Open AccessMeasuring leaf area index from colour digital image of wheat crop
Author(s) -
Bappa Das,
Rabi Narayan Sahoo,
Sourabh Pargal,
Gopal Krishna,
Vinod Kumar Gupta,
Rakesh Kumar Verma,
Viswanathan Chinnusamy
Publication year - 2016
Publication title -
journal of agrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 11
eISSN - 2583-2980
pISSN - 0972-1665
DOI - 10.54386/jam.v18i1.885
Subject(s) - leaf area index , canopy , mathematics , interception , vegetation (pathology) , biomass (ecology) , environmental science , photosynthetically active radiation , horticulture , agronomy , botany , ecology , biology , photosynthesis , medicine , pathology
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.