Preliminary investigations of Agrobacterium-mediated transformation in indica rice MR219 embryogenic callus using gusA gene

Preliminary steps in the genetic transformation of indica rice MR219 was investigated in the plant- Agrobacterium tumefaciens interaction. Agrobacterium tumefaciens strain LBA 4404 carrying a binary vector pCAMBIA 1305.2 harboring the modified GUS gene driven by the CaMV 35S promoter was used. Various transformation parameters influences were optimized using embryogenic calli via β- glucuronidase (GUS) as a reporter marker. Various transformation parameters were optimized including bacterial concentration, age of embryogenic callus, pre-culture period, wounding technique, cocultivation period, immersion time and dry time before co-cultivation, acetosyringone (AS) concentration, pH of co-cultivation media and temperature of the co-cultivation period. The expression of the transient gusA gene in the plant genome was preliminary confirmed by histochemical GUS assay activity (as blue spots). The results from transient gusA gene expression of calli suggested that the Agrobacterium-mediated transfer system of T-DNA in indica rice MR219 was highly efficient. Therefore, the investigation of factors that influence T-DNA delivery is an important first step in the utilization of Agrobacterium in the transformation of indica rice MR219 calli.Key words: Indica rice MR219, Agrobacterium tumefaciens, GUS expression

Development of classification models for basal stem rot (BSR) disease in oil palm using dielectric spectroscopy

Basal stem rot (BSR) is the most destructive disease in oil palm plantations caused by Ganoderma boninense fungus, leading to a major economic setback in palm oil production. In order to reduce the losses caused by this disease, an effective early detection method is needed. Early detection not only prevents production losses, but it also reduces the use of chemicals. Therefore, this paper aims at investigating an early detection method utilizing dielectric properties (impedance, capacitance, dielectric constant, and dissipation factor) of oil palm trees. Leaf samples of healthy, mild, moderate, and severely-infected trees were collected and leaves’ dielectric properties were measured at a frequency range of 100 kHz–30 MHz with 100 kHz intervals. These spectral data were then reduced by principal component analysis (PCA) method. Following that, the reduced spectral data were tested to classify the leaf samples into four levels of disease severity. The classifiers used are linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN), and Naïve Bayes (NB). The results showed that the dielectric spectra of oil palm leaves of diffident BSR severity levels were statistically different (p < 0.0004). In addition, despite the slight better performance of QDA classifier, ANOVA test revealed that there was no significant difference in accuracy between all other classifier models (p = 0.7169). Amongst the tested dielectric properties, impedance is considered the best parameter to assess the severity of BSR disease in oil palm with overall accuracy ranging from 81.82% to 100%. These results verify the potential of dielectric spectroscopy for detecting BSR disease in oil palm

Early detection of diseases in plant tissue using spectroscopy – applications and limitations

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

Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy

Basal stem rot (BSR) is a prominent plant disease caused by Ganoderma boninense fungus, which infects oil palm plantations leading to large economic losses in palm oil production. There is need for novel disease detection techniques that can be used to reduce the oil palm losses due to BSR. Thus, this paper investigated the feasibility of utilizing electrical properties such as impedance, capacitance, dielectric constant, and dissipation factor in early detection of BSR disease in oil palm tree. Leaf samples from different oil palm trees (healthy, mild, moderate, and severely-infected) were collected and measured using a solid test fixture (16451B, Keysight Technologies, Japan) connected to an impedance analyzer (4294A, Agilent Technologies, Japan) at a frequency range of 100 kHz–30 MHz with 300 spectral interval. Genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS) were used to analyze the electrical properties of the dataset and the most significant frequencies were selected. Following the selection of significant frequencies, the features were evaluated using two classifiers, support vector machine (SVM) and artificial neural networks (ANN) to determine the overall and individual class classification accuracies. The selection model comparative feature analysis demonstrated that the best statistical indicators with overall accuracy (88.64%), kappa (0.8480) and low mean absolute error (0.1652) were obtained using significant frequencies produced by SVM-FS model. The results indicated that the SVM classifier shows better performance as compared to ANN classifier. The results also showed that the classes, features selection models, and the electrical properties were found to be significantly different (p < .1). The impedance values were highly classified by Ganoderma disease at different levels of severity with overall accuracies of more than 80%. Impedance can be considered as the best electrical properties that can be used to estimate the severity of BSR disease in oil palm using spectroscopy technique. As such, this study demonstrates the potentials of utilizing electrical properties for detection of Ganoderma diseases in oil palm

