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

Wolters, Sandra and Söderström, Mats and Piikki, Kristin and Börjesson, Thomas and Pettersson, Carl-Göran (2022). Predicting grain protein concentration in winter wheat (Triticum aestivum L.) based on unpiloted aerial vehicle multispectral optical remote sensing. Acta Agriculturae Scandinavica, Section B - Soil and Plant Science. 72 :1 , 788-802
[Research article]

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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.

Authors/Creators:Wolters, Sandra and Söderström, Mats and Piikki, Kristin and Börjesson, Thomas and Pettersson, Carl-Göran
Title:Predicting grain protein concentration in winter wheat (Triticum aestivum L.) based on unpiloted aerial vehicle multispectral optical remote sensing
Series Name/Journal:Acta Agriculturae Scandinavica, Section B - Soil and Plant Science
Year of publishing :2022
Volume:72
Number:1
Page range:788-802
Number of Pages:15
Publisher:TAYLOR and FRANCIS AS
ISSN:0906-4710
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Soil Science
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Agricultural Science
Keywords:Decision support system, multispectral, protein, Sentinel-2, unpiloted aerial vehicle (UAV), wheat
URN:NBN:urn:nbn:se:slu:epsilon-p-118265
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-118265
Additional ID:
Type of IDID
DOI10.1080/09064710.2022.2085165
Web of Science (WoS)000816725700001
ID Code:28711
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Soil and Environment
(S) > Dept. of Soil and Environment
Deposited By: SLUpub Connector
Deposited On:01 Sep 2022 11:51
Metadata Last Modified:01 Sep 2022 12:01

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