Within-field and regional prediction of malting barley protein content using canopy reflectance

M. Söderström; T. Börjesson; C.G. Pettersson; K. Nissen; O. Hagner

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Within-field and regional prediction of malting barley protein content using canopy reflectance

in Precision agriculture '09

Autor:innen:

M. Söderström

M. Söderström
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T. Börjesson

T. Börjesson
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C.G. Pettersson

C.G. Pettersson
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K. Nissen

K. Nissen
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O. Hagner

O. Hagner
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Art:: Kapitel

Seiten:: 119–126

DOI:: https://doi.org/10.1163/9789086866649_015

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Abstract

Producing high quality malting barley is a challenge for all farmers. The protein criterion is strict with a tolerated range between 9.5 and 11.5% grain crude protein. The within-field and regional variability is often considerable due to varying weather and soil conditions. This paper focuses on predicting within-field differences in protein in malting barley at a late growth stage using the Yara N-Sensor as well as explaining and predicting the regional variability in malting barley protein using satellite images. Late stage field predictions of protein in the crop could be useful for farmers in order to plan the harvest, and a regional prediction of barley quality before harvest would be useful for the grain industry. The project was carried out in central Sweden where there is documented variability of malting barley both within fields and regionally. N-sensor scanning and crop sampling were carried out in 2007 and 2008, at ten barley fields each year. The regional data used consisted of weather data, quality analyses of delivered malting barley to the major farmers’ co-operative, crops grown and field boundaries. Satellite scenes (IRS-P6 LISS-III) were acquired from a date as close in time as possible to the N-Sensor scannings. Reasonably good PLS models could be constructed based on weather data and reflexion data from either the N-sensor or satellite data. Most information used by the models was reflectance data, but particularly when using satellite imagery, where the number of spectral bands is very limited, weather data improved the models considerably. Better field models could be created with data from the N-Sensor compared with the satellite image, but a local satellite based model based on a simple ratio (middle infrared/ green) in combination with weather was useful in the regional prediction of malting barley protein.

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Precision agriculture '09

ISBN:: 9789086866649

Verleger:: Wageningen Academic

Print-Publikationsdatum:: 01 Jan 2009

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- Biowissenschaften
  - Allgemein
  - Landwirtschaft und Umwelt

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Within-field and regional prediction of malting barley protein content using canopy reflectance

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Precision agriculture '09

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