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Title
PA meets Lot - Integrating in-situ Sensor Data and Biomass Prediction Tools for Crops and Pastures
Fields of Research (FoR) 2008:
Publication Date
2014
Socio-Economic Objective (SEO) 2008
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
Source of Publication
17th Precision Agriculture Symposium in Australasia Proceedings, p. 100-104
Publisher
Society of Precision Agriculture Australia (SPAA)
Place of Publication
Adelaide, Australia
Fields of Research (FoR) 2020
Socio-Economic Objective (SEO) 2020
HERDC Category Description
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