Climate change and plant disease management

Crosstalk Between Abiotic and Biotic Stresses Responses and the Role of Chloroplast Retrograde Signaling in the Cross-Tolerance Phenomena in Plants

In the natural environment, plants are simultaneously exposed to multivariable abiotic and biotic stresses. Typical abiotic stresses are changes in temperature, light intensity and quality, water stress (drought, flood), microelements availability, salinity, air pollutants, and others. Biotic stresses are caused by other organisms, such as pathogenic bacteria and viruses or parasites. This review presents the current state-of-the-art knowledge on programmed cell death in the cross-tolerance phenomena and its conditional molecular and physiological regulators, which simultaneously regulate plant acclimation, defense, and developmental responses. It highlights the role of the absorbed energy in excess and its dissipation as heat in the induction of the chloroplast retrograde phytohormonal, electrical, and reactive oxygen species signaling. It also discusses how systemic- and network-acquired acclimation and acquired systemic resistance are mutually regulated and demonstrates the role of non-photochemical quenching and the dissipation of absorbed energy in excess as heat in the cross-tolerance phenomenon. Finally, new evidence that plants evolved one molecular system to regulate cell death, acclimation, and cross-tolerance are presented and discussed.

Future climate suitability of Hemileia vastatrix in arabica coffee under CMIP6 scenarios

BACKGROUND

Coffee (Coffea arabica L.) is one of the most important commodities today, with a high economic value worldwide. Coffee leaf rust (Hemileia vastatrix Berk. et Br.) has been showing a high impact on Brazilian coffee trees among the various diseases that attack coffee. The climate has a great influence on the development of diseases, especially when fungi are the causal agents. This study aimed to carry out the zoning of climate favorability for coffee leaf rust in the traditional and main coffee-producing regions of Brazil. The study was conducted in 13 locations in the states of Paraná, São Paulo, Rio de Janeiro, Espírito Santo, Minas Gerais, Goiás and Bahia. Air temperature and daily precipitation data for the current scenario were collected using the WorldClim version 2.1 platform for the last climatological normal and future climate change data. The ideal climate conditions for coffee leaf rust consist of a mean air temperature ranging from 21 to 25 °C and precipitation >30 mm per month. The Coupled Model Intercomparison Projects scenarios associated with the Intergovernmental Panel on Climate Change reports consisted of the Shared Socio-Economic Pathways SSP-1 2.6, SSP-2 4.5, SSP-3 7.0 and SSP-5 8.5, the latter being considered one of the most catastrophic. All steps to carry out the suitability zoning were performed in a tool using the QGIS geographic information system software.

RESULTS

Zoning for coffee leaf rust had three classes: favorable, relatively favorable and unfavorable. Currently, the largest coffee-producing region in Brazil has 49.1% of its analyzed area classified as favorable, 39.2% as relatively favorable and 11.7% as unfavorable. In the current scenario, Patrocínio and Três Pontas are locations with high coffee production in which the favorable class is predominant. The state of Minas Gerais has an annual mean of 55.3% of its entire territory apt for the disease, with the highest occurrence between September and March.

CONCLUSIONS

Climate change has a negative impact on the development of coffee leaf rust, mainly in the long term, as in the period of 2081-2100, in which the SSP-5 8.5 scenario led to a decrease in the favorable and unfavorable areas and an increase in the relatively favorable areas of 9.8%, 18.6% and 71.5% for the Brazilian territory, respectively. © 2024 Society of Chemical Industry.

Understanding the impacts of drought on peanuts (Arachis hypogaea L.): exploring physio-genetic mechanisms to develop drought-resilient peanut cultivars

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production occurs worldwide in arid and semi-arid regions, making drought an important concern in peanut production. In the US about two-thirds of peanuts are grown in non-irrigated lands, where drought accounts for 50 million USD loss each year. The looming threat of climate change exacerbates this situation by increasing erratic rainfall. Drought not only reduces yield but also degrades product quality. Peanuts under drought stress exhibit higher levels of pre-harvest aflatoxin contamination, a toxic fungal metabolite detrimental to both humans and animals. One way to sustain peanut production in drought-prone regions and address pre-harvest aflatoxin contamination is by developing drought-tolerant peanut cultivars, a process that can be accelerated by understanding the underlying physiological and genetic mechanisms for tolerance to drought stress. Different physiological attributes and genetic regions have been identified in drought-tolerant cultivars that help them cope with drought stress. The advent of precise genetic studies, artificial intelligence, high-throughput phenotyping, bioinformatics, and data science have significantly improved drought studies in peanuts. Yet, breeding peanuts for drought tolerance is often a challenge as it is a complex trait significantly affected by environmental conditions. Besides technological advancements, the success of drought-tolerant cultivar development also relies on the identification of suitable germplasm and the conservation of peanut genetic variation.

Impacts of Weather Anomalies and Climate on Plant Disease

Predicting the effects of climate change on plant disease is critical for protecting ecosystems and food production. Here, we show how disease pressure responds to short-term weather, historical climate and weather anomalies by compiling a global database (4339 plant-disease populations) of disease prevalence in both agricultural and wild plant systems. We hypothesised that weather and climate would play a larger role in disease in wild versus agricultural plant populations, which the results supported. In wild systems, disease prevalence peaked when the temperature was 2.7°C warmer than the historical average for the same time of year. We also found evidence of a negative interactive effect between weather anomalies and climate in wild systems, consistent with the idea that climate maladaptation can be an important driver of disease outbreaks. Temperature and precipitation had relatively little explanatory power in agricultural systems, though we observed a significant positive effect of current temperature. These results indicate that disease pressure in wild plants is sensitive to nonlinear effects of weather, weather anomalies and their interaction with historical climate. In contrast, warmer temperatures drove risks for agricultural plant disease outbreaks within the temperature range examined regardless of historical climate, suggesting vulnerability to ongoing climate change.

Interactive Effects of Climate Change and Pathogens on Plant Performance: A Global Meta-Analysis

Plant health is increasingly threatened by abiotic and biotic stressors linked to anthropogenic global change. These stressors are frequently studied in isolation. However, they might have non-additive (antagonistic or synergistic) interactive effects that affect plant communities in unexpected ways. We conducted a global meta-analysis to summarize existing evidence on the joint effects of climate change (drought and warming) and biotic attack (pathogens) on plant performance. We also investigated the effect of drought and warming on pathogen performance, as this information is crucial for a mechanistic interpretation of potential indirect effects of climate change on plant performance mediated by pathogens. The final databases included 1230 pairwise cases extracted from 117 recently published scientific articles (from 2006) on a global scale. We found that the combined negative effects of drought and pathogens on plant growth were lower than expected based on their main effects, supporting the existence of antagonistic interactions. Thus, the larger the magnitude of the drought, the lower the pathogen capacity to limit plant growth. On the other hand, the combination of warming and pathogens caused larger plant damage than expected, supporting the existence of synergistic interactions. Our results on the effects of drought and warming on pathogens revealed a limitation of their growth rates and abundance in vitro but an improvement under natural conditions, where multiple factors operate across the microbiome. Further research on the impact of climate change on traits explicitly defining the infective ability of pathogens would enhance the assessment of its indirect effects on plants. The evaluated plant and pathogen responses were conditioned by the intensity of drought or warming and by moderator categorical variables defining the pathosystems. Overall, our findings reveal the need to incorporate the joint effect of climatic and biotic components of global change into predictive models of plant performance to identify non-additive interactions.

