Classification of Agarwood region using ANN

Najib, Muhammad Sharfi; Ali, Nor Azah Mohd; Arip, Mohamad Nasir Mat; Jalil, Abd. Majid; Taib, Mohd Nasir

doi:10.1109/icsgrc.2010.5562529

Cited by 15 publications

(4 citation statements)

References 11 publications

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“…This approach requires the implementation of statistical analysis such as the hierarchical cluster analysis (HCA) and principal component analysis (PCA) and must be tested on many different samples before it can be used. Once established, the artifi cial neural network can predict the identity of unknown agarwood samples including the region of origin (Hidayat et al 2010 ;Najib et al 2012 ;Ismail et al 2013 ). Another technique that applies sophisticated instrument is the X-ray micro-computed tomography (micro-ct).…”

Section: Quality Of the Essential Oilmentioning

confidence: 99%

Keeping Up Appearances: Agarwood Grades and Quality

Mohamed¹,

Lee²

2016

Tropical Forestry

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Agarwood has many grades and goes by countless different names in both the sourcing and consuming countries. The different grades and classes of agarwood result from long-standing grading practices adopted by the people of each country. No standard method is available partly due to the intricacy during the hierarchical process of selling and buying. The foremost reason is the appearance of the traded agarwood itself, which can come in many forms from raw, such as chips, blocks, and fl akes, to fi nished products such as oil, incenses, perfumes, accessories, and carvings. Agarwood in raw forms is of mixed quality; thus, the price and grade depend on this blended appearance. As the product is passed down from collectors to various levels of traders and fi nally to the buyers, the grade can be readjusted and the price infl ated or understated depending on the interest. Therefore, buyers, traders, and collectors heavily rely upon time-honored trust when concluding a business deal. Authorities have not found the formula to standardize the grading system of agarwood trade, and this leads to the lack of coordination and regulation at international level. Nevertheless, several sourcing and consuming countries have made the effort to grade their agarwood according to their own local market, which can be used as a benchmark in formulating a more contemporary method that could be acceptable to all countries.

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Section: Quality Of the Essential Oilmentioning

confidence: 99%

Keeping Up Appearances: Agarwood Grades and Quality

Mohamed¹,

Lee²

2016

Tropical Forestry

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“…Hierarchical cluster analysis and principal component analysis were used for the segregation of agarwood oil belonging to different regions, and an artificial neural network was used for predicting the category of the unknown agarwood oil sample. 3,12,13 This study also did not explicitly provide the exact point of difference/compound of difference in the different classes of agarwood taken into consideration. To the best of our knowledge, no studies reporting the presence of a particular type and amount of adulterant in agarwood oil samples were found.…”

Section: Introductionmentioning

confidence: 99%

“…In another similar work, E‐nose was used for differentiation of agarwood oil obtained from different origins and thus having varied chemical composition. Hierarchical cluster analysis and principal component analysis were used for the segregation of agarwood oil belonging to different regions, and an artificial neural network was used for predicting the category of the unknown agarwood oil sample 3,12,13 . This study also did not explicitly provide the exact point of difference/compound of difference in the different classes of agarwood taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

Quality control analysis of high‐value agarwood oil by thermogravimetric analysis (TGA)

Kumar

Tripathi

Rout

et al. 2022

Flavour & Fragrance J

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Adulteration is a crucial issue being faced by essential oil and allied industries, especially for high‐value essential oil such as agarwood oil. The recommended analysis in trading essential oils involves visual inspection, olfactory analysis, physico‐chemical characterization and gas chromatography coupled with mass spectroscopy (GC–MS). However, some subtle high‐boiler adulterants like vegetable oils and synthetic polymers go unnoticed via these analyses leading to the penetration of adulterated essential oil in the market. In the current study, the thermogravimetric analysis (TGA) and differential thermogravimetric analysis (DTGA) were utilized and suggested as a rapid, convenient and precise technique for the detection of high‐boiler adulterants in essential oils using the most expensive agarwood oil as a case study. The TGA pattern of pure samples reveals single‐stage volatilization (agarwood oil: 110–260°C, castor oil: 340–500°C, coconut oil: 330–450°C and polyethylene glycol‐400: 260–390°C), whereas the adulterated sample exhibits two‐stage volatilization in both lower‐ and higher‐temperature zone owing to the presence of agarwood oil and high‐boiler adulterant. The DTGA of pure agarwood oil shows only one point of major weight loss, whereas that of the adulterated sample shows two points of major weight loss corresponding to both oil and adulterant. Different percentages of adulterants (5%, 10%, 30% and 50%) have been quantified using TGA and DTGA with the highest accuracy. Further, the method optimization study was conducted to determine the minimum time required for adulterated sample analysis with precise accuracy. TGA can be proposed as a handy and efficient tool for the quality control analysis of essential oils.

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“…In the Malaysian gaharu market, the ABC Agarwood Grading System [ 11 , 16 ], which is highly based on physical characteristics, still remains as the most common method of grading gaharu. The system is widely used by traders, despite various efforts to develop a more viable and scientific method of grading [ 17 , 18 , 19 , 20 ]. However, relying on physical properties as a means of grading has many drawbacks since it is highly dependent on individual human perceptions, possibly resulting in bias and poor reproducibility.…”

Section: Introductionmentioning

confidence: 99%

Discriminative Analysis of Different Grades of Gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-Based Metabolomics Using PLS-DA and Random Forests Classification Models

et al. 2017

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Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using 1H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA) and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a ‘high grade’ group (samples A, B and D), characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an ‘intermediate grade’ group (samples C, F and G), dominated by fatty acid and vanillic acid; and a ‘low grade’ group (sample E and H), which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that 1H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents.

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Classification of Agarwood region using ANN

Cited by 15 publications

References 11 publications

Keeping Up Appearances: Agarwood Grades and Quality

Keeping Up Appearances: Agarwood Grades and Quality

Quality control analysis of high‐value agarwood oil by thermogravimetric analysis (TGA)

Discriminative Analysis of Different Grades of Gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-Based Metabolomics Using PLS-DA and Random Forests Classification Models

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