Vini Garnica

Assistant Professor

Washington State University

I am a quantitative plant pathologist and Assistant Professor in the Department of Plant Pathology at Washington State University. My research sits at the intersection of plant disease epidemiology and data science, using Bayesian and hierarchical models to turn multi-environment trial data into practical disease-management tools for growers and agronomists. At WSU, I am extending this work to potato diseases across the Pacific Northwest.

Download my CV.

Interests

• Bayesian hierarchical modeling
• Disease prediction and epidemiology
• Meta-analysis with spatial modeling
• Multi-environment trial analysis
• Fungicide efficacy and ROI evaluation
• R Shiny applications for agriculture

Education

• Ph.D. in Plant Pathology (Statistics minor), 2024

  North Carolina State University, United States

• M.S. in Agronomy and Plant Pathology (Statistics minor), 2019

  University of Nebraska-Lincoln, United States

• B.Sc. in Agronomy, 2016

  Federal University of Viçosa, Brazil

Posts

Introducing MSE FindR

A Shiny app tool to extract mean square error from treatment means and post hoc test results.

Oct 26, 2022 3 min read

Shiny app Tutorial

Projects

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All Epidemiology Disease management Statistics

How many subsamples are enough?

In field trials, stand counts help evaluate how seed treatments affect crop establishment and, ultimately, yield. But counting every plant in every plot across dozens of trials isn’t practical—especially during peak season, when the team is stretched thin with SCN sampling and other early-season assessments.

Mapping and sampling wheat fields in North Carolina using R

Introduction In this post, I’ll walk you through a workflow for mapping and sampling agricultural fields in the U.S., using wheat in North Carolina as an example. Randomly selecting coordinates of agricultural fields is important when testing a model.

Data imputation for designed experiments

Whenever I get my hands on a new dataset (regardless of data being collected by me or someone else) and I find missing data, and that makes me frustrated. And do you know when that happens?

Analysis of quantitative factors in split-plot design

Analysis of Messy Data Vol.2, Milliken and Johnson, 2009. pg 440 In this experiment, researchers are interested in evaluating the effect of moisture and fertilizer on dry weight of wheat.

Publications

Explore publications by filtering here.

Performance and stability of winter wheat cultivars to Stagonospora nodorum blotch epidemics in multi-environment trials

A factor-analytic mixed-model analysis of 18 soft red winter wheat cultivars across 18 North Carolina environments, characterizing genotype-by-environment interaction in Stagonospora nodorum blotch epidemics and identifying stable, low-severity cultivars to support disease risk assessment.

Vinicius C. Garnica, Mohammad Nasir Shalizi, Peter S. Ojiambo

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Leveraging window-pane analysis with environmental factor loadings of genotype-by-environment interaction to identify high-resolution weather-based variables associated with plant disease

A framework to design high-resolution weather variables associated with genotype-by-environment interactions in plant disease, using Stagonospora nodorum blotch of wheat as a case study.

Vinicius C. Garnica, Peter S. Ojiambo

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MSE FINDR: A Shiny R application to estimate mean square error using treatment means and post hoc test results

A Shiny R tool enabling researchers to recover within-study variance from published treatment means and post hoc test results, allowing previously excluded studies to be included in meta-analyses and effect size calculations.

Vinicius C. Garnica, Denis A. Shah, Paul D. Esker, Peter S. Ojiambo

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A global-temporal analysis on Phytophthora sojae resistance gene efficacy

A global meta-analysis reveals a significant loss of efficacy in widely deployed Rps genes against Phytophthora sojae and an increase in pathogen diversity, highlighting the urgent need to integrate novel resistance genes into soybean cultivars.

Austin G. McCoy, Richard R. Belanger, Carl A. Bradley, Daniel G. Cerritos-Garcia, Vinicius C. Garnica, Loren J. Giesler, Pablo E. Grijalba, Eduardo Guillin, Maria A. Henriquez, Yong Min Kim, Dean K. Malvick, Rashelle L. Matthiesen, Santiago X. Mideros, Zachary A. Noel, Alison E. Robertson, Mitchell G. Roth, Clarice L. Schmidt, Damon L. Smith, Adam H. Sparks, Darcy E. P. Telenko, Vanessa Tremblay, Owen Wally, Martin I. Chilvers

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Impact of residual soil-applied pre-emergence herbicides on soybean seedling disease incidence under field conditions

A multi-environment field study evaluating residual pre-emergence herbicides and soybean seedling diseases, showing no consistent effect of herbicides on root rot severity or yield across environments with varying pathogen communities.

Vinicius C. Garnica, Amit J. Jhala, Robert M. Harveson, Loren J. Giesler

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Comparison of Phytophthora sojae populations in Iowa and Nebraska to identify effective Rps genes for Phytophthora stem and root rot management

A regional survey of Phytophthora sojae pathotypes reveals widespread virulence against commonly deployed Rps1a, Rps1c, and Rps1k genes in Iowa and Nebraska, highlighting a critical mismatch between commercial cultivar resistance and current pathogen populations.

Rashelle L. Matthiesen, Clarice Schmidt, Vinicius C. Garnica, Loren J. Giesler, Alison E. Robertson

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Soybean canopy coverage, population, and yield responses to seed treatment and cultivar resistance to Phytophthora sojae in Nebraska

A field study in Nebraska evaluating the effects of seed treatment and cultivar resistance on soybean emergence, canopy coverage, and yield under Phytophthora stem and root rot conditions, highlighting the combined benefits of host resistance and seed-applied fungicides.

Vinicius C. Garnica, Loren J. Giesler

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