A Comprehensive Review of Climate Change and Plant Diseases in Brazil

Analyzing the impacts of climate change on phytosanitary problems in Brazil is crucial due to the country's special role in global food security as one of the largest producers of essential commodities. This review focuses on the effects of climate change on plant diseases and discusses its main challenges in light of Brazil's diverse agricultural landscape. To assess the risk of diseases caused by fungi, bacteria, viruses, oomycetes, nematodes, and spiroplasms, we surveyed 304 pathosystems across 32 crops of economic importance from 2005 to 2022. Results show that diseases caused by fungi account for 79% of the pathosystems evaluated. Predicting the occurrence of diseases in a changing climate is a complex challenge, and the continuity of this work is strategic for Brazil's agricultural defense. The future risk scenarios analyzed here aim to help guide disease mitigation for cropping systems. Despite substantial progress and ongoing efforts, further research will be needed to effectively prevent economic and environmental damage.

Disease Management in Regenerative Cropping in the Context of Climate Change and Regulatory Restrictions

Regenerative agriculture as a term and concept has gained much traction over recent years. Many farmers are convinced that by adopting these principles they will be able to address the triple crisis of biodiversity loss, climate change, and food security. However, the impact of regenerative agriculture practices on crop pathogens and their management has received little attention from the scientific community. Significant changes to cropping systems may result in certain diseases presenting more or less of a threat. Shifts in major diseases may have significant implications regarding optimal integrated pest management (IPM) strategies that aim to improve profitability and productivity in an environmentally sensitive manner. In particular, many aspects of regenerative agriculture change risk levels and risk management in ways that are central to effective IPM. This review outlines some of the challenges, gaps, and opportunities in our understanding of appropriate approaches for managing crop diseases in regenerative cropping systems.

The Greening of One Health: Plants, Pathogens, and the Environment

One Health has an aspirational goal of ensuring the health of humans, animals, plants, and the environment through transdisciplinary, collaborative research. At its essence, One Health addresses the human clash with Nature by formulating strategies to repair and restore a (globally) perturbed ecosystem. A more nuanced evaluation of humankind's impact on the environment (Nature, Earth, Gaia) would fully intercalate plants, plant pathogens, and beneficial plant microbes into One Health. Here, several examples point out how plants and plant microbes are keystones of One Health. Meaningful cross-pollination between plant, animal, and human health practitioners can drive discovery and application of innovative tools to address the many complex problems within the One Health framework.

Fusarium wilt pandemic: current understanding and molecular perspectives

Plant diseases pose a severe threat to the food security of the global human population. One such disease is Fusarium wilt, which affects many plant species and causes up to 100% yield losses. Fusarium pathogen has high variability in its genetic constitution; therefore, it has evolved into different physiological races to infect different plant species spread across the different geographical regions of the world. The pathogen mainly affects plant roots, leading to colonizing and blocking vascular bundle cells, specifically xylem vessels. This blocking results in chlorosis, vascular discoloration, leaf wilting, shortening of plant, and, in severe cases, premature plant death. Due to the soil-borne nature of the wilt pathogen, neither agronomic nor plant protection measures effectively reduce the incidence of the disease. Therefore, the most cost-effective management strategy for Fusarium wilt is developing varieties resistant to a particular race of the fungus wilt prevalent in a given region. This strategy requires understanding the pathogen, its disease cycle, and epidemiology with climate-changing scenarios. Hence, in the review, we will discuss the pathogenic aspect and genetics of the Fusarium wilt, including molecular interventions for developing climate-smart wilt tolerant/resistant varieties of crops. Overall, this review will add to our knowledge for advancing the breeding of resistance against the wilt pandemic.

Functional Evolution of Pseudofabraea citricarpa as an Adaptation to Temperature Change

Citrus target spot, caused by Pseudofabraea citricarpa, was formerly considered a cold-tolerant fungal disease. However, it has now spread from high-latitude regions to warmer low-latitude regions. Here, we conducted physiological observations on two different strains of the fungus collected from distinct regions, and evaluated their pathogenicity. Interestingly, the CQWZ collected from a low-latitude orchard, exhibited higher temperature tolerance and pathogenicity when compared to the SXCG collected from a high-latitude orchard. To further understand the evolution of temperature tolerance and virulence in these pathogens during the spread process, as well as the mechanisms underlying these differences, we performed genomic comparative analysis. The genome size of CQWZ was determined to be 44,004,669 bp, while the genome size of SXCG was determined to be 45,377,339 bp. Through genomic collinearity analysis, we identified two breakpoints and rearrangements during the evolutionary process of these two strains. Moreover, gene annotation results revealed that the CQWZ possessed 376 annotated genes in the "Xenobiotics biodegradation and metabolism" pathway, which is 79 genes more than the SXCG. The main factor contributing to this difference was the presence of salicylate hydroxylase. We also observed variations in the oxidative stress pathways and core pathogenic genes. The CQWZ exhibited the presence of a heat shock protein (HSP SSB), a catalase (CAT2), and 13 core pathogenic genes, including a LysM effector, in comparison to the SXCG. Furthermore, there were significant disparities in the gene clusters responsible for the production of seven metabolites, such as Fumonisin and Brefeldin. Finally, we identified the regulatory relationship, with the HOG pathway at its core, that potentially contributes to the differences in thermotolerance and virulence. As the global climate continues to warm, crop pathogens are increasingly expanding to new territories. Our findings will enhance understanding of the evolution mechanisms of pathogens under climate change.

Tapping the rhizosphere metabolites for the prebiotic control of soil-borne bacterial wilt disease

Prebiotics are compounds that selectively stimulate the growth and activity of beneficial microorganisms. The use of prebiotics is a well-established strategy for managing human gut health. This concept can also be extended to plants where plant rhizosphere microbiomes can improve the nutrient acquisition and disease resistance. However, we lack effective strategies for choosing metabolites to elicit the desired impacts on plant health. In this study, we target the rhizosphere of tomato (Solanum lycopersicum) suffering from wilt disease (caused by Ralstonia solanacearum) as source for potential prebiotic metabolites. We identify metabolites (ribose, lactic acid, xylose, mannose, maltose, gluconolactone, and ribitol) exclusively used by soil commensal bacteria (not positively correlated with R. solanacearum) but not efficiently used by the pathogen in vitro. Metabolites application in the soil with 1 µmol g^-1 soil effectively protects tomato and other Solanaceae crops, pepper (Capsicum annuum) and eggplant (Solanum melongena), from pathogen invasion. After adding prebiotics, the rhizosphere soil microbiome exhibits enrichment of pathways related to carbon metabolism and autotoxin degradation, which were driven by commensal microbes. Collectively, we propose a novel pathway for mining metabolites from the rhizosphere soil and their use as prebiotics to help control soil-borne bacterial wilt diseases.

Refining Management of Apple Powdery Mildew in New York State with Weather-Based Fungicide Application Timing Programs

In the absence of durable host resistance among commercial cultivars, chemical management continues to be an essential component of disease control in apple production. Apple powdery mildew, caused by the ascomycete Podosphaera leucotricha, is largely managed with regular fungicide applications from the host phenological stages of tight cluster to terminal bud growth set, with applications typically being made in a prophylactic manner irrespective of existing disease pressure. Here we evaluated two management programs that aligned fungicide applications to specific weather thresholds conducive to powdery mildew development using a rotation of single-site fungicides and sulfur. In three separate orchards among four cultivars, we compared powdery mildew disease progression over the growing season for each of the weather factor-based programs and a typical calendar-based application program. In each year of the trial, we found that management programs with weather-based fungicide applications provided levels of disease control similar to the calendar program but required 50 to 83.3% fewer mildew-specific fungicide applications throughout the growing season. Our results provide a framework with which to evaluate future weather-based management programs for apple powdery mildew management. This knowledge could be implemented in the creation of a powdery mildew disease management decision support system to better inform and aid fungicide application programs for continued sustainable apple production in the northeast United States.

