The purpose of this project is to detect the ripeness and quality of the watermelon particularly for red watermelon. The ripeness of the watermelon will be evaluated by using near-infrared spectroscopy sensor (NRIS). The color wavelength will classify the ripeness of the watermelon. An infrared light will be used to get the appropriate wavelength from the watermelon either from the rind or inner of it and the signal received will be analyzed. An appropriate algorithm is used to extract the information of the inner of the watermelon. A microcontroller namely Programmable Interface Controller (PIC) will be used to execute the algorithm and the result will be displayed on Liquid Crystal Display (LCD). Based on the result obtain from the device, the data is computed by using Statistical Package for the Social Sciences (SPSS). This approach is vital to verify the relationship between unripe and ripeness of red watermelon. The objective of this project is to produce an efficient system to detect the ripeness of the watermelon.
This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water.
This paper presents the findings of Visions System performance for the detection of White root disease infection based on capacitance properties. A number of 100 latex samples representing healthy and white root infected rubber tree is tested for its capacitance value using Prototype Console Unit (PCU) developed. An optimized model for ANN using Levenberg Marquardt was designed. It is found that the hidden layer size of neuron 2 gave the best optimized ANN model with 77% sensitivity, 88% specificity, 82.5% accuracy, and uses 5 numbers of connections. A vision system based on this optimized model is developed and has the performance of 78.34% total accuracy.
RRIM clone is a rubber breeding series produced by RRIM (Rubber Research Institute of Malaysia) through "rubber breeding program" to improve latex yield and producing clones attractive to farmers. The objective of this work is to analyse measurement of optical sensing device on latex of selected clone series. The device using transmitting NIR properties and its reflectance is converted in terms of voltage. The obtained reflectance index value via voltage was analyzed using statistical technique in order to find out the discrimination among the clones. From the statistical results using error plots and one-way ANOVA test, there is an overwhelming evidence showing discrimination of RRIM 2002, RRIM 2007 and RRIM 3001 clone series with p value = 0.000. RRIM 2008 cannot be discriminated with RRIM 2014; however both of these groups are distinct from the other clones.
4This chapter is about applying fuzzy logic to categorize the ripeness of Citrus suhuensis using the reflectance measurement. In this study, only selected optical indices were used as reference input to design the fuzzy logic model which are orange, yellow, and green. The wavelength index for yellow is 570 nm, orange at 590 nm, and green at 510 nm. Citrus suhuiensis has same color of skin within the growth stage and maturity stage. The reflectance measurement was taken from an external part, the skin of Citrus suhuiensis. Each Citrus suhuensis was divided into six portions. The data were obtained by using spectrometer. All the data were analyzed using SPSS software for future analysis. For the statistical analysis, input was chosen for fuzzy system. There were two techniques proposed and experimented in this work termed as direct and differential. Direct technique is a direct reflection measurement of optical index representing orange and yellow. Differential technique takes the reflectance measurement slope of orange and yellow with respect to green indices. At the end, all the 212 samples of Citrus suhuensis were successfully tested in this work.
This project describes the development of a capacitive sensor for measuring capacitance of the Dry Rubber Content (DRC) by using parallel plate for classification of rubber clones. Five dry rubber contents from different clones were identified: RRIM2002, RRIM2007, RRIM2008, RRIM2014 and RRIM3001. An aluminium tape had been used as a parallel plate sensor and paired with Arduino microcontroller for the output extraction. The device measures the output in capacitance value from the capacitance sensor based on the dry rubber content samples placed in between the two plates. Statistical analysis using the SPSS software is used to analyse data for each rubber clone; in which for discrimination of data, the normality distribution was tested. The analysis of normality revealed that the data is not normally distributed. Thus, non-parametric test Kruskal-Wallis test is used. Result shows that there is a statistical significance difference of the capacitance value among the five different rubber clone groups. This is proven by significant level of Kruskal-Wallis test of less than 0.05. RRIM2002 has the highest mean rank of capacitance value followed by RRIM2008, RRIM2014, RRIM3001 and the lowest is RRIM2007.
