Open AccessEstimation of leaf antioxidant activity using image processing
Author(s) -
Eko Suhartono,
Bambang Setiawan,
Purwanto Budi Santosa,
Rinaldi Idroes,
M. S. Indrawan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1374/1/012057
Subject(s) - antioxidant , estimation , image processing , artificial intelligence , computer vision , image (mathematics) , biological system , computer science , mathematics , pattern recognition (psychology) , chemistry , biology , economics , biochemistry , management
Physiologically, the influence of inundated conditions on many plants varies. The eco-physiological response of most plantations to flooding is wilt and stomata closure, root damage, reduction of root biomass 2. This results in a decrease in the production of bioactive compounds, which have an effect on decreasing antioxidant activity. Various methods of measuring antioxidant activity still use chemicals through extraction processes that require a long time. So, it is necessary to examine alternative methods that are cheap, easy and fast. This method is digital processing. The leaf samples were then photographed for image analysis in the Telkom School Banjarbaru Multimedia Laboratory. Antioxidant activity was analyzed through the hydroxyl scavenging method at the laboratory of Biochemistry and Biomolecular, Faculty of Medicine, Lambung Mangkurat University, Banjarbaru. The results of image analysis showed that the antioxidant activity model of RGB values was AA= -54.9592 +1.0295 R + 0.3757 G + 2,006 B -0,0004 R*G - 0.0012 R*B + 0.004 G*B (AA = antioxidant activity; R = red; G = green; B = blue) with p = 0.001 (p <0.005) and r = 0.76. In this model, the R value has a significant effect on antioxidant activity. Image analysis using RGB can be used to measure leaf antioxidant activity. However, further research is needed.