Climate change effects on Black Sigatoka disease of banana

Metal Nanoparticles Obtained by Green Hydrothermal and Solvothermal Synthesis: Characterization, Biopolymer Incorporation, and Antifungal Evaluation Against Pseudocercospora fijiensis

Nanoparticles (NPs) have generated significant interest in various fields due to the unique properties that materials exhibit at the nanoscale. This study presents a comparative analysis of copper nanoparticles (Cu-NPs) and cobalt nanoparticles (Co-NPs) synthesized via conventional solvothermal and green hydrothermal synthesis using ethylene glycol and Medicago sativa extract, respectively. The conventional solvothermal synthesis showed higher efficiency for both Cu-NPs and Co-NPs with yields of 32.5% and 26.7%, respectively. Characterization through UV-visible spectroscopy (UV-vis), Fourier-transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM) revealed that while solvothermal synthesis produced larger particles (76.5 nm for Cu-NPs, 86.8 nm for Co-NPs), the green hydrothermal method yielded smaller particles (53.8 nm for Cu-NPs, 67.7 nm for Co-NPs) with better control over particle size distribution and spherical morphology, showing minimal agglomeration. UV-vis confirmed metal oxide formation, while FTIR showed complex patterns in NPs (green hydrothermal), indicating plant extract compounds. Antifungal evaluation against Pseudocercospora fijiensis showed complete inhibition at 2000 ppm for both NP types, with no mycelial growth after 30 days. When integrated into chitosan, solvothermal NPs produced rougher surfaces, and scanning electron microscope (SEM) confirmed the presence of copper and cobalt in the nanocomposites. This study provides insights into the synthesis of nanoparticles using an environmentally friendly process and their microbiological applications for future use in organic agriculture.

Screening of Triploid Banana Population Under Natural and Controlled Black Sigatoka Disease for Genomic Selection

Black sigatoka disease (BSD) is the most important foliar threat in banana production, and breeding efforts against it should take advantage of genomic selection (GS), which has become one of the most explored tools to increase genetic gain, save time, and reduce selection costs. To evaluate the potential of GS in banana for BSD, 210 triploid accessions were obtained from the African Banana and Plantain Research Center to constitute a training population. The variability in the population was assessed at the phenotypic level using BSD- and agronomic-related traits and at the molecular level using single-nucleotide polymorphisms (SNPs). The analysis of variance showed a significant difference between accessions for almost all traits measured, although at the genomic group level, there was no significant difference for BSD-related traits. The index of non-spotted leaves among accessions ranged from 0.11 to 0.8. The accessions screening in controlled conditions confirmed the susceptibility of all genomic groups to BSD. The principal components analysis with phenotypic data revealed no clear diversity partition of the population. However, the structure analysis and the hierarchical clustering analysis with SNPs grouped the population into four clusters and two subpopulations, respectively. The field and laboratory screening of the banana GS training population confirmed that all genomic groups are susceptible to BSD but did not reveal any genetic structure, whereas SNP markers exhibited clear genetic structure and provided useful information in the perspective of applying GS.

Global warming significantly increases the risk of Pierce's disease epidemics in European vineyards

Pierce's disease (PD) is a vector-borne disease caused by the bacteria Xylella fastidiosa, which affects grapevines in the Americas. Currently, vineyards in continental Europe, the world's largest producer of quality wine, have not yet been affected by PD. However, climate change may alter this situation. Here we incorporate the latest regional climate change projections into a climate-driven epidemiological model to assess the risk of PD epidemics in Europe for different levels of global warming. We found a significant increase in risk above + 2 ∘ C in the main wine-producing regions of France, Italy and Portugal, in addition to a critical tipping point above + 3 ∘ C for the possible spread of PD beyond the Mediterranean. The model identifies decreasing risk trends in Spain, as well as contrasting patterns across the continent with different velocities of risk change and epidemic growth rates. Although there is some uncertainty in model projections over time, spatial patterns of risk are consistent across different climate models. Our study provides a comprehensive analysis of the future of PD at multiple spatial scales (country, Protected Designation of Origin and vineyard), revealing where, why and when PD could become a new threat to the European wine industry.

