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Now showing items 1 - 7 of 7

  • Early Detection of Ganoderma Basal Stem Rot of Oil Palms Using Artificial Neural Network Spectral Analysis

    Ahmadi, Parisa   Muharam, Farrah Melissa   Ahmad, Khairulmazmi   Mansor, Shattri   Abu Seman, Idris  

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  • Early Detection of Ganoderma Basal Stem Rot of Oil Palms Using Artificial Neural Network Spectral Analysis

    Ahmadi, Parisa   Muharam, Farrah Melissa   Ahmad, Khairulmazmi   Mansor, Shattri   Abu Seman, Idris  

    Ganoderma boninense is a causal agent of basal stem rot (BSR) and is responsible for a significant portion of oil palm (Elaeis guineensis) losses, which can reach US$500 million a year in Southeast Asia. At the early stage of this disease, infected palms are symptomless, which imposes difficulties in detecting the disease. In spite of the availability of tissue and DNA sampling techniques, there is a particular need for replacing costly field data collection methods for detecting Ganoderma in its early stage with a technique derived from spectroscopic and imagery data. Therefore, this study was carried out to apply the artificial neural network (ANN) analysis technique for discriminating and classifying fungal infections in oil palm trees at an early stage using raw, first, and second derivative spectroradiometer datasets. These were acquired from 1,016 spectral signatures of foliar samples in four disease levels (T1: healthy, T2: mildly-infected, T3: moderately infected, and T4: severely infected). Most of the satisfactory results occurred in the visible range, especially in the green wavelength. The healthy oil palms and those which were infected by Ganoderma at an early stage (T2) were classified satisfactorily with an accuracy of 83.3%, and 100.0% in 540 to 550 nm, respectively, by ANN using first derivative spectral data. The results further indicated that the sensitive frond number modeled by ANN provided the highest accuracy of 100.0% for frond number 9 compared with frond 17. This study showed evidence that employment of ANN can predict the early infection of BSR disease on oil palm with a high degree of accuracy.
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  • Development of behenic acid-ethyl cellulose oleogel stabilized Pickering emulsions as low calorie fat replacer

    Ahmadi, Parisa   Tabibiazar, Mahnaz   Roufegarinejad, Leila   Babazadeh, Afshin  

    This study investigated the optimization of thermal, functional and rheological properties of Ethyl Cellulose (EC)based oleogel considering different concentrations of Behenic Acid (BA) and stability of water in oleogel (w/og) emulsions. The results showed that the combination of EC and BA improved the oleogel properties at specific ratios (2:4 and 1:5 wt%). High strength (G' > 1000 mPa) with good thermo-responsive and viscoelastic behavior in the range of 45-60 degrees C and low loss of oil (<02%) were observed in these oleogel formulations. Polarized light microscopy images and XRD results showed the presence of crystals and high proportion of crystalline regions in the mentioned formulations. There were no significant differences among solid fat content (SFC) of EC contained oleogels. The FTIR results indicated new hydrogen bonds formation. The w/og stabilized emulsions with EC: BA (1:5 wt%) oleogel showed high physical stability even at high ratios of disperse phase (5 to 45 wt% of water). The particle size and polydispersity index (PDI) of emulsions were reduced significantly to 250 nm and 0.19, respectively by increasing the ratio of water phase to 45:55 w/og. The oleogel and developed Pickering w/og emulsion has good potential in the formulation of low calorie food products. (C) 2019 Elsevier B.V. All rights reserved.
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  • 3D-QSAR and docking studies of the stability constants of different guest molecules with beta-cyclodextrin

    Ahmadi, Parisa   Ghasemi, Jahan B.  

