john_conner

The ToowoombaTrio's GovHack 2016 entry

https://github.com/toowoombatrio/john_conner

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
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Scientific vocabulary similarity
Low similarity (9.9%) to scientific vocabulary

Keywords

govhack govhack2016 heat-stress horticulture temperature

Last synced: 6 months ago · JSON representation

Repository

The ToowoombaTrio's GovHack 2016 entry

Basic Info

Host: GitHub
Owner: ToowoombaTrio
License: mit
Language: HTML
Default Branch: master
Homepage: https://toowoombatrio.github.io/John_Conner/
Size: 102 MB

Statistics

Stars: 2
Watchers: 3
Forks: 1
Open Issues: 0
Releases: 0

Topics

govhack govhack2016 heat-stress horticulture temperature

Created over 9 years ago · Last pushed over 8 years ago

Metadata Files

Readme License Codemeta

John_Conner

GovHack 2016

Note

This repository is a historical archive of the original John Conner project that was constructed during #GovHack2016 by the ToowoombaTrio. Any further development of the package is being conducted in the WINS repository. This R package and repository will not be updated further.

The John Conner project was initiated by the Toowoomba Trio to tackle a major and growing problem faced by Queensland vegetable growers. This challenge is Identifying and responding to heat stress in their crops. High temperatures can cause considerable stress to crops, reducing yields and the quality of the produce grown. However, if the stress is identified early enough remedial action can be taken to minimise the damage and save the crop. The John Conner project provides a timely warning system for farmers when a heat stress event has likely occurred. Please watch our YouTube video describing the John Conner Project. The John Conner project is built in the R environment, an open source statistical programing environment. It utilises the QLD SILO patch point weather data, available from the QLD government data portal, and models hourly data using a temperature from chillR. This downscaling is validated against the BoM hourly temperature data set, an official #GovHack 2016 data set, to show that there is good agreement between the modelled hourly data and the observed BoM data.

Install this package

To install this R package and recreate what we've done this weekend for Govhack2016. Install the package and check out our vignette that details how to recreate what we've done.

r install.packages("devtools", dependencies = TRUE) devtools::install_github("ToowoombaTrio/John_Conner")

Owner

Name: Toowoomba Trio
Login: ToowoombaTrio
Kind: organization
Email: adamhsparks@gmail.com
Location: Toowoomba, QLD, AU

Repositories: 1
Profile: https://github.com/ToowoombaTrio

The ToowoombaTrio, hacking since 2016!

CodeMeta (codemeta.json)

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GitHub Events

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Dependencies

DESCRIPTION cran

R >= 3.2.0 depends
chillR * imports
data.table * imports
doParallel * imports
fields * imports
foreach * imports
ggplot2 * imports
iterators * imports
lubridate * imports
mailR * imports
parallel * imports
plyr * imports
raster * imports
readr * imports
reshape * imports
settings * imports
tidyr * imports
viridis * imports
knitr * suggests
rmarkdown * suggests

ecosyste.ms

Data

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Indexes

Applications

Experiments

Open Source Science