AUTHOR=Elsayed Salah , Barmeier Gero , Schmidhalter Urs 

TITLE=Passive Reflectance Sensing and Digital Image Analysis Allows for Assessing the Biomass and Nitrogen Status of Wheat in Early and Late Tillering Stages

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 9 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2018.01478

DOI=10.3389/fpls.2018.01478

ISSN=1664-462X

ABSTRACT=Proximal remote sensing systems depending on spectral reflectance measurements and image analysis can acquire timely and inexpensive information to make management decisions in real time compared with more laborious destructive measurements. There is a need to make nitrogen management decisions at early development stages of cereals when the first top-dressing is made. However, there is very limited information available about the possibility of detecting differences in the biomass or the nitrogen status of cereals at early development stages and even less comparing its relationship to destructively obtained information. In this study, the performance of hyperspectral passive reflectance sensing and digital image analysis was tested in two years to assess the nitrogen uptake, the nitrogen concentration, the biomass fresh and dry weight at early and late tillering stages from BBCH 19 to 30. Wheat plants were subjected to different levels of nitrogen fertilizer applications and differences in biomass and the nitrogen status were further created by varying the seeding rate. Simple linear regression and partial least squares regression (PLSR) models were used to analyze the spectral and digital imaging data. The green pixel digital analysis, spectral reflectance indices and PLSR of spectral reflectance from 400 to 1000 nm were strongly related to the nitrogen uptake and the biomass fresh and dry weights at individual measurements and for the combined dataset at the early crop development stages. However, only the PLSR analysis of the spectral data presented strong relationships to the nitrogen concentration compared with the green pixel analysis and spectral indices. For the relationships between the green pixels, spectral reflectance indices and PLSR with the biomass and nitrogen status parameters, the coefficients of determination for the assessment reached values up to 0.95** through the individual measurements and the combined data set. Reflectance-based spectral sensing allows to detect differences in the biomass and nitrogen status already at very early growth stages in the tillering phase. This might pave the way for more informed management decisions and potentially lead to improved nitrogen fertilizer management at early development stages.