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- W2020395972 abstract "Efficiently measuring and mapping green herbage mass using remote sensing devices offers substantial potential benefits for improved management of grazed pastures over space and time. Several techniques and instruments have been developed for estimating herbage mass, however, they face similar limitations in terms of their ability to distinguish green and senescent material and their use over large areas. In this study we explore the application of an active, near infrared and red reflectance sensor to quantify and map pasture herbage mass using a range of derived spectral indices. The Soil Adjusted Vegetation Index offered the best correlation with green dry matter (GDM), with a root mean square error of prediction of 288 kg/ha. The calibrated sensor was integrated with a Global Positioning System on a 4-wheel motor bike to map green herbage mass. An evaluation of representative, truncated transects indicated the potential to conduct rapid assessments of the GDM in a paddock, without the need for full paddock surveys." @default.
- W2020395972 created "2016-06-24" @default.
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- W2020395972 date "2010-01-01" @default.
- W2020395972 modified "2023-10-15" @default.
- W2020395972 title "Evaluating an active optical sensor for quantifying and mapping green herbage mass and growth in a perennial grass pasture" @default.
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- W2020395972 doi "https://doi.org/10.1071/cp10019" @default.
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