This work presents the characterization of selected bioactive compounds of local herbs
through their photonic spectrum. A Shimadzu spectrophotometer was used to map bioactive
compounds extracted from Andrographis paniculata, Ficus deltoidea, Orthosiphon stamineus
and Centella asiatica. Dominant peaks and repeatability were the determinant parameters
in this study. Absorbance peaks of bioactive compounds were calibrated against respective
standardized chemicals obtained from reputable suppliers. The results obtained indicated
that absorbance peaks from different bioactive compounds could be identified by photonic
spectrum. Most bioactive markers were detected within the wavelength range of 200 nm to 350
nm, using a Deuterium (190 nm to 450 nm) light source and corresponding refraction grating.
A mathematical relationship of concentration versus absorbance at different wavelengths for
selected bioactive compounds were identified. The significance of the photonic characterization
of these phytochemicals forms the basis for a mathematical model in a decision support system
of a proposed mobile sensor prototype development.
Rice plant population density is a key indicator in determining the crop setting and fertilizer application rate. It is therefore essential that the population density is monitored to ensure that a correct crop management decision is taken. The conventional method of determining plant population is by manually counting the total number of rice plant tillers in a 25 cm x 25 cm square frame. Sampling is done by randomly choosing several different locations within a plot to perform tiller counting. This sampling method is time consuming, labour intensive and costly. An alternative fast estimating method was developed to overcome this issue. The method relies on measuring the outer circumference
or ambit of the contained rice plants in a 25 cm x 25 cm square frame to determine the number of tillers within that square frame. Data samples of rice variety MR219 were collected from rice plots in the Muda granary area, Sungai Limau Dalam, Kedah. The data were taken at 50 days and 70 days after seeding (DAS). A total of 100 data samples were collected for each sampling day. A good correlation was obtained for the variety of 50 DAS and 70 DAS. The model was then verified by taking 100 samples with the latching strap for 50 DAS and 70 DAS. As a result, this technique can be used as a fast, economical and practical alternative to manual tiller counting. The technique can potentially be used in the development of an electronic sensing system to estimate paddy plant population density.