Smallholder farmer resilience to extreme weather events in a global food value chain

Extreme weather events have severe impacts on food systems, especially for smallholders in global food value chains (GFVCs). There is an urgent need to understand (a) how climate shocks manifest in food systems, and (b) what strategies can enhance food system resilience. Integrating satellite, household and trade data, we investigate the cascading impacts after two consecutive hurricanes on smallholder banana farmers in Dominican Republic, and determinants of their recovery. We found that farmers experienced an 'all-or-nothing' pattern of damage, where 75% of flooded farmers lost > 90% of production. Recovery of regional production indicators took ca. 450 days. However, farm-level recovery times were highly variable, with both topographic and human capital factors determining recovery. Utilising this case study, we show that engaging in a GFVC impeded recovery via 'double exposure' of production loss and losing market access. Our results suggest that strategies to enhance resilience, with a particular focus on recovery, in GFVCs should promote trader loyalty, facilitate basin-scale collaboration and expand risk-targeted training.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10584-023-03586-1.

Mitigating the repercussions of climate change on diseases affecting important crop commodities in Southeast Asia, for food security and environmental sustainability—A review

Southeast Asia is a fertile land with a warm and humid climate which tends to accommodate various food crops. The development and advancement of the agricultural sector not only allows the countries in the region to feed the increasing population, but are also able to boost the nation's economy through exportation of the crops. Some of the well-known and economically-significant plant commodities found in the region include rice, oil palm, rubber, coconut, banana, sugarcane, pineapple, black pepper, maize, cocoa, durian, and jackfruit. Due to the high production of crops, Southeast Asia is able to stand among the top world producers of these commodities. Nevertheless, the widespread of pathogenic microorganisms has posed a serious threat to the industry over the years; with hundreds of millions of money wasted and total yield being lost due to the devastating diseases associated with each type of the plants. A lot of attention and effort have been continuously devoted to find effective plant management strategies to combat plant diseases, starting from traditional physical and chemical methods to the increasing discoveries on biological approaches made in recent decades. Due to the challenges and limitations faced by conventional approaches and the rising awareness toward the environment, more work has been focused on establishing the application of beneficial microorganisms to tackle plant diseases through direct mechanisms. Thus, by bringing the common plant commodities in Southeast Asia, their associated diseases and various physical, chemical and biological control measures together, this review aims to provide clearer insights and practical information to those who seek to limit the damages caused by plant diseases.

High level of somatic mutations detected in a diploid banana wild relative Musa basjoo

Plants are thought to lack an early segregating germline and often retain both asexual and sexual reproduction, both of which may allow somatic mutations to enter the gametes or clonal progeny, and thereby impact plant evolution. It is yet unclear how often these somatic mutations occur during plant development and what proportion is transmitted to their sexual or cloned offspring. Asexual "seedless" propagation has contributed greatly to the breeding in many fruit crops, such as citrus, grapes and bananas. Whether plants in these lineages experience substantial somatic mutation accumulation is unknown. To estimate the somatic mutation accumulation and inheritance among a clonal population of plant, here we assess somatic mutation accumulation in Musa basjoo, a diploid banana wild relative, using 30 whole-genome resequenced samples collected from five structures, including leaves, sheaths, panicle, roots and underground rhizome connecting three clonal individuals. We observed 18.5 high proportion de novo somatic mutations on average between each two adjacent clonal suckers, equivalent to ~ 2.48 × 10^-8 per site per asexual generation, higher than the per site per sexual generation rates (< 1 × 10^-8) reported in Arabidopsis and peach. Interestingly, most of these inter-ramet somatic mutations were shared simultaneously in different tissues of the same individual with a high level of variant allele fractions, suggesting that these somatic mutations arise early in ramet development and that each individual may develop only from a few apical stem cells. These results thus suggest substantial mutation accumulation in a wild relative of banana. Our work reveals the significance of somatic mutation in Musa basjoo genetics variations and contribute to the trait improvement breeding of bananas and other asexual clonal crops.

