MyMedR

Displaying all 6 publications

Abstract:

Sort:

Drainage increases CO2 and N2 O emissions from tropical peat soils

Prananto JA, Minasny B, Comeau LP, Rudiyanto R, Grace P

Glob Chang Biol, 2020 08;26(8):4583-4600.
PMID: 32391633 DOI: 10.1111/gcb.15147

Tropical peatlands are vital ecosystems that play an important role in global carbon storage and cycles. Current estimates of greenhouse gases from these peatlands are uncertain as emissions vary with environmental conditions. This study provides the first comprehensive analysis of managed and natural tropical peatland GHG fluxes: heterotrophic (i.e. soil respiration without roots), total CO2 respiration rates, CH4 and N2 O fluxes. The study documents studies that measure GHG fluxes from the soil (n = 372) from various land uses, groundwater levels and environmental conditions. We found that total soil respiration was larger in managed peat ecosystems (median = 52.3 Mg CO2 ha-1 year-1 ) than in natural forest (median = 35.9 Mg CO2 ha-1 year-1 ). Groundwater level had a stronger effect on soil CO2 emission than land use. Every 100 mm drop of groundwater level caused an increase of 5.1 and 3.7 Mg CO2 ha-1 year-1 for plantation and cropping land use, respectively. Where groundwater is deep (≥0.5 m), heterotrophic respiration constituted 84% of the total emissions. N2 O emissions were significantly larger at deeper groundwater levels, where every drop in 100 mm of groundwater level resulted in an exponential emission increase (exp(0.7) kg N ha-1 year-1 ). Deeper groundwater levels induced high N2 O emissions, which constitute about 15% of total GHG emissions. CH4 emissions were large where groundwater is shallow; however, they were substantially smaller than other GHG emissions. When compared to temperate and boreal peatland soils, tropical peatlands had, on average, double the CO2 emissions. Surprisingly, the CO2 emission rates in tropical peatlands were in the same magnitude as tropical mineral soils. This comprehensive analysis provides a great understanding of the GHG dynamics within tropical peat soils that can be used as a guide for policymakers to create suitable programmes to manage the sustainability of peatlands effectively.
Fulltext Design and Develop Low-Cost Device on Monitoring Environmental Indoor Air Quality in Factory

Mohd Azrin Mohd Said, Shawn Felix Stephen, Nor Kamaliana Khamis, Abdullah Yassin, Ana Sakura Zainal Abidin, Rudiyanto Philman Jong, et al.

Journal of Engineering and Science Research, 2020;4(4):6-11.
MyJurnal

Environmental indoor air quality is one of the major concerns in occupational safety and health issues related to workers. Nowadays, the evolving of Internet of Things (IoT), the monitoring of the surrounding environmental desired parameters is more fascinating with the use of various sensors. Real time data now can be monitored with the Wi-Fi connection where the data being transfer across the network cloud with different platform service. This research focus is on the environmental monitoring for indoor air quality in terms of carbon monoxide (CO) in selected palm oil mill factory. This project aims to benefit the workers in a way where air quality is monitored. This low-cost device air quality monitoring (LCDAQM) used an ESPduino-32 to collect and process sensed data to the ThingSpeak platform service that can be monitored through web based or apps. The level of the carbon monoxide (CO) will light up the red LED when reach more than 50ppm which was set by OSHA. Result shows that level of CO in factory is unhealthy and need future engineering control action. The validation between LCDAQM and RS CO meter show the percentage error of 14.41%. Therefore, this study will help workers and factory to monitor and reduce the occupational safety and health (OSH) related problems to indoor air quality in factory.
Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products

Maulidiani, Rudiyanto, Abas F, Ismail IS, Lajis NH

Food Chem, 2018 Jun 01;250:37-45.
PMID: 29412925 DOI: 10.1016/j.foodchem.2018.01.023

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO2 assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization.
Complementary NMR- and MS-based metabolomics approaches reveal the correlations of phytochemicals and biological activities in Phyllanthus acidus leaf extracts

Abd Ghafar SZ, Mediani A, Maulidiani M, Rudiyanto R, Mohd Ghazali H, Ramli NS, et al.

