McCarthy, Alison and Shippam, Ralph and Agustina, Lidya (2017) Sense-T: Sensor smart irrigation. Project Report. Sense-T , Australia. [Report]
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.
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| Item Type: | Report (Project Report) |
|---|---|
| Item Status: | Live Archive |
| Additional Information: | Files associated with this item cannot be displayed due to confidentiality and copyright restrictions. |
| Faculty / Department / School: | Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering |
| Date Deposited: | 24 Nov 2017 04:01 |
| Last Modified: | 24 Nov 2017 04:01 |
| Uncontrolled Keywords: | irrigation; crop production; crop yield; remote sensors |
| Fields of Research : | 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling 07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070302 Agronomy |
| Socio-Economic Objective: | D Environment > 96 Environment > 9609 Land and Water Management > 960905 Farmland, Arable Cropland and Permanent Cropland Water Management |
| URI: | http://eprints.usq.edu.au/id/eprint/30766 |
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