Disentangling the Factors Affecting the Dynamic of Pseudocercospora fijiensis: Quantification of Weather, Fungicide, and Landscape Effects

Quantifying the effect of landscape composition on disease dynamics remains challenging because it depends on many factors. In this study, we used a hybrid process-based/statistical modeling approach to separate the effect of the landscape composition on the epidemiology of banana leaf streak disease (BLSD) from weather and fungicide effects. We parameterized our model with a 5-year dataset, including weekly measures of BLSD on 83 plots in Martinique. After estimating the intrinsic growth parameters of the stage evolution of the disease (SED), we evaluated the dynamic effect of five fungicides. Then, we added the intra- and inter-annual effect on disease dynamics using a generalized linear model. Finally, the whole model was used to assess the annual effect of the landscape on the SED for 11 plots. We evaluated the significance of the landscape composition (proportions of landscape elements in 200-, 500-, 800-, 1,000-m-radius buffer zones) on the landscape effect evaluated with the model. The percentage of hedgerows in a 200-m-radius buffer zone was negatively correlated to the landscape effect, i.e., it acted as a constraint against BLSD spreading and development. The proportion of managed-banana-plants in a 1,000-m-radius buffer zone was negatively correlated to the landscape effect, probably due to a mass effect of fungicide treatments. Inversely, the proportions of forest and the proportion of unmanaged-banana-plants, both in 1,000-m-radius buffer zones, were positively correlated with the landscape effect. Our study provides a holistic approach of the role biotic and abiotic factors play on the dynamics of BLSD.

Climate change and plant pathogens

Global food security is threatened by climate change, both directly through responses of crop physiology and productivity, and indirectly through responses of plant-associated microbiota, including plant pathogens. While the interactions between host plants, pathogens and environmental drivers can be complex, recent research is beginning to indicate certain overall patterns in how plant diseases will affect crop production in future. Here, we review the results of three methodological approaches: large-scale observational studies, process-based disease models and experimental comparisons of pathosystems under current and future conditions. We find that observational studies have tended to identify rising temperatures as the primary driver of disease impact. Process-based models suggest that rising temperatures will lead to latitudinal shifts in disease pressure, but drying conditions could mitigate disease risk. Experimental studies suggest that rising atmospheric CO₂ will exacerbate disease impacts. Plant diseases may therefore counteract any crop yield increases due to climate change.

Prioritizing farm management interventions to improve climate change adaptation and mitigation outcomes-a case study for banana plantations

Intervening into agricultural systems necessarily includes risks, uncertainties, and ultimately unknown outcomes. Decision analysis embraces uncertainty through an interdisciplinary approach that involves relevant stakeholders in evaluating complex decisions. We applied decision analysis approaches to prioritize 21 farm management interventions, which could be considered in certification schemes for banana production. We estimated their contribution to climate change adaptation and mitigation as well as ecological outcomes. We used a general model that estimated the impacts of each intervention on adaptation (benefits minus costs), mitigation (global warming potential), ecological parameters (e.g., biodiversity and water and soil quality), and farming aspects (e.g., yield, implementation costs and production risks). We used expert and documented knowledge and presented uncertainties in the form of 90% confidence intervals to feed the model and forecast the changes in system outcomes caused by each intervention compared to a baseline scenario without the measure. By iterating the model function 10,000 times, we obtained probability distributions for each of the outcomes and farm management interventions. Our results suggest that interventions associated with nutrient management (e.g., composting and nutrient management plan) positively affect climate change adaptation, mitigation, and ecological aspects. Measures with no direct yield benefits (e.g., plastic reduction) correlate negatively with adaptation but have positive impacts on ecology. Creating buffer zones and converting low-productivity farmland (incl. unused land) also have positive ecological and adaptation outcomes. Decision analysis can help in prioritizing farm management interventions, which may vary considerably in their relationship with the expected outcomes. Additional work may be required to elaborate a comprehensive assessment of the underlying aspects modulating the impacts of a given measure on the evaluated outcome. Our analysis provides insights on the most promising interventions for banana plantations and may help practitioners and researchers in focusing further studies.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13593-022-00809-0.

