1
|
Gutiérrez-Sánchez Á, Cobos A, López-Herranz M, Canto T, Pagán I. Environmental Conditions Modulate Plant Virus Vertical Transmission and Survival of Infected Seeds. PHYTOPATHOLOGY 2023; 113:1773-1787. [PMID: 36880795 DOI: 10.1094/phyto-11-22-0448-v] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Seed transmission is a major mode for plant virus persistence and dispersal, as it allows for virus survival within the seed in unfavorable conditions and facilitates spread when they become more favorable. To access these benefits, viruses require infected seeds to remain viable and germinate in altered environmental conditions, which may also be advantageous for the plant. However, how environmental conditions and virus infection affect seed viability, and whether these effects modulate seed transmission rate and plant fitness, is unknown. To address these questions, we utilized turnip mosaic virus, cucumber mosaic virus, and Arabidopsis thaliana as model systems. Using seeds from plants infected by these viruses, we analyzed seed germination rates, as a proxy of seed viability, and virus seed transmission rate under standard and altered temperature, CO2, and light intensity. With these data, we developed and parameterized a mathematical epidemiological model to explore the consequences of the observed alterations on virus prevalence and persistence. Altered conditions generally reduced overall seed viability and increased virus transmission rate compared with standard conditions, which indicated that under environmental stress, infected seeds are more viable. Hence, virus presence may be beneficial for the host. Subsequent simulations predicted that enhanced viability of infected seeds and higher virus transmission rate may increase virus prevalence and persistence in the host population under altered conditions. This work provides novel information on the influence of the environment in plant virus epidemics. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Collapse
Affiliation(s)
- Álvaro Gutiérrez-Sánchez
- Centro de Biotecnología y Genómica de Plantas UPM-INIA and E.T.S. Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, 28223, Spain
| | - Alberto Cobos
- Centro de Biotecnología y Genómica de Plantas UPM-INIA and E.T.S. Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, 28223, Spain
| | - Marisa López-Herranz
- Centro de Biotecnología y Genómica de Plantas UPM-INIA and E.T.S. Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, 28223, Spain
| | - Tomás Canto
- Departamento de Biología Medioambiental, Centro de Investigaciones Biológicas, CSIC, Madrid, 28040, Spain
| | - Israel Pagán
- Centro de Biotecnología y Genómica de Plantas UPM-INIA and E.T.S. Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, 28223, Spain
| |
Collapse
|
2
|
Jeger M, Hamelin F, Cunniffe N. Emerging Themes and Approaches in Plant Virus Epidemiology. PHYTOPATHOLOGY 2023; 113:1630-1646. [PMID: 36647183 DOI: 10.1094/phyto-10-22-0378-v] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.
Collapse
Affiliation(s)
- Mike Jeger
- Department of Life Sciences, Imperial College London, Silwood Park, U.K
| | - Fred Hamelin
- IGEPP INRAE, University of Rennes, Rennes, France
| | - Nik Cunniffe
- Department of Plant Sciences, University of Cambridge, Cambridge, U.K
| |
Collapse
|
3
|
Alcalá Briseño RI, Batuman O, Brawner J, Cuellar WJ, Delaquis E, Etherton BA, French-Monar RD, Kreuze JF, Navarrete I, Ogero K, Plex Sulá AI, Yilmaz S, Garrett KA. Translating virome analyses to support biosecurity, on-farm management, and crop breeding. FRONTIERS IN PLANT SCIENCE 2023; 14:1056603. [PMID: 36998684 PMCID: PMC10043385 DOI: 10.3389/fpls.2023.1056603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 02/14/2023] [Indexed: 06/19/2023]
Abstract
Virome analysis via high-throughput sequencing (HTS) allows rapid and massive virus identification and diagnoses, expanding our focus from individual samples to the ecological distribution of viruses in agroecological landscapes. Decreases in sequencing costs combined with technological advances, such as automation and robotics, allow for efficient processing and analysis of numerous samples in plant disease clinics, tissue culture laboratories, and breeding programs. There are many opportunities for translating virome analysis to support plant health. For example, virome analysis can be employed in the development of biosecurity strategies and policies, including the implementation of virome risk assessments to support regulation and reduce the movement of infected plant material. A challenge is to identify which new viruses discovered through HTS require regulation and which can be allowed to move in germplasm and trade. On-farm management strategies can incorporate information from high-throughput surveillance, monitoring for new and known viruses across scales, to rapidly identify important agricultural viruses and understand their abundance and spread. Virome indexing programs can be used to generate clean germplasm and seed, crucial for the maintenance of seed system production and health, particularly in vegetatively propagated crops such as roots, tubers, and bananas. Virome analysis in breeding programs can provide insight into virus expression levels by generating relative abundance data, aiding in breeding cultivars resistant, or at least tolerant, to viruses. The integration of network analysis and machine learning techniques can facilitate designing and implementing management strategies, using novel forms of information to provide a scalable, replicable, and practical approach to developing management strategies for viromes. In the long run, these management strategies will be designed by generating sequence databases and building on the foundation of pre-existing knowledge about virus taxonomy, distribution, and host range. In conclusion, virome analysis will support the early adoption and implementation of integrated control strategies, impacting global markets, reducing the risk of introducing novel viruses, and limiting virus spread. The effective translation of virome analysis depends on capacity building to make benefits available globally.
