Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
 
Articles by M.H.A. Husni
Total Records ( 5 ) for M.H.A. Husni
  M.C. Law , S.K. Balasundram , M.H.A. Husni , O.H. Ahmed and Mohd. Haniff Harun
  This study aimed at quantifying the spatial variability of Soil Organic Carbon (SOC), estimating SOC at unsampled locations and comparing the spatial variability of SOC between young and mature oil palm stands. Two study sites were chosen to represent two different palm age groups, i.e., 5 Years after Planting (YAP) and 17 YAP. A systematic sampling design was employed for soil sampling at the 0-20 cm depth based on a cluster of four palms that comprised three operational zones: Weeded Circle (WC), Frond Heap (FH) and Harvesting Path (HP). A total of 60 sampling clusters were obtained for each site. Soil samples were analyzed for SOC by dry combustion method. All measurement points were geo-referenced by differential Global Positioning System (dGPS). The SOC data were first explored using descriptive statistics, normality check, outlier detection and data transformation, followed by variography and interpolation. Spatial variability of SOC was mapped based on measured and kriged values. Results showed that all operational zones exhibited a definable spatial structure, which were described by either spherical or exponential models. All operational zones exhibited strong spatial dependence. Operational zones of 5-year old palms exhibited a shorter effective range than those of 17 year old palms. Additionally, SOC heterogeneity was evident among operational zones at both sites, where FH registered the highest SOC, followed by WC and HP. SOC concentration at 17 year old palms was found to be more stable than that from 5 year old palms. This study suggests spatial variability assessment appears to be a feasible technique to quantify the variability of SOC in oil palm cultivation.
  M.C. Law , S.K. Balasundram , M.H.A. Husni , O.H. Ahmed and Mohd. Hanif Harun
  This study aimed at quantifying the spatial variability of SOC and estimating SOC concentration in oil palm. This study was carried out in a commercial oil palm plantation bearing 27 year old palms. A systematic design was employed for soil sampling at the 0-20 cm depth based on a cluster of 4 palms that included three operational areas Weeded Circle (WC), Frond Heap (FH) and Harvesting Path (HP). A total of 60 sampling clusters were established. SOC was analyzed using dry combustion method. All measurement points were geo-referenced by a differential Global Positioning System (dGPS). The SOC data were first explored using descriptive statistics, normality check and outlier detection. This followed by variography and interpolation techniques to quantify the spatial variability of SOC. Results showed that all three operational areas exhibited a definable spatial structure and were described by either spherical or exponential models. SOC from WC and HP showed moderate spatial dependence while that from FH showed a strong spatial dependence. The FH had a shorter effective range than other operational areas. Contour maps for WC, FH and HP clearly showed spatial clustering of SOC values. All three operational areas fulfilled the interpolation accuracy criteria. This study suggests that site-specific management could be considered as a strategy to increase SOC sequestration in oil palm.
  M.C. Law , S.K. Balasundram , M.H.A. Husni , O.H. Ahmed and Mohd. Hanif Harun
  .
  S.K. Balasundram , M.H.A. Husni and O.H. Ahmed
  Quantification of spatial variability is a vital prerequisite for precision agriculture. This study was aimed at quantifying the spatial variability of selected chemical properties in a tropical peat cultivated with pineapple. A 1-ha study plot was established in a commercial pineapple plantation in Simpang Rengam, Johor. Georeferenced topsoil samples (n = 60) were obtained systematically from 8x18 m spacings in the x and y direction, respectively. These samples were tested for total C, extractable P, K, Cu, Zn and B. Soil data were first explored using univariate statistics, including normality check, non-spatial outlier detection and data transformation. This was followed by variography and kriging analyses to quantify the spatial variability of chemical properties. Results revealed a high degree of spatial variability in the majority of chemical properties, which exhibited non-normal distributions with CVs ranging from 12 to 54%. All properties exhibited a definable spatial structure, which were described by either spherical or exponential models. Carbon, P and B showed strong spatial dependence. The majority of properties had a short effective range. Surface maps of chemical properties clearly showed spatial clustering of test values. Excepting K, all other properties showed acceptable accuracy of interpolated values. These combined data suggest the need for a site-specific approach in managing tropical peat cultivated with pineapple, particularly with regard to nutrient management.
  S. Selvaraja , S.K. Balasundram , G. Vadamalai and M.H.A. Husni
  Orange Spotting (OS) disease which is caused by Cadang-Cadang Coconut Viroid (CCCVd) is an emerging problem in oil palm. This study was aimed at quantifying the spatial variability of OS disease severity as an effort to augment the effectiveness of OS phytopathometry appraisal. A 4.2 ha study plot was established in a commercial oil palm plantation at Sungai Buloh, Selangor. A total of 587 geo-referenced trees were visually observed for OS disease symptoms. OS disease severity data were first subjected to exploratory analysis and followed by variography and interpolation analyses to assess spatial variability. The incidence OS disease in the study area was 74.3%. Measured OS disease severity ranged from 0-92.3%. The spatial structure of OS disease severity was described by an exponential model with an effective range of 29.1 m. OS disease severity exhibited a strong spatial dependence with a nugget to sill ratio of 0.15. The spatial variability map of OS disease severity revealed spatial clustering of kriged values, where 73% of the study area showed low severity (1-30%), 25% showed moderate severity (30-60%) and approximately 2% showed high severity (> 60%). This study demonstrates the utility of geo-spatial information in understanding the OS disease severity scale which could assist in site-specific disease monitoring and intervention.
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility