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Research article - Peer-reviewed, 2022

Predicting grain protein concentration in winter wheat (Triticum aestivum L.) based on unpiloted aerial vehicle multispectral optical remote sensing

Wolters, Sandra; Soderstrom, Mats; Piikki, Kristin; Borjesson, Thomas; Pettersson, Carl-Goran

Abstract

Prediction models for crude protein concentration (CP) in winter wheat (Triticum aestivum L.) based on multispectral reflectance data from field trials in 2019 and 2020 in southern Sweden were developed and evaluated for independent trial sites. Reflectance data were collected using an unpiloted aerial vehicle (UAV)-borne camera with nine spectral bands having similar specification to nine bands of Sentinel-2 satellite data. Models were tested for application on near-real time Sentinel-2 imagery, on the prospect that CP prediction models can be made available in satellite-based decision support systems (DSS) for precision agriculture. Two different prediction methods were tested: linear regression and multivariate adaptive regression splines (MARS). Linear regression based on the best-performing vegetation index (the chlorophyll index) was found to be approximately as accurate as the best performing MARS model with multiple predictor variables in leave-one-trial-out cross-validation (R-2 = 0.71, R-2 = 0.70 and mean absolute error 0.64%, 0.60% CP respectively). Models applied on satellite data explained to a small degree between-field variations in CP (R-2 = 0.36), however did not reproduce within-field variation accurately. The results of the different methods presented here show the differences between methods used and their potential for application in a DSS.

Keywords

Decision support system; multispectral; protein; Sentinel-2; unpiloted aerial vehicle (UAV); wheat

Published in

Acta Agriculturae Scandinavica, Section B - Soil and Plant Science
2022, volume: 72, number: 1, pages: 788-802
Publisher: TAYLOR and FRANCIS AS

Authors' information

Swedish University of Agricultural Sciences, Department of Soil and Environment
Swedish University of Agricultural Sciences, Department of Soil and Environment
Piikki, Kristin (Persson, Kristin)
Swedish University of Agricultural Sciences, Department of Soil and Environment
Agroväst
Pettersson, Carl-Göran
Lantmännen

UKÄ Subject classification

Soil Science
Agricultural Science

Publication Identifiers

DOI: https://doi.org/10.1080/09064710.2022.2085165

URI (permanent link to this page)

https://res.slu.se/id/publ/118265