Collapse
Affiliation(s)
- Ricardo I. Alcalá Briseño
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
- Plant Pathology Department, Oregon State University, Corvallis, OR, United States
| | - Ozgur Batuman
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Southwest Florida Research and Education Center (SWFREC), Immokalee, FL, United States
| | - Jeremy Brawner
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
| | - Wilmer J. Cuellar
- International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Erik Delaquis
- International Center for Tropical Agriculture (CIAT), Vientiane, Laos
| | - Berea A. Etherton
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
| | | | - Jan F. Kreuze
- Crop and System Sciences Division, International Potato Center (CIP), Lima, Peru
| | - Israel Navarrete
- Crop and System Sciences Division, International Potato Center (CIP), Quito, Ecuador
| | - Kwame Ogero
- Crop and System Sciences Division, International Potato Center (CIP), Mwanza, Tanzania
| | - Aaron I. Plex Sulá
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
| | - Salih Yilmaz
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Southwest Florida Research and Education Center (SWFREC), Immokalee, FL, United States
| | - Karen A. Garrett
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
| |
Collapse
|
4
|
Lovell-Read FA, Parnell S, Cunniffe NJ, Thompson RN. Using 'sentinel' plants to improve early detection of invasive plant pathogens. PLoS Comput Biol 2023; 19:e1010884. [PMID: 36730434 PMCID: PMC9928126 DOI: 10.1371/journal.pcbi.1010884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/14/2023] [Accepted: 01/18/2023] [Indexed: 02/04/2023] Open
Abstract
Infectious diseases of plants present an ongoing and increasing threat to international biosecurity, with wide-ranging implications. An important challenge in plant disease management is achieving early detection of invading pathogens, which requires effective surveillance through the implementation of appropriate monitoring programmes. However, when monitoring relies on visual inspection as a means of detection, surveillance is often hindered by a long incubation period (delay from infection to symptom onset) during which plants may be infectious but not displaying visible symptoms. 'Sentinel' plants-alternative susceptible host species that display visible symptoms of infection more rapidly-could be introduced to at-risk populations and included in monitoring programmes to act as early warning beacons for infection. However, while sentinel hosts exhibit faster disease progression and so allow pathogens to be detected earlier, this often comes at a cost: faster disease progression typically promotes earlier onward transmission. Here, we construct a computational model of pathogen transmission to explore this trade-off and investigate how including sentinel plants in monitoring programmes could facilitate earlier detection of invasive plant pathogens. Using Xylella fastidiosa infection in Olea europaea (European olive) as a current high profile case study, for which Catharanthus roseus (Madagascan periwinkle) is a candidate sentinel host, we apply a Bayesian optimisation algorithm to determine the optimal number of sentinel hosts to introduce for a given sampling effort, as well as the optimal division of limited surveillance resources between crop and sentinel plants. Our results demonstrate that including sentinel plants in monitoring programmes can reduce the expected prevalence of infection upon outbreak detection substantially, increasing the feasibility of local outbreak containment.
Collapse
Affiliation(s)
| | - Stephen Parnell
- Warwick Crop Centre, School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Nik J. Cunniffe
- Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
| | - Robin N. Thompson
- Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| |
Collapse
|
5
|
Biswal AK, Alakonya AE, Mottaleb KA, Hearne SJ, Sonder K, Molnar TL, Jones AM, Pixley KV, Prasanna BM. Maize Lethal Necrosis disease: review of molecular and genetic resistance mechanisms, socio-economic impacts, and mitigation strategies in sub-Saharan Africa. BMC PLANT BIOLOGY 2022; 22:542. [PMID: 36418954 PMCID: PMC9686106 DOI: 10.1186/s12870-022-03932-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Maize lethal necrosis (MLN) disease is a significant constraint for maize producers in sub-Saharan Africa (SSA). The disease decimates the maize crop, in some cases, causing total crop failure with far-reaching impacts on regional food security. RESULTS In this review, we analyze the impacts of MLN in Africa, finding that resource-poor farmers and consumers are the most vulnerable populations. We examine the molecular mechanism of MLN virus transmission, role of vectors and host plant resistance identifying a range of potential opportunities for genetic and phytosanitary interventions to control MLN. We discuss the likely exacerbating effects of climate change on the MLN menace and describe a sobering example of negative genetic association between tolerance to heat/drought and susceptibility to viral infection. We also review role of microRNAs in host plant response to MLN causing viruses as well as heat/drought stress that can be carefully engineered to develop resistant varieties using novel molecular techniques. CONCLUSIONS With the dual drivers of increased crop loss due to MLN and increased demand of maize for food, the development and deployment of simple and safe technologies, like resistant cultivars developed through accelerated breeding or emerging gene editing technologies, will have substantial positive impact on livelihoods in the region. We have summarized the available genetic resources and identified a few large-effect QTLs that can be further exploited to accelerate conversion of existing farmer-preferred varieties into resistant cultivars.
Collapse
Affiliation(s)
- Akshaya Kumar Biswal
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico.
| | - Amos Emitati Alakonya
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Khondokar Abdul Mottaleb
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Kai Sonder
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | | | - Alan M Jones
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kevin Vail Pixley
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | | |
Collapse
|
6
|
Zhang C, Wang D, Li W, Zhang B, Abdel-Fattah Ouf GM, Su X, Li J. The coat protein p25 from maize chlorotic mottle virus involved in symptom development and systemic movement of tobacco mosaic virus hybrids. Front Microbiol 2022; 13:951479. [PMID: 35992724 PMCID: PMC9389212 DOI: 10.3389/fmicb.2022.951479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/14/2022] [Indexed: 11/13/2022] Open
Abstract
Viral coat protein (CP) has numerous critical functions in plant infection, but little is known about p25, the CP of maize chlorotic mottle virus (MCMV; Machlomovirus), which causes severe yield losses in maize worldwide. Here, we investigated the roles of p25 in pathogenicity and systemic movement, as well as potential interactions with host plants, using a hybrid tobacco mosaic virus (TMV)-based expression system. Highly conserved protein p25 is predicted to contain a membrane-anchored nuclear localization signal (NLS) sequence and an extracellular sequence. In transgenic Nicotiana benthamiana plants containing the movement protein (MP) of TMV (TMV-MP), p25 induced severe symptoms, including dwarf and foliar necrosis, and was detected in inoculated and non-inoculated leaves. After the deletion of NLS from nuclear-located p25, the protein was found throughout the host cell, and plant stunting and starch granule deformity were reduced. Systemic movement and pathogenicity were significantly impaired when the C-terminal regions of p25 were absent. Using virus-induced gene silencing (VIGS), the transcript level of heat shock protein HSP90 was distinctly lower in host plants in association with the absence of leaf necrosis induced by TMV-p25. Our results revealed crucial roles for MCMV p25 in viral pathogenicity, long-distance movement, and interactions with N. benthamiana.
