CHAPTER 7: Cassava Viruses: Epidemiology, Evolution, and Management

Mbewe, Willard; Hanley‐Bowdoin, Linda; Ndunguru, Joseph; Duffy, Siobain

doi:10.1094/9780890546383.007

Cited by 5 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Circular single-stranded DNA viruses such as begomoviruses are often cloned in a two-step process to create partial tandem dimers containing two copies of the virus origin of replication, a configuration that enhances infection ( 1 ). Cloned isolates of African cassava mosaic virus (ACMV) and East African cassava mosaic Cameroon virus (EACMCV) provided conclusive proof of synergy between two major clades of cassava begomoviruses ( 2 ), which is a defining feature of the epidemic of mosaic disease that has devastated cassava production in sub-Saharan Africa ( 3 , 4 ). Here, we announce new sequence resources for these frequently used clones, which confirm the EACMCV clones and clarify the identity of the ACMV clones.…”

Section: Announcementmentioning

confidence: 99%

Deeply Sequenced Infectious Clones of Key Cassava Begomovirus Isolates from Cameroon

Hoyer

Fondong

Dallas

et al. 2020

Microbiol Resour Announc

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Announcementmentioning

confidence: 99%

Deeply Sequenced Infectious Clones of Key Cassava Begomovirus Isolates from Cameroon

Hoyer

Fondong

Dallas

et al. 2020

Microbiol Resour Announc

Self Cite

View full text Add to dashboard Cite

show abstract

“…Likewise, cassava growers in Central and East Africa also face a collective action problem to protect their crops from cassava brown streak disease (CBSD), which is considered the greatest threat to cassava productivity in Africa (Legg et al, 2014). CBSD causes leaf chlorosis, brown streaks on the stem and root necrosis, which has devastating consequences, as cassava roots are a prime food security crop (Mbewe et al, 2020). CBSD is caused by two related viruses, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), which are transmitted in a semipersistent manner over short distances by the whitefly B. tabaci (Maruthi et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Institutional approaches for plant health provision as a collective action problem

et al. 2021

View full text Add to dashboard Cite

The provision of plant health has public good attributes when nobody can be excluded from enjoying its benefits and individual benefits do not reduce the ability of others to also benefit. These attributes increase risk of free-riding on plant health services provided by others, giving rise to a collective action problem when trying to ensure plant health in a region threatened by an emerging plant disease. This problem has traditionally been addressed by government intervention, but top-down approaches to plant health are often insufficient and are increasingly combined with bottom-up approaches that promote self-organization by affected individuals. The challenge is how to design plant health institutions that effectively deal with the spatial and temporal dynamics of plant diseases, while staying aligned with the preferences, values and needs of affected societies. Here, we illustrate how Ostrom’s design principles for collective action can be used to guide the incorporation of bottom-up approaches to plant health governance in order to improve institutional fit. Using the ongoing epidemic of huanglongbing (HLB) as a case study, we examine existing institutions designed to ensure citrus health under HLB in Brazil, Mexico, the United States and Argentina, and discuss potential implications of Ostrom’s design principles for the collective provision of plant health under HLB and other plant diseases that are threatening food security worldwide. The discussion leads to an outline for the interdisciplinary research agenda that would be needed to establish the link between institutional approaches and plant health outcomes in the context of global food security.

show abstract

Early Detection of Plant Virus Infection Using Multispectral Imaging and Machine Learning

Grieve,

Duffy,

Dallas

et al. 2024

Plant Health Cases

View full text Add to dashboard Cite

Climate change-resilient crops like cassava are projected to play a key role in 21st-century food security. However, cassava production in East Africa is limited by RNA viruses that cause cassava brown streak disease (CBSD). CBSD typically causes subtle or no symptoms on stems and leaves, while destroying the root tissue, which means farmers are often unaware their fields are infected until they have a failed harvest. The subtle symptoms of CBSD have made it difficult to study the spread of the disease in fields. We will use an engineering advancement, our active multispectral imager (MSI), to rapidly determine the infection status of plants in the field in Tanzania. The MSI observes leaves using many different wavelengths, and the resulting light spectra are interpreted by machine learning models trained on cassava leaf scans. Under laboratory conditions, the MSI detects CBSD infection with 95% accuracy at 28 days post-infection, when plants have no visible symptoms. Our multinational team is studying and modeling the spread of CBSD to assess the efficacy of using the MSI to detect and remove infected cassava plants from fields before CBSD can spread. In addition to improving the food security of people who eat cassava in sub-Saharan Africa, our technology and modeling framework may be useful in diseases of other vegetatively propagated crops such as banana/plantain, potato, sweet potato, and yam. Information © The Authors 2024

show abstract

CHAPTER 7: Cassava Viruses: Epidemiology, Evolution, and Management

Cited by 5 publications

References 0 publications

Deeply Sequenced Infectious Clones of Key Cassava Begomovirus Isolates from Cameroon

Deeply Sequenced Infectious Clones of Key Cassava Begomovirus Isolates from Cameroon

Institutional approaches for plant health provision as a collective action problem

Early Detection of Plant Virus Infection Using Multispectral Imaging and Machine Learning

Contact Info

Product

Resources

About