Plant diseases can greatly affect the total production of food and agricultural materials, which may lead to high amount of losses in terms of quality, quantity and also in economic sense. To reduce the losses due to plant diseases, early diseases detection either based on a visual inspection or laboratory tests are widely employed. However, these techniques are labor-intensive and time consuming. In a view to overcome the shortcoming of these conventional approaches, several researchers have developed non-invasive techniques. Recently, spectroscopy technique has become one of the most available non-invasive methods utilized in detecting plant diseases. However, most of the studies on the application of this novel technology are still in the experimental stages, and are carried out in isolation with no comprehensive information on the most suitable approach. This problem could affect the advancement and commercialization of spectroscopy technology in early plant disease detection. Here, we review the applications and limitations of spectroscopy techniques (visible/infrared, electrical impedance and fluorescence spectroscopy) in early detection of plant disease. Particular emphasis was given to different spectral level, challenges and future outlook.

The repeated usage of frying oil has been proven hazardous due to the degradation process by chemical reactions that lead to changes in the quality of the oil. Currently, the degree of frying oil degradation is indicated by the percentage of its total polar compounds (TPC). In this study, a capacitive sensor was designed to assess frying oil degradation at several heating time intervals by measuring changes on its electrical capacitance. The sensor was designed using interdigitated electrode structure. A total of 30 samples of 130ml palm oil were heated at 180°C up to 30h. For each one hour interval, one sample was moved out from the laboratory oven. The electrical capacitance, total polar compound (TPC) and viscosity of the samples were measured for analysis. Preliminary results demonstrated significant correlation between oil electrical capacitance with TPC and viscosity with R2 ranged from 0.83 to 0.90. The designed sensor has good potential for simple and inexpensive way of determining frying oil quality

A combine harvester has been widely employed for harvesting paddy in Malaysia. However, it is one of the most challenging machines to operate when harvesting grain crops. Improper handling of a combine harvester can lead to a significant amount of grain loss. Any losses during the harvesting process would result in less income for the farmers. Grain loss sensing technology is automated, remote, and prospective. It can help reduce grain losses by increasing harvesting precision, reliability, and productivity. Monitoring and generating real-time sensor data can provide effective combine harvester performance and information that will aid in analyzing and optimizing the harvesting process. Thus, this paper presents an overview of the conventional methods of grain loss measurements, the factors that contribute to grain losses, and further reviews the development and operation of sensor components for monitoring grain loss during harvest. The potential and limitations of the present grain loss monitoring systems used in combine harvesting operations are also critically analyzed. Several strategies for the adoption of the technology in Malaysia are also highlighted. The use of this technology in future harvesting methods is promising as it could lead to an increase in production, yield, and self-sufficiency to meet the increasing demand for food globally.