Collapse
Affiliation(s)
- Chao Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, College of Life Sciences, Hebei Agricultural University, Baoding, China
| | - Di Wang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Weimin Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Baolong Zhang
- Excellence and Innovation Center, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Gamal M. Abdel-Fattah Ouf
- Department of Botany and Applied Microbiology, Faculty of Science, Mansoura University, Mansoura, Egypt
| | - Xiaofeng Su
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jun Li
- State Key Laboratory of North China Crop Improvement and Regulation, College of Life Sciences, Hebei Agricultural University, Baoding, China
| |
Collapse
|
7
|
Yadav S, Kumar V. A prey–predator model approach to increase the production of crops: Mathematical modeling and qualitative analysis. INT J BIOMATH 2022. [DOI: 10.1142/s1793524522500425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This paper expresses the concepts, methods, and applications of mathematical models in agriculture. We propose and analyze an ecosystem consisting of two types of preys and their predators; here the prey-I like sugarcane crops that take a long time to grow and prey-II like vegetables, which have a short life, are grown with sugarcane crops and predators that harm both prey-I and prey-II. The various equilibria of the system are obtained, and the stability conditions are analyzed. Furthermore, a comprehensive analysis of the optimal control strategy is also performed. The optimal control model includes the use of three control variables, such as pesticide application rate, biomass application rate, and control of Cassava mosaic virus in the system. Finally, we apply Pontryagin’s maximum principle to find the optimal control. Furthermore, analytical results are verified by numerical simulations.
Collapse
Affiliation(s)
- Sudhakar Yadav
- Department of Applied Mathematics, Delhi Technological University, New Delhi 110042, India
| | - Vivek Kumar
- Department of Applied Mathematics, Delhi Technological University, New Delhi 110042, India
| |
Collapse
|
8
|
Maity S, Mandal PS. A Comparison of Deterministic and Stochastic Plant-Vector-Virus Models Based on Probability of Disease Extinction and Outbreak. Bull Math Biol 2022; 84:41. [PMID: 35150332 DOI: 10.1007/s11538-022-01001-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 01/24/2022] [Indexed: 11/02/2022]
Abstract
In this investigation, we formulate and analyse a stochastic epidemic model using the continuous-time Markov chain model for the propagation of a vector-borne cassava mosaic disease in a single population. The stochastic model is based upon a pre-existing deterministic plant-vector-virus model. To see how demographic stochasticity affects the vector-borne cassava mosaic disease dynamics, we compare the disease dynamics of both deterministic and stochastic models through disease extinction process. The probability of disease extinction and therefore the major outbreak are estimated analytically using the multitype Galton-Watson branching process (GWbp) approximation. Also, we have found the approximate probabilities of disease extinction numerically based on 30000 sample paths, and it is shown to be good estimate with the calculated probabilities from GWbp approximation. In particular, it is observed that there is a very high probability of disease extinction when the disease is introduced via the infected vectors rather than through infected plants.
Collapse
Affiliation(s)
- Sunil Maity
- Department of Mathematics, NIT Patna, Patna, Bihar, India
| | | |
Collapse
|
9
|
Cunniffe NJ, Taylor NP, Hamelin FM, Jeger MJ. Epidemiological and ecological consequences of virus manipulation of host and vector in plant virus transmission. PLoS Comput Biol 2021; 17:e1009759. [PMID: 34968387 PMCID: PMC8754348 DOI: 10.1371/journal.pcbi.1009759] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/12/2022] [Accepted: 12/15/2021] [Indexed: 12/25/2022] Open
Abstract
Many plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector’s own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding–as well as potential effects of infection on vector population density–on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics. Plant virus diseases–which cause devastating epidemics in plant populations worldwide–are most often transmitted by insect vectors. Recent experimental evidence indicates how vectors do not choose between plants at random, but instead can be affected by whether plants are infected (or not). Virus infection can cause plants to “smell” different, because they produce different combinations of volatile chemicals, or “taste” different, due to chemical changes in infected tissues. Vector reproduction rates can also be affected when colonising infected versus uninfected plants. Potential effects on epidemic spread through a population of plants are not yet entirely understood. There are also interactions with the mode of virus transmission. Some viruses can be transmitted after only a brief probe by a vector, whereas others are only picked up after an extended feed on an infected plant. Furthermore there are differences in how long vectors remain able to transmit the virus. This ranges from a matter of minutes, right up to the entire lifetime of the insect, depending on the plant-virus-vector combination under consideration. Here we use mathematical modelling to synthesise all this complexity into a coherent theoretical framework. We illustrate our model via an online interface https://plantdiseasevectorpreference.herokuapp.com/.
Collapse
Affiliation(s)
- Nik J. Cunniffe
- Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
- * E-mail:
| | - Nick P. Taylor
- Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
| | | | - Michael J. Jeger
- Department of Life Sciences, Imperial College London, Ascot, United Kingdom
| |
Collapse
|
10
|
De Groote H, Munyua BG, Palmas S, Suresh LM, Bruce AY, Kimenju S. Using Panel Community Surveys to Track the Impact of Crop Pests Over Time and Space - The Case of Maize Lethal Necrosis (MLN) Disease in Kenya from 2013 to 2018. PLANT DISEASE 2021; 105:1259-1271. [PMID: 33289406 DOI: 10.1094/pdis-08-20-1730-sr] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Maize lethal necrosis (MLN) disease appeared in Kenya in 2011, causing major damage. In a first survey of 121 communities in 2013, participants estimated the proportion of households affected and the yield loss in affected areas; from this survey, the overall loss was estimated at 22%, concentrated in western Kenya (94%). Efforts to combat the disease included planting resistant varieties, creating awareness of MLN management, and producing pathogen-free seed. In 2018, the same communities were revisited and asked the same questions, establishing a panel community survey. The results showed that incidents of MLN had greatly decreased, and the number of communities that had observed it had reduced from 76% in 2013 to 26% by the long rains of 2018; while still common in western Kenya (60%), MLN had greatly reduced elsewhere (to 10%). In 2013, 40% of farmers were affected, yield loss among affected farmers was estimated at 44%, and total yield loss was estimated at 22% (a production loss of 0.5 million metric tons/year), valued at US$187 million. By the long rains of 2018, 23% of farmers were affected, with a loss among affected farmers of 36%; overall annual loss was estimated at 8.5% or 0.37 million metric tons, valued at US$109 million, concentrated in western Kenya (79%). Of the recommended control measures, only the removal of diseased plants was commonly used (by 62% of affected communities), but not the use of agronomic practices (11%) or resistant varieties (9.5%). The reasons for the reduction in MLN are not well understood; external factors such as spraying insecticide against fall armyworm and unfavorable weather likely played a role, as did using disease-free seed, but not the use of resistant varieties or appropriate management practices. Still, as the pathogen remains in the fields, it is important to keep disseminating these control methods, particularly resistant varieties.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Collapse
