The study used the fruit of Ficus hispida Linn to separation by maceration and sequential extraction method with hexane ethyl acetate and methanol to crude extracts. Crude extracts were assessed for their antioxidant activities tested using DPPH radical scavenging assay total phenolic contents tested using the Folin–Ciocalteu method The results showed that 1. Phytochemical examination of the extracts of F. hispida alkaloids condensed tannins phenolic compounds triterpenes steroids cardiac glycosides anthraquinones 2. Hexane Ethylacetate and Methanol extracts have the ability to reduce the amount of DPPH. The EC50 values were> 1000 285 and 30 g/ml respectively. 3. Hexane Ethylacetate and Methanol extracts contained phenolic compounds values of 3.09 55.25 and 99.59 mg GAE/g dw respectively.

The aim of this work was to validate the sample preparation using a microwave digestion for determination of total arsenic in a spiked soil. Graphite fernace atomic absorbtion spectrophotometer (GFAAS) technique was used to determine the total arsenic using palladium nitrate Pd(NO3)3 as a modifier agent. The instrumental detection was performed under the condition steps of drying ashing atomizing and cleaning to be 100 1200 2250 and 2600 C. The external calibration curve was constructed using the automatic program based on the master standard of arsenic with 20 ppb. It was found that linearity range was in the range of 1 to 20 ppb with R2>0.999. Based on microwave digestion condition the sample preparation with and without HF was also compared the total arsenic in the spiked soil with a 10 ppb. The result shoewd that the arsenic content obtained fron the prearation with and without HF did not significantly diferent at the 95% confidence limit. The recovery was 80.3 and 82.3% for the spiked sample with 2.5 and 10 ppb respectively. The relative standard deviation was 2.15% (n=11). The results of this work can also confirmed that the preparation method using microwave digestion provided the more advantages such as rapid a little volume of reagents completely digestion.

Utilizing coconut coir fiber can offer an alternative method of adding value to agricultural wastes and help to conserve the environment. The aim of this research was to investigate the potential use of coconut coir fiber as cement composite as an environmentally material. The properties of cement composites mixed with different proportions of paper wastes were compared with ordinary white Portland cement. In addition the surface structure and chemical characteristics of samples were examined by a scanning electron microscope (SEM) and energy dispersive x-ray spectrometer (EDS). The results show that the main elements - C O Ca Al Si and K respectively were found in cement composites. The compressive and flexural strength of the cement composite decreased with an increase in the coconut coir fiber volume fraction.

Thailand is an agricultural country. So that the water resources are important. The water management is very important for keep the water used in necessary time. The monsoon is causes a heavy rain. The monsoon prediction by the mathematical model is important. The accuracy of the forecasts by the predictability measurement method is very important. In this research improvement the predictability measurement for the winter monsoon prediction in the Southeast Asia by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) are used. The data for run the model on 19 December 2059 from the WCRP CMIP3 is the initial condition. The model is run for 7 days forecast. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of the model and improvement the largest Lyapunov exponent (LLE) by limit theorems for verify the efficiency of the model too. The results to show that the shallow water model can be prediction the winter monsoon for 4 days forecast is accuracy when compare with the BCCR-BCM2.0 model and measure the accuracy by LE. In addition the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon for 4 days forecast to same as the LE. Therefore the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon prediction in Thailand by the shallow water model are suitable.

The objectives of this research are to propose a model for estimating and detecting rice yields in Thailand to investigate the factors related to the rice yields to find the trend and to construct the maps of rice yields in Thailand. A linear mixed model (LMM) including the spatial effects which follow the conditional autoregressive model (CAR) and the time effects which follow the first-order linear autoregressive (AR(1)) model is proposed. The estimated rice yields are used to construct the rice yield maps in Thailand. The dependent variables are the rice yield in each month of each province. The factors considered are rainfall average temperatures and regions. The results indicate that the factors enfluencing the rice yields are rainfall average temperatures and regions (North Northeast South East West Central region is a refrence region). The trend also effects the rice yields. The rice yeilds maps are easy for readers to identify which areas have high or low yields and easy to compare the yields among areas by looking at their different colors.