Evaluation of portable tools for fast field assessment of winter wheat grain quality

Bruno Morandin Figueiredo; Mats Söderström; Kristin Persson; T. Börjesson

doi:10.3920/978-90-8686-947-3_16

Evaluation of portable tools for fast field assessment of winter wheat grain quality

Department of Soil and Environment

Publication: Chapter in Book/Report/Conference proceeding › Conference paper in proceedings › peer-review

Abstract

The grain crude protein analysis tool evaluated in this project, combined with satellite imagery has the potential to be an alternative to combine harvester protein mapping devices. Evaluation showed that a calibration is necessary for accurate results. Field-specific and general calibrations were developed bringing MAE to as low as 0.14% for a field-specific calibration. In combination with satellite imagery, protein prediction models were developed using 9 available wavelength bands from a wide range of images throughout the cropping season. Predictions had a MAE as low as 0.10% for a field-specific model.

Original language	English
Title of host publication	Precision agriculture ’23
Publisher	Wageningen Academic Publishers
Pages	141-151
Number of pages	11
ISBN (Electronic)	978-90-8686-947-3
ISBN (Print)	978-90-8686-393-8
DOIs	https://doi.org/10.3920/978-90-8686-947-3_16
Publication status	Published - 2023

Keywords

crude protein
prediction model
remote sensing
satellite
winter wheat

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10.3920/978-90-8686-947-3_16

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title = "Evaluation of portable tools for fast field assessment of winter wheat grain quality",

abstract = "The grain crude protein analysis tool evaluated in this project, combined with satellite imagery has the potential to be an alternative to combine harvester protein mapping devices. Evaluation showed that a calibration is necessary for accurate results. Field-specific and general calibrations were developed bringing MAE to as low as 0.14\% for a field-specific calibration. In combination with satellite imagery, protein prediction models were developed using 9 available wavelength bands from a wide range of images throughout the cropping season. Predictions had a MAE as low as 0.10\% for a field-specific model.",

keywords = "crude protein, prediction model, remote sensing, satellite, winter wheat, crude protein, prediction model, remote sensing, satellite, winter wheat",

author = "\{Morandin Figueiredo\}, Bruno and Mats S{\"o}derstr{\"o}m and Kristin Persson and T. B{\"o}rjesson",

year = "2023",

doi = "10.3920/978-90-8686-947-3\_16",

language = "English",

isbn = "978-90-8686-393-8",

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AU - Morandin Figueiredo, Bruno

AU - Söderström, Mats

AU - Persson, Kristin

AU - Börjesson, T.

PY - 2023

Y1 - 2023

N2 - The grain crude protein analysis tool evaluated in this project, combined with satellite imagery has the potential to be an alternative to combine harvester protein mapping devices. Evaluation showed that a calibration is necessary for accurate results. Field-specific and general calibrations were developed bringing MAE to as low as 0.14% for a field-specific calibration. In combination with satellite imagery, protein prediction models were developed using 9 available wavelength bands from a wide range of images throughout the cropping season. Predictions had a MAE as low as 0.10% for a field-specific model.

AB - The grain crude protein analysis tool evaluated in this project, combined with satellite imagery has the potential to be an alternative to combine harvester protein mapping devices. Evaluation showed that a calibration is necessary for accurate results. Field-specific and general calibrations were developed bringing MAE to as low as 0.14% for a field-specific calibration. In combination with satellite imagery, protein prediction models were developed using 9 available wavelength bands from a wide range of images throughout the cropping season. Predictions had a MAE as low as 0.10% for a field-specific model.

KW - crude protein

KW - prediction model

KW - remote sensing

KW - satellite

KW - winter wheat

KW - crude protein

KW - prediction model

KW - remote sensing

KW - satellite

KW - winter wheat

UR - https://res.slu.se/id/publ/122672

U2 - 10.3920/978-90-8686-947-3_16

DO - 10.3920/978-90-8686-947-3_16

M3 - Conference paper in proceedings

SN - 978-90-8686-393-8

SP - 141

EP - 151

BT - Precision agriculture ’23

PB - Wageningen Academic Publishers

ER -

Evaluation of portable tools for fast field assessment of winter wheat grain quality

Abstract

Keywords

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