Forecasting Model Tools: API and Dashboard

This API leverages the power of environmental data to predict the likelihood of diseases like Tarspot, Spore and Gray Leaf Spot on corn crops.

Features

• Predicts the probability of disease incidence based on key environmental variables.
• Customizable action thresholds that allow users to define risk levels for interventions.
• Returns the probability and risk classification for the given thresholds.

Dashboard

Visit our dashboard here

API Endpoints

Base URL: Forecast Crop Disease API

Endpoints:

• /predict_tarspot_risk
  Predicts the probability and risk level for Tarspot.

• /predict_gray_leaf_spot_risk
  Predicts the probability and risk level for Gray Leaf Spot.

• /predict_sporecaster_risk
  Predicts the probability and risk level for Spore.

Method: POST

Response: A JSON object containing the predicted probability of tar spot incidence and the associated risk level.

To install

git clone https://github.com/UW-Madison-DSI/corn_disease_forecast_api.git
cd corn_disease_forecast_api

Usage

See example of how to do an api call on this tool HERE

Project Structure

├── LICENSE
├── README.md                       <- The top-level README for developers using this project.
├── plumber.R                       <- Logic to create API
├── R                               <- Main functionalities for API
│   ├── crop_mangm_validations.R      <- Crop management validations
│   ├── logit_function.R              <- Core functions for forecasting disease api
│   ├── var_schema.R                  <- Variables schema
├── materials                       <- Examples of API calls and plug in with Wisconet
│   ├── call_wisconet                 <- Wisconet call example
│   ├── docs                          <- Documentation of the schema
│   ├── example                       <- Examples to call the API
├── app                             <- Shinny dashboard code.
│   ├── app.R                         <- app logic, ui and server
│   ├── functions                     <- API functions
│   │   ├── logic.R                       <- Logic to call the Wisconet Station weather data and call the forecasting models on the preparation of the inputs
│   │   ├── stations.R                    <- List of stations currently active from Wisconet  
├── test                            <- Code Testing modules
│   ├── testthat.R    

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• This work is part of an Open-Source initiative from the Open Source Program Office at the University of Madison Wisconsin, aimed at fostering collaboration and innovation in forecasting tools.
• The models presented are based on plant pathology research in the University of Madison Wisconsin, paper: Nature Scientific Reports, 2023
• This software was created by the Data Science Institute at the University of Wisconsin-Madison