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Authentication analysis of red fruit (Pandanus Conoideus Lam) oil using FTIR spectroscopy in combination with chemometrics

Rohman A, Man YB, Riyanto S

Phytochem Anal, 2011 Sep-Oct;22(5):462-7.
PMID: 22033916 DOI: 10.1002/pca.1304

Red fruit (Pandanus conoideus Lam) is endemic plant of Papua, Indonesia and Papua New Guinea. The price of its oil (red fruit oil, RFO) is 10-15 times higher than that of common vegetable oils; consequently, RFO is subjected to adulteration with lower price oils. Among common vegetable oils, canola oil (CaO) and rice bran oil (RBO) have similar fatty acid profiles to RFO as indicated by the score plot of principal component analysis; therefore, CaO and RBO are potential adulterants in RFO.

Matched MeSH terms: Discriminant Analysis
The use of Fourier transform mid infrared (FT-MIR) spectroscopy for detection and quantification of adulteration in virgin coconut oil

Rohman A, Che Man YB

Food Chem, 2011 Nov 15;129(2):583-588.
PMID: 30634271 DOI: 10.1016/j.foodchem.2011.04.070

Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000-650cm-1 on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R2) of 0.999.

Matched MeSH terms: Discriminant Analysis
Fulltext The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN

Rashid M, Bari BS, Hasan MJ, Razman MAM, Musa RM, Ab Nasir AF, et al.

PeerJ Comput Sci, 2021;7:e374.
PMID: 33817022 DOI: 10.7717/peerj-cs.374

Brain-computer interface (BCI) is a viable alternative communication strategy for patients of neurological disorders as it facilitates the translation of human intent into device commands. The performance of BCIs primarily depends on the efficacy of the feature extraction and feature selection techniques, as well as the classification algorithms employed. More often than not, high dimensional feature set contains redundant features that may degrade a given classifier's performance. In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. The common spatial pattern (CSP) has been applied to extract the features from the MI response, and the effectiveness of random forest (RF)-based feature selection algorithm has also been investigated. In order to evaluate the efficacy of the proposed method, an experimental study has been implemented using four publicly available MI dataset (BCI Competition III dataset 1 (data-1), dataset IIIA (data-2), dataset IVA (data-3) and BCI Competition IV dataset II (data-4)). It was shown that the ensemble-based random subspace k-NN approach achieved the superior classification accuracy (CA) of 99.21%, 93.19%, 93.57% and 90.32% for data-1, data-2, data-3 and data-4, respectively against other models evaluated, namely linear discriminant analysis, support vector machine, random forest, Naïve Bayes and the conventional k-NN. In comparison with other classification approaches reported in the recent studies, the proposed method enhanced the accuracy by 2.09% for data-1, 1.29% for data-2, 4.95% for data-3 and 5.71% for data-4, respectively. Moreover, it is worth highlighting that the RF feature selection technique employed in the present study was able to significantly reduce the feature dimension without compromising the overall CA. The outcome from the present study implies that the proposed method may significantly enhance the accuracy of MI data classification.

Matched MeSH terms: Discriminant Analysis
Fulltext Organic cultivation practices enhanced antioxidant activities and secondary metabolites in giant granadilla (Passiflora quadrangularis L.)

Ramaiya SD, Lee HH, Xiao YJ, Shahbani NS, Zakaria MH, Bujang JS

PLoS One, 2021;16(7):e0255059.
PMID: 34310644 DOI: 10.1371/journal.pone.0255059

Passiflora quadrangularis L. belongs to the family Passifloraceae which bears larger fruit with edible juicy mesocarp and pulp known as a good source of phytochemicals. Cultivation and plant management practices are known to influence the phytochemical compositions of agricultural produce. This study aimed to examine the influence of the cultivation practices on the antioxidant activities and secondary metabolites of the organically and conventionally grown P. quadrangularis. Findings revealed organically treated P. quadrangularis plants showed enhancement in their antioxidant properties and secondary metabolites profiles. Among the plant parts, leaves of P. quadrangularis grown organically possessed higher antioxidant activities compared to the conventional in all assays evaluated. The antioxidant activities in the edible parts of the P. quadrangularis fruit have also been enhanced through organic cultivation with significantly higher total phenolic content and DPPH in mesocarp, and the pulp showed higher total flavonoid content, DPPH and FRAP. This observation is supported by a higher level of vitamins and secondary metabolites in the samples. The secondary metabolites profile showed mesocarps were phenolic rich, the pulps were flavonoids rich while leaves showed good composition of phenolics, flavonoids and terpenoids with outstanding antioxidant activities. The common secondary metabolites for organically produced P. quadrangularis in different plant parts include 2-isopropyl-3-methoxycinnamic acid (mesocarp and pulp), myricetin isomers (pulp and leaves), and malvidin-3-O-arabinoside isomers (pulp and leaves). This study confirmed that organic cultivated P. quadrangularis possessed higher antioxidant activities contributed by its vitamins and secondary metabolites.

Matched MeSH terms: Discriminant Analysis
Fulltext The relationship between perceptions and self-paid hepatitis B vaccination: A structural equation modeling approach

Rajamoorthy Y, Radam A, Taib NM, Rahim KA, Wagner AL, Mudatsir M, et al.

PLoS One, 2018;13(12):e0208402.
PMID: 30521602 DOI: 10.1371/journal.pone.0208402

BACKGROUND: Malaysia has a comprehensive, publicly-funded immunization program for hepatitis B (HepB) among infants, but adults must pay for the vaccine. The number of HepB carriers among adults is expected to increase in the future; therefore, we examined the impact of five constructs (cues to action, perceived barriers, perceived benefit, perceived severity, and perceived susceptibility) on adults' willingness to pay (WTP) for HepB vaccine; secondarily, we examined the association between perceived barriers and perceived benefits.
METHODS: Adults were selected through a stratified, two-stage cluster community sample in Selangor, Malaysia. The reliability, convergent validity, and discriminant validity of the measurement model were assessed before implementing a partial least squares structural equation model (PLS-SEM) to evaluate the significance of the structural paths.
RESULTS: A total of 728 participants were enrolled. The five constructs all showed adequate internal reliability, convergent validity, and discriminant validity. There was a significant, positive relationship to WTP from constructs (perceived barriers [Path coefficient (β) = 0.082, P = 0.036], perceived susceptibility [β = 0.214, P<0.001], and cues to action [β = 0.166, P<0.001]), and the model all together accounted for 8.8% of the variation in WTP. There was a significant, negative relationship between perceived barriers and perceived benefit [β = -0.261, P<0.001], which accounted for 6.8% of variation in perceived benefit.
CONCLUSIONS: Policy and programs should be targeted that can modify individuals' thoughts about disease risk, their obstacles in obtaining the preventive action, and their readiness to obtain a vaccine. Such programs include educational materials about disease risk and clinic visits that can pair HepB screening and vaccination.

Matched MeSH terms: Discriminant Analysis
Fulltext Classification of car paint primers using Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC-MS) and chemometric techniques

Raja Zubaidah Raja Sabaradin, Norashikin Saim, Rozita Osman, Hafizan Juahir

Pertanika Journal of Science & Technology, 2017;25(107):53-66.
MyJurnal

Pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) has been recognised as an effective technique to analyse car paint. This study was conducted to assess the combination of Py-GC-MS and chemometric techniques to classify car paint primer, the inner layer of car paint system. Fifty car paint primer samples from various manufacturers were analysed using Py-GC-MS, and data set of identified pyrolysis products was subjected to principal component analysis (PCA) and discriminant analysis (DA). The PCA rendered 16 principal components with 86.33% of the total variance. The DA was useful to classify the car paint primer samples according to their types (1k and 2k primer) with 100% correct classification in the test set for all three modes (standard, stepwise forward and stepwise backward). Three compounds, indolizine, 1,3-benzenedicarbonitrile and p-terphenyl, were the most significant compounds in discriminating the car paint primer samples.

Matched MeSH terms: Discriminant Analysis
Fulltext Vocalisation Repertoire of Female Bluefin Gurnard (Chelidonichthys kumu) in Captivity: Sound Structure, Context and Vocal Activity

Radford CA, Ghazali SM, Montgomery JC, Jeffs AG

PLoS One, 2016;11(2):e0149338.
PMID: 26890124 DOI: 10.1371/journal.pone.0149338

Fish vocalisation is often a major component of underwater soundscapes. Therefore, interpretation of these soundscapes requires an understanding of the vocalisation characteristics of common soniferous fish species. This study of captive female bluefin gurnard, Chelidonichthys kumu, aims to formally characterise their vocalisation sounds and daily pattern of sound production. Four types of sound were produced and characterised, twice as many as previously reported in this species. These sounds fit two aural categories; grunt and growl, the mean peak frequencies for which ranged between 129 to 215 Hz. This species vocalized throughout the 24 hour period at an average rate of (18.5 ± 2.0 sounds fish-1 h-1) with an increase in vocalization rate at dawn and dusk. Competitive feeding did not elevate vocalisation as has been found in other gurnard species. Bluefin gurnard are common in coastal waters of New Zealand, Australia and Japan and, given their vocalization rate, are likely to be significant contributors to ambient underwater soundscape in these areas.