Affiliation(s)
- Hugo De Groote
- International Maize and Wheat Improvement Centre (CIMMYT), PO Box 2041-00621, Nairobi, Kenya
| | - Bernard G Munyua
- International Maize and Wheat Improvement Centre (CIMMYT), PO Box 2041-00621, Nairobi, Kenya
| | - Sebastian Palmas
- International Maize and Wheat Improvement Centre (CIMMYT), PO Box 2041-00621, Nairobi, Kenya
| | - L M Suresh
- International Maize and Wheat Improvement Centre (CIMMYT), PO Box 2041-00621, Nairobi, Kenya
| | - Anani Y Bruce
- International Maize and Wheat Improvement Centre (CIMMYT), PO Box 2041-00621, Nairobi, Kenya
| | | |
Collapse
|
11
|
Optimal Control of Plant Disease Epidemics with Clean Seed Usage. Bull Math Biol 2021; 83:46. [PMID: 33745017 DOI: 10.1007/s11538-021-00872-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 02/13/2021] [Indexed: 10/21/2022]
Abstract
The distribution and use of pathogen-free planting material ("clean seeds") is a promising method to control plant diseases in developing countries. We address the question of minimizing disease prevalence in plants through the optimal usage of clean seeds. We consider the simplest possible S-I model together with a simple economic criterion to be maximized. The static optimization problem shows a diversity of possible outcomes depending on economical and epidemiological parameters. We derive a simple condition showing to what extent subsidizing clean seeds relative to the epidemiological features of the disease may help eradicate or control the disease. Then we consider dynamic optimal control and Pontryagin's maximum principle to study the optimal usage of clean seeds to control the disease. The dynamical results are comparable to the static ones and are even simpler in some sense. In particular, the condition on the critical subsidy rate that makes clean seed usage economically viable is unchanged from the static optimization case. We discuss how these results may apply to the control of maize lethal necrosis in East-Africa.
Collapse
|
12
|
Emerging infectious diseases threatening food security and economies in Africa. GLOBAL FOOD SECURITY 2021. [DOI: 10.1016/j.gfs.2020.100479] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
|
13
|
Jeger MJ. The Epidemiology of Plant Virus Disease: Towards a New Synthesis. PLANTS (BASEL, SWITZERLAND) 2020; 9:E1768. [PMID: 33327457 PMCID: PMC7764944 DOI: 10.3390/plants9121768] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 12/07/2020] [Accepted: 12/10/2020] [Indexed: 02/07/2023]
Abstract
Epidemiology is the science of how disease develops in populations, with applications in human, animal and plant diseases. For plant diseases, epidemiology has developed as a quantitative science with the aims of describing, understanding and predicting epidemics, and intervening to mitigate their consequences in plant populations. Although the central focus of epidemiology is at the population level, it is often necessary to recognise the system hierarchies present by scaling down to the individual plant/cellular level and scaling up to the community/landscape level. This is particularly important for diseases caused by plant viruses, which in most cases are transmitted by arthropod vectors. This leads to range of virus-plant, virus-vector and vector-plant interactions giving a distinctive character to plant virus epidemiology (whilst recognising that some fungal, oomycete and bacterial pathogens are also vector-borne). These interactions have epidemiological, ecological and evolutionary consequences with implications for agronomic practices, pest and disease management, host resistance deployment, and the health of wild plant communities. Over the last two decades, there have been attempts to bring together these differing standpoints into a new synthesis, although this is more apparent for evolutionary and ecological approaches, perhaps reflecting the greater emphasis on shorter often annual time scales in epidemiological studies. It is argued here that incorporating an epidemiological perspective, specifically quantitative, into this developing synthesis will lead to new directions in plant virus research and disease management. This synthesis can serve to further consolidate and transform epidemiology as a key element in plant virus research.
Collapse
Affiliation(s)
- Michael J Jeger
- Department of Life Sciences, Imperial College London, Silwood Park, Ascot SL5 7PY, UK
| |
Collapse
|
14
|
Thompson RN, Brooks-Pollock E. Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants. Philos Trans R Soc Lond B Biol Sci 2020; 374:20190038. [PMID: 31056051 DOI: 10.1098/rstb.2019.0038] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
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'.
Collapse
Affiliation(s)
- Robin N Thompson
- 1 Mathematical Institute, University of Oxford , Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG , UK.,2 Department of Zoology, University of Oxford , Peter Medawar Building, South Parks Road, Oxford OX1 3SY , UK.,3 Christ Church, University of Oxford , St Aldates, Oxford OX1 1DP , UK
| | - Ellen Brooks-Pollock
- 4 Bristol Veterinary School, University of Bristol , Langford BS40 5DU , UK.,5 National Institute for Health Research, Health Protection Research Unit in Evaluation of Interventions, Bristol Medical School , Bristol BS8 2BN , UK
| |
Collapse
|
15
|
Separate seasons of infection and reproduction can lead to multi-year population cycles. J Theor Biol 2020; 489:110158. [PMID: 31926973 DOI: 10.1016/j.jtbi.2020.110158] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 01/03/2020] [Accepted: 01/07/2020] [Indexed: 11/22/2022]
Abstract
Many host-pathogen systems are characterized by a temporal order of disease transmission and host reproduction. For example, this can be due to pathogens infecting certain life cycle stages of insect hosts; transmission occurring during the aggregation of migratory birds; or plant diseases spreading between planting seasons. We develop a simple discrete-time epidemic model with density-dependent transmission and disease affecting host fecundity and survival. The model shows sustained multi-annual cycles in host population abundance and disease prevalence, both in the presence and absence of density dependence in host reproduction, for large horizontal transmissibility, imperfect vertical transmission, high virulence, and high reproductive capability. The multi-annual cycles emerge as invariant curves in a Neimark-Sacker bifurcation. They are caused by a carry-over effect, because the reproductive fitness of an individual can be reduced by virulent effects due to infection in an earlier season. As the infection process is density-dependent but shows an effect only in a later season, this produces delayed density dependence typical for second-order oscillations. The temporal separation between the infection and reproduction season is crucial in driving the cycles; if these processes occur simultaneously as in differential equation models, there are no sustained oscillations. Our model highlights the destabilizing effects of inter-seasonal feedbacks and is one of the simplest epidemic models that can generate population cycles.
