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Fulltext A bio-inspired herbal tea flavour assessment technique

Zakaria NZ, Masnan MJ, Zakaria A, Shakaff AY

Sensors (Basel), 2014;14(7):12233-55.
PMID: 25010697 DOI: 10.3390/s140712233

Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied.
Fulltext Morphological Variability Identification of Harumanis Mango (Mangifera indica L.) Harvested from Different Location and Tree Age

Yusuf SNA, Rahman AMA, Zakaria Z, Subbiah VK, Masnan MJ, Wahab Z

Trop Life Sci Res, 2020 Jul;31(2):107-143.
PMID: 32922671 DOI: 10.21315/tlsr2020.31.2.6

Harumanis is one of the main signatures of Perlis with regards to its delightful taste, pleasant aroma and expensive price. Harumanis authenticity and productivity had become the remarks among the farmers, entrepreneurs, consumers and plant breeders due to the existence of morphological characteristics variation among the fruits and high production cost. Assessment of Harumanis morphological characteristics of natural population and different tree ages may represent a possible source of important characteristics for development and breeding purposes of Harumanis. The aim of this study is to evaluate the morphological variation of Harumanis collected from different location in Perlis and tree age. A total of 150 Harumanis fruits from 50 trees with three different stages of development (young, middle-aged and old) were characterised using 11 traits; 10 quantitative and one qualitative morphological trait. The ANOVA analyses in combination with Dunn's pairwise and Kruskal-Wallis multiple comparison test able to point out the existence of environmental factor and age influence towards the significant different of identified morphological traits except for Total Soluble Solid (TSS) and pulp percentage. Five clusters of 50 Harumanis accessions reflect a grouping pattern which not according to neither geographical region nor age. The result of Principal Component Analysis (PCA) using the first two principal components (PCs) provided a good approximation of the data explaining 84.09% of the total variance which majorly contributed by parameters of weight, fruit dimensional characteristics, peel percentage and hue angle, h. Preliminary screening of important morphological characteristics which contribute to the phenotypic diversity of Harumanis is successfully achieved. The findings can be employed by the plant breeders and farmers for the establishment of standard grading of Harumanis and advancement of breeding crop of Harumanis in future.
Fulltext Improved maturity and ripeness classifications of Magnifera Indica cv. Harumanis mangoes through sensor fusion of an electronic nose and acoustic sensor

Zakaria A, Shakaff AY, Masnan MJ, Saad FS, Adom AH, Ahmad MN, et al.

Sensors (Basel), 2012;12(5):6023-48.
PMID: 22778629 DOI: 10.3390/s120506023

In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied.
Fulltext Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors

Zakaria A, Shakaff AY, Adom AH, Ahmad MN, Masnan MJ, Aziz AH, et al.

Sensors (Basel), 2010;10(10):8782-96.
PMID: 22163381 DOI: 10.3390/s101008782

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
Clinical profiles and predictors of survival in severe dengue cases

Che Isa Z, Lim JA, Ain AM, Othman FA, Kueh YC, Tew MM, et al.

Singapore Med J, 2023 Nov 03.
PMID: 38037775 DOI: 10.4103/singaporemedj.SMJ-2022-072

INTRODUCTION: Dengue is endemic in tropical countries. Severe dengue has a high risk of morbidity and mortality. We aimed to identify factors associated with dengue survival among our intensive care unit (ICU) patients.
METHODS: A retrospective study was conducted among dengue cases admitted to the ICU of Hospital Sultan Abdul Halim, Kedah, Malaysia from 2016 to 2019.
RESULTS: Out of 1,852 dengue cases admitted to the hospital, 7.2% of patients required ICU admission. Survival rate was 88.6% among severe dengue cases. The majority of severe dengue patients were obese, while other notable comorbidities included hypertension and diabetes mellitus. Also, 73% of patients presented in the critical phase, at a median of Day 4 of illness. All patients admitted to the ICU had a history of fever. The predominant warning signs were lethargy, fluid accumulation and haemoconcentration with rapid platelet reduction. Among nonsurvivors, 69.2% had fulminant hepatitis, 53.8% had massive bleeding or disseminated intravascular coagulation, 38.5% had haemophagocytic lymphohistiocytosis and 30.8% had myocarditis. The predominant serotypes were DENV-3 and DENV-1. The least number of cases was seen in 2017, when all serotypes were equally presented. Multiple logistic regression showed that Sequential Organ Failure Assessment (SOFA) score, peak international normalised ratio, peak partial thromboplastin time and aspartate aminotransferase on admission were independent risk factors for survival. This model had an area under the curve of 0.98, giving an overall 98.2% accuracy.
CONCLUSIONS: Specific warning signs and blood investigations in dengue patients may aid in early decision for ICU admission. Monitoring of SOFA scores plus coagulation and liver enzyme profiles could improve dengue survival rates.
Fulltext A biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration

Zakaria A, Shakaff AY, Masnan MJ, Ahmad MN, Adom AH, Jaafar MN, et al.

Sensors (Basel), 2011;11(8):7799-822.
PMID: 22164046 DOI: 10.3390/s110807799

The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.
Fulltext In-vitro diagnosis of single and poly microbial species targeted for diabetic foot infection using e-nose technology

Yusuf N, Zakaria A, Omar MI, Shakaff AY, Masnan MJ, Kamarudin LM, et al.

BMC Bioinformatics, 2015;16:158.
PMID: 25971258 DOI: 10.1186/s12859-015-0601-5

Effective management of patients with diabetic foot infection is a crucial concern. A delay in prescribing appropriate antimicrobial agent can lead to amputation or life threatening complications. Thus, this electronic nose (e-nose) technique will provide a diagnostic tool that will allow for rapid and accurate identification of a pathogen.