Matched MeSH terms: Discriminant Analysis
Fulltext Reliability and validity of the Spielberger State-Trait Anxiety Inventory (STAI) among urological patients: a Malaysian study

Quek KF, Low WY, Razack AH, Loh CS, Chua CB

Med J Malaysia, 2004 Jun;59(2):258-67.
PMID: 15559178 MyJurnal

To validate the English version of the Spielberger State-Trait Anxiety Inventory (STAI) in a sample of Malaysia patients with and without urinary symptoms. Validity and reliability were studied in patients with lower urinary tract symptoms (LUTS) and patients without LUTS. Reliability was evaluated using the test-retest method and internal consistency was assessed using Cronbach's alpha. Sensitivity to change was expressed as the effect size in the pre-intervention versus post-intervention score in additional patients with LUTS who underwent transurethral resection of the prostate (TURP). Internal consistency was excellent. A high degree of internal consistency was observed for each of the 40 items with Cronbach's alpha value = 0.38 to 0.89 while the Cronbach's alpha for the total scores was 0.86. Test-retest correlation coefficients for the 40 items score were highly significant. Intraclass correlation coefficient was high (ICC=0.39 to 0.89). A high degree of sensitivity and specificity to the effects of treatment was observed. A high degree of significant level between baseline and post-treatment scores was observed across nearly half of the items in surgical group but not in the non-LUTS group (control subjects). The STAI is reliable, valid and sensitive to clinical change in a sample of Malaysian patients with and without urinary symptoms.

Matched MeSH terms: Discriminant Analysis
The Accuracy of Sex Estimation on Metatarsal Bones in a Northeastern Thai Population

Phatsara M, Das S, Laowatthanaphong S, Tuamsuk P, Mahakkanukrauh P

Clin Ter, 2016 May-Jun;167(3):72-6.
PMID: 27424506 DOI: 10.7417/CT.2016.1929

BACKGROUND: This study was carried out to evaluate the accuracy of sex estimation by discriminant analysis and stepwise discriminant analysis equations generated from metatarsal bones in a Thai population.
MATERIAL AND METHODS: The testing samples utilized in this study consisted of 50 skeletons (25 males and 25 females) obtained from the Khon Kaen University Skeletal Collection, Department of Anatomy, Faculty of Medicine, Khon Kaen University. Seven measurements of metatarsal bones were measured in centimeters, using either a mini-osteometric board (MOB) or a sliding caliper. The values measured from the Khon Kaen Skeletal Collection were used to determine the accuracy and applicability of sex determination, as predicted by Y1-Y6 equations which were generated from a Chiang Mai Skeletal Collection.
RESULTS: The percentage of sex determination accuracies predicted from the Y1-Y6 equations demonstrated accuracy rates of 80-95.6.
CONCLUSIONS: The Chiang Mai sex determination equations, generated from metatarsal bones by discriminant analysis (Y1-Y3) and stepwise discriminant analysis (Y4-Y6), demonstrated high accuracy rates of prediction, suggesting that these equations may be useful for sex determination within the Thai population.
KEYWORDS: Foot; Metatarsal bones; Sex determination; Thailand

Matched MeSH terms: Discriminant Analysis
Chemometric application in identifying sources of organic contaminants in Langat river basin

Osman R, Saim N, Juahir H, Abdullah MP

Environ Monit Assess, 2012 Jan;184(2):1001-14.
PMID: 21494831 DOI: 10.1007/s10661-011-2016-8

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.

Matched MeSH terms: Discriminant Analysis
Fulltext Changes in the urinary metabolites in losartan-treated spontaneously hypertensive rats

Norasikin Ab Azis, Mohd Saleh Ahmad Kamal, Zurain Radjeni, Ahmed Mediani, Renu Agarwal

