Prediction of protein content in malting barley using proximal and remote sensing |
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Authors: | Mats Söderström Thomas Börjesson Carl-Göran Pettersson Knud Nissen Olle Hagner |
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Institution: | 1. Department of Soil and Environment, Swedish University of Agricultural Sciences, P.O. Box 234, 532 23, Skara, Sweden 3. Sweco Position AB, P.O. Box 2203, 403 14, G?teborg, Sweden 2. Lantm?nnen Lantbruk, P.O. Box 30192, 104 92, Stockholm, Sweden 4. Department of Forest Resource Management, Swedish University of Agricultural Sciences, 901 83, Ume?, Sweden
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Abstract: | This paper examines the prediction of within-field differences in protein in malting barley at a late growth stage using the
Yara N-Sensor and prediction of its regional variation with medium resolution satellite images. Field predictions of protein
in the crop at a late growth stage could be useful for harvest planning, whereas regional prediction of barley quality before
harvest would be useful for the grain industry. The project was carried out in central Sweden where the variation in protein
content of malting barley has been documented both within fields and regionally. Scanning with an N-sensor and crop sampling
were carried out in 2007 and 2008 at several fields. The regional data used consisted of weather data, quality analyses of
the malting barley delivered to the major farmers’ co-operative, crops grown and field boundaries. Satellite scenes (SPOT
5 and IRS-P6 LISS-III) were acquired from a date as close as possible to the N-sensor scans. Reasonable partial least squares
(PLS) models could be constructed based on weather and reflectance data from either the N-sensor or satellite. The models
used mainly reflectance data, but the weather data improved them. Better field models could be created with data from the
N-sensor than from the satellite image, but a local satellite-based model based on a simple ratio (middle infrared/green)
in combination with weather was useful in regional prediction of malting barley protein. A regional prediction model based
only on the weather variables explained about half the variation in recorded protein. |
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