Interpolation map of salinity is a helpful scientific instrument for environmental monitoring and for social economic development especially for the community who lived in Sungai Merbok. This research was conducted to develop a spatial model of salinity using spline interpolation technique. 20 sampling stations were randomly set up to measure the level of salinity using YSI 650 Multiparameter Display System (MDS). Quantitative analysis of standard regression and error index were used to evaluate the developed model. The research found that the tension splines type performed better than regularized splines type. The local government and community, who live in Sungai Merbok, can use the developed map of salinity for guidelines and future development of Sungai Merbok, Kedah.

This research is conducted to assess the accuracy of spline interpolation methods to predict and model the surface water pH of Pulau Tuba, Langkawi, Kedah, Malaysia. In-situ sampling activities using pH-meter and Geographic Positioning Systems (GPS) were carried out during high tides and at noon in November 2018. The development of spatial models was constructed using Regularized and Tension spline methods. Then, validation of models was carried out to compare the observed and predicted values of pH using correlation analysis, regression analysis, and error analysis. The accuracy of the developed map was calculated using the overall accuracy equation. This research found that the regularized spline method had more accuracy in estimating surface water pH variability than the tension spline method. Pearson correlation coefficient (r), Coefficient of determination (R2), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were reported at 0.896, 0.803, 0.0265 and 0.0344 for the regularized spline method,respectively. The developed spatial model was then transformed into a map by adding map elements such as legend, title, north arrow, and scales for effective visualization. The developed map has an accuracy of 87.50%. The surface water pH was found at the range of 7-8. Low reading of pH is expected due to the addition of rainwater to the coastal water of Pulau Tuba, Langkawi, Kedah. The research outcomes would benefit government and non-government agencies to monitor the coastal and ocean acidification and the development of strategic policies and rules to reduce the impact of anthropogenic activities and climate changes for this area.

The purpose of this research is to evaluate the precision of the Inverse Distance Weighted (IDW) to estimate and map the coastal water pH for the sustainability of Pulau Tuba, Langkawi, Kedah. 30 sampling points have been set up during two sampling activities in November 2018. The pH meter has been calibrated and lowered to 1 meter below the water surface to measure the reading of pH. The development of the spatial model was developed using the spatial analyst tool available in ArcGIS Software. Several types of statistical analyses were carried to compare the observed and predicted value of pHs such as correlation analysis, regression analysis, and error analysis. Accuracy assessment was carried later after the transformation of a spatial model into a surface map. The research found that the IDW method successfully interpolated the pH readings. The research found that there is a strong positive correlation between the observed and predicted values. For error analysis, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were recorded at 0.033 and 0.044, respectively. After the transformation of the spatial model to the surface map, the accuracy of the map is recorded at 81.25%. The map produced can be used by residents and local government for social and economic development and protection of biodiversity at the coastal water of Pulau Tuba, Langkawi, Kedah.

No abstract

The colour of the fish skin is one of the important factors to determine the freshness of a fish. There are potential to use the fish images as an alternative to determining the fish freshness. However, the freshness relationship of the fish skin image to the Red, Green, Blue (RGB) colour channel needs to be elucidated to achieve an accurate interpretation of fish freshness. The objective of this study is to determine the freshness of the fish samples using QIM assessment and to extract the RGB colour value from fish skin images. Finally, to establish the relationship between the QIM scores ranging from 1 (fresh) to 3 (spoiled) and RGB value for freshness indicator using fish images. The effects of temperature, environment, and storage method have been shown to play an important role in determining the rate of deterioration towards the quality and freshness level in fish. From this study, a freshness indicator based on the Quality Index Method (QIM) and RGB value for Queenfish and Threadfin were created. Based on the QIM score, Threadfin was easier to deteriorate as compared to Queenfish from its leaner body type properties. Different fish would reflect different freshness reading as Threadfin is in a fresh state when it possesses a QIM score of 1 with RGB values to range between of 143 to 172. As deterioration progresses, the QIM score is at 3 and the RGB values are ranging from 132 to 161. While Queenfish is found to be in a fresh state when it acquires QIM score of 1 and the RGB values are in the range of 148 to 170. It starts to spoil when the QIM score is at 3 and the RGB values are ranging from 154 to 184.