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Evaluation of Individual Plant Growth Estimation in an Intercropping Field with UAV Imagery

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  • Norazlida Jamil

    (Farm Technology, Department of Plant Sciences, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
    Faculty of Fisheries and Food Sciences, Universiti Malaysia Terengganu, Kuala Nerus 21030, Terengganu, Malaysia)

  • Gert Kootstra

    (Farm Technology, Department of Plant Sciences, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands)

  • Lammert Kooistra

    (Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands)

Abstract

Agriculture practices in monocropping need to become more sustainable and one of the ways to achieve this is to reintroduce intercropping. However, quantitative data to evaluate plant growth in intercropping systems are still lacking. Unmanned aerial vehicles (UAV) have the potential to become a state-of-the-art technique for the automatic estimation of plant growth. Individual plant height is an important trait attribute for field investigation as it can be used to derive information on crop growth throughout the growing season. This study aimed to investigate the applicability of UAV-based RGB imagery combined with the structure from motion (SfM) method for estimating the individual plants height of cabbage, pumpkin, barley, and wheat in an intercropping field during a complete growing season under varying conditions. Additionally, the effect of different percentiles and buffer sizes on the relationship between UAV-estimated plant height and ground truth plant height was examined. A crop height model (CHM) was calculated as the difference between the digital surface model (DSM) and the digital terrain model (DTM). The results showed that the overall correlation coefficient (R 2 ) values of UAV-estimated and ground truth individual plant heights for cabbage, pumpkin, barley, and wheat were 0.86, 0.94, 0.36, and 0.49, respectively, with overall root mean square error (RMSE) values of 6.75 cm, 6.99 cm, 14.16 cm, and 22.04 cm, respectively. More detailed analysis was performed up to the individual plant level. This study suggests that UAV imagery can provide a reliable and automatic assessment of individual plant heights for cabbage and pumpkin plants in intercropping but cannot be considered yet as an alternative approach for barley and wheat.

Suggested Citation

  • Norazlida Jamil & Gert Kootstra & Lammert Kooistra, 2022. "Evaluation of Individual Plant Growth Estimation in an Intercropping Field with UAV Imagery," Agriculture, MDPI, vol. 12(1), pages 1-23, January.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:1:p:102-:d:723343
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    References listed on IDEAS

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    1. William C. Wetzel & Heather M. Kharouba & Moria Robinson & Marcel Holyoak & Richard Karban, 2016. "Variability in plant nutrients reduces insect herbivore performance," Nature, Nature, vol. 539(7629), pages 425-427, November.
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    Cited by:

    1. Meriem Barbouchi & Rachid Lhissou & Riadh Abdelfattah & Anas El Alem & Karem Chokmani & Nadhira Ben Aissa & Hatem Cheikh M’hamed & Mohamed Annabi & Haithem Bahri, 2022. "The Potential of Using Radarsat-2 Satellite Image for Modeling and Mapping Wheat Yield in a Semiarid Environment," Agriculture, MDPI, vol. 12(3), pages 1-15, February.
    2. Emanuela Alice Luță & Manuela Ghica & Cerasela Elena Gîrd, 2022. "The Initiation of a Phytosociological Study on Certain Types of Medicinal Plants," Agriculture, MDPI, vol. 12(2), pages 1-23, February.

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