Comparison of different Methods of In-situ Leaf Area Measurement of Betel Leaf (Piper betle L.)
Amar Kumar Dey1, P. Guha2, Manisha Sharma3, M. R. Meshram4
1Amar Kumar Dey, Department of Electronics and Telecommunication, Bhilai Institute of Technology, Durg (C.G), India.
2P. Guha, Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal, India.
3Manisha Sharma, Department of Electronics and Telecommunication, Bhilai Institute of Technology, Durg (C.G), India.
4M.R. Meshram, Department of Electronics and Telecommunication, GEC, Jagdalpur (C.G), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1512-1516 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2622037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The knowledge of leaf surface area is important for the evaluation of crop performance. Leaf area is a significant variable in many models describing the analysis of Crop growth, photosynthetic efficiency of the plant, plant nutrients and pest management, etc. Therefore, it becomes essential to study instruments and methods for measurement of leaf area which are quick, efficient, accurate, easy, convenient and cost-effective. This leads to two methods of leaf area determination of which the non-destructive methods are preferred to the destructive methods on many grounds. The present paper reviews and compares five ground-based techniques for in-situ leaf surface area measurement based on percentage error and execution time. The result shows that all ground based leaf surface area measurement method is reliable, but the method based on Digital Image Processing (DIP) approach is the most accurate, convenient and fast technique
Keywords: Leaf area, Digital image processing, Counting grid, Accuracy, Growth analysis
Scope of the Article: Signal and Image Processing