2026 NCCC170 Annual Meeting
Cargill, Lewisburg, Ohio
Thursday, June 11, 2026
8:00 AM
Registration, check-in, coffee
8:45 AM
Welcome to NCCC170 2026 and Cargill
Neil Paton, Principal Statistician - Cargill, Lewisburg, OH, US
Neil Paton, Principal Statistician - Cargill, Lewisburg, OH, US
9:00 AM
Matrix-free High Dimensional Gaussian Simulation
Somak Dutta, Department of Statistics, Iowa State University, Ames, IA, US
Sampling from high-dimensional Gaussian distributions arises frequently in both Bayesian and frequentist inference. Such sampling is typically carried out using dense matrix factorizations, which can be computationally prohibitive and difficult to scale.
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9:30 AM
Deep Learning and Machine Learning Frameworks for Sorghum Yield Forecasting Using UAV and Laboratory Imagery
Md Abdullah Al Bari, Department of Agronomy, Kansas State University, and Department of Plant and Environmental Sciences, New Mexico State University
Department of Computer Science, Kansas State University
Trevor D. Witt, Department of Entomology, Kansas State University
Scott Bean, Center for Grain and Animal Health Research, ARS-USDA, Manhattan, KS
S.V. Krishna Jagadish, Department of Plant and Soil Science, Texas Tech University
Terry Felderhoff*, Department of Agronomy, Kansas State University
Recent advances in artificial intelligence (AI), graphics processing units (GPUs), and open-source computing platforms have accelerated the application of machine learning (ML) and deep learning (DL) approaches in agricultural research. These technologies enable rapid extraction of phenotypic information from imagery and offer new opportunities for digital phenotyping and yield forecasting in plant breeding programs.
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10:00 AM
Environmental Survival of Avian Metapneumovirus on Common Agricultural Surfaces
Aaron Rendahl, College of Veterinary Medicine, University of Minnesota
Avian metapneumovirus (aMPV) is a major respiratory pathogen of poultry worldwide. While it is known to be transmitted through the air, the contribution of surface contamination to viral spread is unknown.
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10:30 AM
Morning break
11:00 AM
Revisiting Meta-analytic Strategies for Latin Square Designs
Robert J. Tempelman, Department of Animal Science, Michigan State University
Meta-analyses studies continue to be published within the Journal of Dairy Science (JDS), with much of the corresponding analysis techniques developed in some landmark JDS papers. These techniques have served the JDS research community reasonably well with respect to the estimation of overall treatment effects or slopes and their standard errors in completely randomized designs (CRD).
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11:30 AM
Robust Variance Estimation in Meta-analysis with correlated effect sizes
Laurence V. Madden, Ohio State University
Pierce A. Paul, Ohio State University
Felipe Dalla Lana, Louisiana State University AgCenter
Meta-analysis has grown greatly in popularity in the agricultural sciences over the past quarter-century for synthesizing the results from multiple independent studies. In a classical random-effects meta-analysis, there is one estimated effect size per study, such as a mean difference, log response ratio, log odds, slope, or correlation coefficient.
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12:00 PM
Lunch
1:30 PM
Best Practices for GLMM Implementation: Group Updates and Planning
Nora M. Bello, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Bruce A. Craig, Department of Statistics, Purdue University
Xin Dai, Animal, Dairy & Veterinary Sciences, Utah State University
Philip Dixon, Department of Statistics, Iowa State University
Susan L. Durham, Department of Watershed Sciences and Ecology Center, Utah State University
Conor G. Fair, College of Agricultural and Environmental Sciences, University of Georgia
Réka Howard, Department of Statistics, University of Nebraska-Lincoln
Clark Kogan, Department of Pharmaceutical Sciences, Washington State University
Josefina Lacasa, Department of Statistics, Kansas State University
Raúl E. Macchiavelli, College of Agricultural Sciences, University of Puerto Rico
Daniel G. Palmer, StatsCraft, Spokane, WA
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences, University of Idaho
Quentin D. Read, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Walter W. Stroup, Department of Statistics, University of Nebraska-Lincoln
Our ongoing project initiated in 2024 and investigates best practices for the application of Generalized Linear Mixed Models (GLMMs), including topics in statistical modeling and software implementation. As we transition into the project’s next phase, this meeting will serve as a working session to review our progress and plan our future steps.
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3:00 PM
Afternoon break
3:30 PM
New Resource: Online Guide for Implementing Linear Mixed Model
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences University of Idaho
Linear mixed models (LMMs) are commonly used for analyzing agricultural studies. SAS, R and GUI-based tools (e.g. SPSS) are popular options for implementing LMMs. The documentation for implementing LMMs in SAS is detailed, easy to find and navigate, and provides numerous helpful examples.
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4:00 PM
Agricultural Affairs Regional/Multi-state Project and DC Update
Jane Schuh, Associate Dean, Kansas Agricultural Experiment Station
An overview of the role and importance of multistate research within the region, emphasizing its value in fostering collaboration, leveraging shared resources, and delivering impactful outcomes across land grant institutions. It outlines the funding structure under the Hatch Act, current federal funding considerations, and the organizational framework of agInnovation North Central.
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4:30 PM
Assessing Accuracy and Precision of Measurement and Sampling Schemes in Aquaculture Research
Nora Bello, USDA Agricultural Research Service Northeast Area Office, Beltsville, MD
Gary Burr, USDA Agricultural Research Service, National Cold Water Marine Aquaculture Center (NCWMAC), Franklin, ME
Brian C. Peterson, USDA Agricultural Research Service, National Cold Water Marine Aquaculture Center (NCWMAC), Franklin, ME
Measurement and sampling techniques commonly used in aquaculture research studies are varied and range from bulk-tank measurements (i.e. netting fish from a tank into a smaller calming receptacle on a scale to determine the total weight of fish in a tank) to individual weighing of all or a netted subset of fish from a tank.
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5:00 PM
Adjourn
Friday, June 12, 2026
9:00 AM
AI Discussion Panel
Bruce Craig, Department of Statistics, Purdue University
Neil Paton, Principal Statistician - Cargill, Lewisburg, OH
Bruce Craig, Department of Statistics, Purdue University
Neil Paton, Principal Statistician - Cargill, Lewisburg, OH
10:00 AM
Break
10:30 AM
NCCC-170 Business meeting
Announcements:
Thank you to our local host Neil Paton and program chair Conor Fair A special thank you to Angela Vencil for all the catering and local arrangements NCCC170 website https://nccc170.
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12:00 PM
Lunch
1:00 PM