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UAV-based multispectral vegetation indices for assessing the interactive effects of water and nitrogen in irrigated horticultural crops production under tropical sub-humid conditions: A case of African eggplant

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  • Mwinuka, Paul Reuben
  • Mourice, Sixbert K.
  • Mbungu, Winfred B.
  • Mbilinyi, Boniphace P.
  • Tumbo, Siza D.
  • Schmitter, Petra

Abstract

UAV-based multispectral vegetation indices are often used to assess crop performance and water consumptive use. However, their ability to assess the interaction between water, especially deficit irrigation, and nitrogen application rates in irrigated agriculture has been less explored. Understanding the effect of water-nitrogen interactions on vegetation indices could further support optimal water and N management. Therefore, this study used a split plot design with water being the main factor and N being the sub-factor. African eggplants were drip irrigated at 100% (I100), 80% (I80) or 60% (I60) of the crop water requirements and received 100% (F100), 75% (F75), 50% (F50) or 0% (F0) of the crop N requirements. Results showed that the transformed difference vegetation index (TDVI) was best in distinguishing differences in leaf moisture content (LMC) during the vegetative stage irrespective of the N treatment. The green normalized difference vegetation index (GNDVI) worked well to distinguish leaf N during vegetative and full vegetative stages. However, the detection of the interactive effect of water and N on crop performance required a combination of GNDVI, NDVI and OSAVI across both stages as each of these 3 VI showed an ability to detect some but not all treatments. The fact that a certain amount of irrigation water can optimize the efficiency of N uptake by the plant is an important criterion to consider in developing crop specific VI based decision trees for crop performance assessments and yield prediction.

Suggested Citation

  • Mwinuka, Paul Reuben & Mourice, Sixbert K. & Mbungu, Winfred B. & Mbilinyi, Boniphace P. & Tumbo, Siza D. & Schmitter, Petra, 2022. "UAV-based multispectral vegetation indices for assessing the interactive effects of water and nitrogen in irrigated horticultural crops production under tropical sub-humid conditions: A case of Africa," Agricultural Water Management, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:agiwat:v:266:y:2022:i:c:s0378377422000634
    DOI: 10.1016/j.agwat.2022.107516
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    1. Mwinuka, Paul Reuben & Mbilinyi, Boniface P. & Mbungu, Winfred B. & Mourice, Sixbert K. & Mahoo, H.F. & Schmitter, Petra, 2021. "The feasibility of hand-held thermal and UAV-based multispectral imaging for canopy water status assessment and yield prediction of irrigated African eggplant (Solanum aethopicum L)," Agricultural Water Management, Elsevier, vol. 245(C).
    2. Zotarelli, Lincoln & Scholberg, Johannes M. & Dukes, Michael D. & Muñoz-Carpena, Rafael & Icerman, Jason, 2009. "Tomato yield, biomass accumulation, root distribution and irrigation water use efficiency on a sandy soil, as affected by nitrogen rate and irrigation scheduling," Agricultural Water Management, Elsevier, vol. 96(1), pages 23-34, January.
    3. Klem, Karel & Záhora, Jaroslav & Zemek, František & Trunda, Petr & Tůma, Ivan & Novotná, Kateřina & Hodaňová, Petra & Rapantová, Barbora & Hanuš, Jan & Vavříková, Jana & Holub, Petr, 2018. "Interactive effects of water deficit and nitrogen nutrition on winter wheat. Remote sensing methods for their detection," Agricultural Water Management, Elsevier, vol. 210(C), pages 171-184.
    4. Shen Yuan & Shaobing Peng, 2017. "Exploring the Trends in Nitrogen Input and Nitrogen Use Efficiency for Agricultural Sustainability," Sustainability, MDPI, vol. 9(10), pages 1-15, October.
    5. Nahry, A.H. El & Ali, R.R. & Baroudy, A.A. El, 2011. "An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques," Agricultural Water Management, Elsevier, vol. 98(4), pages 517-531, February.
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