Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/15063
Title: Use of proximal sensors to evaluate at the sub-paddock scale a pasture growth-rate model based on light-use efficiency
Contributor(s): Rahman, Muhammad Moshiur (author)orcid ; Lamb, David (author); Stanley, John (author); Trotter, Mark (author)
Publication Date: 2014
DOI: 10.1071/CP14071
Handle Link: https://hdl.handle.net/1959.11/15063
Abstract: Monitoring pasture growth rate is an important component of managing grazing livestock production systems. In this study, we demonstrate that a pasture growth rate (PGR) model, initially designed for NOAA AVHRR normalised difference vegetation index (NDVI) and since adapted to MODIS NDVI, can provide PGR at spatial resolution of ~2 m with an accuracy of ~2 kg DM/ha.day when incorporating in-situ sensor data. A PGR model based on light-use efficiency (LUE) was combined with 'in-situ' measurements from proximal weather (temperature), plant (fraction of absorbed photosynthetically active radiation, fAPAR) and soil (relative moisture) sensors to calculate the growth rate of a tall fescue pasture. Based on an initial estimate of LUEmax for the candidate pasture, followed by a process of iterating LUEmax to reduce prediction errors, the model was capable of estimating PGR with a root mean square error of 1.68 kg/ha.day (R² = 0.96, P-value ≈ 0). The iterative process proved to be a convenient means of estimating LUE of this pasture (1.59 g DM/MJ APAR) under local conditions. The application of the LUE-PGR approach to developing an in-situ pasture growth rate monitoring system is discussed.
Publication Type: Journal Article
Source of Publication: Crop and Pasture Science, 65(4), p. 400-409
Publisher: CSIRO Publishing
Place of Publication: Australia
ISSN: 1836-0947
1836-5795
Field of Research (FOR): 070104 Agricultural Spatial Analysis and Modelling
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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Appears in Collections:Journal Article
School of Environmental and Rural Science

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