Design and Analysis of Blast Resistant RC Beams for Concrete Structures at Off-Site Oil & Gas Plants

The impact resistance of Reinforced Concrete (RC) beams, as the major structural load-bearing member, is an integral consideration in the design of concrete structures at the off-site of oil and gas pants against powerful dynamic loads. As a result, impact-resistant design is crucial for the maintenance, preservation, and safety of such structures. The RC beams' impact performance, on the other hand, remain unclear, and approaches for reinforcing RC structures at oil and gas plants to withstand impact loads are currently limited. This paper presents the Finite Element Analysis (FEA) used to simulate the behavior of Reinforced Concrete (RC) beams strengthened with Carbon Fiber Reinforced Polymer (CFRP) laminates. Five beams were modelled in FEA software. In those five beams, one beam was used as control beam without CFRP reinforcement, two beams were reinforced with single CFRP sheet, and the other two were reinforced with two CFRP sheets. Total deformation, von Misses stress, shear stress and principal strain were obtained and compared with the experimental results. The numerical simulation results agree well with the test findings reported in Neagoe's experimental study. The simulation results demonstrated that CFRP could indeed relieve high stress in impact unstable concrete, decrease beam body deformation, constrain crack development, and offer additional impact resistance. Under various impact load scenarios, CFRP can successfully restrain deformation. As a result, strengthening RC beams with CFRP is an efficient way to improve impact load resistance. Using computer software to design and simulate these elements was also much quicker and less costly. As a result, ANSYS can be used to model experimental beams. Finite element ANSYS software can also be used to validate experimental results

The research of blast resistant of reinforcement concrete beams in concrete structures at off-site oil and gas plant

In the recent decades, blasts and gas explosions at the off-site of oil and gas plants have increased leading to destruction of important concrete structures, essential equipment and loss of human life. In response, structural engineers have come up with different ways of reinforcing beams of concrete structures using fiber reinforced polymers composite materials to produce blast resistant structures to minimize the impact of the blast loads, due to their unique and individual characteristics like high flexural and shear strength. This paper seeks to research the dynamic behavior, response and performance of reinforce concrete beams strengthened with Carbon Fiber Reinforced Polymer composites when subjected to blast loading. The study aims at proposing a design model of strengthening reinforce concrete beams with Carbon Fiber Reinforced Polymer in supporting concrete structures at off-site oil and gas plants against hydrocarbon explosions. Carbon Fiber Reinforced Polymer composites exhibit higher modulus of elasticity, higher energy absorption capacity, resistant to all forms of alkali and higher tensile strength compared to all other fiber reinforced polymers reinforcements and therefore the need to assess its capacity in protecting concrete structures at oil and gas plants against dynamic loads. The research will be carried out through numerical analysis using the finite element analysis computer program, ANSYS

Model analysis of carbon fiber reinforcement properties for reinforced concrete beams to resist blast loads

Safety is paramount in Oil & Gas plants, and continuous monitoring and improvements ensure that all measures are taken to protect them. The purpose of this paper is to examine how composite materials can be used to improve the structural reinforcement of concrete beams. Concrete structural beams have been improved in the past by using varying Fiber Reinforced Properties (FRP). It has been investigated how Carbon Fiber Reinforced Properties (CFRP) composites perform under blast loads and how they behave, respond, and perform as reinforcement for reinforced concrete beams. The response of RC beams to blasts was analyzed using a software modelling program called ANSYS that can mimic RC beam properties when reinforced with CFRP in concrete structures. The reason CFRP was chosen was because its properties showed great potential and it is well suited for testing and analysis. As well as absorbing a lot of energy, this material is strong, elastomeric, and alkali-resistant. A numerical analysis and model analysis have been performed with the help of the ANSYS software program. In the experimental results, CFRP was found to increase the flexural and shear strength of RC beams. The RC beams reinforced with CFRP has outperformed RC beam (control beam) in factors such as in Deformation, Equivalent Stress, and Shear Stress by a minimum percentage difference of 0.784% and maximum of 7.09% depending on the layers of CFRP and load applied on the beams in each factor

