TY - JOUR

T1 - Can reproducible comparisons of cereal genotypes be generated in field experiments based on UAV imagery using RGB cameras?

AU - Svensgaard, Jesper

AU - Jensen, Signe Marie

AU - Westergaard, Jesper Cairo

AU - Nielsen, Jon

AU - Christensen, Svend

AU - Rasmussen, Jesper

PY - 2019/5/1

Y1 - 2019/5/1

N2 - In agricultural research involving unmanned aerial vehicle (UAV) imagery, the quality of measurements is often benchmarked against ground measurements. This study adopted a supplementary approach by introducing repeatability and reproducibility analyses. Repeatability was defined as the variation associated with the measurement itself, and reproducibility was defined as the impact of different ways of measuring or different measuring conditions. In this study, different ways of measuring were represented by different cameras, and different light conditions and flight altitudes represented different measuring conditions. The aim was to investigate the repeatability and reproducibility of measurements based on consumer-grade colour cameras mounted on UAVs without calibration of incoming light. Three field-plot experiments with different genotypes of winter cereals were used to investigate how repeatability and reproducibility affected comparisons of genotypes based on the excess green vegetation index (ExG). Four different statistical methods were used to analyse data. The results showed little variation between repeated measurements based on UAV imagery, and that the variation was smaller than ground measurements of crop coverage (CC) based on sampling. Reproducibility was mainly influenced by the cameras. When incoming light was stable during image capture, light conditions and flight altitude had little or no impact on reproducibility. Shifting light conditions during image capture reduced it. Different cameras resulted in different ExG levels for the genotypes, whereas flight altitude and light conditions were found to be of minor importance for genotype comparisons. The extent to which the camera posed a problem was discussed and potential solutions proposed.

AB - In agricultural research involving unmanned aerial vehicle (UAV) imagery, the quality of measurements is often benchmarked against ground measurements. This study adopted a supplementary approach by introducing repeatability and reproducibility analyses. Repeatability was defined as the variation associated with the measurement itself, and reproducibility was defined as the impact of different ways of measuring or different measuring conditions. In this study, different ways of measuring were represented by different cameras, and different light conditions and flight altitudes represented different measuring conditions. The aim was to investigate the repeatability and reproducibility of measurements based on consumer-grade colour cameras mounted on UAVs without calibration of incoming light. Three field-plot experiments with different genotypes of winter cereals were used to investigate how repeatability and reproducibility affected comparisons of genotypes based on the excess green vegetation index (ExG). Four different statistical methods were used to analyse data. The results showed little variation between repeated measurements based on UAV imagery, and that the variation was smaller than ground measurements of crop coverage (CC) based on sampling. Reproducibility was mainly influenced by the cameras. When incoming light was stable during image capture, light conditions and flight altitude had little or no impact on reproducibility. Shifting light conditions during image capture reduced it. Different cameras resulted in different ExG levels for the genotypes, whereas flight altitude and light conditions were found to be of minor importance for genotype comparisons. The extent to which the camera posed a problem was discussed and potential solutions proposed.

KW - Colour camera

KW - Field experiments

KW - Repeatability

KW - Reproducibility

KW - Statistics

KW - UAV

UR - http://www.scopus.com/inward/record.url?scp=85063671056&partnerID=8YFLogxK

U2 - 10.1016/j.eja.2019.03.006

DO - 10.1016/j.eja.2019.03.006

M3 - Journal article

AN - SCOPUS:85063671056

VL - 106

SP - 49

EP - 57

JO - European Journal of Agronomy

JF - European Journal of Agronomy

SN - 1161-0301

ER -