Effects of climate change on the distribution of Fusarium spp. in Italy

This work studies the incidence of Fusarium spp. on wheat kernels about current and future climatic conditions in Italy. Epidemiological analyses were performed from 2007 to 2013 and the resulting dataset was used to find correlations between the disease incidence of five important Fusarium species monitored in Italy (Fusarium graminearum, F. langsethiae, F. sporotrichioides, F. poae and F. avenaceum) and climatic and geographical parameters. Probabilistic-based modelling of the actual distribution of Fusarium spp. was achieved by using the Zero-inflated Poisson regression. The probabilistic geographical distribution of the Fusarium species was assessed by applying future climatic scenarios (RCPs 4.5 and 8.5). The shift from current to future climatic scenarios highlighted changes on a national and regional scale. The tightening of environmental conditions from the RCP4.5 to 8.5 scenarios resulted in a sporadic presence of F. avenaceum only in the northern region of Italy. Fusarium graminearum was plentifully present in the current climate, but the tightening of minimum and maximum temperatures and the decrease of precipitation between May-June in the RCP8.5 no longer represents the optimum conditions for it. Fusarium langsethiae was currently distributed in all of Italy, showing an increase in the probability of detecting it by moving from high to low latitudes and from low to high longitudes in the RCP8.5. Fusarium poae, unlike other Fusarium species, grows and develops in arid climatic conditions. High values of F. poae were recorded at low latitudes and longitudes. Under the RCP scenarios, it showed high incidence probabilities in the southeast and northeast areas of Italy. Fusarium sporotrichioides is scarcely present in Italy, found at high latitudes and in the central areas. Climate change altered this distribution, and the chances of discovering it increased significantly moving to southern Italy. Overall, the study shows that climate change conditions are likely to lead to an increase in the incidence of Fusarium species on wheat kernels in Italy, highlighting the importance of developing strategies to mitigate the effects of climate change on wheat production, quality, and safety.

Synergism: biocontrol agents and biostimulants in reducing abiotic and biotic stresses in crop

In today's fast-shifting climate change scenario, crops are exposed to environmental pressures, abiotic and biotic stress. Hence, these will affect the production of agricultural products and give rise to a worldwide economic crisis. The increase in world population has exacerbated the situation with increasing food demand. The use of chemical agents is no longer recommended due to adverse effects towards the environment and health. Biocontrol agents (BCAs) and biostimulants, are feasible options for dealing with yield losses induced by plant stresses, which are becoming more intense due to climate change. BCAs and biostimulants have been recommended due to their dual action in reducing both stresses simultaneously. Although protection against biotic stresses falls outside the generally accepted definition of biostimulant, some microbial and non-microbial biostimulants possess the biocontrol function, which helps reduce biotic pressure on crops. The application of synergisms using BCAs and biostimulants to control crop stresses is rarely explored. Currently, a combined application using both agents offer a great alternative to increase the yield and growth of crops while managing stresses. This article provides an overview of crop stresses and plant stress responses, a general knowledge on synergism, mathematical modelling used for synergy evaluation and type of in vitro and in vivo synergy testing, as well as the application of synergism using BCAs and biostimulants in reducing crop stresses. This review will facilitate an understanding of the combined effect of both agents on improving crop yield and growth and reducing stress while also providing an eco-friendly alternative to agroecosystems.

Influence of altitude as a proxy for temperature on key Musa pests and diseases in watershed areas of Burundi and Rwanda

Pests and diseases are key biotic constraints limiting banana production among smallholder farmers in Eastern and Central Africa. Climate changemay favour pest and disease development and further exacerbate the vulnerability of smallholder farming systems to biotic constraints. Information on effects of climate change on pests and pathogens of banana is required byby policy makers and researchers in designing control strategies and adaptation plans. Since altitude is inversely related to temperature, this study used the occurrence of key banana pests and diseases along an altitude gradient as a proxy for the potential impact of changes in temperature associated with global warming on pests and diseases. We assessed the occurrence of banana pests and diseases in 93 banana fields across three altitude ranges in Burundi and 99 fields distributed in two altitude ranges in Rwanda watersheds. Incidence and prevalence of Banana Bunchy Top Disease (BBTD) and Fusarium wilt (FW) was significantly associated with temperature and altitude in Burundi, revealing that increasing temperatures may lead to upward movement of banana diseases. No significant associations with temperature and altitude were observed for weevils, nematodes and Xanthomonas wilt of banana (BXW). Data collected in this study provides a baseline to verify and guide modelling work to predict future pest and disease distribution according to climate change scenarios. Such information is useful in informing policy makers and designing appropriate management strategies.

Global predictions for the risk of establishment of Pierce's disease of grapevines

The vector-borne bacterium Xylella fastidiosa is responsible for Pierce's disease (PD), a lethal grapevine disease that originated in the Americas. The international plant trade is expanding the geographic range of this pathogen, posing a new threat to viticulture worldwide. To assess the potential incidence of PD, we have built a dynamic epidemiological model based on the response of 36 grapevine varieties to the pathogen in inoculation assays and on the vectors' distribution when this information is available. Key temperature-driven epidemiological processes, such as PD symptom development and recovery, are mechanistically modelled. Integrating into the model high-resolution spatiotemporal climatic data from 1981 onward and different infectivity (R0) scenarios, we show how the main wine-producing areas thrive mostly in non-risk, transient, or epidemic-risk zones with potentially low growth rates in PD incidence. Epidemic-risk zones with moderate to high growth rates are currently marginal outside the US. However, a global expansion of epidemic-risk zones coupled with small increments in the disease growth rate is projected for 2050. Our study globally downscales the risk of PD establishment while highlighting the importance of considering climate variability, vector distribution, and an invasive criterion as factors to obtain better PD risk maps.

Key infection stages defending heat stress in high-temperature-resistant Blumeria graminis f. sp. tritici isolates

With the increase of temperature in the winter wheat-growing regions in China, the high-temperature-resistant Blumeria graminis f. sp. tritici (Bgt) isolates developed in the fields. To clarify the key infection stages and the roles of heat shock protein (HSP) genes of high-temperature-resistant Bgt isolates defending high temperature, 3 high-temperature-resistant and 3 sensitive Bgt isolates were selected from 55 isolates after determination of temperature sensitivity. And then they were used to investigate the infection stages and the expression levels of HSP genes, including Bgthsp60, Bgthsp70, Bgthsp90, and Bgthsp104, at 18°C and 25°C. The formation frequency of abnormal appressoria and inhibition rate of haustoria formation of high-temperature-resistant isolates at 25°C were lower than those of high-temperature-sensitive isolates, while major axis of microcolonies of high-temperature-resistant isolates was higher than those of high-temperature-sensitive isolates at 25°C. The results indicated that haustoria formation and hyphal expansion were the key infection stages of defense against heat stress in high-temperature-resistant isolates. Further analyses of HSP genes found the expression levels of Bgthsp60 and Bgthsp70c were upregulated at 24 and 72 h post-inoculation in high-temperature-resistant isolates, while no significant difference was observed for Bgthsp90 and Bgthsp104 genes. Taken together, the basis of high-temperature-resistant Bgt isolates is associated with induced expression of Bgthsp60 and Bgthsp70c response to heat stress in haustoria formation and hyphal expansion stages.