Dry rubber content (DRC) is one of main material existing inside latex. It is usually in ranged of 25% - 45% of rubber latex. Statistical analysis are done to determine the discrimination of dry rubber content of latex between healthy and white root infected rubber tree. Based on 150 rubber trees and 10 clones tested, parametric test which include normality test, error-bar plot, and paired samples test are done. The result outcomes have shown that both data of dry rubber content of latex for healthy and white root infected rubber tree are normally distributed. Error-bar plot test is clearly indicated that there is visible discrimination between both cases. Paired samples test are done to reinforce this findings in terms of numerical p- value which is found to be less than 0.05. Thus, this indicate overwhelming evidence that healthy group can be discriminated from white root. Conclusively, changes in DRC content in latex can be correlated with white root disease infections of rubber tree.
In this paper, the aim of this project is to analyze the acquired information based on Near Infrared (NIR) measurement on dry rubber sheets with respect to white root disease (WRD) infected rubber tree. Then, it will be evaluated statistically using SPSS. WRD is the most serious disease where it can be spread to another tree by root to root. The tree will die slowly once it is infected by WRD. Prevention of WRD is needed to avoid higher losses in a rubber plantation. Hence, this leads the investigation in detecting WRD to overcome the problem through dry rubber sheets. Up till now there is no information and research about the WRD based on NIR spectrum through the dry rubber sheet as a subject. The measurement of NIR via dry rubber sheet using spectrometer MCS600 attached with measuring head OFK 30. NIR spectrum measurement was applied to 7 different regions of Interest (ROI) at dry rubber sheets. The outcome from measurement produces the spectrum responses which are lower peak and upper peak. The output spectrum responses obtained from the experiment are recorded and analyzed using skewness method. The SPSS software is used to analyze the skewness value. From the statistical result, it can be summarized that, healthy and WRD rubber tree can be discriminated from each other through dry rubber sheet using skewness method since the results from analysis produced significant difference at the lower peak in both cases.
White root disease caused by Rigidoporus lignosus is one of most serious disease in rubber plantation. Until now, research about white root disease relates to electrical properties is still less. Hence, this research investigated the differences in electrical properties of healthy and white root disease through dielectric constant value. Seventy six samples of healthy and white root disease respectively were collected from rubber estate located in Kota Tinggi, Johor. Measurement of dielectric constant value for both conditions of latex has been done using Electrochemical Impedance Spectroscopy (EIS) in the range of frequency between 50 Hz up to 10 kHz. The result obtained from this measurement was proceeding with the statistical analysis to analyze the differences of healthy and white root disease. It was found that at frequency 150 Hz, the dielectric constant of healthy and white root disease have show significant differences.
The most serious disease known in rubber industry is root disease and among the major root diseases, white root is the most destructive agent of trees and agricultural crops. Since, it is too difficult and expensive to treat root disease infection on trees; prevention is important whereby one must rely on symptoms appearing on roots themselves in order to recognize the disease. Infection symptom on the tree is detected when leaves became discolored yellowish and dying. The main objective of this work is to investigate empirically an infected rubber trees infected by white root disease where its symptom could be detected visually from leaves gradual discolouration. Visible spectrum of optical measurements is taken on four different regions of interest (ROI) locations of the top side leaf sample features such as petiolule, main vein/midrib, vein and leaf cell of rubber trees. Statistical techniques is used to analyse for conclusive scientific findings of which ROIs above has shown clear discrimination between the healthy, medium and worst condition. The scope of work involves raw data inclusion of leaf samples belong only to 2025 rubber tree clone. This clone is recommended by Rubber Research Institute of Malaysia (RRIM) management due to its popularity and commercially used by small scale planters. Outcomes of this work has suggested that only main vein/midrib and leaf cell ROIs produced convincing significant discrimination between healthy, medium and worst case. Thus, their measurements can be recommended for developing on the shelf technology engineering sensor instrument using non-invasive advanced signal processing techniques and intelligent system for early detection of white root disease.
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