Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/20180
Title: PA meets Lot - Integrating in-situ Sensor Data and Biomass Prediction Tools for Crops and Pastures
Contributor(s): Rahman, Muhammad Moshiur  (author)orcid ; Lamb, David  (author); Stanley, John  (author); Trotter, Mark  (author)
Publication Date: 2014
Handle Link: https://hdl.handle.net/1959.11/20180
Abstract: Monitoring pasture growth rate is an important component of managing grazing livestock production systems. In this study we demonstrate a pasture growth rate (PGR) model, initially designed for very large scale satellite imagery, can be operated at a scale of metres when incorporating in-situ sensor data. A light use efficiency (LUE)-based PGR model was combined with in-situ measurements from proximal weather (temperature), plant (fAPAR) and soil (relative moisture) sensors to calculate the growth rate of a tall fescue pasture. When incorporating in-situ measurements of temperature and moisture index, the model provided an accuracy (RMSE) of 1.68 kg/ha.day (R² = 0.96, p-value ≈ 0).
Publication Type: Conference Publication
Conference Name: 17th Symposium on Precision Agriculture in Australasia, Adelaide, Australia, 2nd - 3rd September, 2014
Conference Details: 17th Symposium on Precision Agriculture in Australasia, Adelaide, Australia, 2nd - 3rd September, 2014
Source of Publication: 17th Precision Agriculture Symposium in Australasia Proceedings, p. 100-104
Publisher: SPAA Precision Agriculture Association
Place of Publication: Adelaide, Australia
Field of Research (FOR): 070399 Crop and Pasture Production not elsewhere classified
070302 Agronomy
HERDC Category Description: E2 Non-Refereed Scholarly Conference Publication
Other Links: http://sydney.edu.au/agriculture/pal/documents/2014/17th%20PA%20Symposium%20Proceedings.pdf
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School of Environmental and Rural Science

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