K. F. Andersen

University of Florida

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Karen A. Garrett

University of Florida

Christopher E. Buddenhagen

AgResearch

G. A. Forbes

Stanford University

Erik Delaquis

International Center for Tropical Agriculture

Jorge Andrade-Piedra

International Potato Center

Yanru Xing

University of Florida

Stef de Haan

Universidad Univer

S. Thomas‐Sharma

Louisiana State University Agricultural Center

Jonathan Newby

International Center for Tropical Agriculture

Maria Eleanor Karssenberg

Wageningen University & Research

Cooperative Institutions

University of Florida

Kansas State University

International Potato Center

CGIAR

Plant (United States)

United States Department of Agriculture

Wageningen University & Research

International Center for Tropical Agriculture

Agricultural Research Service

International Center for Tropical Agriculture

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Influence of Rainfall Patterns on the Development of Fusarium Head Blight, Accumulation of Deoxynivalenol and Fungicide Efficacy

K. F. Andersen

Vomitoxin

Source

Cite

Citations (1)

Early Season Environmental Indicators of Wheat Stripe Rust Epidemics in Kansas and the Central Great Plains Region of the United States

Plant Disease (2022)

E. D. De Wolf K. F. Andersen Romulo P. Lollato

During the past two decades, the wheat-producing areas of the Great Plains region in North America experienced frequent, severe yield losses to stripe rust (Puccinia striiformis f. sp. tritici). In general, outbreaks of rust diseases in the Southern Great Plains region often precede disease problems in the Central and Northern Great Plains. However, these generalizations provide little information, and our objective for this study was to identify weather variables, geographical areas, and time periods that influence the early stages of stripe rust epidemics in the Great Plains. Data used in this analysis consisted of monthly summaries of temperature, precipitation, and soil moisture from 10 climate districts in Texas of the United States. These environmental variables were paired with estimates of wheat yield losses to stripe rust in Kansas from 2000 to 2019, with yield loss coded as a binary variable (1 = >4% statewide yield loss). An ensemble of simple models representing weather variables, time periods, and geographical locations were hypothesized to be influential in the development of stripe rust epidemics. Model performance was verified with observations not used in model development. Results of this study indicated that soil moisture within two to three climate districts in Texas were particularly influential in regional disease development. These areas of Texas were 700 to 1,000 km away from locations in Kansas where the disease-related yield losses were observed, and they often preceded disease losses by 3 to 6 months. In the future, these models could help establish priority locations and time periods for disease scouting and inform regional estimates of disease risk.

Rust (programming language)

Stripe rust

Growing season

10.1094/pdis-08-22-1873-re

Cite

Citations (0)

Decision support for managing an invasive pathogen through efficient clean seed systems: Cassava mosaic disease in Southeast Asia

bioRxiv (Cold Spring Harbor Laboratory) (2024)

K. F. Andersen Erik Delaquis Jonathan Newby Stef de Haan Thuy Cu Thi Le

Abstract CONTEXT Effective seed systems must both distribute high-performing varieties efficiently and slow or stop the spread of pathogens and pests. Epidemics increasingly threaten crops around the world, endangering the incomes and livelihoods of smallholder farmers. Responding to these food and economic security challenges requires stakeholders to act quickly and decisively during the early stages of invasions, typically with very limited resources. The recent introduction of cassava mosaic virus into southeast Asia threatens cassava production in the region. OBJECTIVES Our goal in this study is to provide a decision-support framework for efficient management of healthy seed systems, applied to cassava mosaic disease. The specific objectives are to (1) evaluate disease risk in disease-free parts of Cambodia, Lao PDR, Thailand, and Vietnam by integrating disease occurrence, climate, topology, and land use, using machine learning; (2) incorporate this predicted environmental risk with seed exchange survey data and whitefly spread in the landscape to model epidemic spread in a network meta-population model; and (3) use scenario analysis to identify candidate regions to be prioritized in seed system management. RESULTS AND CONCLUSIONS The analyses allow stakeholders to evaluate strategy options for allocating their resources in the field, guiding the implementation of seed system programs and responses. Fixed rather than adaptive deployment of clean seed produced more favorable outcomes in this model, as did prioritization of a higher number of districts through the deployment of smaller volumes of clean seed. SIGNIFICANCE The decision-support framework presented here can be applied widely to seed systems challenged by the dual goals of distributing seed efficiently and reducing disease risk. Data-driven approaches support evidence-based identification of optimized surveillance and mitigation areas in an iterative fashion, providing guidance early in an epidemic, and revising them as data accrue over time.

Mosaic

10.1101/2024.02.13.580210

Cite

Citations (0)

Assessment of the Effect of Temperature on the Late Blight Disease Cycle Using a Detached Leaf Assay

Journal of the Pennsylvania Academy of Science (2011)