Patterns and Distribution of Botryosphaeriaceae Fungi Related to Dieback in Big Berry Manzanita

Dieback and mortality in wildland plant species due to climate change have been on the rise in recent decades, and latent fungal pathogens might play a significant role in these events. During a severe multiyear drought, canopy dieback associated with latent pathogens in the Botryosphaeriaceae (Bot) family was observed in stands of a dominant shrub species, big berry manzanita (Arctostaphylos glauca), across chaparral landscapes in California. These fungi are significant pathogens of woody agricultural species, especially in hosts experiencing stress, and have become a threat to economically important crops worldwide. However, little is known regarding their occurrence, distribution, and impact in wildland systems. We conducted a field survey of 300 A. glauca shrubs across an elevational gradient to identify Bot species infection as it relates to (i) A. glauca dieback severity and (ii) landscape variables associated with plant drought stress. Our results show that Bots are widely infecting A. glauca across the landscape, and there is a significant correlation between elevation and dieback severity. Dieback severity was significantly higher at lower elevations, suggesting that infected shrubs at lower elevations are at greater risk than those at higher elevations. Furthermore, two Bot species, Neofusicoccum australe and Botryosphaeria dothidea, were most frequently isolated, with N. australe being the most common and, based on haplotype analysis, likely the most recently introduced of the two. Our results confirm the wide distribution of latent Bot fungi in a wild shrubland system and provide valuable insight into areas of greatest risk for future shrub dieback and mortality. These findings could be particularly useful for informing future wildlands management strategies with regard to introduced latent pathogens.

Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation

Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers' phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.

Modelling cassava production and pest management under biotic and abiotic constraints

We summarise modelling studies of the most economically important cassava diseases and arthropods, highlighting research gaps where modelling can contribute to the better management of these in the areas of surveillance, control, and host-pest dynamics understanding the effects of climate change and future challenges in modelling. For over 30 years, experimental and theoretical studies have sought to better understand the epidemiology of cassava diseases and arthropods that affect production and lead to considerable yield loss, to detect and control them more effectively. In this review, we consider the contribution of modelling studies to that understanding. We summarise studies of the most economically important cassava pests, including cassava mosaic disease, cassava brown streak disease, the cassava mealybug, and the cassava green mite. We focus on conceptual models of system dynamics rather than statistical methods. Through our analysis we identified areas where modelling has contributed and areas where modelling can improve and further contribute. Firstly, we identify research challenges in the modelling developed for the surveillance, detection and control of cassava pests, and propose approaches to overcome these. We then look at the contributions that modelling has accomplished in the understanding of the interaction and dynamics of cassava and its' pests, highlighting success stories and areas where improvement is needed. Thirdly, we look at the possibility that novel modelling applications can achieve to provide insights into the impacts and uncertainties of climate change. Finally, we identify research gaps, challenges, and opportunities where modelling can develop and contribute for the management of cassava pests, highlighting the recent advances in understanding molecular mechanisms of plant defence.

Heterogeneous effects of climatic conditions on Andean bean landraces and cowpeas highlight alternatives for crop management and conservation

The use and conservation of agrobiodiversity have become critical to face the actual and future challenges imposed by climate change. Collecting phytogenetic resources is a first step for their conservation; however, the genetic material must be analysed to understand their potential to improve agricultural resilience and adaptation to the new climatic conditions. We have selected nine Phaseolus vulgaris, one P. lunatus and two Vigna unguiculata landraces from two different climatic backgrounds of the Andean region of South Ecuador and one P. vulgaris commercial cultivar, and we grew them under two different conditions of temperature and humidity (open field and greenhouse). Then, we recorded data for 32 characters of plant architecture, flower and fruit characteristics and yield, and 17 events in the phenology of the plants. We analysed the impact of treatment on species, climatic background, and each of the landraces, and identified both characters and landraces that are mostly affected by changes in their environmental conditions. Overall, higher temperatures were benign for all materials except for two P. vulgaris landraces from cold background, which performed better or developed faster under cold conditions. Finally, we calculated a climate resilience landrace index, which allowed us to classify the landraces by their plasticity to new environmental conditions, and found heterogeneous landrace susceptibility to warmer conditions. Two P. vulgaris landraces were highlighted as critical targets for conservation.

Genotype and Phenotype Interaction between OsWKRYq6 and BLB after Xanthomonas oryzae pv. Oryzae Inoculation in the Field

Bacterial leaf blight (BLB) is an important and devastating rice disease caused by the pathogen Xanthomonas oryzae pv. Oryzae (Xoo). In particular, in recent years, the occurrence of abnormal climate and warming phenomena has produced a good environment for the occurrence of BLB, and the rice yield due to the occurrence of BLB continues to decrease. Currently, molecular breeding is applied by searching for resistant genes to development of BLB resistance cultivar. In addition, there are many methods for screening resistant genes, and among them, phenotype analysis in the field and applied research is rarely conducted. Due to recent rapid climate change, BLB is a major problem that has a more serious negative effect on rice yield. Therefore, we suggest OsWRKYq6 to be effectively used for breeding BLB-resistant cultivars by screening BLB-resistant genes. In this study, the BLB-resistant gene was screened using the lesion length, which most definitely changes to the phenotype when Xoo is infected. OsWRKYq6 was finally selected as a BLB resistance gene by analyzing the phenotype and genotype after inoculating Xoo in 120 Cheongcheong/Nagdong double haploid (CNDH) lines in the field. After Xoo inoculation, lesion length and yield were investigated, and 120 CNDH lines were divided from BLB-resistant and susceptible lines. Moreover, when the transcription level of OsWRKYq6 was analyzed in the resistant and susceptible lines after Xoo inoculation in the field, the expression level was regulated to a high level in the resistant line. In this study, we propose OsWRKYq6 as a transcription factor involved in BLB resistance. Currently, the differentiation of various races is proceeding rapidly due to rapid climate change. In addition, screening of transcription factor genes involved in BLB resistance in the field can be effectively applied to molecular breeding to develop resistant cultivars in preparation for rapid climate change.

Phytoparasitic nematodes of organic vegetables in the Argan Biosphere of Souss-Massa (Southern Morocco)

Agroecological productivity of the Arganeraie Biosphere Reserve of Morocco is limited by the wide spread and dynamics of plant parasitic nematodes (PPN). Ecological studies of nematode communities are required to develop effective biological management of these bioagressors as conventional control methods of PPN are inadequate and have persistent harmful effects. Fifty-nine organic vegetable soils in Souss-Massa were nematologically sampled, and assessment of taxonomic proliferation was made in relation to host species, geographical origin, and climatic and microclimatic factors. Twenty-four nematode genera were identified as obligate and facultative plant feeders. Taxonomic diversity increased from Chtouka to Taroudant and Tiznit provinces. Soil texture, organic matter, pH, nitrogen, zinc, magnesium, copper, altitude, and humidity and temperature were seen to effect driving roles in the abundance, distribution, and community structures of nematodes. The most prevalent taxa posing a high risk to organic agriculture of Souss Massa were needle nematodes (Longidorus spp.) and root-knot nematodes (Meloidogyne spp.). Edaphic and climatic variables effected nematode populations greatly. A combination of biological treatments and appropriate agroecological practices restricting important economic PPN growth and enhancing soil quality are required to achieve sustainable management in the area.

Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam

We analyzed the agricultural land-use changes in the coastal areas of Tien Hai district, Thai Binh province, in 2005, 2010, 2015, and 2020, using Landsat 5 and Landsat 8 data. We used the object-oriented classification method with the maximum likelihood algorithm to classify six types of land uses. The series of land-use maps we produced had an overall accuracy of more than 80%. We then conducted a spatial analysis of the 5-year land-use change using ArcGIS software. In addition, we surveyed 150 farm households using a structured questionnaire regarding the impacts of climate change on agricultural productivity and land uses, as well as farmers’ adaptation and responses. The results showed that from 2005 to 2020, cropland decreased, while aquaculture land and forest land increased. We observed that the most remarkable decreases were in the area of rice (485.58 ha), the area of perennial crops (109.7 ha), and the area of non-agricultural land (747.35 ha). The area of land used for aquaculture and forest increased by 566.88 ha and 772.60 ha, respectively. We found that the manifestations of climate change, such as extreme weather events, saltwater intrusion, drought, and floods, have had a profound impact on agricultural production and land uses in the district, especially for annual crops and aquaculture. The results provide useful information for state authorities to design land-management strategies and solutions that are economic and effective in adapting to climate change.

Bitter Rot of Apple in the Mid-Atlantic United States: Causal Species and Evaluation of the Impacts of Regional Weather Patterns and Cultivar Susceptibility

Apple growers in the Mid-Atlantic region of the United States have been reporting an increase in losses to bitter rot of apple and are requesting up-to-date management recommendations. Management is complicated by variations in apple cultivar susceptibility, temperature, rainfall, and biology of the Colletotrichum spp. that cause bitter rot. Over 500 apple fruit with bitter rot were obtained from 38 orchards across the Mid-Atlantic and the causal species were identified as Colletotrichum fioriniae and C. nymphaeae of the C. acutatum species complex and C. chrysophilum, C. noveboracense, C. siamense, C. fructicola, C. henanense, and C. gloeosporioides sensu stricto of the C. gloeosporioides species complex, the latter two being first reports. Species with faster in vitro growth rates at higher temperatures were more abundant in warmer regions of the Mid-Atlantic, while those with slower growth rates at higher temperatures were more abundant in cooler regions. Regional bloom dates are earlier and weather data show a gradual warming trend that likely influenced but was not necessarily the main cause of the recent increase in bitter rot in the region. A grower survey of apple cultivar susceptibility showed high variation, with the increase in acres planted to the highly susceptible cultivar Honeycrisp broadly corresponding to the increase in reports of bitter rot. These results form a basis for future studies on the biology and ecology of the Colletotrichum spp. responsible, and suggest that integrated bitter rot management must begin with selection of less-susceptible apple cultivars.

The impact of weather and increased atmospheric CO2 from 1892 to 2016 on simulated yields of UK wheat

Climate change effects on UK winter wheat grain yield are complex: warmer temperature, negative; greater carbon dioxide (CO2) concentration, positive; but other environmental variables and their timing also affect yield. In the absence of long-term experiments where temperature and CO2 concentration were manipulated separately, we applied the crop simulation model Sirius with long-term daily meteorological data (1892-2016) for Rothamsted, Hertfordshire, UK (2007-2016 mean growing season temperature 1.03°C warmer than 1892-1991), and CO2 concentration over this period, to investigate the separate effects of historic CO2 and weather on simulated grain yield in three wheat cultivars of the modern era. We show a slight decline in simulated yield over the period 1892-2016 from the effect of weather (daily temperature, rainfall and sunshine hours) at fixed CO2 (294.50 ppm, 1892 reference value), but a maximum 9.4% increase when accounting for increasing atmospheric CO2 (from 294.50 to 404.21 ppm), differing slightly among cultivars. Notwithstanding considerable inter-annual variation, the slight yield decline at 294.50 ppm CO2 over this 125-year period from the historic weather simulations for Rothamsted agrees with the expected decline from temperature increase alone, but the positive yield trend with actual CO2 values does not match the recent stagnation in UK wheat yield.

Smart paddy field monitoring system using deep learning and IoT

Paddy is an essential nutrient worldwide. Rice gives 21% of worldwide human per capita energy and 15% of per capita protein. Asia represented 60% of the worldwide populace, about 92% of the world’s rice creation, and 90% of worldwide rice utilization. With the increase in population, the demand for rice is increased. So, the productivity of farming is needed to be enhanced by introducing new technology. Deep learning and IoT are hot topics for research in various fields. This paper suggested a setup comprising deep learning and IoT for monitoring of paddy field remotely. The vgg16 pre-trained network is considered for the identification of paddy leaf diseases and nitrogen status estimation. Here, two strategies are carried out to identify images: transfer learning and deep feature extraction. The deep feature extraction approach is combined with a support vector machine (SVM) to classify images. The transfer learning approach of vgg16 for identifying four types of leaf diseases and prediction of nitrogen status results in 79.86% and 84.88% accuracy. Again, the deep features of Vgg16 and SVM results for identifying four types of leaf diseases and prediction of nitrogen status have achieved an accuracy of 97.31% and 99.02%, respectively. Besides, a framework is suggested for monitoring of paddy field remotely based on IoT and deep learning. The suggested prototype’s superiority is that it controls temperature and humidity like the state-of-the-art and can monitor the additional two aspects, such as detecting nitrogen status and diseases.

In Vitro and In Planta Studies on Temperature Adaptation of Exserohilum turcicum Isolates from Maize in Europe and South America

Northern Corn Leaf Blight (NCLB) is a fungal leaf disease in maize caused by Exserohilum turcicum. NCLB occurs worldwide, from tropical to temperate zones raising the question about plasticity of temperature adaptation of local isolates of the pathogen. Seven isolates of E. turcicum originating from South America and seven from Europe were compared for their response to temperature variations in vitro and in vivo between 15 and 30 °C. In vitro, isolates originating from Europe and South America significantly differed in mycelial growth rate at 30 °C and in sporulation at 25 °C and 30 °C. Aggressiveness of E. turcicum isolates was evaluated on three susceptible maize cultivars (maize lines B37, Sus1 and the German hybrid Niklas) under different day/night temperature regimes (15/10 °C, 20/15 °C, 25/20 °C, or 30/25 °C) with a photoperiod of 14 h. Aggressiveness, recorded as area under the disease progress curve (AUDPC), of South American isolates was higher than for European isolates at 15 °C, 20 °C and 25 °C, and for sporulation in vivo in all temperatures. In general, aggressiveness components were most influenced by temperature. Therefore, multivariate analysis was performed with aggressiveness component data at 30 °C, which expressed the highest number of variables with significant differences between isolate origins. According to their aggressiveness, European and South American isolates can be grouped separately, demonstrating that South American isolates are better adapted to higher temperatures and display a higher level of aggressiveness under similar conditions than European isolates from a cool climate. It is concluded that plasticity of temperature adaptation in E. turcicum populations is relatively large and allowed E. turcicum to follow the recent expansion of maize cultivation into cool climate zones in Europe. However, our data suggest that adaptation to higher temperature is likely to increase aggressiveness of NCLB on maize in cooler climate zones when experiencing further climate warming. This plasticity in adaptation to environmental conditions of E. turcicum may also hamper the success of breeding programs as it may decrease the durability of resistance.

Capsule network with K-Means routingfor plant disease recognition

Capsule Networks (CapsNets) excel on simple image recognition problems. However, they fail to perform on complex images with high similarity and background objects. This paper proposes Local Binary Pattern (LBP) k-means routing and evaluates its performance on three publicly available plant disease datasets containing images with high similarity and background objects. The proposed routing algorithm adopts the squared Euclidean distance, sigmoid function, and a ‘simple-squash’ in place of dot product, SoftMax normalizer, and the squashing function found respectively in the dynamic routing algorithm. Extensive experiments conducted on the three datasets showed that the proposed model achieves consistent improvement in test accuracy across the three datasets as well as allowing an increase in the number of routing iterations with no performance degradation. The proposed model outperformed a baseline CapsNet by 8.37% on the tomato dataset with an overall test accuracy of 98.80%, comparable to state-of-the-art models on the same datasets.

