A two-part Zoom workshop

Part 1: Friday May 3, 10:30a - 12:00p PDT

Part 2: Friday May 10, 10:30a - 12:00p PDT

Click Here to Register

 

Overview:

Degree day models are widely used in agriculture to predict the development of plants and insects. These models are based on research that quantify how growth rates and the timing of phenology events are correlated with accumulated exposure to heat. Combined with live weather data, these models can be extremely useful for crop management such as integrated pest management and harvesting. These same models can also be fed by data from climate models to study the effects of climate change.

This two-part workshop will teach participants how to turn a degree day model into a web-based decision support tool using R (example). Part I will cover importing weather data thru APIs, common data wrangling operations, computing degree days, and applying the model. Part II will demonstrate how to use the Shiny R package to turn your degree model into a simple decision support tool that you can publish online.

Agenda:

Part I. Weather Data and Degree Days
Friday May 3, 2024
10:30a - 12:00p PDT

• Overview of degree day models
• Accessing weather data in R
• Data wrangling
• Computing degree days
• Applying degree days models

Part II. Building a Shiny App
Friday May 10, 2024
10:30a - 12:00p PDT

• Introduction to Shiny
• Reactive programming 101
• Build a basic Shiny app
• Input and output widgets
• Publishing your Shiny app

Participants are encouraged to sign-up for both sessions. Part II will build upon Part I. Participants who miss Part I will be expected to watch the recording in order to understand what we're doing in Part II.

Audience:

• Cooperative Extension personnel
• UC students & faculty
• AIFS affiliates (including UC Davis, UC Berkeley, Cornell, U. Illinois, & USDA)
• Agricultural researchers and practitioners

When & Where:

Part 1: Friday May 3, 2024. 10:30a - 12:00p PDT

Part 2: Friday May 10, 2024. 10:30a - 12:00p PDT

This is a virtual workshop. You will receive a Zoom link via email prior to the training day.

Cost: This is a free workshop.

Requirements:

No experience with degree day models is needed, but some experience with R is expected for those participants who wish to complete the hands-on exercises. Beginners are welcome to watch but this is not an introductory R workshop.

The hands-on exercises will include a mix of "ready to go" code and short challenge questions. Code examples will make extensive use of data wrangling techniques from the tidyverse, including dplyr, tidyr, and lubridate. If these packages are completely unfamiliar to you, you are encouraged to review prior workshop recordings including Intro to R (Parts 3 and 4), and/or Computing Agroclimate Metrics in R.

Participants will need to have a recent version of R, RStudio Desktop, and required packages installed prior to the workshop (instructions will be provided in the welcome email). Participants are also encouraged, but not required, to create free accounts on CIMIS, Synoptic, and ShinyApps.io.

Having an external monitor is strongly recommended, so you can view the instructor's slides and demo on one monitor, while working in RStudio on the other.

Registration:

Click here to register.

This course content is the result of a collaborative effort between UC ANR IGIS Statewide Program, the USDA-NIFA/NSF AI Institute for Next Generation Food Systems (AIFS), and the UC Berkeley Geospatial Innovation Facility (GIF).

For information regarding other upcoming IGIS workshops, please see IGIS training or contact Sean Hogan at sdhogan@ucanr.edu