Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10-1 to 10-5 ng/?l were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Fish oil is a common source of fat in fish feed production. However, there is a tendency to substitute fish oil with other fats such as lard to reduce production costs. Thus, an efficient method for lard detection is highly needed for fish feed’s authenticity. In this study, sn-2 fatty acids (sn-2 FAs) and fatty acid (FA) compositions were incorporated with chemometric techniques namely Principal Component Analysis (PCA), Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA), and Orthogonal Partial Least Square-Regression (OPLS-R) to identify lard adulteration in the fish feeds. The inclusion of sn-2 FAs into PCA model 2 exhibited a preferable variation pattern relative to PCA model 1. The PCA identified C14:0, C18:0, C18:2, C18:3, C20:0 sn-2 C16:0, sn-2 C18:0, sn-2 C18:1, and sn-2 C18:2 were the most significant FAs to discriminate the fish feeds. The inclusion of sn-2 FA composition improved the OPLS-DA model 2 performance by providing more significant class discrimination between lard-adulterated, and non-adulterated fish feeds as compared to OPLS-DA model 1. The OPLS-DA model 2 identified C18:0, C18:2, C18:3, and sn-2 C16:0 FAs as markers of lard adulteration with an increment in the value of the coefficient of determination (R2) and decrement in the Root Mean Square Error of Estimation (RMSEE) and Root Mean Standard of Cross-Validation (RMSECV) values. The Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron-Artificial Neural Network (MLP-ANN), and internal and external validations corroborated the OPLS-DA model 2 and OPLS-R model 2 performances. Therefore, the incorporation of sn-2 FA and FA compositions coupled with the chemometric techniques had improved the detection and quantification of lard adulteration in fish feeds.

Disaster And its Threat To Food: Analysis Of Crisis This study aims to assess and evaluate the disaster response system of food in Malaysia, the capacity to respond to disasters, and to promote the strategy for the dissemination of disaster management. The effectiveness of an emergency response in Malaysia will depend on the national food safety system in place and public health preparedness planning for emergency situations and preparedness plans that are developed and implemented long before any event occurs. For disaster which is classified as non-disastrous, the relevant agencies can handle using minimum resources and facilities at local level. In case of disaster caused by fire or hazardous materialsp (hazmat), Fire and Rescue Department Malaysia will act as a main agency to handle it. District Police Chief or State Police Chief which is relevant, still hold the responsibility as commander of disaster operation on scene to coordinate the involvement of the other agencies. Among the non-disastrous incidents are the vehicle accidentqthe small fire or a mishap in a lake or river. Therefore going by this directive, Emergency Rensponse Team (ERT) has a role to contribute and play in both disastrous and non disastrous disaster in assisting the government machinery.

Discrimination between lard and other edibles fats is a challenging task for halal determination especially after the fats were heated at high temperature for a long period. In this study, three multivariate regression models such as partial least square regression (PLSR), principal component regression (PCR) and support vector machine regression (SVMR) were applied to evaluate the spectral data of FTIR (n=195) obtained from lard, chicken, beef, mutton and vegetable fats after heated at different conditions (120-240°C and 0.5-3 hrs). The regression of the Y-binary matrix was used to discriminate lard (as 1) and the others edibles fats (as 0). Kennard Stone (KS) algorithm selected a subset of the training set (n=145) and test set (n=50). The test set was used to validate the prediction ability of the suggested models. The obtained results showed the ability of the three proposed models to discriminate the heated lard simultaneously. The values of the R2 , adjusted R2 , root-mean-square error (RMSE) and root mean-square error of validation (RMSEV) showed a good results under Basic ATR correction transformation as PLSR (0.984, 0.977, 0.052 and 0.062); PCR (0.974, 0.971, 0.067 and 0.070), and SVMR (0.971, 0.959, 0.087 and 0.102) respectively. However, when using mean square error (MSE), it gives lower prediction error for PLSR (0.006), PCR (0.007) and SVMR (0.015). The results showed that PLSR as the best model for discrimination spectral data of lard and other edible fats after heating treatments for halal determination.

Accuracy, reliability, defensibility, and timeliness are all aspects of laboratory quality. The outcomes must be error-free in order to produce high accuracy data. Valid methods and calibrated equipment are referred to as reliability. To dispute the laboratory results, all possible errors were identified and the measurement uncertainties were estimated. The certificate of analysis or report must be issued timely. Laboratories in Malaysia was referred to the ISO/IEC 17025 for accreditation purpose. There are three essential elements defined as the backbone of the laboratory quality system. Validate analytical methods, accreditation involving third part auditing and participation in proficiency testing (PT). For this study, PT data is used as a tool to assess laboratory quality management systems' competency. Even if their performance is satisfactory according to the PT provider's evaluation criteria, participants in PT can interpret their results to detect inaccuracies and possibilities for continuous improvement. One of the PT schemes from MyKIMIA Proficiency Testing Provider (PTP) selected for the case study, the overall percentage of satisfactory for the Food Analysis Scheme (FODAS) 1-20 Benzoic acid (BA) and Sorbic acid (SA) in cordial was in the range from 82% to 88%. Statistic performance evaluation was based on a calculation of Z score for Test 1, Test 2 and Test 4. The laboratories shall recalculate the Z score based on the PTP assigned value and fit for purpose standard deviation proficiency assessment (SDPA). Zeta score can be calculated to check the plausibility of the laboratory's measurement uncertainty estimate. The outlier data received that cause the poor performance include human errors, random errors, and systematic errors. Investigation on the errors is consistently based on four main factors: manpower, method, material, and machinery (4M).

