Wan Ishak Wan Ismail

Development of Image Based Modeling for Determination of Oil Content and Days Estimation for Harvesting of Fresh Fruit Bunches

In this study, the relationship of oil extraction rate (OER) and fruit ripeness will be determined. The sample of oil palm fruits was collected from the unripe until the overripe stage and the oil content of the mesocarp for fresh fruit bunches (FFB) was extracted by using bunch analysis procedure to get the oil extraction rate. Using the same samples of FFB, the pixel value of images which measure in hue, was determined by developed image analysis software. The images were captured under an outdoor environment in an oil palm plantation. The sunlight intensity of environment was recorded using Extech light meter at various times of the day from morning to afternoon in the oil palm plantation. The result of the experiment that showed a good relationship was found between the oil content of FFB with its image pixel values. The mathematical model was developed in determining the optimum days for FFB harvesting.

Design and Development of a Segmented Rubber Tracked Vehicle for Sepang Peat Terrain in Malaysia

In order to improve the crossing ability, the tractive performance of a vehicle operating on low bearing capacity peat terrain and the loss of income resulting from downtime and maintenance cost, the vehicle must be designed with an ability to adapt to the changes of prevailing operation conditions. This paper describes the design and development of a new segmented rubber tracked vehicle for peat terrain in Malaysia. A new mathematical model for peat terrain, which was used to determine the forces at the ground contact parts of the track element of front idler-terrain, intermediate roadwheels-terrain, and rear sprocket-terrain interfaces is developed. The simulated performance results, such as vehicle average motion resistance coefficient of 6.8–7.9%, drawbar pull coefficient of 25.22–47%, and the tractive efficiency of 74–77% for the vehicle slippage of 5–20% indicate that the vehicle can meet the peat terrain field requirement with its optimal power consumption.

Modeling of oil palm fruit maturity for the development of an outdoor vision system.

Color is the most important indicator farmers use to determine the maturity of the oil palm fruit called fresh fruit bunches (FFB) in the manual harvesting process. To automate the harvesting operation, the development of a vision system will replace the human eye for mature FFB recognition. In real plantation environments, variations in the daylight caused the light intensity to change, thus becoming the main issue that affects the automatic recognition process. In this study, the matured FFB was captured using a Sony digital Handycam on the day shift period. At the same time period of daylight intensity, a unit on foot candles (FC) also was simultaneously recorded using an Extech lightmeter data logger. From the linear regression analysis process, the mathematical model shows that there is a linear change between daylight intensity with the pixel value of the components green and blue. For the pixel value of the red component, the value will be linear at a maximum of 255 and at a certain intensity. To validate the mathematical model, this equation is used in the development of software for outdoor recognition processes.

Outdoor colour recognition system for oil palm fresh fruit bunches (ffb)

The variations of day light intensity must be taken into account to recognize the color of the agriculture product when using camera vision system. In this study, the development of outdoor image analysis for oil palm fruit fresh bunches (FFB) was developed to analyses image of oil palm FFB. The software analysis will generates the mathematical model and correlation factor between the light intensity in relation to value of FFB from Red, Green and Blue component (RGB) of image taken. The visual basic programming language was used. An Excel worksheet programming software was developed to draw a chart and modify the charts location and dimensions. The API (Application Programming Interface) called GDI32 (Graphic Device Interface: 32-bit version) was applied to read and manipulate the pixel value of image. The software automation technique was used in the development of outdoor image analysis for agriculture product. The automation concept is to describe the automatic generation of the software to manipulate the data for producing the graph, mathematical analysis and equation, automatically from a bundle of data collected by only a click of mouse button. The result generated was used to develop mathematical model for color-based recognition for outdoor image of agriculture product. Linear regression function was used to find the equation of mathematical model for outdoors image analysis. To find the best equation of mathematical model, various trendline of data manipulation can be chosen manually from option provided in Microsoft Excel. The images of FFB were taken by using sony digital camera Handycam at various times of day from morning to afternoon in the oil palm plantation. Keywords - Outdoors Vision System, Colour Recognition, Software Automation, Oil Palm FFB

Machine Vision to Determine Agricultural Crop Maturity

Agriculture in Malaysia is still one of the biggest enterprise and the most important sector in Malaysia’s economy. In the last 35 years, Malaysia has emerged as the number one producer of palm oil. In year 2010, Malaysia accounts for about 55% of world palm oil production and about 62% of world exports. The Malaysian oil palm industry continues to contribute significantly to the country’s economic development and foreign exchange earnings. However, the Malaysian oil palm industry needs more emphasis on its research and development to meet the world challenge and to maintain Malaysia as the top world producer of palm oil. The major problem faced by the oil palm plantation is shortage of labor, especially in harvesting of oil palm FFB (MPOIP, 2007).

Processes involved in the design of a segmented rubber tracked vehicle for Sepang peat terrain in Malaysia

This paper describes a framework for designing a new segmented rubber track vehicle for low bearing capacity Sepang peat terrain in Malaysia. Based on a given set of vehicle dimensions and terrain-track system constants, a simulation technique is then used to optimise the design parameters of the vehicle by establishing mathematical models for the track-peat terrain mechanism. The simulation results showed that the nominal ground pressure of the vehicle is 23.5% lower than the bearing capacity of the peat terrain. The location of the centre of gravity of the vehicle at 300mm rearward from the mid-point of the track ground contact length ensures a maximum sinkage of 90 mm, a minimum motion resistance of 12% and a maximum tractive efficiency of 74% during traversing at 10 km/hr on the peat terrain. Finally, the vehicle components have been designed by using 3D-CAD drawing software package.