TY - CHAP
T1 - Analysis of Stomata Distribution Patterns for Quantification of the Foliar Plasticity of Tradescantia Zebrina
AU - Florindo, Joao Batista
AU - Landini, Gabriel
AU - Almeida Filho, Humberto
AU - Bruno, Odemir Martinez
PY - 2015
Y1 - 2015
N2 - Here we propose a method for the analysis of the stomata distribution patterns on the surface of plant leaves. We also investigate how light exposure during growth can affect stomata distribution and the plasticity of leaves. Understanding foliar plasticity (the ability of leaves to modify their structural organization to adapt to changing environmental resources) is a fundamental problem in Agricultural and Environmental Sciences. Most published work on quantification of stomata has concentrated on descriptions of their density per unit of leaf area, however density alone does not provide a complete description of the problem and leaves several unanswered questions (e.g. whether the stomata patterns change across various areas of the leaf, or how the patterns change under varying observational scales). We used two approaches here, to know, multiscale fractal dimension and complex networks, as a means to provide a description of the complexity of these distributions. In the experiments, we used 18 samples from the plant Tradescantia Zebrina grown under three different conditions (4 hours of artificial light each day, 24 hours of artificial light each day, and sunlight) for a total of 69 days. The network descriptors were capable of correctly discriminating the different conditions in 88% of cases, while the fractal descriptors discriminated 83% of the samples. This is a significant improvement over the correct classification rates achieved when using only stomata density (56% of the samples).
AB - Here we propose a method for the analysis of the stomata distribution patterns on the surface of plant leaves. We also investigate how light exposure during growth can affect stomata distribution and the plasticity of leaves. Understanding foliar plasticity (the ability of leaves to modify their structural organization to adapt to changing environmental resources) is a fundamental problem in Agricultural and Environmental Sciences. Most published work on quantification of stomata has concentrated on descriptions of their density per unit of leaf area, however density alone does not provide a complete description of the problem and leaves several unanswered questions (e.g. whether the stomata patterns change across various areas of the leaf, or how the patterns change under varying observational scales). We used two approaches here, to know, multiscale fractal dimension and complex networks, as a means to provide a description of the complexity of these distributions. In the experiments, we used 18 samples from the plant Tradescantia Zebrina grown under three different conditions (4 hours of artificial light each day, 24 hours of artificial light each day, and sunlight) for a total of 69 days. The network descriptors were capable of correctly discriminating the different conditions in 88% of cases, while the fractal descriptors discriminated 83% of the samples. This is a significant improvement over the correct classification rates achieved when using only stomata density (56% of the samples).
U2 - 10.1088/1742-6596/633/1/012113
DO - 10.1088/1742-6596/633/1/012113
M3 - Chapter (peer-reviewed)
VL - 633
T3 - Journal of Physics: Conference Series
BT - Journal of Physics: Conference Series
PB - IOP Publishing
T2 - 4th International Conference on Mathematical Modeling in Physical Sciences (IC-MSquare2015)
Y2 - 5 June 2015 through 8 June 2015
ER -