Performance of UAV-derived Normalized Difference Vegetation Index (NDVI) for Early Estimation of Rice Yield

Authors

  • P.P. Dharmaratne Department of Horticulture and Landscape Gardening, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila 60170, Sri Lanka
  • W.M.U.K. Rathnayake Rice Research and Development Institute, Bathalagoda, Ibbagamuwa 60500, Sri Lanka
  • A.D.A.J.K. Weerasinghe Retail Information Technologies Pvt Ltd, Bambalapitiya 00300, Sri Lanka
  • A.S.A. Salgadoe Department of Horticulture and Landscape Gardening, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila 60170, Sri Lanka

DOI:

https://doi.org/10.31357/ait.v3i2.7351

Keywords:

NDVI, rice crop, UAV-Multispectral, yield

Abstract

Traditionally, the rice yield is measured after the harvest, which is too late then to revert any agronomic practices to improve yield. The aerial spectral reflectance images of crops captured by a multispectral camera mounted in an Unmanned Aerial Vehicle (UAV) are capable of quantitatively measuring the internal physiological condition of crops directly associated with their health status. The aim of this study was to evaluate the performance of UAV-multispectral image derived-NDVI as a method for estimating rice yield. Multispectral drone images including single band images were acquired from a controlled rice field at Rice Research and Development Institute (RRDI), Sri Lanka. Rice variety Bg 300 was cultivated in the Yala season under four levels of Nitrogen (N) fertilizer treatment plots. According to the regression co-relation analysis the derived NDVI values at 15 and 25 m flying heights from the rice crops at the booting stage were moderately (R2=0.65 and R2=0.67, p<0.05, respectively) associated with the actual yield. The derived NDVI values indicated the rice crop vigor at the booting stage is a useful indicator for early estimation of the rice yield prior to actual harvest.

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Published

2024-04-08

How to Cite

P.P. Dharmaratne, W.M.U.K. Rathnayake, A.D.A.J.K. Weerasinghe, & A.S.A. Salgadoe. (2024). Performance of UAV-derived Normalized Difference Vegetation Index (NDVI) for Early Estimation of Rice Yield . Advances in Technology, 3(2). https://doi.org/10.31357/ait.v3i2.7351

Issue

Volume 3 Issue 2 (2023)

Section

Articles

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Copyright (c) 2024 P.P. Dharmaratne, W.M.U.K. Rathnayake, A.D.A.J.K. Weerasinghe, A.S.A. Salgadoe

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