Journal of Clinical and Health Sciences, 2021;6(1):32-45.
MyJurnal

Introduction: This study examined the association of losartan induced changes in urinary
metabolomic profile with the changes in blood pressure (BP) and renin-angiotensinaldosterone system (RAAS) in spontaneously hypertensive rats (SHR). Methods: Male SHR
were administered with either 0.5 mL of distilled water (control group, n=6) or 10 mg.kg-1 of
losartan (group 2, n=6) daily by oral gavage for 4 weeks. Body weight, BP, food and water
intake were measured weekly. At week 4, urine was collected for urinary electrolyte analysis
and metabolite profiling, after which the animals were euthanised by decapitation and blood
was collected for analysis of components of RAAS and electrolyte concentrations. Urine
metabolite profile of SHR was determined using proton nuclear magnetic resonance (
1H-NMR)
spectrometry combined with multivariate data analysis. Results: At week 4, losartan-treated
SHR had significantly lower BP than non-treated SHR. There were no differences in water
and food intake, body weight, serum and urinary electrolyte concentrations or in their urinary
excretions between the two groups. No differences were evident in the components of RAAS
except that the angiotensinogen level was significantly higher in losartan-treated SHR
compared to non-treated SHR. Orthogonal partial least squares discriminant analysis (OPLSDA) showed clear separation of urinary metabolites between control and losartan-treated
SHR. Losartan-treated SHR group was separated from the control group by changes in the
intermediates involved in glycine, serine and threonine metabolism. Conclusion:
Antihypertensive effect of losartan in SHR seems to be associated with changes in urinary
metabolite profile, particularly involving the metabolism of glycine, serine and threonine.

Matched MeSH terms: Discriminant Analysis
Fulltext Chromatographic fingerprint and Chemometric approach for quality control of Tongkat Ali (Eurycoma Longifolia)

Nor Nasriah Zaini, Mardiana Saaid, Hafizan Juahir, Rozita Osman

Pertanika Journal of Science & Technology, 2017;25(103):345-354.
MyJurnal

Tongkat Ali (Eurycoma longifolia) is one of the most popular tropical herbal plants as it is believed to enhance virility and sexual prowess. This study looked examined chromatographic fingerprint of Tongkat Ali roots and its products generated using online solid phase-extraction liquid chromatography (SPE-LC) combined with chemometric approaches. The aim was to determine its quality. Pressurised liquid extraction (PLE) technique was used prior to online SPE-LC using polystyrene divinyl benzene (PSDVB) and C18 columns. Seventeen Tongkat Ali roots and 10 products (capsules) were analysed. Chromatographic dataset was subjected to chemometric techniques, namely cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) using 37 selected peaks. The samples were grouped into three clusters based on their quality. The PCA resulted in 11 latent factors describing 90.8% of the whole variance. Pattern matching analysis showed no significant difference (p>0.05) between the roots and products within the same CA grouping. The findings showed the combination of chromatographic fingerprint and chemometric techniques provided comprehensive evaluation for efficient quality control of Tongkat Ali formulation.

Matched MeSH terms: Discriminant Analysis
A discrimination method for the detection of pneumonia using chest radiograph

Noor NM, Rijal OM, Yunus A, Abu-Bakar SA

Comput Med Imaging Graph, 2010 Mar;34(2):160-6.
PMID: 19758785 DOI: 10.1016/j.compmedimag.2009.08.005

This paper presents a statistical method for the detection of lobar pneumonia when using digitized chest X-ray films. Each region of interest was represented by a vector of wavelet texture measures which is then multiplied by the orthogonal matrix Q(2). The first two elements of the transformed vectors were shown to have a bivariate normal distribution. Misclassification probabilities were estimated using probability ellipsoids and discriminant functions. The result of this study recommends the detection of pneumonia by constructing probability ellipsoids or discriminant function using maximum energy and maximum column sum energy texture measures where misclassification probabilities were less than 0.15.

Matched MeSH terms: Discriminant Analysis
Fulltext Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly

Nik Mohd Fakhruddin NNI, Shahar S, Ismail IS, Ahmad Azam A, Rajab NF

Nutrients, 2020 Sep 23;12(10).
PMID: 32977370 DOI: 10.3390/nu12102900

Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson's correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in "taurine and hypotaurine metabolism" and "tryptophan metabolism" in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.

Matched MeSH terms: Discriminant Analysis
Discriminant analysis of normal and malignant breast tissue based upon INAA investigation of elemental concentration

Ng KH, Ong SH, Bradley DA, Looi LM

Appl Radiat Isot, 1997 Jan;48(1):105-9.
PMID: 9022216

Discriminant analysis of six trace element concentrations measured by instrumental neutron activation analysis (INAA) in 26 paired-samples of malignant and histologically normal human breast tissues shows the technique to be a potentially valuable clinical tool for making malignant-normal classification. Nonparametric discriminant analysis is performed for the data obtained. Linear and quadratic discriminant analyses are also carried out for comparison. For this data set a formal analysis shows that the elements which may be useful in distinguishing between malignant and normal tissues are Ca, Rb and Br, providing correct classification for 24 out of 26 normal samples and 22 out of 26 malignant samples.