Subterranean Microbiome Affiliations of Plantain (Musa spp.) Under Diverse Agroecologies of Western and Central Africa

Plantain (Musa spp.) is a staple food crop and an important source of income for millions of smallholder farmers in sub-Saharan Africa (SSA). However, there is a paucity of knowledge on soil microbial diversity in agroecologies where plantains are grown. Microbial diversity that increases plant performance with multi-trophic interactions involving resiliency to environmental constraints is greatly needed. For this purpose, the bacterial and fungal communities of plantain fields in high rainfall forests (HR) and derived savannas (SV) were studied using Illumina MiSeq for 16S rDNA and ITS amplicon deep sequencing. Microbial richness (α- and β-diversity), operational taxonomic units, and Simpson and Shannon-Wiener indexes (observed species (Sobs), Chao, ACE; P < 0.05) suggested that there were significant differences between HR and SV agroecologies among the most abundant bacterial communities, and some specific dynamic response observed from fungal communities. Proteobacteria formed the predominant bacterial phylum (43.7%) succeeded by Firmicutes (24.7%), and Bacteroidetes (17.6%). Ascomycota, Basidiomycota, and Zygomycota were the three most dominant fungal phyla in both agroecologies. The results also revealed an immense array of beneficial microbes in the roots and rhizosphere of plantain, including Acinetobacter, Bacillus, and Pseudomonas spp. COG and KEGG Orthology database depicted significant variations in the functional attributes of microbes found in the rhizosphere to roots. This result indicates that the different agroecologies and host habitats differentially support the dynamic microbial profile and that helps in altering the structure in the rhizosphere zone for the sake of promoting synergistic host-microbe interactions particularly under resource-poor conditions of SSA.

Gene Expression, Histology and Histochemistry in the Interaction between Musa sp. and Pseudocercospora fijiensis

Bananas are the main fruits responsible for feeding more than 500 million people in tropical and subtropical countries. Black Sigatoka, caused by the fungus Pseudocercospora fijiensis, is one of the most destructive disease for the crop. This fungus is mainly controlled with the use of fungicides; however, in addition to being harmful to human health, they are associated with a high cost. The development of resistant cultivars through crosses of susceptible commercial cultivars is one of the main focuses of banana breeding programs worldwide. Thus, the objective of the present study was to investigate the interaction between Musa sp. and P. fijiensis through the relative expression of candidate genes involved in the defence response to black Sigatoka in four contrasting genotypes (resistant: Calcutta 4 and Krasan Saichon; susceptible: Grand Naine and Akondro Mainty) using quantitative real-time PCR (RT-qPCR) in addition to histological and histochemical analyses to verify the defence mechanisms activated during the interaction. Differentially expressed genes (DEGs) related to the jasmonic acid and ethylene signalling pathway, GDSL-like lipases and pathogenesis-related proteins (PR-4), were identified. The number and distance between stomata were directly related to the resistance/susceptibility of each genotype. Histochemical tests showed the production of phenolic compounds and callosis as defence mechanisms activated by the resistant genotypes during the interaction process. Scanning electron microscopy (SEM) showed pathogenic structures on the leaf surface in addition to calcium oxalate crystals. The resistant genotype Krasan Saichon stood out in the analyses and has potential for use in breeding programs for resistance to black Sigatoka in banana and plantains.