Food Res Int, 2020 10;136:109312.
PMID: 32846521 DOI: 10.1016/j.foodres.2020.109312

Proton nuclear magnetic resonance (1H NMR)- and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS)-based analytical tools are frequently used in metabolomics studies. These complementary metabolomics platforms were applied to identify and quantify the metabolites in Phyllanthus acidus extracted with different ethanol concentrations. In total, 38 metabolites were tentatively identified by 1H NMR and 39 via UHPLC-MS, including 30 compounds are reported for the first time from this plant. The partial least square analysis (PLS) revealed the metabolites that contributed to α-glucosidase and nitric oxide (NO) inhibitory activities, including kaempferol, quercetin, myricetin, phyllanthusol A, phyllanthusol B, chlorogenic, catechin, cinnamic coumaric, caffeic, quinic, citric, ellagic and malic acids. This study shows the significance of combining 1H NMR- and UHPLC-MS-based metabolomics as the best strategies in identifying metabolites in P. acidus extracts and establishing an extract with potent antioxidant, anti-diabetic, and anti-inflammatory properties.
Rapid assessment of total MCPD esters in palm-based cooking oil using ATR-FTIR application and chemometric analysis

Goh KM, Maulidiani M, Rudiyanto R, Wong YH, Ang MY, Yew WM, et al.

Talanta, 2019 Jun 01;198:215-223.
PMID: 30876552 DOI: 10.1016/j.talanta.2019.01.111

The technique of Fourier transform infrared spectroscopy is widely used to generate spectral data for use in the detection of food contaminants. Monochloropropanediol (MCPD) is a refining process-induced contaminant that is found in palm-based fats and oils. In this study, a chemometric approach was used to evaluate the relationship between the FTIR spectra and the total MCPD content of a palm-based cooking oil. A total of 156 samples were used to develop partial least squares regression (PLSR), artificial neural network (nnet), average artificial neural network (avNNET), random forest (RF) and cubist models. In addition, a consensus approach was used to generate fusion result consisted from all the model mentioned above. All the models were evaluated based on validation performed using training and testing datasets. In addition, the box plot of coefficient of determination (R2), root mean square error (RMSE), slopes and intercepts by 100 times randomization was also compared. Evaluation of performance based on the testing R2 and RMSE suggested that the cubist model predicted total MCPD content with the highest accuracy, followed by the RF, avNNET, nnet and PLSR models. The overfitting tendency was assessed based on differences in R2 and RMSE in the training and testing calibrations. The observations showed that the cubist and avNNET models possessed a certain degree of overfitting. However, the accuracy of these models in predicting the total MCPD content was high. Results of the consensus model showed that it slightly improved the accuracy of prediction as well as significantly reduced its uncertainty. The important variables derived from the cubist and RF models suggested that the wavenumbers corresponding to the MCPDs originated from the -CH=CH2 or CH=CH (990-900 cm-1) and C-Cl stretch (800-700 cm-1) regions of the FTIR spectrum data. In short, chemometrics in combination with FTIR analysis especially for the consensus model represent a potential and flexible technique for estimating the total MCPD content of refined vegetable oils.
Fulltext NMR and LCMS analytical platforms exhibited the nephroprotective effect of Clinacanthus nutans in cisplatin-induced nephrotoxicity in the in vitro condition

Mahmod II, Ismail IS, Alitheen NB, Normi YM, Abas F, Khatib A, et al.

BMC Complement Med Ther, 2020 Oct 22;20(1):320.
PMID: 33092571 DOI: 10.1186/s12906-020-03067-3

BACKGROUND: Clinacanthus nutans (C. nutans) Lind. locally known as Belalai Gajah or Sabah snake grass is a medicinal plant belonging to Acanthaceae family. In Asia, this plant is traditionally used for treating skin rashes, insects and snake bites, diabetes mellitus, fever and for diuretic effect. C. nutans has been reported to possess biological activities including anti-oxidant, anti-inflammation, anti-cancer, anti-diabetic and anti-viral activities.
METHODS: Proton Nuclear Magnetic Resonance (1H NMR) and Liquid Chromatography Mass Spectroscopy (LCMS) coupled with multivariate data analysis were employed to characterize the metabolic variations of intracellular metabolites and the compositional changes of the corresponding culture media in rat renal proximal tubular cells (NRK-52E).
RESULTS: NMR and LCMS analysis highlighted choline, creatine, phosphocholine, valine, acetic acid, phenylalanine, leucine, glutamic acid, threonine, uridine and proline as the main metabolites which differentiated the cisplatin-induced group of NRK-52E from control cells extract. The corresponding media exhibited lactic acid, glutamine, glutamic acid and glucose-1-phosphate as the varied metabolites. The altered pathways perturbed by cisplatin nephrotoxic on NRK-52E cells included changes in amino acid metabolism, lipid metabolism and glycolysis.
CONCLUSION: The C. nutans aqueous extract (1000 μg/mL) exhibited the most potential nephroprotective effect against cisplatin toxicity on NRK-52E cell lines at 89% of viability. The protective effect could be seen through the changes of the metabolites such as choline, alanine and valine in the C. nutans pre-treated samples with those of the cisplatin-induced group.