Potential of imaging spectroscopy as tool for pasture management

The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spa...

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Main Authors: Schut, Antonius, Lokhorst, C., Hendriks, M., Kornet, J., Kasper, G.
Format: Journal Article
Published: Blackwell Publishing 2005
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/15483
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author Schut, Antonius
Lokhorst, C.
Hendriks, M.
Kornet, J.
Kasper, G.
author_facet Schut, Antonius
Lokhorst, C.
Hendriks, M.
Kornet, J.
Kasper, G.
author_sort Schut, Antonius
building Curtin Institutional Repository
collection Online Access
description The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spatial (0.28-1.45 mm2) and spectral resolution. Data from two experiments with Lolium perenne L. mini-swards were used where the degree of sward damage or N-fertilizer application varied. Regression models were calibrated and validated and the potential reduction in prediction error with multiple observations was estimated. The mean prediction errors for DM mass, DM content and N, total sugars, ash and crude fibre concentrations were 235-268 kg ha-1, 9.6-16.8 g kg-1, 2.4-3.4 g kg DM-1, 16.2-27.7 g kg DM-1, 5.8-6.5 g kg DM-1 and 8.4-10.4 g kg DM-1 respectively. The predictions for concentrations of P, K, S and Mg allowed identification of deficiency levels, in contrast to the concentrations of Na, Zn, Mn and Ca which could not be predicted with adequate precision. Prediction errors of DM mass maybe maximally reduced to 95-142 kg ha-1 with 25 replicate measurements per field.It is concluded that imaging spectroscopy can provide an accurate means for assessment of DM mass of standing grass herbage. Predictions of macro nutrient content and feeding value were satisfactory. The methodology requires further evaluation under field conditions.
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spelling curtin-20.500.11937-154832017-09-13T15:56:51Z Potential of imaging spectroscopy as tool for pasture management Schut, Antonius Lokhorst, C. Hendriks, M. Kornet, J. Kasper, G. herbage mass imaging spectroscopy pasture management feeding value herbage - quality mineral composition of herbage The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spatial (0.28-1.45 mm2) and spectral resolution. Data from two experiments with Lolium perenne L. mini-swards were used where the degree of sward damage or N-fertilizer application varied. Regression models were calibrated and validated and the potential reduction in prediction error with multiple observations was estimated. The mean prediction errors for DM mass, DM content and N, total sugars, ash and crude fibre concentrations were 235-268 kg ha-1, 9.6-16.8 g kg-1, 2.4-3.4 g kg DM-1, 16.2-27.7 g kg DM-1, 5.8-6.5 g kg DM-1 and 8.4-10.4 g kg DM-1 respectively. The predictions for concentrations of P, K, S and Mg allowed identification of deficiency levels, in contrast to the concentrations of Na, Zn, Mn and Ca which could not be predicted with adequate precision. Prediction errors of DM mass maybe maximally reduced to 95-142 kg ha-1 with 25 replicate measurements per field.It is concluded that imaging spectroscopy can provide an accurate means for assessment of DM mass of standing grass herbage. Predictions of macro nutrient content and feeding value were satisfactory. The methodology requires further evaluation under field conditions. 2005 Journal Article http://hdl.handle.net/20.500.11937/15483 10.1111/j.1365-2494.2005.00449.x Blackwell Publishing restricted
spellingShingle herbage mass
imaging spectroscopy
pasture management
feeding value
herbage - quality
mineral composition of herbage
Schut, Antonius
Lokhorst, C.
Hendriks, M.
Kornet, J.
Kasper, G.
Potential of imaging spectroscopy as tool for pasture management
title Potential of imaging spectroscopy as tool for pasture management
title_full Potential of imaging spectroscopy as tool for pasture management
title_fullStr Potential of imaging spectroscopy as tool for pasture management
title_full_unstemmed Potential of imaging spectroscopy as tool for pasture management
title_short Potential of imaging spectroscopy as tool for pasture management
title_sort potential of imaging spectroscopy as tool for pasture management
topic herbage mass
imaging spectroscopy
pasture management
feeding value
herbage - quality
mineral composition of herbage
url http://hdl.handle.net/20.500.11937/15483