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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 7 , ISSUE 1 (March 2014) > List of articles


H. Tavakoli / S.S. Mohtasebi * / R. Alimardani / R. Gebbers

Keywords : Leaf area index (LAI), plant height, vegetation indices, digital camera, precision agriculture

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 1, Pages 337-359, DOI: https://doi.org/10.21307/ijssis-2017-659

License : (CC BY-NC-ND 4.0)

Received Date : 11-October-2013 / Accepted: 03-February-2014 / Published Online: 27-December-2017



Different approaches of non-destructive estimation of the LAI in winter wheat were compared. Plant height had weak relation with the LAI, while estimated biomass showed high logarithmic relationship (R2=0.839). NDRE and REIP were logarithmically well related to the LAI (R2=0.726 and 0.779 respectively). Saturation effect of NDRE and REIP was less than NDVI. Some RGB-based indices also showed good potential to estimate the LAI. Among the indices, Gm, GMB, RMB, and NRMB were better related to the LAI. The results indicated that digital cameras can be used as an affordable and simple approach for assessment of the LAI of crops.

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