Dielectric constant and chlorophyll content measurements for basal stem rot (BSR) disease detection

Basal stem rot (BSR) is a common plant disease that is largely responsible for high economic losses in oil palm production. Several novel techniques have recently been develop and reported in the literature for detecting BSR disease in oil palm plantations. However, studies on the application of electrical properties in detecting BSR disease in oil palm does not exist. Therefore, this paper aims to contribute to the existing knowledge by investigating the potential of dielectric constant (DC) and chlorophyll properties in detecting BSR disease in oil palms. The study involved the collection of different leaf samples namely; healthy, mild, moderate, and severely-infected. Impedance analyzer operating at a frequency range of 100 kHz-30 MHz with 300 spectral intervals and SPAD 502 were used to measure the DC and chlorophyll of the samples collected, respectively. ANOVA, Duncan's multiple range test (DMRT) and principal component analysis (PCA) were used for statistical analysis. The results of this study showed a significant relationship between DC and different severity levels of BSR disease (p <; 0.0001). Specifically, BSR disease severity levels of all samples collected were clearly discriminated based on DC. Conversely, the chlorophyll content could not classify the different levels of BSR disease into distinct separate groups but two groups (healthy and BSR-infected). As such, the results demonstrated that DC and chlorophyll content at certain extend could be used as a sensing parameter for Ganoderma disease detection

Comparison of different protein extraction methods for gel-based proteomic analysis of Ganoderma spp.

Ganoderma species are a group of fungi that have the ability to degrade lignin polymers and cause severe diseases such as stem and root rot and can infect economically important plants and perennial crops such as oil palm, especially in tropical countries such as Malaysia. Unfortunately, very little is known about the complex interplay between oil palm and Ganoderma in the pathogenesis of the diseases. Proteomic technologies are simple yet powerful tools in comparing protein profile and have been widely used to study plant–fungus interaction. A critical step to perform a good proteome research is to establish a method that gives the best quality and a wide coverage of total proteins. Despite the availability of various protein extraction protocols from pathogenic fungi in the literature, no single extraction method was found suitable for all types of pathogenic fungi. To develop an optimized protein extraction protocol for 2-DE gel analysis of Ganoderma spp., three previously reported protein extraction protocols were compared: trichloroacetic acid, sucrose and phenol/ammonium acetate in methanol. The third method was found to give the most reproducible gels and highest protein concentration. Using the later method, a total of 10 protein spots (5 from each species) were successfully identified. Hence, the results from this study propose phenol/ammonium acetate in methanol as the most effective protein extraction method for 2-DE proteomic studies of Ganoderma spp

Exploiting surface plasmon with dielectric coating in copper wires waveguide for the propagation of terahertz waves

Recently, metallic wires have gained popularity for utilization as waveguides in propagating sub-THz and THz waves through surface plasmonic polaritons (SPPs). Single and double metallic wire waveguides have demonstrated the ability to propagate these high frequencies with minimal loss and nearly zero dispersion. However, wires typically installed commercially are often coated with dielectric material. Therefore, this paper investigated the effects of using two and four metallic copper wires, both with and without dielectric coating. The impact of various gap distances on different propagation characteristics was also analyzed. Computer Simulation Technology (CST) Microwave Studio was employed in this study for electromagnetic simulations of both uncoated and coated configurations of two and four wires. The introduction of a dielectric coating led to an enhancement in reducing conductor losses and improving energy confinement, with the goal of enhancing the overall efficiency of waveguide signal propagation