Measuring leaf area index from colour digital image of wheat crop

Authors

  • BAPPA DAS Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi - 110012, India
  • R.N. SAHOO Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi - 110012, India
  • SOURABH PARGAL Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi - 110012, India
  • GOPAL KRISHNA Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi - 110012, India
  • V.K. GUPTA Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi - 110012, India
  • R. VERMA Division of Plant Physiology, Indian Agricultural Research Institute, New Delhi 110 012
  • C. VISWANATHAN Division of Plant Physiology, Indian Agricultural Research Institute, New Delhi 110 012

DOI:

https://doi.org/10.54386/jam.v18i1.885

Keywords:

Leaf area index, colour indices, digital photography, image segmentation, histogram threshold

Abstract

Leaf area index (LAI) is an important physiological trait that determines solar radiation interception and thus biomass. In this study leaf area index (LAI) was estimated from vertical gap fraction derived from top-of-canopy digital colour photography ofwheat canopies. An improved vegetation index, Excess Green minus Excess Red (ExG-ExR) was compared to the commonly used Excess Green (ExG), Excess Red (ExR) and normalized difference (NDI) indices. A histogram-based threshold technique was used to separate green vegetation tissues from background soil in order to derive the canopy vertical gap fraction. LAI derived from the ExG-ExR, ExG indexed image was comparable to the LAI measured using the commercial plant canopy analyzer (LAI-2200,LI-CORInc., USA) (R2 = 0.68 and 0.66 for ExG-ExRand ExG, respectively) with RMSE of 0.63 and 0.79, respectively.However, NDI was overestimated while Ex Rwas found to be under estimated LAI as compared with that measured using the commercial plant canopy analyzer(R2 = 0.47 and 0.35 for NDI and ExR, respectively) with RMSE of 4.09 and 2.19, respectively. Thus, digital photography based ExG-ExRmethod can be used as low cost, non-destructive high through put method for assessing LAI, early vigour and gap fraction of wheat and potentially other cereal crops.

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Published

01-06-2016

How to Cite

BAPPA DAS, R.N. SAHOO, SOURABH PARGAL, GOPAL KRISHNA, V.K. GUPTA, R. VERMA, & C. VISWANATHAN. (2016). Measuring leaf area index from colour digital image of wheat crop. Journal of Agrometeorology, 18(1), 22–28. https://doi.org/10.54386/jam.v18i1.885

Issue

Vol. 18 No. 1 (2016): June

Section

Research Paper

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