Detection of Banana Mild Mosaic Virus in Musa In Vitro Plants: High-Throughput Sequencing Presents Higher Diagnostic Sensitivity Than (IC)-RT-PCR and Identifies a New Betaflexiviridae Species

The banana mild mosaic virus (BanMMV) (Betaflexiviridae, Quinvirinae, unassigned species) is a filamentous virus that infects Musa spp. and has a very wide geographical distribution. The current BanMMV indexing process for an accession requires the testing of no less than four plants cultivated in a greenhouse for at least 6 months and causes a significant delay for the distribution of the germplasm. We evaluated the sensitivity of different protocols for BanMMV detection from in vitro plants to accelerate the testing process. We first used corm tissues from 137 in vitro plants and obtained a diagnostic sensitivity (DSE) of only 61% when testing four plants per accession. After thermotherapy was carried out to eliminate BanMMV infection, the meristem was recovered and further grown in vitro. The same protocol was evaluated in parallel on the corm tissue surrounding the meristem, as a rapid screening to evaluate virus therapy success, and was compared to the results obtained following the standard protocol. The obtained results showed 28% false negatives when conducting testing from corm tissues, making this protocol unsuitable in routine processes. Furthermore, RT-PCR and high-throughput sequencing (HTS) tests were applied on tissues from the base (n = 39) and the leaves (n = 36). For RT-PCR, the average DSE per sample reached 65% from either the base or leaves. HTS was applied on 36 samples and yielded 100% diagnostic specificity (DSP) and 100% DSE, whatever the sampled tissue, allowing the identification of a new Betaflexiviridae species infecting Musa. These results suggest that a reliable diagnostic of BanMMV from in vitro plants using RT-PCR or HTS technologies might represent an efficient alternative for testing after greenhouse cultivation.

Comprehensive account of present techniques for in-field plant disease diagnosis

The early detection of plant pathogens is an appropriate preventive strategy for the management of crop yield and quality. For this reason, effective diagnostic techniques and tools, which are simple, specific, rapid and economic, are needed to be developed. Although several such technologies have been developed still most of them suffer one or the other limitation. Major limitations of the widely used diagnostic methods are requirement of trained staff and laboratory setup. Development of point-of-care diagnostic devices (handy portable devices) that require no specialized staff and can directly be used in fields is need of the hour. The aim of this review is to compile the information on current promising techniques that are in use for plant-pathogen diagnosis. Additionally, it focuses on the latest in-field pathogen diagnostic techniques with associated advantages and limitations.

Nonlinear shifts in infectious rust disease due to climate change

Range shifts of infectious plant disease are expected under climate change. As plant diseases move, emergent abiotic-biotic interactions are predicted to modify their distributions, leading to unexpected changes in disease risk. Evidence of these complex range shifts due to climate change, however, remains largely speculative. Here, we combine a long-term study of the infectious tree disease, white pine blister rust, with a six-year field assessment of drought-disease interactions in the southern Sierra Nevada. We find that climate change between 1996 and 2016 moved the climate optimum of the disease into higher elevations. The nonlinear climate change-disease relationship contributed to an estimated 5.5 (4.4-6.6) percentage points (p.p.) decline in disease prevalence in arid regions and an estimated 6.8 (5.8-7.9) p.p. increase in colder regions. Though climate change likely expanded the suitable area for blister rust by 777.9 (1.0-1392.9) km² into previously inhospitable regions, the combination of host-pathogen and drought-disease interactions contributed to a substantial decrease (32.79%) in mean disease prevalence between surveys. Specifically, declining alternate host abundance suppressed infection probabilities at high elevations, even as climatic conditions became more suitable. Further, drought-disease interactions varied in strength and direction across an aridity gradient-likely decreasing infection risk at low elevations while simultaneously increasing infection risk at high elevations. These results highlight the critical role of aridity in modifying host-pathogen-drought interactions. Variation in aridity across topographic gradients can strongly mediate plant disease range shifts in response to climate change.

