatments is a major issue from both an environmental and a public health point of view. One solution would be to identify vineyards that are likely to be heavily attacked in spring and then apply fungicidal treatments only to these situations. In this perspective, we use here a dataset including 9 years of GDM observations to develop and compare several generalized linear models and machine learning algorithms predicting the probability of high incidence and severity in the Bordeaux region. The algorithms tested use the date of disease onset and/or average monthly temperatures and precipitation as input variables. The accuracy of the tested models and algorithms is assessed by year-by-year cross validation. LASSO, random forest and gradient boosting algorithms show better performance than generalized linear models. The date of onset of the disease has a greater influence on the accuracy of forecasts than weather inputs and, among weather inputs, precipitation has a greater influence than temperature. The best performing algorithm was selected to evaluate the impact of contrasted climate scenarios on GDM risk levels. Results show that risk of GDM at bunch closure decreases with reduced rainfall and increased temperatures in April-May. Our results also show that the use of fungicide treatment decision rules that take into account local characteristics would reduce the number of treatments against GDM in the Bordeaux vineyards compared to current practices by at least 50%.

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers' views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.

Plant nonhost resistance: paradigms and new environments

Nonhost resistance (NHR) protects plants from a large and diverse array of potential phytopathogens. Each phytopathogen can parasitise some plant species, but most plant species are nonhosts that are innately immune due to a series of physical, chemical and inducible defenses these nonadapted pathogens cannot overcome. New evidence supports the NHR paradigm that posits the inability of potential pathogens to colonise nonhost plants is frequently due to molecular incompatibility between pathogen virulence factors and plant cellular targets. While NHR is durable, it is not insurmountable. Environmental changes can facilitate pathogen host jumps or alternatively result in new encounters between previously isolated plant species and pathogens. Climate change is predicted to substantially alter the current distribution of plants and their pathogens which could result in parasitism of new plant species.

Studies on the mechanism of agricultural chemicals focused on plant hormone signals

In recent years, it has become clear that the crosstalk of various plant hormones controls plant growth and disease resistance. Plant hormone signals may also be involved in the actions of a variety of pesticides and disease control techniques used for crop protection. From this point of view, we have focused on plant hormones to analyze the mode of action of pesticides that function in plants. Disease resistance inducers are pesticides that induce systemic acquired resistance (SAR) by activating the salicylic acid (SA)-mediated signaling pathway. However, when under unfavorable climate conditions, such as cold and cloudy weather, the resistance inducers are not sufficiently effective. Since the environmental stress response mediated by abscisic acid (ABA) may affect disease resistance, extensive studies of tobacco and tomato plants were performed, which clarified that SAR induction was suppressed by ABA. On the other hand, it was shown that transient high temperature treatment enhanced disease resistance via SA biosynthesis. These results suggest that changes in temperature due to climate change have an impact on disease resistance. The mode of action of a plant-growth regulator was analyzed by focusing on plant hormones. Isoprothiolane (IPT), an active ingredient of Fuji-one, is used as a plant-growth regulator and a fungicide. In Arabidopsis thaliana, we demonstrated that jasmonic acid and ethylene are required for the root elongation-promoting effect of IPT. As shown above, mode-of-action studies on pesticides in relation to plant hormones will lead to the development of new techniques for the better cultivation and protection of crops.

Plant pathogen responses to Late Pleistocene and Holocene climate change in the central Atacama Desert, Chile

Future climate change has the potential to alter the distribution and prevalence of plant pathogens, which may have significant implications for both agricultural crops and natural plant communities. However, there are few long-term datasets against which modelled predictions of pathogen responses to climate change can be tested. Here, we use 18S metabarcoding of 28 rodent middens (solidified deposits of rodent coprolites and nesting material) from the Central Atacama, spanning the last ca. 49 ka, to provide the first long-term late Quaternary record of change in plant pathogen communities in response to changing climate. Plant pathogen richness was significantly greater in middens deposited during the Central Andean Pluvial Event (CAPE); a period of increased precipitation between 17.5–8.5 ka. Moreover, the occurrence frequency of Pucciniaceae (rust fungi) was significantly greater during the CAPE, and the highest relative abundances for five additional potentially pathogenic taxa also occurred during this period. The results demonstrate the promising potential for ancient DNA analysis of late Quaternary samples to reveal insights into how plant pathogens responded to past climatic and environmental change, which could help predict how pathogens may responded to future change.

Climate change accelerates local disease extinction rates in a long-term wild host-pathogen association

Pathogens are a significant component of all plant communities. In recent years, the potential for existing and emerging pathogens of agricultural crops to cause increased yield losses as a consequence of changing climatic patterns has raised considerable concern. In contrast, the response of naturally occurring, endemic pathogens to a warming climate has received little attention. Here, we report on the impact of a signature variable of global climate change - increasing temperature - on the long-term epidemiology of a natural host-pathogen association involving the rust pathogen Triphragmium ulmariae and its host plant Filipendula ulmaria. In a host-pathogen metapopulation involving approximately 230 host populations growing on an archipelago of islands in the Gulf of Bothnia we assessed changes in host population size and pathogen epidemiological measures over a 25-year period. We show how the incidence of disease and its severity declines over that period and most importantly demonstrate a positive association between a long-term trend of increasing extinction rates in individual pathogen populations of the metapopulation and increasing temperature. Our results are highly suggestive that changing climatic patterns, particularly mean monthly growing season (April-November) temperature, are markedly influencing the epidemiology of plant disease in this host-pathogen association. Given the important role plant pathogens have in shaping the structure of communities, changes in the epidemiology of pathogens have potentially far-reaching impacts on ecological and evolutionary processes. For these reasons, it is essential to increase understanding of pathogen epidemiology, its response to warming, and to invoke these responses in forecasts for the future.

