This is an interactive web app designed to run sampling simulation in a food safety context. The simulation model and the web app were built by Xianbin (Eric) Cheng, a graduated PhD student, and are maintained by researchers of the Stasiewicz Food Safety Lab under the department of Food Science and Human Nutrition at the University of Illinois at Urbana-Champaign . For more information about the Stasiewicz Food Safety Lab, please click this link .

Who We Are

We are a group of researchers in the department of Food Science and Human Nutrition at the University of Illinois at Urbana-Champaign, dedicated to using risk analysis, at the interface between microbiology and engineering, to analyze and develop solutions to applied problems in food safety and security. We endeavor to create a world where everyone and everywhere is food secure.


We aim to provide a tool to simulate bulk sampling in 1D (e.g. Dairy Powders), 2D (e.g. a produce field) or 3D (e.g. a grain container) scenarios and evaluate the performance of any specific sampling plan.

Funding Sources

This web app is the product of three research projects funded by International Life Sciences Institute (ILSI), The Institute for the Advancement of Food and Nutrition Sciences (IAFNS), and Center for Produce Safety (CPS).

Major Outputs

This simulation model and web app have been used extensively in the following research articles or posters.

  • Cheng, X., Stasiewicz, M. J. (2021). Evaluation of the impact of skewness, clustering, and probe sampling plan on aflatoxin detection in corn. Risk Analysis. Link
  • Stasiewicz, M. J., Wiedmann, M. (2019). Simulation analysis of in-field produce sampling for risk-based sampling plan development. CPS. Link
  • Quintanilla Portillo J., Cheng X., Belias A.M., Weller D.L., Wiedmann M., Stasiewicz, M. J. (2023). A Validated Preharvest Sampling Simulation Shows that Sampling Plans with a Larger Number of Randomly Located Samples Perform Better than Typical Sampling Plans in Detecting Representative Point-Source and Widespread Hazards in Leafy Green Fields Link
  • Kim M.,Reyes G.A., Cheng X., Stasiewicz, M. J. (2023). Simulation Evaluation of Power of Sampling Plans to Detect Cronobacter in Powdered Infant Formula Production Link


The current version is 4.0.2 and was updated on: 06/16/2023. Previous versions and source code can be found on GitHub ( link ).


Please feel free to contact us if you have any questions.

Matthew Stasiewicz : Principal Investigator, Assistant Professor, PhD. Email: mstasie@illinois.edu
Xianbin (Eric) Cheng Corn Sampling Lead, Email: ericxbcheng@gmail.com LinkedIn
Jorge Quintanilla : Produce Sampling Lead. Email: jfq@illinois.edu
Minho Kim : Powder Sampling Lead. Email: minho3@illinois.edu


Q1: Which type of product do you want to simulate?

Visualization for one iteration

Powder Sampling Input Parameters

Iteration section

Visualization for one iteration

2D Input Parameters

Iteration section

Visualization for one iteration

3D Input Parameters

Cluster covariance matrix

Iteration section

Visualization for one iteration

Selected parameters

Visualization for multiple iterations

Download the simulation data

Click the following button to download the csv file that contains the simulation data.


Variable interpretation

The csv file contains a header with multiple variables. The interpretation is as follows.

seed : The random seed that determines the locations of contaminated kernels.
P_rej : Probability of rejection
Paccept : Probability of acceptance = 1 - P_rej
param : The primary tuning parameter
param2 : The secondary tuning parameter
c_true : The true mycotoxin concentration in the container (ppb).