Sense-T: Sensor smart irrigation

Project report


McCarthy, Alison, Shippam, Ralph and Agustina, Lidya. 2017. Sense-T: Sensor smart irrigation. Australia. Sense-T.
Title

Sense-T: Sensor smart irrigation

Report TypeProject report
AuthorsMcCarthy, Alison (Author), Shippam, Ralph (Author) and Agustina, Lidya (Author)
Institution of OriginUniversity of Southern Queensland
Number of Pages6
Year2017
PublisherSense-T
Place of PublicationAustralia
Web Address (URL)http://www.sense-t.org.au/latest-news/news-items/focus-on-the-sensor-smart-irrigation-project
Abstract

The Sense-T Sensor-Smart Irrigation app predicts daily soil-water in the infield spatial zones using FAO-56. The irrigation requirement is determined in each zone from the difference between the predicted soil-water and field capacity. Incorporation of a biophysical crop production model enhances prediction capability for crop yield and impacts of irrigation management decisions on production and water use efficiency over the prediction horizon.Crop production models can be calibrated to reflect field conditions using machine vision and imagery from infield or remote sensors. This section presents an investigation of crop production models for incorporation into the app for production prediction.

Keywordsirrigation; crop production; crop yield; remote sensors
ANZSRC Field of Research 2020300206. Agricultural spatial analysis and modelling
300403. Agronomy
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Byline AffiliationsNational Centre for Engineering in Agriculture
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