Matched MeSH terms: Discriminant Analysis
Fulltext The parasitoid, Verticia fasciventris causes morphological and behavioral changes in infected soldiers of the fungus-growing termite, Macrotermes carbonarius

Neoh KB, Lee CY

J Insect Sci, 2011;11:47.
PMID: 21861651 DOI: 10.1673/031.011.4701

The larval parasitoid Verticia fasciventris Malloch (Diptera: Calliphoridae) develops in the head of soldiers of the fungus-growing termite Macrotermes carbonarius (Hagen) (Isoptera: Termitidae). Morphological and behavioral changes in the host were evaluated and the termite castes and stages that were parasitized were identified. The larval emergence process is also described and possible mechanisms for the parasitoid fly's entry into the host body are discussed based on qualitative observations. Only a single larva per host was found. The mature larva pupated outside the host's body by exiting between the abdominal cerci. Parasitized soldiers possess a short and square-shaped head capsule, a pair of notably short mandibles, and a pair of 18-segmented antennae. Although parasitized soldiers were statistically less aggressive than healthy soldiers (P < 0.05), they expressed varying levels of aggression. Both minor and major soldiers can be parasitized and based on evidence from presoldiers, parasitization may begin during the precursor stages of soldiers. However, the stage at which parasitism first occurs has not been determined.

Matched MeSH terms: Discriminant Analysis
Fulltext A novel investigation of the effect of iterations in sliding semi-landmarks for 3D human facial images

Nazri A, Agbolade O, Yaakob R, Ghani AA, Cheah YK

BMC Bioinformatics, 2020 May 24;21(1):208.
PMID: 32448182 DOI: 10.1186/s12859-020-3497-7

BACKGROUND: Landmark-based approaches of two- or three-dimensional coordinates are the most widely used in geometric morphometrics (GM). As human face hosts the organs that act as the central interface for identification, more landmarks are needed to characterize biological shape variation. Because the use of few anatomical landmarks may not be sufficient for variability of some biological patterns and form, sliding semi-landmarks are required to quantify complex shape.
RESULTS: This study investigates the effect of iterations in sliding semi-landmarks and their results on the predictive ability in GM analyses of soft-tissue in 3D human face. Principal Component Analysis (PCA) is used for feature selection and the gender are predicted using Linear Discriminant Analysis (LDA) to test the effect of each relaxation state. The results show that the classification accuracy is affected by the number of iterations but not in progressive pattern. Also, there is stability at 12 relaxation state with highest accuracy of 96.43% and an unchanging decline after the 12 relaxation state.
CONCLUSIONS: The results indicate that there is a particular number of iteration or cycle where the sliding becomes optimally relaxed. This means the higher the number of iterations is not necessarily the higher the accuracy.

Matched MeSH terms: Discriminant Analysis
Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis

Mustapha A, Aris AZ

J Environ Sci Health A Tox Hazard Subst Environ Eng, 2012;47(10):1455-65.
PMID: 22571534 DOI: 10.1080/10934529.2012.673305

Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.

Matched MeSH terms: Discriminant Analysis
Fulltext Temporal aspects of surface water quality variation using robust statistical tools

Mustapha A, Aris AZ, Ramli MF, Juahir H

ScientificWorldJournal, 2012;2012:294540.
PMID: 22919302 DOI: 10.1100/2012/294540

Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P < 0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P < 0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (r(p) = 0.829) and moderate (r(p) = 0.614) relationships between five-day biochemical oxygen demand (BOD(5)) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH(3)) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R(2) = 0.976 and r = 0.970, R(2) = 0.942 (P < 0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P < 0.05.

Matched MeSH terms: Discriminant Analysis
River water quality assessment using environmentric techniques: case study of Jakara River Basin

Mustapha A, Aris AZ, Juahir H, Ramli MF, Kura NU

Environ Sci Pollut Res Int, 2013 Aug;20(8):5630-44.
PMID: 23443942 DOI: 10.1007/s11356-013-1542-z

Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH4). Partial correlation analysis (r p) results showed that there is a strong relationship between salinity and turbidity (r p=0.930, p=0.001) and BOD5 and COD (r p=0.839, p=0.001) controlling for the linear effects of conductivity and NH4, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD5, COD, SS, NH4, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin.

Matched MeSH terms: Discriminant Analysis

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