Cassava brown streak disease: historical timeline, current knowledge and future prospects

Cassava is the second most important staple food crop in terms of per capita calories consumed in Africa and holds potential for climate change adaptation. Unfortunately, productivity in East and Central Africa is severely constrained by two viral diseases: cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). CBSD was first reported in 1936 from northeast Tanzania. For approximately 70 years, CBSD was restricted to coastal East Africa and so had a relatively low impact on food security compared with CMD. However, at the turn of the 21st century, CBSD re-emerged further inland, in areas around Lake Victoria, and it has since spread through many East and Central African countries, causing high yield losses and jeopardizing the food security of subsistence farmers. This recent re-emergence has attracted intense scientific interest, with studies shedding light on CBSD viral epidemiology, sequence diversity, host interactions and potential sources of resistance within the cassava genome. This review reflects on 80 years of CBSD research history (1936-2016) with a timeline of key events. We provide insights into current CBSD knowledge, management efforts and future prospects for improved understanding needed to underpin effective control and mitigation of impacts on food security.

Prospects for engineering and improvement of cross-protective virus strains

Mild strain cross-protection is currently an important method for the production of high quality plant products; despite challenge from severe virus isolates the initial protecting strain precludes symptom development. The mechanism of cross-protection is not yet resolved as RNA silencing does not sufficiently explain the phenomenon. Six requirements have been put forward to ensure long-lasting protection. We propose two additional requirements for effective and durable mild strain cross-protection; mild strains based on knowledge of the mechanism and consideration of impacts to consumers. Future research on predicting phenotype from genotype and understanding virus-plant and virus-vector interactions will enable improvement of cross-protective strains. Shared international databases of whole ecosystem interactions across a wide range of virus patho- and symbiotic-systems will form the basis for making step-change advances towards our collective ability to engineer and improve mild strain cross-protection.

Trichoderma for climate resilient agriculture

Climate change is one of the biggest challenges of the twenty-first century for sustainable agricultural production. Several reports highlighted the need for better agricultural practices and use of eco-friendly methods for sustainable crop production under such situations. In this context, Trichoderma species could be a model fungus to sustain crop productivity. Currently, these are widely used as inoculants for biocontrol, biofertilization, and phytostimulation. They are reported to improve photosynthetic efficiency, enhance nutrient uptake and increase nitrogen use efficiency in crops. Moreover, they can be used to produce bio-energy, facilitate plants for adaptation and mitigate adverse effect of climate change. The technological advancement in high throughput DNA sequencing and biotechnology provided deep insight into the complex and diverse biotic interactions established in nature by Trichoderma spp. and efforts are being made to translate this knowledge to enhance crop growth, resistance to disease and tolerance to abiotic stresses under field conditions. The discovery of several traits and genes that are involved in the beneficial effects of Trichoderma spp. has resulted in better understanding of the performance of bioinoculants in the field, and will lead to more efficient use of these strains and possibly to their improvement by genetic modification. The present mini-review is an effort to elucidate the molecular basis of plant growth promotion and defence activation by Trichoderma spp. to garner broad perspectives regarding their functioning and applicability for climate resilient agriculture.

A Perspective on CRN Proteins in the Genomics Age: Evolution, Classification, Delivery and Function Revisited

Plant associated microbes rely on secreted virulence factors (effectors) to modulate host immunity and ensure progressive infection. Amongst the secreted protein repertoires defined and studied in pathogens to date, the CRNs (for CRinkling and Necrosis) have emerged as one of only a few highly conserved protein families, spread across several kingdoms. CRN proteins were first identified in plant pathogenic oomycetes where they were found to be modular factors that are secreted and translocated inside host cells by means of a conserved N-terminal domain. Subsequent localization and functional studies have led to the view that CRN C-termini execute their presumed effector function in the host nucleus, targeting processes required for immunity. These findings have led to great interest in this large protein family and driven the identification of additional CRN-like proteins in other organisms. The identification of CRN proteins and subsequent functional studies have markedly increased the number of candidate CRN protein sequences, expanded the range of phenotypes tentatively associated with function and revealed some of their molecular functions toward virulence. The increased number of characterized CRNs also has presented a set of challenges that may impede significant progress in the future. Here, we summarize our current understanding of the CRNs and re-assess some basic assumptions regarding this protein family. We will discuss the latest findings on CRN biology and highlight exciting new hypotheses that have emanated from the field. Finally, we will discuss new approaches to study CRN functions that would lead to a better understanding of CRN effector biology as well as the processes that lead to host susceptibility and immunity.