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Articles by Mohd Kamil Yusoff
Total Records ( 3 ) for Mohd Kamil Yusoff
  Petronella G. Ah Tung , Mohd Kamil Yusoff , Nik Muhamad Majid , Goh Kah Joo and Gan Huang Huang
  Problem statement: The oil palms are mainly grown in the humid tropics with high rainfall. Soluble Nitrogen (N) and Potassium (K) fertilizers are commonly required by the oil palm plantations to maximize palm productivity due to the highly weathered soils with low fertility. Thus, leaching losses of N and K nutrients may be unavoidable and these nutrients may move further downward and eventually cause groundwater pollution. This study reports the leaching of N and K nutrients in a mature oil palm field as affected by fertilizer rates and soil depths and its effect on groundwater quality during the monsoon period in Tawau, Sabah. Approach: The sources of N and K fertilizer were Ammonium Chloride (AC) and Muriate of Potash (MOP), respectively. Soil water samplers were installed at depths of 30, 60 and 120 cm in four fertilizer treatments, namely, N0P0K0 (Control plot, no N and K), N0P2K1 (K1 = 4.5 kg MOP palm-1 year-1), N1P2K1 (N1 = 3.75 AC kg palm-1 year-1) and N1P2K0. Three replications were used in the experiment. Monitoring wells were installed in the above treatment plots and in another treatment, N2P2K1 (N2 = 7.5 kg AC palm-1 year-1) to investigate the effect of excessive N rate on groundwater quality. Samplings were done at 15 day intervals for a duration of 150 days from October 2008-February 2009 to cover the entire monsoon period in Sabah. Water samples were analyzed for NH4-N by automated phenate method, NO3-N + NO2-N and NO2-N by automated hydrazine reduction method on Auto Analyzer 3 and K by flame photometric method using flame photometer. Results: The mean NH4-N concentration of N1P2K1 at 33.69 mg L-1 was significantly higher than N1P2K0 at 8.15 mg L-1. In the presence of K, NH4-N concentrations increased 4.1 fold when N fertilizer was applied and 3.5 times in the absence of N application. The mean NH4-N concentration was 17.89 mg L-1 at 30 cm depth declining to 12.19 and 6.52 mg L-1 at soil depths of 60 and 120 cm, respectively. The transformation of NH4-N to NO3-N was not a major process during the monsoon period. The leaching losses of inorganic N were 1.0 and 1.6% of the applied fertilizer for N1P2K0 and N1P2K1 respectively. For K, the leaching losses were 5.3 and 2.4% for N0P2K1 and N1P2K1 respectively. The concentrations of NH4-N, NO3-N and K in groundwater ranged from 0.23-2.7, 0.07-0.25 and 0.63-9.54 mg L-1, respectively. Conclusion/Recommendations: N and K concentrations in the soil solution decreased with soil depth and their leaching losses were related to rainfall pattern, fertilizer treatment and nutrient uptake by roots. Groundwater quality was not affected by the applications of N and K fertilizers at the optimum rates for mature oil palms.
  Shah Christirani Azhar , Ahmad Zaharin Aris , Mohd Kamil Yusoff and Mohammad Firuz Ramli
  Classification of river water quality needs an efficient method to reduce energy, save time and decrease the risk of errors. This study describes the application of an Artificial Neural Network (ANN) with the softmax activation function to forecast the Water Quality Class (WQC) under the National Water Quality Standard (NWQS) of the Muda River Basin (MRB) (Malaysia). The water quality was classified automatically without Water Quality Index (WQI) calculation. Two different sets of Water Quality Variables (WQVs) were applied as input variables. The modelling discover that the optimal network architecture was the 1:6-1:6-1:1 and used a 60-20-20% splitting plan. ANN1 with the six WQVs was selected to predict the WQC in the MRB. Predictions of the WQC rendered by this model for the training set were very accurate (96.8% correct, Percent Incorrect Prediction (PIP) = 3.2, CEE = 3.44). The approach presented is a very useful and offers a compelling alternative to forecasting of river class, mainly because WQI calculation involves a complex and lengthy calculations. Subsequently, this approach could be applied to water quality classification in other river basins for better water quality management.
  Hazilia Hussain , Mohd Kamil Yusoff , Mohd Firuz Ramli , Puziah Abd Latif , Hafizan Juahir and Mohamed Azwan Mohammed Zawawi
  Nitrate-nitrogen leaching from agricultural areas is a major cause for groundwater pollution. Polluted groundwater with high levels of nitrate is hazardous and cause adverse health effects. Human consumption of water with elevated levels of NO3¯N has been linked to the infant disorder methemoglobinemia and also to non-Hodgkin’s disease lymphoma in adults. This research aims to study the temporal patterns and source apportionment of nitrate–nitrogen leaching in a paddy soil at Ladang Merdeka Ismail Mulong in Kelantan, Malaysia. The complex data matrix (128x16) of nitrate-nitrogen parameters was subjected to multivariate analysis mainly Principal Component Analysis (PCA) and Discriminant Analysis (DA). PCA extracted four principal components from this data set which explained 86.4% of the total variance. The most important contributors were soil physical properties confirmed using Alyuda Forecaster software (R2 = 0.98). Discriminant analysis was used to evaluate the temporal variation in soil nitrate-nitrogen on leaching process. Discriminant analysis gave four parameters (hydraulic head, evapotranspiration, rainfall and temperature) contributing more than 98% correct assignments in temporal analysis. DA allowed reduction in dimensionality of the large data set which defines the four operating parameters most efficient and economical to be monitored for temporal variations. This knowledge is important so as to protect the precious groundwater from contamination with nitrate.
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