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In this paper, a FSR two-profile environment ground clutter-measured signal with very high frequency (VHF) and ultra high frequency (UFH) at a border of dense forest and free space area are presented. Statistical distribution method is used to model the clutter signal, namely Weibull, Gamma, Log-Logistic and Log-Normal distribution. Two goodness-of-fit (GOF) tests are used to calculate the error between the amplitude of the clutter data and the statistical model, which are the root mean square error (RMSE) and chi-square (CS). At the end of this analysis, Weibull model was found to be the best fit for 64 MHz clutter signal while Gamma model is best fitted at 151 MHz carrier frequency. Another model known as Log-Logistic model fits well to a clutter signal measured with 434 MHz carrier frequency.

This article presents the use of Z-score in assessing the significant chemical compounds extracted by head space solid phase microextraction (HS-SPME) and gas chromatography – mass spectrometry (GC-MS) analysis of an agarwood oil obtained from Melaka, Malaysia. Two types of SPME fiber; polydimethylsiloxane (PDMS) and divinylbenzene-carboxen-polydimethylsiloxane (DVB-CAR-PDMS) were used. During the extraction analysis, the results showed that at least 27 and 29 compounds were identified using PDMS and DVB-CAR-PDMS fiber, respectively. DVB-CAR-PDMS fiber was found to be more efficient in terms of selectivity of compounds extraction. The application of Z-score showed that eight and eleven marker compounds were determined in PDMS and DVB-CAR-PDMS fibers, respectively. 4-Phenyl-2-butanone, a-guaiene, β-agarofuran, a-bulnesene, a-agarofuran and 10-epi-g-eudesmol were some of the compounds selected and were often reported significantly in agarwood oils as key odor compounds. The information gathered will be used for compound selection towards grading of agarwood oils by sensor technology.

This paper presents an overview of analysis agarwood oil and its quality grading. The review suggested agarwood oil can be graded according to their chemical properties and so that there is a common standard recognized worldwide on grading the agarwood oil. Analysis based on chemical profiles is required to ensure that agarwood oil can be classified based on their respective classes or grades where the accurate results can be measured. Conventionally, the grading of agarwood oil is performed by trained human graders (sensory panels) depends on its physical appearance such as color, odor, high fixative and consumer perception. However, this method is limited due to human nose cannot accept many samples in one time and easily get fatigues especially when dealing with continuous production. The human sensory panel also limited in terms of subjectivity, poor reproducibility, time consumption and large labour expense. These are constraining factors in increasing agarwood oil trade and market penetration.