    This study aims at developing a three dimensional quantitative structure-activity relationship (3D-QSAR) model for predicting complexation of a variety of 126 organic compounds with beta-cyclodextrins (beta-CD). Molecular descriptors were computed using GRid INdependent Descriptors (GRIND) approach. After variable selection via genetic algorithm method, GRIND are correlated with beta-CD complexes stability constants by PLS regression. Kennard-Stone algorithm selected a training dataset comprised of 98 guest molecules. This strategy led to a final QSAR model that showed good internal cross-validation statistics and good predictivity on external data. Those GRIND information which influencing the complexation with beta-CD were also confirmed by the 3D-QSAR and docking studies. All these information revealed that the presence of hydrogen bond acceptor and hydrogen bond donor groups in the molecules caused a more difficult and/or unfavorable complexation reaction with beta-CDs. The size and shape of the molecules as well as hydrogen bonding interactions effects on the stabilities of beta-CDs in inclusion complexes are discussed.
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  • Sensitive electrochemical sensor for urea determination based on F-doped SnO2 electrode modified with ZnO-Fe3O4 nanoparticles transducer:Application in biological fluids

    Mikani, Mohaddeseh   Talaei, Sam   Rahmanian, Reza   Ahmadi, Parisa   Mahmoudi, Asieh  

    As a unique strategy, a sensitive urea biosensor media involving dip coated ZnO and Fe3O4 nanocomposite, at the optimized instrumental deposition conditions, on the F-doped SnO2 conducting glass was designed (Fe3O4-ZnO/SnO2:F) to achieve an excellent platform for urease enzyme (Urs) immobilization (Urs/Fe3O4-ZnO/SnO2:F). The Fe3O4-ZnO nanocomposite selection principles were based on urea biosensing improvement by Urs immobilization on ZnO nanoparticles by electrostatic adsorption, while Fe3O4 selection criteria were dependent upon giving high electronic density to the biosensor surface as an electrostatic repulsion layer at the biological media for the anionic interferents. Surface morphology characterization of the nanocomposite film by field emission-scanning electron microscopy (FE-SEM) displays nanocomposite film as an operative biosensing area for Urs enzyme immobilization. Step by step monitoring of Urs/Fe3O4-ZnO/SnO2:F biosensor fabrication was done using electrochemical techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Urs/Fe3O4-ZnO/SnO2:F biosensor was exploited for urea quantification by I-V assessment The I-V consequences show high sensitivity for urea detection within 5-150 mg dL(-1) and limit of detection as 5 mg dL(-1). Consequently, the proposed method presented a potential application for producing the disposable sensor with good repeatability. Additionally, fast response of fabricated sensor can usually allow real-time analysis of real samples.
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  • Sensitive electrochemical sensor for urea determination based on F-doped SnO2 electrode modified with ZnO-Fe3O4 nanoparticles transducer: Application in biological fluids

    Mikani, Mohaddeseh   Talaei, Sam   Rahmanian, Reza   Ahmadi, Parisa   Mahmoudi, Asieh  

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  • Development of Ethyl Cellulose-based Formulations:A Perspective on the Novel Technical Methods

    Ahmadi, Parisa   Jahanban-Esfahlan, Ali   Ahmadi, Azam   Tabibiazar, Mahnaz   Mohammadifar, Mohammadamin  

    Cellulose is known as the most abundant natural polymer and ethyl cellulose (EC) is one of its important derivatives. Recently, EC, as a non-toxic and biodegradable polymer, has attracted attention thanks to its unique properties such as oleogel formation, delivery of active component, and film-forming ability in the food and pharmaceutical sectors. EC-based oleogels have great promise for replacing with unhealthy hydrogenated oils in food products. The EC emulgel could be used as a fat replacer in different food and drug formulation and also for encapsulation of active components. EC, as a non-digestable and water-insoluble polymer, forms micro- and nano-particles with unique properties. Accordingly, this paper tries to focus on mechanistic review of different methods for the fabrication of EC-based formulations and micro/nanoparticles with emphasis on recent progress on wide range applications of the water-insoluble polymer. Additionally, different techniques are discussed in this paper including oleogelation, anti-solvent, emulsion, Pickering emulsion, and electrospinning for the preparation of EC-based formulations.
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