Rahman, Muhammad Moshiur

Lamb, David

Stanley, John

Trotter, Mark

2014

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).

17th Precision Agriculture Symposium in Australasia Proceedings, p. 100-104

https://hdl.handle.net/1959.11/20180

Society of Precision Agriculture Australia (SPAA)

PA meets Lot - Integrating in-situ Sensor Data and Biomass Prediction Tools for Crops and Pastures

Conference Publication

Publication