Exploratory data analysis was performed on DAD-HPLC and on-flow HPLC-NMR data sets to determine the number of components (rank) in the mixture, and their elution times. The performance of principal component analysis, correlation plots, Euclidean distance, derivative plots, orthogonal projection approach, SIMPLISMA (SIMPLe-to-use Interactive Self-modelling Mixture Analysis) and evolving principal component analysis were compared on a mixture of three regio isomers of dihydroxynaphthalene. It was shown that derivatives and SIMPLISMA performed better with HPLC-NMR data than the other methods. OPA and evolving PCA performed best in DAD-HPLC. The relative performance of each chemometric method differs for each analytical technique, suggesting that criteria are dependent on instrumental method.

Multivariate statistical tools like cluster analysis have proved useful in characterizing and studying geneticdiversity of germplasm resources. Thus, this study was aimed at classifying the diversity pattern in oil palmgermplasm using two hierarchical clustering methods (single linkage clustering method and Ward’s method). 595 oil palm genotypes grouped into 44 accessions were morphologically characterized for yieldtraits, bunch quality traits, morphological and physiological traits and fatty acid traits. The two clusteringmethods classified the accessions into eight groups and differ slightly in the assigning of the accessions into groups. The oil palm germplasm with different characteristics were identified and the genetic distancewithin and between the groups was estimated.

The soap-making process involves heating, encompassing various mechanisms such as oxidation and thermal reactions. These reactions can potentially modify the chemical structure of both animal and vegetable oils, making it challenging to trace their original sources in processed products. In this study, seven distinct bar soaps were produced using the saponification method, employing locally available commercial oils, including Canola Oil (LA), Coconut Oil (CN),Corn Oil (CO), Olive Oil (OV), Palm Oil (PO), Sunflower Oil (SF), and animal fat from Lard (LD). The chemical profiles of the raw lard and vegetable oils, as well as their respective soaps and the fats/oils extracted from the soap, were obtained using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy, followed by analysis through a chemometric approach. Principal Components Analysis (PCA) was employed after pretreatment of the FTIR dataset to discern their distribution in a score plot for determining clustering. For clustering lard from vegetable oils, the wavenumbers ranging from 1500 to 1000 cm-1 were selected in the PCA analysis. The extraction of fats/oils from the final product, coupled with the chemometric method, successfully demonstrated the differentiation of soaps produced from vegetable oils and animal fats commonly sold in the market.

Discrimination of fatty acids (FAs) of lard in used cooking oil is important in halal determination. The aim of this study was to find the information related to the changes FAs of lard when frying in cooking oil. Quantitative analysis of FAs composition extracted from a series of experiments which involving frying cooking oil spiked with lard at three different parameters; concentration of spiked lard, heating temperatures and period of frying. The samples were analyzed using Gas Chromatography (GC) and Principal Components Analysis (PCA) technique. Multivariate data from chromatograms of FAs were standardized and computed using Unscrambler X10 into covariance matrix and eigenvectors correspond to Principal Components (PCs). Results have shown that the first and second PCs contribute to the FAs mapping which can be visualized by scores and loading plots to discriminate FAs of lard in used cooking oil.

The utilization of biopolymer derived from Moringa oleifera bark using ZnCl2 and H2SO4 as activating agents for eliminating methylene blue, Escherichia coli and Pseudomonas aeruginosa from producing wastewater. In this study, methylene blue and both bacteria were effectively adsorbed by activated carbon with lowest dosage. The activated carbon was prepared from natural by product of Moringa oleifera bark by pyrolysis in a furnace at 700 °C for 1 h. The characteristics of activated carbon have been determined using Scanning Electron Microscopy (SEM), Brunauer-Emmett-Teller (BET), pHzpc (zero point charge), and FTIR spectroscopy. The obtained result were closely fitted with Freundlich isotherm model and adsorption kinetics follow the pseudo second order model with the highest value of correlation coefficient (R2~1). Adsorption quantity was dose dependent and bacteria were maximum adsorbed using 10 mg of activated carbon as well as 25 mg for methylene blue. The maximum adsorption capacity showed within 1 hour. The bacterial cells were reduced by 98 % for E. coli, 96 % for P. aeruginosa as well as methylene blue reduced 94.2 % from aqueous solution using batch adsorption methods. Adsorption process controlled by film diffusion mechanism. These results proposed that the activated carbon of Moringa oleifera bark can be used as a good adsorbent for the removal of Methylene blue, E. coli and P. aeruginosa.

The utilization of biopolymer derived from Moringa oleifera bark using ZnCl2 and H2SO4 as activating agents for eliminating Methylene blue, Escherichia coli and Pseudomonas aeruginosa from producing wastewater. In this study, Methylene blue and both bacteria were effectively adsorbed by activated carbon with lowest dosage. The activated carbon was prepared from natural-by product of Moringa oleifera bark by pyrolysis in a furnace at 700°C for 1 h. The characteristics of activated carbon have been determined using Scanning Electron Microscopy (SEM), Brunauer-Emmett-Teller (BET), pHzpc (zero point charge), and FTIR spectroscopy. The obtained result were closely fitted with Freundlich isotherm model and adsorption kinetics follow the pseudo-second order model with the highest value of correlation coefficient (R2~1). Adsorption quantity was dose dependent and bacteria were maximum adsorbed using 10 mg of activated carbon as well as 25mg for methylene blue. The maximum adsorption capacity showed within 1 hour. The bacterial load was reduced by 98% for E. coli, 96% for P. aeruginosa as well as methylene blue reduced 94.2% from aqueous solution using batch adsorption methods. Adsorption process controlled by film diffusion mechanism. These result proposed that the activated carbon of Moringa oleifera can be used as a good adsorbent for the removal of Methylene blue, E. coli and P. aeruginosa.