Genetic Improvement for Resistance to Black Sigatoka in Bananas: A Systematic Review

Bananas are an important staple food crop in tropical and subtropical regions in Asia, sub-Saharan Africa, and Central and South America. The plant is affected by numerous diseases, with the fungal leaf disease black Sigatoka, caused by Mycosphaerella fijiensis Morelet [anamorph: Pseudocercospora fijiensis (Morelet) Deighton], considered one of the most economically important phytosanitary problem. Although the development of resistant cultivars is recognized as most effective method for long term control of the disease, the majority of today's cultivars are susceptible. In order to gain insights into this pathosystem, this first systematic literature review on the topic is presented. Utilizing six databases (PubMed Central, Web of Science, Google Academic, Springer, CAPES and Scopus Journals) searches were performed using pre-established inclusion and exclusion criteria. From a total of 3,070 published studies examined, 24 were relevant with regard to the Musa-P. fijiensis pathosystem. Relevant papers highlighted that resistant and susceptible cultivars clearly respond differently to infection by this pathogen. M. acuminata wild diploids such as Calcutta 4 and other diploid cultivars can harbor sources of resistance genes, serving as parentals for the generation of improved diploids and subsequent gene introgression in new cultivars. From the sequenced reference genome of Musa acuminata, although the function of many genes in the genome still require validation, on the basis of transcriptome, proteome and biochemical data, numerous candidate genes and molecules have been identified for further evaluation through genetic transformation and gene editing approaches. Genes identified in the resistance response have included those associated with jasmonic acid and ethylene signaling, transcription factors, phenylpropanoid pathways, antioxidants and pathogenesis-related proteins. Papers in this study also revealed gene-derived markers in Musa applicable for downstream application in marker assisted selection. The information gathered in this review furthers understanding of the immune response in Musa to the pathogen P. fijiensis and is relevant for genetic improvement programs for bananas and plantains for control of black Sigatoka.

Unlocking the inherent potential of plant genetic resources: food security and climate adaptation strategy in Fiji and the Pacific

Pacific Island Countries (PICs) are the center of origin and diversity for several root, fruit and nut crops, which are indispensable for food security, rural livelihoods, and cultural identity of local communities. However, declining genetic diversity of traditional food crops and high vulnerability to climate change are major impediments for maintaining agricultural productivity. Limited initiatives to achieve food self-sufficiency and utilization of Plant Genetic Resources (PGR) for enhancing resilience of agro-ecosystems are other serious constraints. This review focuses on the visible and anticipated impacts of climate ge, on major food and tree crops in agriculture and agroforestry systems in the PICs. We argue that crop improvement through plant breeding is a viable strategy to enhance food security and climatic resilience in the region. The exploitation of adaptive traits: abiotic and biotic stress tolerance, yield and nutritional efficiency, is imperative in a world threatened by climatic extremes. However, the insular constraints of Fiji and other small PICs are major limitations for the utilization of PGR through high throughput techniques which are also cost prohibitive. Crop Improvement programs should instead focus on the identification, conservation, documentation and dissemination of information on unique landraces, community seed banks, introduction of new resistant genotypes, and sustaining and enhancing allelic diversity.

What is the elephant in the room when considering new therapies for fungal diseases?

The global scenario of antimicrobial resistance is alarming, and the development of new drugs has not appeared to make substantial progress. The constraints on drug discovery are due to difficulties in finding new targets for therapy, the high cost of development, and the mismatch between the time of drug introduction in a clinic and microorganism adaptation to a drug. Policies to address neglected diseases miss the broad spectrum of mycosis. Society is not aware of the actual threat represented by fungi to human health, food security, and biodiversity. The evidence discussed here is critical for warning governments to establish effective surveillance policies for fungi.HIGHLIGHTSFungal diseases are ignored even among neglected disease classifications.There are few options to treat mycoses, which is an increasing concern regarding fungal resistance to drugs, as evidenced by the spread of Candida auris.Fungal diseases represent a real threat to human health and food security.Investment in research to investigate the potential of repurposing drugs already in use could obtain results in the short term.

Preface to theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'

This preface forms part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.