Collapse
|
16
|
Modelling Vector Transmission and Epidemiology of Co-Infecting Plant Viruses. Viruses 2019; 11:v11121153. [PMID: 31847125 PMCID: PMC6950130 DOI: 10.3390/v11121153] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 12/03/2019] [Accepted: 12/06/2019] [Indexed: 12/24/2022] Open
Abstract
Co-infection of plant hosts by two or more viruses is common in agricultural crops and natural plant communities. A variety of models have been used to investigate the dynamics of co-infection which track only the disease status of infected and co-infected plants, and which do not explicitly track the density of inoculative vectors. Much less attention has been paid to the role of vector transmission in co-infection, that is, acquisition and inoculation and their synergistic and antagonistic interactions. In this investigation, a general epidemiological model is formulated for one vector species and one plant species with potential co-infection in the host plant by two viruses. The basic reproduction number provides conditions for successful invasion of a single virus. We derive a new invasion threshold which provides conditions for successful invasion of a second virus. These two thresholds highlight some key epidemiological parameters important in vector transmission. To illustrate the flexibility of our model, we examine numerically two special cases of viral invasion. In the first case, one virus species depends on an autonomous virus for its successful transmission and in the second case, both viruses are unable to invade alone but can co-infect the host plant when prevalence is high.
Collapse
|
17
|
Hamelin FM, Allen LJS, Bokil VA, Gross LJ, Hilker FM, Jeger MJ, Manore CA, Power AG, Rúa MA, Cunniffe NJ. Coinfections by noninteracting pathogens are not independent and require new tests of interaction. PLoS Biol 2019; 17:e3000551. [PMID: 31794547 PMCID: PMC6890165 DOI: 10.1371/journal.pbio.3000551] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 11/04/2019] [Indexed: 12/26/2022] Open
Abstract
If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models. If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts can be obtained by simply multiplying the individual prevalences. However, even simple epidemiological models show this to be untrue. This study develops new tests for interaction between pathogens that account for this surprising lack of statistical independence.
Collapse
Affiliation(s)
- Frédéric M. Hamelin
- IGEPP, Agrocampus Ouest, INRA, Université de Rennes 1, Université Bretagne-Loire, Rennes, France
| | - Linda J. S. Allen
- Department of Mathematics and Statistics, Texas Tech University, Lubbock, Texas, United States of America
| | - Vrushali A. Bokil
- Department of Mathematics, Oregon State University, Corvallis, Oregon, United States of America
| | - Louis J. Gross
- National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Frank M. Hilker
- Institute of Environmental Systems Research, School of Mathematics and Computer Science, Osnabrück University, Osnabrück, Germany
| | - Michael J. Jeger
- Centre for Environmental Policy, Imperial College London, Ascot, United Kingdom
| | - Carrie A. Manore
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Alison G. Power
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, United States of America
| | - Megan A. Rúa
- Department of Biological Sciences, Wright State University, Dayton, Ohio, United States of America
| | - Nik J. Cunniffe
- Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
- * E-mail:
| |
Collapse
|
18
|
Andersen KF, Buddenhagen CE, Rachkara P, Gibson R, Kalule S, Phillips D, Garrett KA. Modeling Epidemics in Seed Systems and Landscapes To Guide Management Strategies: The Case of Sweet Potato in Northern Uganda. PHYTOPATHOLOGY 2019; 109:1519-1532. [PMID: 30785374 PMCID: PMC7779973 DOI: 10.1094/phyto-03-18-0072-r] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/14/2019] [Indexed: 05/29/2023]
Abstract
Seed systems are critical for deployment of improved varieties but also can serve as major conduits for the spread of seedborne pathogens. As in many other epidemic systems, epidemic risk in seed systems often depends on the structure of networks of trade, social interactions, and landscape connectivity. In a case study, we evaluated the structure of an informal sweet potato seed system in the Gulu region of northern Uganda for its vulnerability to the spread of emerging epidemics and its utility for disseminating improved varieties. Seed transaction data were collected by surveying vine sellers weekly during the 2014 growing season. We combined data from these observed seed transactions with estimated dispersal risk based on village-to-village proximity to create a multilayer network or "supranetwork." Both the inverse power law function and negative exponential function, common models for dispersal kernels, were evaluated in a sensitivity analysis/uncertainty quantification across a range of parameters chosen to represent spread based on proximity in the landscape. In a set of simulation experiments, we modeled the introduction of a novel pathogen and evaluated the influence of spread parameters on the selection of villages for surveillance and management. We found that the starting position in the network was critical for epidemic progress and final epidemic outcomes, largely driven by node out-degree. The efficacy of node centrality measures was evaluated for utility in identifying villages in the network to manage and limit disease spread. Node degree often performed as well as other, more complicated centrality measures for the networks where village-to-village spread was modeled by the inverse power law, whereas betweenness centrality was often more effective for negative exponential dispersal. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.[Formula: see text] Copyright © 2019 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Collapse
Affiliation(s)
- K. F. Andersen
- Plant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Institute for Sustainable Food Systems, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611-0680, U.S.A
| | - C. E. Buddenhagen
- Plant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Institute for Sustainable Food Systems, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611-0680, U.S.A
| | - P. Rachkara
- Department of Rural Development and Agribusiness, Gulu University, Gulu, Uganda
| | - R. Gibson
- Natural Resource Institute, University of Greenwich, Greenwich, United
| | - S. Kalule
- Department of Rural Development and Agribusiness, Gulu University, Gulu, Uganda
| | - D. Phillips
- Natural Resource Institute, University of Greenwich, Greenwich, United
| | - K. A. Garrett
- Plant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Institute for Sustainable Food Systems, University of Florida, Gainesville, FL 32611-0680, U.S.A
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611-0680, U.S.A
| |
Collapse
|
19
|
Allen-Perkins A, Estrada E. Mathematical modelling for sustainable aphid control in agriculture via intercropping. Proc Math Phys Eng Sci 2019; 475:20190136. [PMID: 31293361 PMCID: PMC6598064 DOI: 10.1098/rspa.2019.0136] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 05/16/2019] [Indexed: 11/12/2022] Open
Abstract
Agricultural losses to pests represent an important challenge in a global warming scenario. Intercropping is an alternative farming practice that promotes pest control without the use of chemical pesticides. Here, we develop a mathematical model to study epidemic spreading and control in intercropped agricultural fields as a sustainable pest management tool for agriculture. The model combines the movement of aphids transmitting a virus in an agricultural field, the spatial distribution of plants in the intercropped field and the presence of 'trap crops' in an epidemiological susceptible-infected-removed model. Using this model, we study several intercropping arrangements without and with trap crops and find a new intercropping arrangement that may improve significantly pest management in agricultural fields with respect to the commonly used intercrop systems.