Effect of elevated ozone and carbon dioxide interaction on growth, yield, nutrient content and wilt disease severity in chickpea grown in Northern India

Wilt caused by Fusarium oxysporum, sp. Ciceris (FOC) is an important disease causing losses up to 10% in chickpea yield. Experiments were conducted growing chickpea in free air ozone and carbon dioxide enrichment rings under four treatments of elevated ozone (O3) (EO:60 ± 10 ppb), elevated carbon dioxide (CO2) (ECO2:550 ± 25 ppm), combination of elevated CO2 and O3 (EO + ECO2) and ambient control for quantifying the effect on growth, yield, biochemical and nutrient content of chickpea. For studying the impact on wilt disease, chickpea was grown additionally in pots with soil containing FOC in these rings. The incidence of Fusarium wilt reduced significantly (p < 0.01) under EO as compared to ambient and ECO2. The activities of pathogenesis-related proteins chitinase and β-1,3- glucanase, involved in plant defense mechanism were enhanced under EO. The aboveground biomass and pod weight declined by 18.7 and 15.8% respectively in uninnoculated soils under EO, whereas, in FOC inoculated soil (diseased plants), the decline under EO was much less at 8.6 and 9.9% as compared to the ambient. Under EO, the activity of super oxide dismutase increased significantly (p < 0.5, 40%) as compared to catalase (12.5%) and peroxidase (17.5%) without any significant increase under EO + ECO2. The proline accumulation was significantly (p < 0.01) higher in EO as compared to EO + ECO2, and ECO2. The seed yield declined under EO due to significant reduction (p < 0.01) in the number of unproductive pods and seed weight. No change in the protein, total soluble sugars, calcium and phosphorus content was observed in any of the treatments, however, a significant decrease in potassium (K) content was observed under EO + ECO2. Elevated CO2 (554ppm) countered the impacts of 21.1 and 14.4 ppm h (AOT 40) O3 exposure on the seed yield and nutrient content (except K) in the EO + CO2 treatment and reduced the severity of wilt disease in the two years' study.

Ancestral chemotypes of cultivated grapevine with resistance to Botryosphaeriaceae-related dieback allocate metabolism towards bioactive stilbenes

Grapevine trunk diseases have devastating consequences on vineyards worldwide. European wild grapevines (Vitis vinifera subs. sylvestris) from the last viable population in Germany along the Rhine river showed variable degrees of resistance against Neofusicoccum parvum (strain Bt-67), a fungus associated with Botryosphaeriaceae-related dieback. Representative genotypes from different subclades of this population were mapped with respect to their ability to induce wood necrosis, as well as their defence responses in a controlled inoculation system. The difference in colonization patterns could be confirmed by cryo-scanning electron microscopy, while there was no relationship between vessel diameter and infection success. Resistant lines accumulated more stilbenes, that were in addition significantly partitioned to nonglycosylated viniferin trimers. By contrast, the susceptible genotypes accumulated less stilbenes with a significantly higher proportion of glycosylated piceid. We suggest a model in which in the resistant genotypes phenylpropanoid metabolism is channelled rapidly and specifically to the bioactive stilbenes. Our study specifies a resistant chemotype against grapevines trunk diseases and paves a way to breed for resistance against grapevine Botryosphaeriaceae-related dieback.

Study of the species composition and population structure of winter wheat leaf blotch pathogens in the central chernozem region of the Russian Federation

For the period of 2020, the species composition of winter wheat leaf blotch pathogens on the territory of the Central Chernozem region was studied. It is shown that the Zymoseptoria tritici species dominates in the pathogenic complex during all phases of wheat vegetation. Under the conditions of the year, the other two species - the pathogen of the disease: Parastagonospora nodorum and Parastagonospora avenae f. sp. triticea had no economic significance. The populations of the species Zymoseptoria tritici, formed on winter and spring wheat cultivats according to morphological, physiological and pathogenic properties, were studied. It is shown that black corrugated colonies with an average growth rate and high sporulation predominate. Using monogenic lines, virulence phenotypes were determined in isolates taken from infectious wheat material. Seven virulence phenotypes were identified. All isolates hit the test lines from 2 to 4 points, therefore they were characterized by wide virulence and high aggressiveness. The information obtained is necessary for the development of a methodology for resistance breeding.

Temperature differentially modulates the transcriptome response in Oryza sativa to Xanthomonas oryzae pv. oryzae infection

Bacterial blight is caused by the pathogen Xanthomonas oryzae pv. oryzae (Xoo). Genome scale integrative analysis on the interaction of high and low temperatures on the molecular response signature in rice during the Xoo infection has not been conducted yet. We have analysed a unique RNA-Seq dataset generated on the susceptible rice variety IR24 under combined exposure of Xoo with low 29/21 °C (day/night) and high 35/31 °C (day/night) temperatures. Differentially regulated key genes and pathways in rice plants during both the stress conditions were identified. Differential dynamics of the regulatory network topology showed that WRKY and ERF families of transcription factors play a crucial role during signal crosstalk events in rice plants while responding to combined exposure of Xoo with low temperature vs. Xoo with high temperatures. Our study suggests that upon onset of high temperature, rice plants tend to switch its focus from defence response towards growth and reproduction.

Potential effects of a high CO2 future on leguminous species

Legumes provide an important source of food and feed due to their high protein levels and many health benefits, and also impart environmental and agronomic advantages as a consequence of their ability to fix nitrogen through their symbiotic relationship with rhizobia. As a result of our growing population, the demand for products derived from legumes will likely expand considerably in coming years. Since there is little scope for increasing production area, improving the productivity of such crops in the face of climate change will be essential. While a growing number of studies have assessed the effects of climate change on legume yield, there is a paucity of information regarding the direct impact of elevated CO2 concentration (e[CO2]) itself, which is a main driver of climate change and has a substantial physiological effect on plants. In this review, we discuss current knowledge regarding the influence of e[CO2] on the photosynthetic process, as well as biomass production, seed yield, quality, and stress tolerance in legumes, and examine how these responses differ from those observed in non-nodulating plants. Although these relationships are proving to be extremely complex, mounting evidence suggests that under limiting conditions, overall declines in many of these parameters could ensue. While further research will be required to unravel precise mechanisms underlying e[CO2] responses of legumes, it is clear that integrating such knowledge into legume breeding programs will be indispensable for achieving yield gains by harnessing the potential positive effects, and minimizing the detrimental impacts, of CO2 in the future.

Developing Public-Private Partnerships in Plant Pathology Extension: Case Studies and Opportunities in the United States

Public-private partnerships (PPPs) can be an effective and advantageous way to accomplish extension and outreach objectives in plant pathology. The greatest opportunities for extension-focused PPPs may be in response to large-scale or emerging disease management concerns or in addressing complex issues that impact agriculture, such as climate change, digital technology, and public perception of science. The most fertile ground for forming PPPs is where the needs and strengths of the public and private sectors are complementary. Developing PPPs depends as much on professional relationships as on technical skills or contracts. Defining and making room for the success of all partners, identifying and addressing barriers to success, and earning and maintaining trust are components that contribute to the effectiveness of PPPs. Case studies in plant pathology demonstrate the positive impact PPPs can have on partners and stakeholders and provide guidance on the formation of PPPs in the future.

