No abstract

It is essential to control the quality of diesel products so that they comply with relevant fuel specifications, however, the quality assessments rely upon conventional wet chemical analyses that are costly and time consuming. Rapid, simultaneous quality measurement enabling immediate online optimisation for process control and blending offers tremendous cost savings by minimising product quality give-away, shipment demurrage, tank inventory, and laboratory analysis. In this study, the use of near infrared spectroscopy and chemometrics demonstrates a straightforward workflow for simultaneous determination of the petroleum diesel’s boiling point at 95% recovery (T95), flash point (FP), cloud point (CP), and cetane index (CI) calibration development. It involved appropriate spectral region selection, calibration/validation set partition, data pre-processing, regression modelling and validation. Based on the calibration and validation results, the supervised learning models that are obtained from a combination region of 4000–4800 cm−1 on a randomly selected calibration set managed to deliver promising predictive performance in terms of coefficient of determination for prediction (r2P/T95 ≥ 0.94, r2P/FP ≥ 0.89, r2P/CP ≥ 0.89, r2P/CI ≥ 0.993), root mean square error of prediction (RMSEP (T95) ≤ 5.2°C, RMSEP (FP) ≤ 2.0°C, RMSEP (CP) ≤ 2.4°C, RMSEP (CI) ≤ 0.3), and ratio of performance deviation (RPD (T95) ≥ 3.7, RPD (FP) ≥ 3.0, RPD (CP) ≥ 2.9, RPD (CI) ≥ 11). Regardless of principal component regression or partial least square regression on either the multiplicative scattering corrected spectra or Savitzky Golay second derivative spectra, the developed models met respective ASTM reproducibility requirements, and were considered adequate for immediate quality assessment of diesel.

Submontance forest at five different altitudes along the western slope of Frasers' Research Centre (FHRC) in Raub District, Pahang State of Malaysia by Ward Linkage Method (WLM) was classified. Five plots were set at 1000 m (P1), 1050 m (P2), 1100 m (P3), 1150 m (P4) and 1200 m (P5), and all the trees with diameter at breast height (DBH) ≥ 5 cm have been measured. Cluster analysis by WLM of these plots resulted in the identification of four forest zones (FZ) denoted by FZ1P1, FZ2P2, FZ3P3P4 and FZ4P5. These forest zones were denoted by three most dominant species in term of importance value (Iv) such as Dacrydium elatum (Roxb.) Wall. ex Hook.- Prunus arborea (Blume) Kalkman - Adinandra dumosa Jack (Zone FZ1P1), Trigonobalanus verticillata Forman - Syzygium stapfianum (King) I.M. Turner - Syzygium subdecussatum (Wall. ex Duthie) I.M. Turner (Zone FZ2P2), Syzygium leptostemon (Korth.) Merr. & L.M. Perry - Wikstroemia polyantha Merr - Syzygium napiforme (Koord. & Valeton) Merr. & L.M. Perry (Zone FZ3P3P4) and Syzygium filiforme (Wall. ex Duthie) P. Chantaranothai & J. Parn.- Decaspermum parviflorum (Lam.) A.J. Scott - Litsea machilifolia Gamble (Zones FZ4P5). Correlation analysis showed that the number of trees in 0.1 ha, density/ha, DBH, mean DBH, number of species, number of family, number of genus, basal area (BA), mean BA, R, H and E and species with the biggest DBH decreased with increasing altitude. The r-values obtained for these 13 attributes were from – 0.13 to – 0.99. The distribution of trees were found to differ between DBH Class (DBHC) in all FZ. This study revealed that 73.1 to 88.17% of trees in all FZ fall into DBHC1 and DBHC2. On the other hand, 1.02 to 6.28% fall into DBHC5, DBHC6 and DBHC7. The distribution of species was different between Iv Class (IvC) all the four FZ. It was found that from 77.68 to 93.75% of the species fall into IvC1 and IvC2, and between 1.66 to 5.12% of the species fall into IvC4 and IvC5. Key words: Cluster analysis; Submontane forest; Western slope; Malaysia DOI: http://dx.doi.org/10.3329/bjb.v40i2.9767   Bangladesh J. Bot. 40(2): 121-132, 2011 (December)