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Multispectral Analysis of Small Plots Based on Field and Remote Sensing Surveys—A Comparative Evaluation

Author

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  • József Csajbók

    (Institute of Crop Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Erika Buday-Bódi

    (Institute of Water and Environmental Management, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Attila Nagy

    (Institute of Water and Environmental Management, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Zsolt Zoltán Fehér

    (Institute of Water and Environmental Management, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • András Tamás

    (Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • István Csaba Virág

    (Institute of Crop Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Csaba Bojtor

    (Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Fanni Forgács

    (Institute of Crop Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Attila Miklós Vad

    (Institutes for Agricultural Research and Educational Farm, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

  • Erika Kutasy

    (Institute of Crop Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Böszörményi Str. 138, H-4032 Debrecen, Hungary)

Abstract

Remote sensing is an efficient method of monitoring experiments rapidly and by enabling the collection of significantly more detailed data, than using only field measurements, ensuring new possibilities in scientific research. A small plot field experiment was conducted in a randomized block design with winter oat ( Avena sativa L.) varieties in Debrecen, Hungary in the 2020/2021 cropping year. Multiple field measurements and aerial surveys were carried out examining the response of oat on Silicon and Sulfur foliar fertilization treatments thereby monitoring their effects on the physiology, production and stress tolerance. Parallel application of in situ (elevation, soil pH, NDVI, SPAD, chlorophyll content) and aerial (NDVI, NDRE) surveys including unmanned aerial vehicles (UAVs) provided a diverse source of data for evaluation. Both the oat varieties (88.9%) and the foliar fertilization treatments (87.5%) were correctly classified and clearly separated with the discriminant analysis based on measured data. The Pearson correlation analysis showed a very strong positive connection (r = 0.895–1.00) between the NDVI values measured using a hand-held system and UAV-installed camera, except the third measurement time, where the correlation was weaker (r = 0.70). Our results indicate that field experiments can be effectively supported by UAVs.

Suggested Citation

  • József Csajbók & Erika Buday-Bódi & Attila Nagy & Zsolt Zoltán Fehér & András Tamás & István Csaba Virág & Csaba Bojtor & Fanni Forgács & Attila Miklós Vad & Erika Kutasy, 2022. "Multispectral Analysis of Small Plots Based on Field and Remote Sensing Surveys—A Comparative Evaluation," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3339-:d:769727
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    References listed on IDEAS

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    1. Ferhat Kizilgeci & Mehmet Yildirim & Mohammad Sohidul Islam & Disna Ratnasekera & Muhammad Aamir Iqbal & Ayman EL Sabagh, 2021. "Normalized Difference Vegetation Index and Chlorophyll Content for Precision Nitrogen Management in Durum Wheat Cultivars under Semi-Arid Conditions," Sustainability, MDPI, vol. 13(7), pages 1-11, March.
    2. Junaid Shah & Xiukang Wang & Sami Ullah Khan & Sajjad Khan & Zulfiqar Ali Gurmani & Sajid Fiaz & Abdul Qayyum, 2021. "Optical-Sensor-Based Nitrogen Management in Oat for Yield Enhancement," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
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    1. Luís Guilherme Teixeira Crusiol & Liang Sun & Zheng Sun & Ruiqing Chen & Yongfeng Wu & Juncheng Ma & Chenxi Song, 2022. "In-Season Monitoring of Maize Leaf Water Content Using Ground-Based and UAV-Based Hyperspectral Data," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    2. Pompilica Iagăru & Pompiliu Pavel & Romulus Iagăru & Anca Șipoș, 2022. "Aerial Monitorization—A Vector for Ensuring the Agroecosystems Sustainability," Sustainability, MDPI, vol. 14(10), pages 1-12, May.
    3. András Tamás & Elza Kovács & Éva Horváth & Csaba Juhász & László Radócz & Tamás Rátonyi & Péter Ragán, 2023. "Assessment of NDVI Dynamics of Maize ( Zea mays L.) and Its Relation to Grain Yield in a Polyfactorial Experiment Based on Remote Sensing," Agriculture, MDPI, vol. 13(3), pages 1-17, March.

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