UAV-Based Multispectral Phenotyping for Disease Resistance to Accelerate Crop Improvement under Changing Climate Conditions

Accelerating crop improvement for increased yield and better adaptation to changing climatic conditions is an issue of increasing urgency in order to satisfy the ever-increasing global food demand. However, the major bottleneck is the absence of high-throughput plant phenotyping methods for rapid and cost-effective data-driven variety selection and release in plant breeding. Traditional phenotyping methods that rely on trained experts are slow, costly, labor-intensive, subjective, and often require destructive sampling. We explore ways to improve the efficiency of crop phenotyping through the use of unmanned aerial vehicle (UAV)-based multispectral remotely sensed data in maize (Zea mays L.) varietal response to maize streak virus (MSV) disease. Twenty-five maize varieties grown in a trial with three replications were evaluated under artificial MSV inoculation. Ground scoring for MSV infection was carried out at mid-vegetative, flowering, and mid-grain filling on a scale of 1 (resistant) to 9 (susceptible). UAV-derived spectral data were acquired at these three different phenological stages in multispectral bands corresponding to Green (0.53–0.57 μm), Red (0.64–0.68 μm), Rededge (0.73–0.74 μm), and Near-Infrared (0.77–0.81 μm). The imagery captured was stitched together in Pix4Dmapper, which generates two types of multispectral orthomosaics: the NoAlpha and the transparent mosaics for each band. The NoAlpha imagery was used as input into QGIS to extract reflectance data. Six vegetation indices were derived for each variety: normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), Rededge NDVI (NDVIrededge), Simple Ratio (SR), green Chlorophyll Index (CIgreen), and Rededge Chlorophyll Index (CIrededge). The Random Forest (RF) classifier was used to evaluate UAV-derived spectral and VIs with and without variable optimization. Correlations between the UAV-derived data and manual MSV scores were significant (R = 0.74–0.84). Varieties were classified into resistant, moderately resistant, and susceptible with overall classification accuracies of 77.3% (Kappa = 0.64) with optimized and 68.2% (Kappa = 0.51) without optimized variables, representing an improvement of ~13.3% due to variable optimization. The RF model selected GNDVI, CIgreen, CIrededge, and the Red band as the most important variables for classification. Mid-vegetative was the most ideal phenological stage for accurate varietal phenotyping and discrimination using UAV-derived multispectral data with RF under artificial MSV inoculation. The results provide a rapid UAV-based remote sensing solution that offers a step-change towards data availability at high spatial (submeter) and temporal (daily/weekly) resolution in varietal analysis for quick and robust high-throughput plant phenotyping, important for timely and unbiased data-driven variety selection and release in plant breeding programs, especially as climate change accelerates.

Potential occurrence of Puccinia sorghi in corn crops in Paraná, under scenarios of climate change

In the face of climate change scenarios, it is important to evaluate the possibility of an increase in the incidence of corn crop diseases and to promote studies aimed at creating mitigation measures. This paper aims to study the impacts that regional climate changes may have on the potential occurrence of corn common rust (Puccinia sorghi), in the region of Castro, Paraná (Brazil). The Eta climate model was driven by the global model CanESM2. We use the Historical simulation of the EtaCanESM2 model from 1981 to 2005, and future projections from 2046 to 2070 to simulate the occurrence of common rust. The criteria was adopted to simulate the common rust disease favored in environments with the minimum temperature lower than 8 °C, the maximum temperature higher than 32 °C, average temperature between 16 and 23 °C, and relative humidity higher than 95%. In Brazil, there are two different seasons for corn crop (Normaland Safrinha). Results show that relative humidity and minimum temperature simulated by the model presented good skills, approaching the observed data. Compared to the Historical simulation, the projections show a tendency to increase of maximum and minimum temperature in the future, and a tendency to decrease relative humidity. There is an increase in the number of days with the potential for the occurrence of the disease. The distribution of days with favorable conditions to rust disease tends to change in the future. In the Normaland Safrinhaseasons, there is a tendency to increase the number of days with favorable conditions to common rust occurrence. The influence of planting time is greater in Historical simulation when compared to future scenarios. The Safrinhaseason may present more days with the potential for the occurrence of common rust in the future than the Normalseason.

Future Climate Significantly Alters Fungal Plant Pathogen Dynamics during the Early Phase of Wheat Litter Decomposition

Returning wheat residues to the soil is a common practice in modern agricultural systems and is considered to be a sustainable practice. However, the negative contribution of these residues in the form of “residue-borne pathogens” is recognized. Here, we aimed to investigate the structure and ecological functions of fungal communities colonizing wheat residues during the early phase of decomposition in a conventional farming system. The experiment was conducted under both ambient conditions and a future climate scenario expected in 50–70 years from now. Using MiSeq Illumina sequencing of the fungal internal transcribed spacer 2 (ITS2), we found that plant pathogenic fungi dominated (~87% of the total sequences) within the wheat residue mycobiome. Destructive wheat fungal pathogens such as Fusarium graminearum, Fusarium tricinctum, and Zymoseptoria tritci were detected under ambient and future climates. Moreover, future climate enhanced the appearance of new plant pathogenic fungi in the plant residues. Our results based on the bromodeoxyuridine (BrdU) immunocapture technique demonstrated that almost all detected pathogens are active at the early stage of decomposition under both climate scenarios. In addition, future climate significantly changed both the richness patterns and the community dynamics of the total, plant pathogenic and saprotrophic fungi in wheat residues as compared with the current ambient climate. We conclude that the return of wheat residues can increase the pathogen load, and therefore have negative consequences for wheat production in the future.

Facing Climate Change: Application of Microbial Biostimulants to Mitigate Stress in Horticultural Crops

In the current scenario of rapidly evolving climate change, crop plants are more frequently subjected to stresses of both abiotic and biotic origin, including exposure to unpredictable and extreme climatic events, changes in plant physiology, growing season and phytosanitary hazard, and increased losses up to 30% and 50% in global agricultural productions. Plants coevolved with microbial symbionts, which are involved in major functions both at the ecosystem and plant level. The use of microbial biostimulants, by exploiting this symbiotic interaction, represents a sustainable strategy to increase plant performances and productivity, even under stresses due to climate changes. Microbial biostimulants include beneficial fungi, yeasts and eubacteria sharing the ability to improve plant nutrition, growth, productivity and stress tolerance. This work reports the current knowledge on microbial biostimulants and provides a critical review on their possible use to mitigate the biotic and abiotic stresses caused by climate changes. Currently, available products often provide a general amelioration of cultural conditions, but their action mechanisms are largely undetermined and their effects often unreliable. Future research may lead to more specifically targeted products, based on the characterization of plant-microbe and microbial community interactions.

Sick plants in grassland communities: a growth-defense trade-off is the main driver of fungal pathogen abundance

Aboveground fungal pathogens can substantially reduce biomass production in grasslands. However, we lack a mechanistic understanding of the drivers of fungal pathogen infection and impact. Using a grassland global change and biodiversity experiment we show that the trade-off between plant growth and defense is the main determinant of infection incidence. In contrast, nitrogen addition only indirectly increased incidence via shifting plant communities towards faster growing species. Plant diversity did not decrease incidence, likely because spillover of generalist pathogens or dominance of susceptible plants counteracted negative diversity effects. A fungicide treatment increased plant biomass production and high levels of infection incidence were associated with reduced biomass. However, pathogen impact was context dependent and infection incidence reduced biomass more strongly in diverse communities. Our results show that a growth-defense trade-off is the key driver of pathogen incidence, but pathogen impact is determined by several mechanisms and may depend on pathogen community composition.

