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Comparative performance of ground vs. aerially assessed RGB and multispectral indices for early-growth evaluation of maize performance under phosphorus fertilization

Author: Gracia-Romero, A.
Author: Kefauver, S.C.
Author: Vergara Diaz, O.
Author: Zaman-Allah, M.
Author: Prasanna, B.M.
Author: Cairns, J.E.
Author: Araus, J.L.
Year: 2017
URI: https://hdl.handle.net/10883/19227
Abstract: Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However, these correlations were clearly weaker than against grain yield and only under low phosphorous conditions. This work reinforces the effectiveness of canopy remote sensing for plant phenotyping and crop management of maize under different phosphorus nutrient conditions and suggests that the RGB indices are the best option.
Format: PDF
Language: English
Publisher: Frontiers
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: Switzerland
Pages: 1-13
Volume: 8
DOI: 10.3389/fpls.2017.02004
Keywords: UAV
Keywords: RGB Vis
Keywords: Multispectral Vis
Keywords: Phophorous Fertilization
Agrovoc: MAIZE
Agrovoc: REMOTE SENSING
Agrovoc: AERIAL SURVEYING
Agrovoc: MULTISPECTRAL IMAGERY
Agrovoc: PHOSPHATE FERTILIZERS
Related Datasets: https://www.frontiersin.org/articles/file/downloadfile/309121_supplementary-materials_datasheets_1_docx/octet-stream/Data%20Sheet%201.DOCX/1/309121
Journal: Frontiers in Plant Science
Article number: 2004


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  • Maize
    Maize breeding, phytopathology, entomology, physiology, quality, and biotech

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