Agronomic Forecasting Lab Unversity of Illinois at Urbana - CHampaign

News

  • Our latest publication

    Our latest publication tilted "A comprehensive uncertainty quantification of large-scale process-based crop modeling frameworks" is now formally accpeted and can be viewed here.

    06/29/2021
  • Fellowship award

    Congrats to Marissa Kivi for wining the Kraft/Frerichs graduate fellowship award. Well deserved !

    05/20/2021
  • Precision Agriculture Talent Pipeline Initiative

    A grant proposal led by our group was awarded $200k by CHS foundation to develop a precision agriculture talent pipline. This program aims to ‘even playing field’ for young and brilliant under-represented minorities seeking for an opportunity in precision Agriculture.

    11/23/2020
  • Open Positions

    We are looking for motivated students with a background in statistics and computer coding to work on interesting data fusion crop modeling projects. Please contact me to learn more about the available positions

    11/10/2020

Vision

The long-term vision for our lab is to synthesize, analyze and create new value from the rich data streams generated by all phases of agricultural production. We will work towards developing novel data-driven approaches at the interface of computer science, statistics and crop science with the goal of improving and protecting our food system. In addition, we are always excited to welcome new graduate and undergraduate students with research interests aligned with the focus of the lab.

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Projects

Forecasting planting and harvesting windows of opportunities by predicting soil moisture content through Sequantial Data Assimilation (SDA)

In this project, we are leverging our APSIM - SDA workflow to predict next windows of opportunities for field operations including planting and harvesting.

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Improving Soil N cycle simulation through sequential data assimilation

We are interested in assimilating in-situ soil moisture and soil temperature data obtained from soil sensors into APSIM, a robust process-based crop model, to see if the model is better able to predict soil N and yield at Energy Farm when compared to a model run without data assimilation

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Uncertainty assessment of large-scale crop simulation models

In this study we use a multi-model regional crop simulatin platform to study the contribution of different sources of uncertainty in total variance simulated around crop yield and nitrate leaching for corn and soybean.

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Tools/Data Products

Not all tools and data products presented in this section is developed in our lab.


Yield response to biochar

This tool allows you to estimate the probability of crop yield increase following Biochar application for the state of Illinois.

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Rye Decision Support Tool

This tool helps farmers with predicting rye phenology and specifically termination date.

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Corn Productivity Index

This tool allows you to explore the new corn productivity index across the U.S Midwest.

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NO3 leaching susceptibility Index

This tool allows you to explore the new Nitrate leaching susceptibility index across the U.S Midwest.

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Teaching

Digital Agriculture

Digital agriculture is concerned with the use of digital technologies for understanding underlying processes and solving agricultural issues. The ultimate goal of the Digital Agriculture course is to help students develop an understanding around three main components in digital agriculture including:

1) Statistical modeling and machine learning
2) Process-based crop modeling and
3) Remote sensing, where they all revolve around crop physiology and production.

In this course students will start by learning the fundamentals of crop physiology and familiarizing themselves with the current major issues around crop production in large. Then, students will learn about three powerful tools including statistical modeling, process-based modeling and remote sensing to addresses those challenges. This section is restricted to online programs only.

Regression Analysis

Publications

A comprehensive uncertainty quantification of large-scale process-based crop modeling frameworks

Hamze Dokoohaki, et al., . 2021/6/29. Environmental Research Letters

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Nonlinear Regression Models and Applications

Fernando Miguez, Sotirios Archontoulis, Hamze Dokoohaki. 2017/8/3. Applied Statistics in Agricultural, Biological, and Environmental Sciences

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Where should we apply biochar?

Hamze Dokoohaki, Fernando E Miguez, David Laird, Jerome Dumortier. 2019/3/29.Environmental Research Letters

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Coupling and testing a new soil water module in DSSAT CERES-Maize model for maize production under semi-arid condition

Hamze Dokoohaki, Mahdi Gheysari, Sayed-Farhad Mousavi, Shahrokh Zand-Parsa, Fernando E. Miguez, Sotirios V. Archontoulis, Gerrit Hoogenboom. 2016/1/1. Agricultural Water Management

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Use of inverse modelling and Bayesian optimization for investigating the effect of biochar on soil hydrological properties

Hamze Dokoohaki, Fernando E Miguez, Sotirios Archontoulis, David Laird. 2018/9/30. Agricultural Water Management

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Assessing the biochar effects on selected physical properties of a sandy soil: an analytical approach

Hamze Dokoohaki, Fernando E Miguez, David Laird, Robert Horton, Andres S Basso.2017/7/4 . Communications in Soil Science and Plant Analysis

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Applying the CSM-CERES-Wheat model for rainfed wheat with specified soil characteristic in undulating area in Iran

Hamze Dokoohaki, Mahdi Gheysari, Abdolmohammad Mehnatkesh, Shamsollah Ayoubi.2015 .Iranian Water Research Journal

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Effects of different irrigation regimes on soil moisture availability evaluated by CSM-CERES-Maize model under semi-arid condition

Hamze Dokoohaki, Mahdi Gheysari, Sayed-Frahad Mousavi, Gerrit Hoogenboom. 2017/7/1 . Ecohydrology & Hydrobiology

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Flow and Sediment Transport Modeling in Rivers

Masoomeh Fakhri, Hamze Dokohaki, Saeid Eslamian, Iman Fazeli Farsani, Mohammad Reza Farzaneh. 2014/3.Handbook of Engineering Hydrology: Modeling, Climate Change, and Variability

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Our Lab

We are always excited to welcome new graduate and under graduate students with research interests aligned with the focus of the lab.

Hamze Dokoohaki
Principle Investigator
Teerath Rai
Postdoctoral associate
Marissa Kivi
Graduate Student
Smriti Kandel
Graduate Student
Alexandra Jakucewicz
Research Assistant

Contact Us

N315 Turner Hall 1102 S. Goodwin Ave. Urbana, IL 61801