Preliminary study on detection of fungal infection in stored paddy using thermal image

Paddy plantation is still threatened by many factors that make rice production become less productive. One of the main factors is paddy infected with fungal. Mycotoxins are toxic substances produced by fungi that grow on seeds or grains in storage and usually will harm human health and animal. Thermal imaging technique is a potential method for the remote detection of abnormality in agricultural products based on temperature changes. In this research, the thermal images of fungal infected paddy were obtained using mid infrared thermal camera after heating for 180s and then cooling in ambient temperature for 30s. Average pixel of the image was used as feature to determine the moisture content. Based on the experiment, fungal infected paddy gave higher average pixel values compared with non-fungal paddy

Determination of Chokanan mango sweetness (Mangifera indica) using non-destructive image processing technique

The Chokanan mango (Mangifera indica) has a high commercial potential. Its sugar content increases as the colour changes during the maturation process. In this research, the relationship between the sweetness of the Chokanan mango and its mean pixel values in RGB and HSB colour space is analyzed. This information could be utilized in determining the level of sweetness of the Chokanan mango without destroying the fruit. A Keyence machine vision system was employed to capture the images of the mango in RGB and HSB colour spaces. Based on the findings, it could be concluded that hue not only has the highest correlation value (-0.916), but also has the lowest value of the standard deviation at all levels of sweetness compared to other colour components. It is possible to determine sweetness at Level 1 and Level 2 with a 100% success rate and a 87% success rate at Level 3

Colour spaces for paddy soil moisture content determination

A study using RGB, HSV and CIELUV colour spaces was conducted to determine the paddy soil moisture content at two different soil depths. Results from the experiment showed that each layer of soil gave a different soil colour as the soil moisture content varies with the depth of the soil layer. By comparing the result of laboratory work with the result of image processing technique, it was shown that 15 cm depth soil which had higher moisture content gave a lower value of mean pixel intensity compared to the surface soil. When the digital images of soil were transformed to HSV (USGS Munsell), a colour space commonly used to represent soil colour, the result showed that the mean pixel intensity was not consistent for each soil layer. To overcome this problem, the RGB and CIELUV colour spaces were used. The CIELUV colour space gave more consistent mean pixel intensity for each soil layer. It successfully indicated that lower moisture content will give higher value of mean pixel intensity. Results from statistical analysis also showed that RGB and CIELUV colour spaces were significantly related to the soil moisture content. CIELUV gave the highest value of correlation at –0.548 and a smaller value of RMSE in linear regression analysis

Historical analysis of the land movement in landslide area using elastic image registration and conditional statement approach.

Temporal amount of land movement is one of the important input parameter in a study of landslide detection and prediction. Automatic approach in monitoring this movement is needed to replace conventional ground surveying technique which is time consuming. An elastic image registration and change-unchanged conditional statements procedure appropriate for historical analysis of the land movement in landslide area is presented herein. Four deformation operators were used during the registration process. The similarity between two images was measured by a similarity function which takes into consideration the value of mutual information, geometric deformation and maximum overlapping area between the two images. Landslide areas were detected using the amount of pixel movement during a registration process. Two stages of four change-unchanged conditional statements had been developed to monitor landslides of future years. These conditional statements made used of the sequence of detected change images as the input parameter. It was shown that the size of pixel movement can be used to detect changes in landslide areas. The more sequences of changed images were used, the more information about the history of the area can be gathered

Application of artificial neural network in predicting crop yield: a review

Agricultural system is very complex since it deals with large data situation which comes from a number of factors. A lot of techniques and approaches have been used to identify any interactions between factors that affecting yields with the crop performances. The application of neural network to the task of solving non-linear and complex systems is promising. This paper presents a review on the use of artificial neural network (ANN) in predicting crop yield using various crop performance factors. General overview on the application of ANN and the basic concept of neural network architecture are also presented. From the literature, it has been shown that ANN provides better interpretation of crop variability compared to the other methods

Determination of the difference on color changes of watermelons by laser light backscattering imaging

