Test Frequency Optimization Using Single Factor ANOVA for Capacitive Oil Palm Fruit Ripeness Sensor
نویسندگان
چکیده
منابع مشابه
Intelligent Color Vision System for Ripeness Classification of Oil Palm Fresh Fruit Bunch
Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and analyzed using digital image processing technique...
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Fruit ripeness identification is hard to measure especially when it involves color as main indicator. Suitable color model must be chosen to determine the right color for the ripeness identification. Hue, Saturation and Value (HSV) are proved to be a better choice because it can define the color intensity. Besides, it also helps to choose colors which are similar to the eyes. Manual grading pro...
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Among palm oil millers, the ripeness of oil palm Fresh Fruit Bunch (FFB) is determined through visual inspection. To increase the productivity of the millers, many researchers have proposed with a new detection method to replace the conventional one. The sensitivity of such a sensor plays a crucial role in determining the effectiveness of the method. In our preliminary study a novel oil palm fr...
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This project deals with the ripeness of oil palm fruit. The current procedure in the palm oil mills is grading the oil palm fruit manually using human graders. This method is subjective and inconsistence because each graders has its own techniques and may vary from each other’s. Hence, it affects the quality and quantity of the oil that can be extracted. In this project, a new model of automate...
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ژورنال
عنوان ژورنال: IOP Conference Series: Materials Science and Engineering
سال: 2020
ISSN: 1757-899X
DOI: 10.1088/1757-899x/932/1/012073