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White root disease (WRD) infection in rubber plantations which is caused by Rigidiporus micropores can lead to a significant yield loss. At the early infection stage, it is very difficult to diagnose the disease because infected trees do not exhibit any symptoms. Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. A total of 50 leaf samples were used in this work, representing five severity levels; healthy, light, moderate, severe and very severe infection. A visible shortwave near-infrared (VSNIR) spectrometer was used to record the spectral data of the leaf samples. The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). The result of the study demonstrates good classification accuracy of 90, 82, 78, and 72% for ANN, SVM, kNN and RF, respectively. This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.

The objective of this study was to study the ability of the VIS-NIR spectroscopy to classify the pure and adulterated stingless bee honey across the wavelength range of 450–969 nm using an optical spectrometer. The physicochemical properties such as soluble solid content (SSC) and moisture content (refractive index, RI) of pure and adulterated honey has also been investigated using a refractometer. The result showed that pure stingless bee honey has the highest transmittance rate, SSC and RI value compared to adulterated honey. There are significant differences (P < 0.0001) in the transmittance rate, SSC and RI of stingless bee honey over five different types of treatments. The results also showed that VIS-NIR data were good in classifying the samples into different treatments with 99.33% accuracy rate. About thirty-four wavelengths were found to be the most significant to discriminate the different treatments by principal component analysis (PCA) and linear discriminant analysis (LDA) techniques.

The sprayed chemicals by drones have been widely reported to be off-targeted and not uniformly distributed. This study aims to evaluate the drone blade’s revolutions per minute (RPM) and its travelling pattern at different payloads and flight speeds. The obtained results were used to relate to the potential effects on the quantity and quality of spraying. In a test flight on an area of 1000 m2, a hexacopter, Advansia A1 was tested in 6 different flying paths of 56 m length. The drone was set to fly at 5 payloads (10, 8, 6, 4, and 2 kg) and 4 flying speeds (i.e. 1, 3, 5, and 7 m.s-1) combinations. The drone travelling pattern and individual rotor blade rpm at each payload-flying speed combinations were analysed. From the result, the RPM of each rotor blade were found to decrease by 14 to 20% as the payload was decreased from 10kg to 0kg. Thus, in actual spraying activities, the changes in RPM could produce a downwash airflow pattern that continually varies from starting point up to the finishing point that would effect on pesticide's distribution along the flying path. On drone travelling pattern, at higher flying speed, a much lesser time and distance was required for the drone to be stabilized to the targeted speed. This relates to the longer time needed by the drone to accelerate and decelerate. The average real speed of the drone was notably reduced to 0.96, 2.72, 3.83 and 4.05 m.s-1, in which, it was, far less than the initial specified speed set at 1, 3, 5, and 7 m.s-1, respectively. The drone flying pattern during spraying needs to be considered for application rate determination to avoid for the crops to be under or over pesticide applications. The obtained finding is remarkably critical and useful in ensuring the efficiency of agricultural chemical spraying activities using drone.

Paperboard box produced in large volume for packaging purpose either to pack light or heavy product. When a heavy product is packed, high strength and structural stability against compression and deformation of the paperboard box are demanded. This paper investigates the effects of different shape of fluting mediums on the von Mises stress and deformation using finite element analysis (FEA) tool. Solidworks and ANSYS software were used to design a 3-D model and perform static structural analysis, respectively. The result from the analysis and simulation revealed that common s-shape geometry experienced the lowest von Mises stress and deformation. Honeycomb geometry experienced the highest von Mises stress of 0.19576 MPa while triangle fluting medium recorded the highest deformation at 1.8695E-4mm.

For the chili plantation in Malaysia, there are currently no harvesting mechanisation involved. The harvesting is still done manually utilising skilled labour and the cost of current harvesting process can reach up to 30% of the total price of the chili in the market. This high cost contributes to the inability of local chili production to compete with cheaper imported chili that had to be brought in to fulfil local needs. The current paper is concerned with the harvesting mechanism that is adapted from another crop type to be used in chili harvesting. The two mechanisms looked at in this paper are rotational harvesting mechanism and vibrational harvesting mechanism. The first utilizes rotational arm that either hits or plucks the fruit as it rotates using harvesting tips. The second vibrates the tree to dislodge the fruit from the tree. The adaptation of these mechanisms to chili is demonstrated with some success for both rotating and vibration mechanism however not without damaging the tree.

The usage of UAV as a pesticide application technology is becoming a common practice in South East Asia with a very significant proportion of agricultural areas have now being treated using such method. Up to date, about more than 169 of various designs and configurations of UAV have been produced to cater the demand, however it is in doubt whether all these available models were optimally integrated with the spray systems to give the required spraying qualities. Despite of each UAV configuration has their own unique aerodynamic effects, it is crucial to determine their downwash airflow patterns, the spray distributions and the effective application parameters that could give high spraying quality. This research outlines the development of an indoor testing facility and its standardised testing procedure for evaluating the spraying performances of any model UAVs that are used in agricultural applications. The testing facility was developed to imitate the UAV in the actual field spraying operation. With 23 m travel length, the developed testing facility was designed to carry the test UAV up to 100 kg, adjust the test UAV at three levels of spraying heights (1.5, 2.5, and 3.5 m), and moves the test UAV up to a maximum travelling speed of 10 m/s. The 6x6 m sampling platform structure for the pressure sensors and water sensitive papers was built underneath the rail support structure to measure and collect data for spraying distributions and downwash 3D profile spectrum. With the availability of this indoor UAV Testing Facility, it is expected that any efforts to increase the spraying efficiency using UAV could be tested repeatedly with same standard protocols, so that proper recommendations could be made on the flying requirements of the UAV in order to achieve an efficient agricultural chemical spraying operation.

Social Innovation is a concept of promoting social development of a community through the introduction of innovation to promote the community to change for the better. The innovation here can be technological, economic, social or combinations of these that aims to improve the community standard of living. One way to start a social innovation is by understanding the problems of the community through experiential learning. A Social Innovation through Team Entrepreneurial Learning (SITEL) workshop was held in Kota Kinabalu, Sabah in June 2018 where one project focuses on stingless bee community in Kg. Mitabang, Kiulu. Through experiential learning of living, discussing and befriending the community, a project was born to help the community to improve their stingless bee honey production by the introduction of homemade stingless bee honey pump. The technology simplification uses items obtainable from local hardware store and aquarium shop to build the pump that could be self-made and self-maintained by the community through a training video. The feedback from the community was positive after the initial introduction of the pump where they are reporting honey production every two weeks compared to months prior to using the pumps.