The potential of laser light backscattering imaging was investigated for monitoring color parameters of seeded and seedless watermelons during storage. Two watermelon cultivars were harvested and stored for 3 weeks with seven measuring storage days (0, 4, 8, 12, 15, 18, and 21). The color parameters of watermelons were monitored using the conventional colorimetric methods (L*, a*, b*, C*, H*, and ∆E*) and laser light backscattering imaging system. A laser diode emitting at 658 nm and 30 mW power was used as a light source to obtain the backscattering image. The backscattering images were evaluated by the extraction of backscattering parameters based on the mean pixel values. The results showed that a good color prediction was achieved by the seedless watermelon with the R2 are all above 0.900. Thus, the application of the laser light backscattering imaging can be used for evaluating the color parameters of watermelons during the storage period

Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques

Basal stem rot (BSR) is a type of disease that induces oil palm death within a short span of the appearance of symptoms. BSR early detection would facilitate to curb this by adopting appropriate strategies. In this paper, a systematic review was undertaken to demonstrate the need for authentic health condition monitoring of oil palm plantations. The currently used remotely sensed (RS) techniques for BSR detection and classification were reviewed. Several kinds of RS techniques were exerted for BSR detection and its severity classification up to four levels. It was identified that applied geospatial technologies, including multispectral and hyperspectral remote sensing, terrestrial laser scanning, spatial maps, tomography images, intelligent e-nose and Microfocus X-ray fluorescence, were capable of distinguishing infected oil palms from the non-infected ones. Furthermore, some of them are able to categorize BSR severity level up to four levels as well as of its early detection

Optical parameters in food and agricultural processing

The non-destructive feature of optical techniques has gained interests for quality assessment of various agricultural produce as well as in food processing technology. The principle and interaction of light with food and agricultural produce provide essential information for quality assessment which promotes non-destructive inspection methods. This review encompasses the determination of optical properties associated with the evaluation of the quality of agricultural produce. The understanding of how light interacts with turbid agricultural produce is also presented, including light characteristics such as absorption and scattering. A brief overview of the estimation and application of the optical parameters in food and agricultural processing are discussed. The problems and implementation of optical parameters as well as its future trend are also included

Effect of nitrogen fertilizer to growth, biomass and grain yield of paddy

Nitrogen (N) fertilizer is an important plant nutrient for plant growth and yield. This study was conducted with four levels of N i.e., 0, 85, 170 and 250 kg ha-1using two rice cultivars i.e., 'MR219' and 'MR220'. The experiment was carried out in a factorial design with four replications and grown under flooded condition. The study focused on analysing the effect of N fertilizer level and cultivar to growth, biomass and grain yield. Statistical results showed that N significantly affected the plant height, SPAD reading, biomass and yield but did not affect the varieties. The interaction effect between the N level and cultivars also does not show significant difference. With the increment in N application, all parameters were also increased significantly. Maximum plant height (70.46 cm), SPAD reading (39.13), biomass (927.29 g m-2) and yield (830.99 g m-2) were obtained from 250 kg ha-1 nitrogen application. Correlation and regression analysis between plant heights, SPAD reading, biomass and grain yield exhibited a strong and positive relationship. The result also indicate that plant height is a better indicator to estimate biomass (R=0.794, R2=0.630) and grain yield (R=0.634, R2=0.397) compared to SPAD reading

Effect of chitosan and carrageenan-based edible coatings on post-harvested longan (Dimocarpus longan) fruits

The effect of chitosan/carrageenan and glycerol as edible coating materials in preserving the fresh longan fruits stored at ambient temperature was evaluated. The concentration of coating components played an important role in the process of controlling quality changes and quantity losses. Changes in fruits’ weight loss, respiration rate and color were used as a measure of the coating’s effectiveness. Results have shown that increase in the chitosan or carrageenan concentration led to significant (p 1.19%) of the carrageenan resulted in slight increases in water and weight losses. From the multiple response optimization analysis, a combination of 1.29% (w/v) chitosan with 0.42% glycerol and 1.49% (w/v) carrageenan with 0.03% glycerol were predicted to give the desired coating because they were able to preserve the longan by showing minimal quality changes and quantity losses