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Off-nadir hyperspectral measurements in maize to predict dry matter yield, protein content and metabolisable energy in total biomass

Off-nadir hyperspectral measurements in maize to predict dry matter yield, protein content and... Sensor-based methods of analysis to assess dry matter yield and quality constituents of crops are time- and labour-saving, and can facilitate site-specific management. Nevertheless, standard nadir measurements of maize (Zea mays cv. Ambrosius), based on top-of-canopy reflectance, are difficult due to plant heights of more than three metres. This study was conducted to explore the potential of off-nadir field spectral measurements for the non-destructive prediction of dry matter yield (DM), metabolisable energy (ME) and crude protein (CP) in total biomass in a maize canopy. Plants were measured at five different heights (0–50, 50–100, 100–50, 150–200 and 200–250 cm above the soil) at three zenith view angles (60°, 75° and 90°, respectively). Modified partial least squares regression was used for analysis of the hyperspectral data (355–2300 nm and 620–1000 nm). Optimum combinations of angle and height as well as an optimum one-sensor-strategy were determined for DM yield, CP and ME in total biomass. Coefficients of determination for off-nadir measurements were compared to nadir measurements; the results showed improved prediction accuracies for DM yield and ME using off-nadir measurements, but not for CP for which nadir measurements were better. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Off-nadir hyperspectral measurements in maize to predict dry matter yield, protein content and metabolisable energy in total biomass

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References (56)

Publisher
Springer Journals
Copyright
Copyright © 2010 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
DOI
10.1007/s11119-010-9175-4
Publisher site
See Article on Publisher Site

Abstract

Sensor-based methods of analysis to assess dry matter yield and quality constituents of crops are time- and labour-saving, and can facilitate site-specific management. Nevertheless, standard nadir measurements of maize (Zea mays cv. Ambrosius), based on top-of-canopy reflectance, are difficult due to plant heights of more than three metres. This study was conducted to explore the potential of off-nadir field spectral measurements for the non-destructive prediction of dry matter yield (DM), metabolisable energy (ME) and crude protein (CP) in total biomass in a maize canopy. Plants were measured at five different heights (0–50, 50–100, 100–50, 150–200 and 200–250 cm above the soil) at three zenith view angles (60°, 75° and 90°, respectively). Modified partial least squares regression was used for analysis of the hyperspectral data (355–2300 nm and 620–1000 nm). Optimum combinations of angle and height as well as an optimum one-sensor-strategy were determined for DM yield, CP and ME in total biomass. Coefficients of determination for off-nadir measurements were compared to nadir measurements; the results showed improved prediction accuracies for DM yield and ME using off-nadir measurements, but not for CP for which nadir measurements were better.

Journal

Precision AgricultureSpringer Journals

Published: May 16, 2010

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