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

• Published in: Agricultural water management Vol. 266; p. 107516
• Main Authors: Mwinuka, Paul Reuben, Mourice, Sixbert K., Mbungu, Winfred B., Mbilinyi, Boniphace P., Tumbo, Siza D., Schmitter, Petra
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 31.05.2022
• Subjects: Irrigation; Nitrogen use efficiency; UAV; Vegetation indices; Water stress; Water use efficiency; Nitrogen use efficiency; Irrigation; Water use efficiency; UAV; Water stress; Vegetation indices
• ISSN: 0378-3774; 1873-2283
• DOI: 10.1016/j.agwat.2022.107516

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. •NIR and green bands are sensitive in detecting leaf moisture and N content.•TDVI is sensitive to leaf moisture content at different levels of N.•GNDVI distinguished well leaf N content at various levels of irrigation.•Vegetation indices are most effective to distinguish water and N separately.•Multi VI calibration is required to assess the interactive effects of water and N.