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Soil compaction mapping by plant height and spectral responses of coffee in multispectral images obtained by remotely piloted aircraft system

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Abstract

Soil compaction is considered one of the main threats to structural soil degradation, and it promotes increased densification of soil particles, impairs ecosystem services, the plant development, and therefore affects agricultural profitability. In this sense, this study aimed to analyze the feasibility of using a Remotely Piloted Aircraft System (RPAS) by relating parameters derived from aerial images based on Vegetation Indices (VIs) and the Canopy Height Model (CHM) with soil compaction in a coffee plantation area. The study was conducted in a commercial coffee plantation with the cultivar Mundo Novo with 14 years of implantation. Two aerial surveys were carried out, the first to determine the CHM and define the sampling points and the second for radiometric calculations of VIs. In the sampling point were collected data plant height, soil characterization, soil penetration resistance and productivity. Images were processed by Pix4D software, and the data analysis at QGIS and RStudio. As at results, no statistically significant differences were detected between the different plant height zones in the soil chemical analysis; significant statistical differences between plant height zones were detected for penetration resistance, which is correlated to productivity data; and the radiometric data presented a correlation with the penetration resistance data, making it possible to determine VIs (NDRE and MTCI) with correlation to the compaction data allowing the estimation of such variable. In this way, the possibility of monitoring the height variations of the coffee crop using RPAS to demarcate compacted zones was evidenced.

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Acknowledgements

The authors acknowledge the Embrapa Café - Consórcio Pesquisa Café, the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES), the Federal University of Lavras (UFLA), and Bom Jardim Farm.

Funding

This research was funded by the National Council for Scientific and Technological Development (CNPq) (project 305953/2020-6) and Embrapa Café - Coffee Research Consortium (project 10.18.20.041.00.00).

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  1. Department of Agricultural Engineering, School of Engineering, Federal University of Lavras - UFLA, Trevo Rotatório Professor Edmir Sá Santos, s/n, PO Box 3037, Lavras, MG, 37200-900, Brazil

    Nicole Lopes Bento, Gabriel Araújo e Silva Ferraz, Lucas Santos Santana, Rafael de Oliveira Faria, Mirian de Lourdes Oliveira e Silva, Michel Martins Araújo Silva & Diego José Carvalho Alonso

  2. Academic Unit Specialized in Agricultural Sciences, Agricultural School of Jundiaí - Federal University of Rio Grande do Norte, RN 160, Km 03, District of Jundiaí, PO Box 07, Macaíba, RN, 59280-000, Brazil

    Jhones da Silva Amorim

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by all authors. The first draft of the manuscript was written by [NLB] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Bento, N.L., Silva Ferraz, G.A., Santana, L.S. et al. Soil compaction mapping by plant height and spectral responses of coffee in multispectral images obtained by remotely piloted aircraft system. Precision Agric 25, 729–750 (2024). https://doi.org/10.1007/s11119-023-10090-0

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