Ali Yeon Md Shakaff
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Preferred name
Ali Yeon Md Shakaff
Official Name
Ali Yeon, Md Shakaff
Alternative Name
Shakaff, A. Y. M.
Shakaff, A. Y.Md
Shakaff, A. Y.
Shakaff, Ali Y.M.
Main Affiliation
Scopus Author ID
8721012500
Researcher ID
DPT-4421-2022

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  • Publication
    Disposable E-Tongue for the assessment of water quality in fish tanks
    ( 2008)
    Chew-Cheen Chang
    ;
    Bahruddin Saad
    ;
    Misni Surif
    ;
    Mohd Affendi Ahmad Pozin
    ;
    Ali Yeon Md Shakaff
    A disposable screen-printed e-tongue based on sensor array and pattern recognition that is suitable for the assessment of water quality in fish tanks is described. The characteristics of sensors fabricated using two kinds of sensing materials, namely (i) lipids (referred to as Type 1), and (ii) alternative electroactive materials comprising liquid ion-exchangers and macrocyclic compounds (Type 2) were evaluated for their performance stability, sensitivity and reproducibility. The Type 2 e-tongue was found to have better sensing performance in terms of sensitivity and reproducibility and was thus used for application studies. By using a pattern recognition tool i.e. principal component analysis (PCA), the e-tongue was able to discriminate the changes in the water quality in tilapia and catfish tanks monitored over eight days. E-tongues coupled with partial least squares (PLS) was used for the quantitative analysis of nitrate and ammonium ions in catfish tank water and good agreement were found with the ion-chromatography method (relative error, ±1.04- 4.10 %).
  • Publication
    Development of multichannel artificial lipid-polymer membrane sensor for phytomedicine application
    ( 2006)
    Mohd Noor Ahmad
    ;
    Zhari Ismail
    ;
    Oon–Sim Chew
    ;
    AKM Islam
    ;
    Ali Yeon Md Shakaff
    Quality control of herbal medicines remain a challenging issue towards integrating phytomedicine into the primary health care system. As medicinal plants is a complicated system of mixtures, a rapid and cost-effective evaluation method to characterize the chemical fingerprint of the plant without performing laborious sample preparation procedure is reported. A novel research methodology based on an in-house fabricated multichannel sensor incorporating an array of artificial lipid-polymer membrane as a fingerprinting device for quality evaluation of a highly sought after herbal medicine in the Asean Region namely Eurycoma longifolia (Tongkat Ali). The sensor array is based on the principle of the bioelectronic tongue that mimics the human gustatory system through the incorporation of artificial lipid material as sensing element. The eight non-specific sensors have partially overlapping selectivity and cross-sensitivity towards the targeted analyte. Hence, electrical potential response represented by radar plot is used to characterize extracts from different parts of plant, age, batch-to-batch variation and mode of extraction of E. longifolia through the obtained potentiometric fingerprint profile. Classification model was also developed classifying various E. longifolia extracts with the aid of chemometric pattern recognition tools namely hierarchical cluster analysis (HCA) and principal component analysis (PCA). The sensor seems to be a promising analytical device for quality control based on potentiometric fingerprint analysis of phytomedicine.
  • Publication
    A Disposable sensor for assessing artocarpus heterophyllus L. (Jackfruit) maturity
    ( 2003)
    Maxsim Sim
    ;
    Mohd Noor Ahmad
    ;
    Ali Yeon Md Shakaff
    ;
    Chang Ju
    ;
    Chang Cheen
    The purpose of this work was an attempt to monitor the ripeness process and to investigate the different maturity stages of jackfruit by chemometric treatment of the data obtained from the disposable sensor. Response of the sensor strip fabricated using screen- printing technology was analyzed using Principal Component Analysis (PCA) and the classification model constructed by means of Canonical Discriminant Analysis (CDA) enable unknown maturity stages of jackfruit to be identified. Results generated from the combination of the two classification principles show the capability and the performance of the sensor strip towards jackfruit analysis.
  • Publication
    Monitoring of milk quality with disposable taste sensor
    ( 2003)
    Maxsim Sim
    ;
    Teo Jau Shya
    ;
    Mohd Noor Ahmad
    ;
    Ali Yeon Md Shakaff
    ;
    Abdul Othman
    ;
    Muhammad Hitam
    A disposable screen-printed multi channel taste sensor composed of several types of lipid as transducers and a computer as data analyzer could detect taste in a manner similar to human gustatory sensation. The disposable taste sensor was used to measure the electrical potential resulted from the interaction between lipid membranes and taste substances. In the present study, two types of packaged commercial milk, the ultra high temperature (UHT) and the pasteurized milk were tested. It was found that the disposable taste sensor is capable to discriminate reliably between fresh and spoiled milk and to follow the deterioration of the milk quality when it is stored at room temperature based on a pattern recognition principle namely Principle Component Analysis (PCA). This research could provide a new monitoring method ideally for simple and cheap decentralized testing for controlling the quality of milk, which may be of great use in the dairy industries.
  • Publication
    A hybrid sensing approach for pure and adulterated honey classification
    ( 2012)
    Norazian Subari
    ;
    Junita Mohamad Saleh
    ;
    Ali Yeon Md Shakaff
    ;
    Ammar Zakaria
    This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.
  • Publication
    Labview™ for Nutra-Biostrip in Herbal Quality Assessment
    ( 2004)
    Mohd Noor Ahmad
    ;
    Maxsim Yap Mee Sim
    ;
    Mohd Kamal Mohamed Ramly Nil
    ;
    Ali Yeon Md Shakaff
    ;
    Chang Chew Cheen
    In this work, we introduce the approach on the development of a stand-alone laptop based data acquisition of an array sensor system, namely Nutra-BioStrip coupled with pattern recognition algorithm for herbal quality assessment. The array sensor system control program, developed in Lab View 6. 1 programming languages allow data acquired from the array sensor to be analyzed by means of Principal Component Analysis (PCA) and displayed in the form of an interactive twodimensional cluster mapping with detail statistical analysis results for rapid and real-time herbal quality assessment.