Collapse
Affiliation(s)
- Alfonso Allen-Perkins
- Instituto de Física, Universidade Federal da Bahia, 40210-210 Salvador, Brazil
- Complex System Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Ernesto Estrada
- Institute of Applied Mathematics (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain
- ARAID Foundation, Government of Aragón, 50018 Zaragoza, Spain
- Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Caixa Postal 668, 13560-970 São Carlos, São Paulo, Brazil
| |
Collapse
|
20
|
Bokil VA, Allen LJS, Jeger MJ, Lenhart S. Optimal control of a vectored plant disease model for a crop with continuous replanting. JOURNAL OF BIOLOGICAL DYNAMICS 2019; 13:325-353. [PMID: 31149889 DOI: 10.1080/17513758.2019.1622808] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 04/28/2019] [Indexed: 06/09/2023]
Abstract
Vector-transmitted diseases of plants have had devastating effects on agricultural production worldwide, resulting in drastic reductions in yield for crops such as cotton, soybean, tomato, and cassava. Plant-vector-virus models with continuous replanting are investigated in terms of the effects of selection of cuttings, roguing, and insecticide use on disease prevalence in plants. Previous models are extended to include two replanting strategies: frequencyreplanting and abundance-replanting. In frequency-replanting, replanting of infected cuttings depends on the selection frequency parameter ε, whereas in abundance-replanting, replanting depends on plant abundance via a selection rate parameter also denoted as ε. The two models are analysed and new thresholds for disease elimination are defined for each model. Parameter values for cassava, whiteflies, and African cassava mosaic virus serve as a case study. A numerical sensitivity analysis illustrates how the equilibrium densities of healthy and infected plants vary with parameter values. Optimal control theory is used to investigate the effects of roguing and insecticide use with a goal of maximizing the healthy plants that are harvested. Differences in the control strategies in the two models are seen for large values of ε. Also, the combined strategy of roguing and insecticide use performs better than a single control.
Collapse
Affiliation(s)
- V A Bokil
- a Department of Mathematics, Oregon State University , Corvallis , OR , USA
| | - L J S Allen
- b Department of Mathematics & Statistics, Texas Tech University , Lubbock , TX , USA
| | - M J Jeger
- c Centre for Environmental Policy, Imperial College , London , UK
| | - S Lenhart
- d Department of Mathematics, University of Tennessee , Knoxville , TN , USA
| |
Collapse
|
21
|
Abstract
Maize lethal necrosis (MLN) is a disease of maize caused by coinfection of maize with maize chlorotic mottle virus (MCMV) and one of several viruses from the Potyviridae, such as sugarcane mosaic virus, maize dwarf mosaic virus, Johnsongrass mosaic virus or wheat streak mosaic virus. The coinfecting viruses act synergistically to result in frequent plant death or severely reduce or negligible yield. Over the past eight years, MLN has emerged in sub-Saharan East Africa, Southeast Asia, and South America, with large impacts on smallholder farmers. Factors associated with MLN emergence include multiple maize crops per year, the presence of maize thrips ( Frankliniella williamsi), and highly susceptible maize crops. Soil and seed transmission of MCMV may also play significant roles in development and perpetuation of MLN epidemics. Containment and control of MLN will likely require a multipronged approach, and more research is needed to identify and develop the best measures.
Collapse
Affiliation(s)
- Margaret G Redinbaugh
- Department of Plant Pathology, Ohio State University, Wooster, Ohio 44691, USA; .,United States Department of Agriculture, Agricultural Research Service, Wooster, Ohio 44691, USA;
| | - Lucy R Stewart
- Department of Plant Pathology, Ohio State University, Wooster, Ohio 44691, USA; .,United States Department of Agriculture, Agricultural Research Service, Wooster, Ohio 44691, USA;
| |
Collapse
|
22
|
Elderfield JAD, Lopez-Ruiz FJ, van den Bosch F, Cunniffe NJ. Using Epidemiological Principles to Explain Fungicide Resistance Management Tactics: Why do Mixtures Outperform Alternations? PHYTOPATHOLOGY 2018; 108:803-817. [PMID: 29377769 DOI: 10.1094/phyto-08-17-0277-r] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Whether fungicide resistance management is optimized by spraying chemicals with different modes of action as a mixture (i.e., simultaneously) or in alternation (i.e., sequentially) has been studied by experimenters and modelers for decades. However, results have been inconclusive. We use previously parameterized and validated mathematical models of wheat Septoria leaf blotch and grapevine powdery mildew to test which tactic provides better resistance management, using the total yield before resistance causes disease control to become economically ineffective ("lifetime yield") to measure effectiveness. We focus on tactics involving the combination of a low-risk and a high-risk fungicide, and the case in which resistance to the high-risk chemical is complete (i.e., in which there is no partial resistance). Lifetime yield is then optimized by spraying as much low-risk fungicide as is permitted, combined with slightly more high-risk fungicide than needed for acceptable initial disease control, applying these fungicides as a mixture. That mixture rather than alternation gives better performance is invariant to model parameterization and structure, as well as the pathosystem in question. However, if comparison focuses on other metrics, e.g., lifetime yield at full label dose, either mixture or alternation can be optimal. Our work shows how epidemiological principles can explain the evolution of fungicide resistance, and also highlights a theoretical framework to address the question of whether mixture or alternation provides better resistance management. It also demonstrates that precisely how spray tactics are compared must be given careful consideration. [Formula: see text] Copyright © 2018 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .
Collapse
Affiliation(s)
- James A D Elderfield
- First and fourth authors: Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom; second author: Curtin University, Centre for Crop and Disease Management, Department of Environment and Agriculture, Bentley, WA 6845, Australia; and third author: Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
| | - Francisco J Lopez-Ruiz
- First and fourth authors: Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom; second author: Curtin University, Centre for Crop and Disease Management, Department of Environment and Agriculture, Bentley, WA 6845, Australia; and third author: Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
| | - Frank van den Bosch
- First and fourth authors: Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom; second author: Curtin University, Centre for Crop and Disease Management, Department of Environment and Agriculture, Bentley, WA 6845, Australia; and third author: Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
| | - Nik J Cunniffe
- First and fourth authors: Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom; second author: Curtin University, Centre for Crop and Disease Management, Department of Environment and Agriculture, Bentley, WA 6845, Australia; and third author: Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
| |
Collapse
|
23
|
Jones MW, Penning BW, Jamann TM, Glaubitz JC, Romay C, Buckler ES, Redinbaugh MG. Diverse Chromosomal Locations of Quantitative Trait Loci for Tolerance to Maize chlorotic mottle virus in Five Maize Populations. PHYTOPATHOLOGY 2018; 108:748-758. [PMID: 29287150 DOI: 10.1094/phyto-09-17-0321-r] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
The recent rapid emergence of maize lethal necrosis (MLN), caused by coinfection of maize with Maize chlorotic mottle virus (MCMV) and a second virus usually from the family Potyviridae, is causing extensive losses for farmers in East Africa, Southeast Asia, and South America. Although the genetic basis of resistance to potyviruses is well understood in maize, little was known about resistance to MCMV. The responses of five maize inbred lines (KS23-5, KS23-6, N211, DR, and Oh1VI) to inoculation with MCMV, Sugarcane mosaic virus, and MLN were characterized. All five lines developed fewer symptoms than susceptible controls after inoculation with MCMV; however, the virus was detected in systemic leaf tissue from each of the lines similarly to susceptible controls, indicating that the lines were tolerant of MCMV rather than resistant to it. Except for KS23-5, the inbred lines also developed fewer symptoms after inoculation with MLN than susceptible controls. To identify genetic loci associated with MCMV tolerance, large F2 or recombinant inbred populations were evaluated for their phenotypic responses to MCMV, and the most resistant and susceptible plants were genotyped by sequencing. One to four quantitative trait loci (QTL) were identified in each tolerant population using recombination frequency and positional mapping strategies. In contrast to previous studies of virus resistance in maize, the chromosomal positions and genetic character of the QTL were unique to each population. The results suggest that different, genotype-specific mechanisms are associated with MCMV tolerance in maize. These results will allow for the development of markers for marker-assisted selection of MCMV- and MLN-tolerant maize hybrids for disease control.
Collapse
Affiliation(s)
- Mark W Jones
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Bryan W Penning
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Tiffany M Jamann
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Jeff C Glaubitz
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Cinta Romay
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Edward S Buckler
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Margaret G Redinbaugh
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| |
Collapse
|
24
|
Wamaitha MJ, Nigam D, Maina S, Stomeo F, Wangai A, Njuguna JN, Holton TA, Wanjala BW, Wamalwa M, Lucas T, Djikeng A, Garcia-Ruiz H. Metagenomic analysis of viruses associated with maize lethal necrosis in Kenya. Virol J 2018; 15:90. [PMID: 29792207 PMCID: PMC5966901 DOI: 10.1186/s12985-018-0999-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 05/07/2018] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Maize lethal necrosis is caused by a synergistic co-infection of Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA. METHODS We used next-generation sequencing to identify viruses associated to maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties. RESULTS Complete and partial genomes were assembled for MCMV, SCMV, Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses (MCMV, SCMV, MSV and MYDV-RMV) were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for other four potyviruses and one polerovirus. CONCLUSION Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different to isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved.
Collapse
Affiliation(s)
- Mwathi Jane Wamaitha
- Kenya Agricultural and Livestock Research Organization (KALRO), P. O. Box 14733-00800, Nairobi, Kenya
| | - Deepti Nigam
- Department of Plant Pathology and Nebraska Center for Virology, University of Nebraska- Lincoln, Lincoln, NE 68583 USA
| | - Solomon Maina
- School of Agriculture and Environment and UWA Institute of Agriculture, Faculty of Science, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009 Australia
- Cooperative Research Centre for Plant Biosecurity, Canberra, ACT 2617 Australia
| | - Francesca Stomeo
- Biosciences Eastern and Central Africa-International Livestock Research Institute (BecA-ILRI), Hub, Nairobi, Kenya
| | - Anne Wangai
- Kenya Agricultural and Livestock Research Organization (KALRO), P. O. Box 14733-00800, Nairobi, Kenya
| | - Joyce Njoki Njuguna
- Biosciences Eastern and Central Africa-International Livestock Research Institute (BecA-ILRI), Hub, Nairobi, Kenya
| | - Timothy A. Holton
- Plant Innovation Centre, Post-Entry Quarantine, Department of Agriculture and Water Resources, 135 Donnybrook Road, Mickleham, VIC 3064 Australia
| | - Bramwel W. Wanjala
- Biosciences Eastern and Central Africa-International Livestock Research Institute (BecA-ILRI), Hub, Nairobi, Kenya
| | - Mark Wamalwa
- Biosciences Eastern and Central Africa-International Livestock Research Institute (BecA-ILRI), Hub, Nairobi, Kenya
| | - Tanui Lucas
- Kenya Agricultural and Livestock Research Organization (KALRO), P. O. Box 14733-00800, Nairobi, Kenya
| | - Appolinaire Djikeng
- Biosciences Eastern and Central Africa-International Livestock Research Institute (BecA-ILRI), Hub, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health (CTLGH), The University of Edinburgh, Edinburgh, Scotland EH25 9RG UK
| | - Hernan Garcia-Ruiz
- Department of Plant Pathology and Nebraska Center for Virology, University of Nebraska- Lincoln, Lincoln, NE 68583 USA
| |
Collapse
|
25
|
Jeger MJ, Madden LV, van den Bosch F. Plant Virus Epidemiology: Applications and Prospects for Mathematical Modeling and Analysis to Improve Understanding and Disease Control. PLANT DISEASE 2018; 102:837-854. [PMID: 30673389 DOI: 10.1094/pdis-04-17-0612-fe] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
In recent years, mathematical modeling has increasingly been used to complement experimental and observational studies of biological phenomena across different levels of organization. In this article, we consider the contribution of mathematical models developed using a wide range of techniques and uses to the study of plant virus disease epidemics. Our emphasis is on the extent to which models have contributed to answering biological questions and indeed raised questions related to the epidemiology and ecology of plant viruses and the diseases caused. In some cases, models have led to direct applications in disease control, but arguably their impact is better judged through their influence in guiding research direction and improving understanding across the characteristic spatiotemporal scales of plant virus epidemics. We restrict this article to plant virus diseases for reasons of length and to maintain focus even though we recognize that modeling has played a major and perhaps greater part in the epidemiology of other plant pathogen taxa, including vector-borne bacteria and phytoplasmas.