An Analysis of Climate Impacts on Herbicide, Insecticide, and Fungicide Expenditures

The climate alters pest populations and in turn, pesticide use and cost as well as use of other pest treatments. This paper analyzes the effect of the climate on pesticide expenditures by category, namely: fungicides, herbicides, and insecticides. This is done by econometrically estimating the effects of climate variables such as mean temperature and precipitation as well as the number of hot days, cold days, and wet days on the mean and variance of expenditures by category. The estimates are performed for corn, soybeans, spring and winter wheat, and potatoes. We find that climate factors influence fungicide, herbicide, and insecticide expenditures and that this influence is heterogeneous, varying in nature across crops and pesticide categories. Moreover, we find that climate extremes are more important in determining pesticide expenditures than climate averages in several cases.

Spatio-Temporal Trends of Monthly and Annual Precipitation in Aguascalientes, Mexico

The objective of this research was to analyze the temporal patterns of monthly and annual precipitation at 36 weather stations of Aguascalientes, Mexico. The precipitation trend was determined by the Mann–Kendall method and the rate of change with the Theil–Sen estimator. In total, 468 time series were analyzed, 432 out of them were monthly, and 36 were annual. Out of the total monthly precipitation time series, 42 series showed a statistically significant trend (p ≤ 0.05), from which 8/34 showed a statistically significant negative/positive trend. The statistically significant negative trends of monthly precipitation occurred in January, April, October, and December. These trends denoted more significant irrigation water use, higher water extractions from the aquifers in autumn–winter, more significant drought occurrence, low forest productivity, higher wildfire risk, and greater frost risk. The statistically significant positive trends occurred in May, June, July, August, and September; to a certain extent, these would contribute to the hydrology, agriculture, and ecosystem but also could provoke problems due to water excess. In some months, the annual precipitation variability and El Niño-Southern Oscillation (ENSO) were statistically correlated, so it could be established that in Aguascalientes, this phenomenon is one of the causes of the yearly precipitation variation. Out of the total annual precipitation time series, only nine series were statistically significant positive; eight out of them originated by the augments of monthly precipitation. Thirteen weather stations showed statistically significant trends in the total precipitation of the growing season (May, June, July, August, and September); these stations are located in regions of irrigated agriculture. The precipitation decrease in dry months can be mitigated using shorter cycle varieties with lower water consumption, irrigation methods with high efficiency, and repairing irrigation infrastructure. The precipitation increase in humid months can be used to store water and use it during the dry season, and its adverse effects can be palliated with the use of varieties resistant to root diseases and lodging. The results of this work will be beneficial in the management of agriculture, hydrology, and water resources of Aguascalientes and in neighboring arid regions affected by climate change.

Potential Control of Potato Soft Rot Disease by the Obligate Predators Bdellovibrio and Like Organisms

Bacterial soft rot diseases caused by Pectobacterium spp. and Dickeya spp. affect a wide range of crops, including potatoes, a major food crop. As of today, farmers mostly rely on sanitary practices, water management, and plant nutrition for control. We tested the bacterial predators Bdellovibrio and like organisms (BALOs) to control potato soft rot. BALOs are small, motile predatory bacteria found in terrestrial and aquatic environments. They prey on a wide range of Gram-negative bacteria, including animal and plant pathogens. To this end, BALO strains HD100, 109J, and a ΔmerRNA derivative of HD100 were shown to efficiently prey on various rot-causing strains of Pectobacterium and Dickeya solani BALO control of maceration caused by a highly virulent strain of Pectobacterium carotovorum subsp. brasilense was then tested in situ using a potato slice assay. All BALO strains were highly effective at reducing disease, up to complete prevention. Effectivity was concentration dependent, and BALOs applied before P. carotovorum subsp. brasilense inoculation performed significantly better than those applied after the disease-causing agent, maybe due to in situ consumption of glucose by the prey, as glucose metabolism by live prey bacteria was shown to prevent predation. Dead predators and the supernatant of BALO cultures did not significantly prevent maceration, indicating that predation was the major mechanism for the prevention of the disease. Finally, plastic resistance to predation was affected by prey and predator population parameters, suggesting that population dynamics affect prey response to predation.IMPORTANCE Bacterial soft rot diseases caused by Pectobacterium spp. and Dickeya spp. are among the most important plant diseases caused by bacteria. Among other crops, they inflict large-scale damage to potatoes. As of today, farmers have few options to control them. The bacteria Bdellovibrio and like organisms (BALOs) are obligate predators of bacteria. We tested their potential to prey on Pectobacterium spp. and Dickeya spp. and to protect potato. We show that different BALOs can prey on soft rot-causing bacteria and prevent their growth in situ, precluding tissue maceration. Dead predators and the supernatant of BALO cultures did not significantly prevent maceration, showing that the effect is due to predation. Soft rot control by the predators was concentration dependent and was higher when the predator was inoculated ahead of the prey. As residual prey remained, we investigated what determines their level and found that initial prey and predator population parameters affect prey response to predation.

Karnal Bunt: A Re-Emerging Old Foe of Wheat

Wheat (Triticum aestivum L.) crop health assumes unprecedented significance in being the second most important staple crop of the world. It is host to an array of fungal pathogens attacking the plant at different developmental stages and accrues various degrees of yield losses owing to these. Tilletia indica that causes Karnal bunt (KB) disease in wheat is one such fungal pathogen of high quarantine importance restricting the free global trade of wheat besides the loss of grain yield as well as quality. With global climate change, the disease appears to be shifting from its traditional areas of occurrence with reports of increased vulnerabilities of new areas across the continents. This KB vulnerability of new geographies is of serious concern because once established, the disease is extremely difficult to eradicate and no known instance of its complete eradication using any management strategy has been reported yet. The host resistance to KB is the most successful as well as preferred strategy for its mitigation and control. However, breeding of KB resistant wheat cultivars has proven to be not so easy, and the low success rate owes to the scarcity of resistance sources, extremely laborious and regulated field screening protocols delaying identification/validation of putative resistance sources, and complex quantitative nature of resistance with multiple genes conferring only partial resistance. Moreover, given a lack of comprehensive understanding of the KB disease epidemiology, host-pathogen interaction, and pathogen evolution. Here, in this review, we attempt to summarize the progress made and efforts underway toward a holistic understanding of the disease itself with a specific focus on the host-pathogen interaction between T. indica and wheat as key elements in the development of resistant germplasm. In this context, we emphasize the tools and techniques being utilized in development of KB resistant germplasm by illuminating upon the genetics concerning the host responses to the KB pathogen including a future course. As such, this article could act as a one stop information primer on this economically important and re-emerging old foe threatening to cause devastating impacts on food security and well-being of communities that rely on wheat.

Bioprospecting desert plant Bacillus endophytic strains for their potential to enhance plant stress tolerance

Plant growth-promoting bacteria (PGPB) are known to increase plant tolerance to several abiotic stresses, specifically those from dry and salty environments. In this study, we examined the endophyte bacterial community of five plant species growing in the Thar desert of Pakistan. Among a total of 368 culturable isolates, 58 Bacillus strains were identified from which the 16 most divergent strains were characterized for salt and heat stress resilience as well as antimicrobial and plant growth-promoting (PGP) activities. When the 16 Bacillus strains were tested on the non-host plant Arabidopsis thaliana, B. cereus PK6-15, B. subtilis PK5-26 and B. circulans PK3-109 significantly enhanced plant growth under salt stress conditions, doubling fresh weight levels when compared to uninoculated plants. B. circulans PK3-15 and PK3-109 did not promote plant growth under normal conditions, but increased plant fresh weight by more than 50% when compared to uninoculated plants under salt stress conditions, suggesting that these salt tolerant Bacillus strains exhibit PGP traits only in the presence of salt. Our data indicate that the collection of 58 plant endophytic Bacillus strains represents an important genomic resource to decipher plant growth promotion at the molecular level.