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Abigail Gaiser, Caroline Linker, Hailey Nies
If the variegation of a Japanese Pittosporum leaf affects the CO2 production, then the CO2 produced from a variegate leaf will be less due to the variegated plants having less pigment, and therefore, less chloroplasts-->plant metabolism will be less because chloroplast have a direct relationship with photosynthesis
To be tested: a leaf would be placed within a container, and the gas sensor would be placed in after. The CO2 of the leaf was measured by the Logger Pro for five minutes and then recorded.
The same would be done for the same leaf, but in a dark environment. The results would be recorded. This was done with 5 variegated leaves and 5 non-variegated leaves.
The Net GPP was found between each of the recorded results for each leaf after a dark and light trial. A Statistical T-Test was used in this experiment following data collection.
The results show no change in CO2 production between a variegated leaf and a non-variegated leaf of a Japanese Pittosporum.
Our results showed there is no correlation between variegated and non-variegated Pittosporum plants and the CO2 production
Other studies conducted similar experiments to show the difference in CO2 levels. These experiments found that the yellow variegated part of a green leaf produced much lower respiration levels in the dark than full green leaves did. The relative growth response to high CO2 was significantly greater for the variegated plants compared to completely green plants.
Regarding the Japanese Pittosporum results, the data was seemingly off and inconsistent. For example, the previous experiment used yellow leaves instead of white, which is the color of the Japanese Pittosporum. This might show less presence of chloroplasts. Also, the calibration on the CO2 sensor would extend as high as 800 ppm, and as low as 100 ppm. This shows inconsistency within results because calibration should be shown in the range 300-600 ppm. Future study should stay consistent to the atmospheric range of 300-600 ppm to receive the most logical data.
Thank You!