K. F. Andersen Manuel D. Ospina-Giraldo

ABSTRACT Phytophthora infestans is a fungal-like organism belonging to the Phylum Oomycota, which is currently classified within the Kingdom Stramenopila. This oomycete is the causal agent of potato late blight, and as such, it is believed to be a major contributor to the Potato Famine, which ravaged Ireland in the 1840's. Current annual losses worldwide due to P. infestans gross over $6.8 billion. Interactions between two different isolates of the US-8 race and three potato (Solanum tuberosum) cultivars, and in particular, the effect of temperature on the disease cycle, were analyzed using a Detached Leaf Assay (DLA), under controlled laboratory conditions. Incubation period was variable between conditions and, in general, incubation period was longest for each isolate at low temperatures. For isolate NC092ba, mean incubation period was longest at 12°C and did not vary significantly between cultivars. At 18°C, incubation period also did not vary between cultivars but it was shorter than at 12°C. For leaves infected at 24°C with isolate NC092ba, there was a significant difference in incubation period between cultivars, with Russet Burbank being longest. For leaves infected with isolate PSUPotb, incubation period was again longest at 12°C and there was no significant difference between cultivars. At 18°C and 24°C, incubation period was longer for Russet Burbank than for Kennebec or Red Norland. Furthermore, disease progress over time was more severe at higher temperatures for each isolate, across cultivars. Confirmation of pathogen presence in infected leaf tissue was successfully obtained using previously developed P. infestans specific primers in a standard Polymerase Chain Reaction (PCR) assay.

Phytophthora infestans

Incubation period

Oomycete

Solanum tuberosum

10.5325/jpennacadscie.85.4.0165

Cite

Citations (0)

Farmer surveys in Cambodia and Vietnam: cassava planting material use and exchange at national level with 4 district-level case studies 03. National survey responses.csv

Harvard Dataverse (2018)

Erik Delaquis K. F. Andersen Nami Minato Cu Thi Le Thuy Maria Eleanor Karssenberg

Anonymized responses of the 240 and 206 questionnaire respondents in Cambodia and Vietnam, respectively

10.7910/dvn/vvcx4j/qcp4hs

Cite

Citations (0)

Farmer surveys in Cambodia and Vietnam: cassava planting material use and exchange at national level with 4 district-level case studies

Harvard Dataverse (2018)

Erik Delaquis K. F. Andersen Nami Minato Cu Thi Le Thuy Maria Eleanor Karssenberg

The data includes national surveys of 15 districts in Vietnam and 16 districts in Cambodia, with 15 responses by district. Districts were selected based on high cassava production density and expert input from local government officials. National surveys covered the following themes: (a) respondent information, (b) seed use overview, and (c) field and household data. In addition to the aforementioned categories, the subnational surveys collected data on (d) quality, (e) affordability/profitability, and (f) information sources.

10.7910/dvn/vvcx4j

Cite

Citations (0)

Where to Invest Project Efforts for Greater Benefit: A Framework for Management Performance Mapping with Examples for Potato Seed Health

Phytopathology (2021)

Christopher E. Buddenhagen Yanru Xing Jorge Andrade-Piedra G. A. Forbes Peter Kromann

Policymakers and donors often need to identify the locations where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher-quality information may help to target the high-benefit locations, but often actions are needed with limited information. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of specific information compared with the results of acting without considering that information. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate the use of recursive partitioning, XGBoost, and Bayesian network models to characterize the relationships among seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high management performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can contribute to targeted development programs and support a culture of continuous improvement for interventions.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Value of information

Information needs

10.1094/phyto-05-20-0202-r

Cite

Citations (15)

Global Cropland Connectivity: A Risk Factor for Invasion and Saturation by Emerging Pathogens and Pests

BioScience (2020)

Yanru Xing John Fredy Hernández Nopsa K. F. Andersen Jorge Andrade-Piedra Fenton Beed

The geographic pattern of cropland is an important risk factor for invasion and saturation by crop-specific pathogens and arthropods. Understanding cropland networks supports smart pest sampling and mitigation strategies. We evaluate global networks of cropland connectivity for key vegetatively propagated crops (banana and plantain, cassava, potato, sweet potato, and yam) important for food security in the tropics. For each crop, potential movement between geographic location pairs was evaluated using a gravity model, with associated uncertainty quantification. The highly linked hub and bridge locations in cropland connectivity risk maps are likely priorities for surveillance and management, and for tracing intraregion movement of pathogens and pests. Important locations are identified beyond those locations that simply have high crop density. Cropland connectivity risk maps provide a new risk component for integration with other factors-such as climatic suitability, genetic resistance, and global trade routes-to inform pest risk assessment and mitigation.

Saturation (graph theory)

10.1093/biosci/biaa067

Cite

Citations (38)

Farmer surveys in Cambodia and Vietnam: cassava planting material use and exchange at national level with 4 district-level case studies 04. Subnational survey responses.csv

Harvard Dataverse (2018)

Erik Delaquis K. F. Andersen Nami Minato Cu Thi Le Thuy Maria Eleanor Karssenberg

Anonymized responses of the questionnaire respondents in Cambodia (Battambang n=100, Ratanakiri n=100) and Vietnam (Tay Ninh n=100, Dak Lak n=94), respectively

10.7910/dvn/vvcx4j/dlczlg

Cite

Citations (0)

CHAPTER 3: Adapting Disease Management Systems Under Global Change

The American Phytopathological Society eBooks (2020)

Karen A. Garrett Ricardo I. Alcalá-Briseño K. F. Andersen Robin A. Choudhury Wanita Dantes

Climate change is a challenge for plant pathologists and will likely affect their work in providing management tools for disease. The new emphasis on the availability of data in agriculture can help develop adaptation strategies for a community of practice in plant pathology. The authors also explore how countries such as Haiti can address their goals for improving infrastructure and production and the livelihoods of smallholder farmers as they navigate climate change adaptations.

10.1094/9780890546383.003

Cite

Citations (2)