Collapse
Affiliation(s)
- M J Jeger
- Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, United Kingdom
| | - L V Madden
- Department of Plant Pathology, Ohio State University, Wooster, OH 44691
| | - F van den Bosch
- Computational and Systems Biology, Rothamsted Research, Harpenden AL5 2JQ, United Kingdom
| |
Collapse
|
26
|
Thomas-Sharma S, Andrade-Piedra J, Carvajal Yepes M, Hernandez Nopsa JF, Jeger MJ, Jones RAC, Kromann P, Legg JP, Yuen J, Forbes GA, Garrett KA. A Risk Assessment Framework for Seed Degeneration: Informing an Integrated Seed Health Strategy for Vegetatively Propagated Crops. PHYTOPATHOLOGY 2017; 107:1123-1135. [PMID: 28545348 DOI: 10.1094/phyto-09-16-0340-r] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Pathogen buildup in vegetative planting material, termed seed degeneration, is a major problem in many low-income countries. When smallholder farmers use seed produced on-farm or acquired outside certified programs, it is often infected. We introduce a risk assessment framework for seed degeneration, evaluating the relative performance of individual and combined components of an integrated seed health strategy. The frequency distribution of management performance outcomes was evaluated for models incorporating biological and environmental heterogeneity, with the following results. (1) On-farm seed selection can perform as well as certified seed, if the rate of success in selecting healthy plants for seed production is high; (2) when choosing among within-season management strategies, external inoculum can determine the relative usefulness of 'incidence-altering management' (affecting the proportion of diseased plants/seeds) and 'rate-altering management' (affecting the rate of disease transmission in the field); (3) under severe disease scenarios, where it is difficult to implement management components at high levels of effectiveness, combining management components can be synergistic and keep seed degeneration below a threshold; (4) combining management components can also close the yield gap between average and worst-case scenarios. We also illustrate the potential for expert elicitation to provide parameter estimates when empirical data are unavailable. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Collapse
Affiliation(s)
- S Thomas-Sharma
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - J Andrade-Piedra
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - M Carvajal Yepes
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - J F Hernandez Nopsa
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - M J Jeger
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - R A C Jones
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - P Kromann
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - J P Legg
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - J Yuen
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - G A Forbes
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| | - K A Garrett
- First, fourth, and eleventh authors: Department of Plant Pathology, Kansas State University, Manhattan; first author: Department of Plant Pathology, University of Wisconsin-Madison, Madison; second author: International Potato Center, Lima, Peru; third author: International Center for Tropical Agriculture, Cali, Colombia; fourth and eleventh authors: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville; fifth author: Centre for Environmental Policy, Imperial College London; sixth author: Institute of Agriculture, University of Western Australia, Crawley, Australia; seventh author: International Potato Center, Quito, Ecuador; eighth author: International Institute of Tropical Agriculture, Dar es Salaam, Tanzania; ninth author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; and tenth author: International Potato Center, Kunming, China
| |
Collapse
|
27
|
Ojiambo PS, Yuen J, van den Bosch F, Madden LV. Epidemiology: Past, Present, and Future Impacts on Understanding Disease Dynamics and Improving Plant Disease Management-A Summary of Focus Issue Articles. PHYTOPATHOLOGY 2017; 107:1092-1094. [PMID: 29205105 DOI: 10.1094/phyto-07-17-0248-fi] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Epidemiology has made significant contributions to plant pathology by elucidating the general principles underlying the development of disease epidemics. This has resulted in a greatly improved theoretical and empirical understanding of the dynamics of disease epidemics in time and space, predictions of disease outbreaks or the need for disease control in real-time basis, and tactical and strategic solutions to disease problems. Availability of high-resolution experimental data at multiple temporal and spatial scales has now provided a platform to test and validate theories on the spread of diseases at a wide range of spatial scales ranging from the local to the landscape level. Relatively new approaches in plant disease epidemiology, ranging from network to information theory, coupled with the availability of large-scale datasets and the rapid development of computer technology, are leading to revolutionary thinking about epidemics that can result in considerable improvement of strategic and tactical decision making in the control and management of plant diseases. Methods that were previously restricted to topics such as population biology or evolution are now being employed in epidemiology to enable a better understanding of the forces that drive the development of plant disease epidemics in space and time. This Focus Issue of Phytopathology features research articles that address broad themes in epidemiology including social and political consequences of disease epidemics, decision theory and support, pathogen dispersal and disease spread, disease assessment and pathogen biology and disease resistance. It is important to emphasize that these articles are just a sample of the types of research projects that are relevant to epidemiology. Below, we provide a succinct summary of the articles that are published in this Focus Issue .
Collapse
Affiliation(s)
- P S Ojiambo
- 2017 Focus Issue Senior Editors First author: Center for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh 27695; second author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; third author: Rothamsted Research, West Common, Harpenden, AL5 2JQ, U.K.; and fourth author: Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691
| | - J Yuen
- 2017 Focus Issue Senior Editors First author: Center for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh 27695; second author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; third author: Rothamsted Research, West Common, Harpenden, AL5 2JQ, U.K.; and fourth author: Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691
| | - F van den Bosch
- 2017 Focus Issue Senior Editors First author: Center for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh 27695; second author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; third author: Rothamsted Research, West Common, Harpenden, AL5 2JQ, U.K.; and fourth author: Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691
| | - L V Madden
- 2017 Focus Issue Senior Editors First author: Center for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh 27695; second author: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden; third author: Rothamsted Research, West Common, Harpenden, AL5 2JQ, U.K.; and fourth author: Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691
| |
Collapse
|