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Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe

Creator: Gracia-Romero, Adrian
Creator: Kefauver, S.C.
Creator: Vergara, O.
Creator: Hamadziripi, E.
Creator: Zaman-Allah, M.
Creator: Thierfelder, C.
Creator: Prasanna, B.M.
Creator: Cairns, J.E.
Creator: Araus, J.L.
Year: 2020
URI: https://hdl.handle.net/10883/20964
Format: PDF
Language: English
Publisher: Nature Publishing Group
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: London (United Kingdom)
Issue: 1
Volume: 10
DOI: 10.1038/s41598-020-73110-3
Description: Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs.
Agrovoc: AGROECOLOGY
Agrovoc: IMAGE ANALYSIS
Agrovoc: REMOTE SENSING
Agrovoc: PLANT PHYSIOLOGY
Agrovoc: STRESS
Related Datasets: https://www.nature.com/articles/s41598-020-73110-3#Sec23
ISSN: 2045-2322
Journal: Nature Scientific Reports


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This item appears in the following Collection(s)

  • Maize
    Maize breeding, phytopathology, entomology, physiology, quality, and biotech
  • Sustainable Intensification
    Sustainable intensification agriculture including topics on cropping systems, agronomy, soil, mechanization, precision agriculture, etc.

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