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The agarwood oil quality has been divided into four grades, including low, medium-low, medium-high, and high, and has been thoroughly examined in this manuscript. Recently, there has been a high demand for agarwood oil but the current grading method is based on conventional techniques that rely on visual inspection of various characteristics such as intensity, smell, texture, and weight. However, this method is not standardized, making it difficult to grade agarwood oil accurately. Therefore, the use of artificial neural networks (ANN) in artificial intelligence (AI) was employed to develop a system for identifying agarwood oil quality using the Levenberg-Marquardt (LM) algorithm. Data from 660 samples of chemical compounds extracted from agarwood oil were used to train the ANN. To enhance the accuracy of agarwood oil quality identification with LM performance, the data was split into 70% for validation, 15% for training, and 15% for testing. The results showed that the ANN with the eleven inputs (10-epi- $\gamma $ -eudesmol, $\alpha $ -agarofuran, $\gamma $ -eudesmol, $\beta $ -agarofuran, ar-curcumene, valerianol, $\beta $ -dihydro agarofuran, $\alpha $ -guaiene, allo aromadendrene epoxide and $\Upsilon $ -cadinene) trained by ten hidden neurons of LM algorithm provided the best performance with 100% for accuracy, specificity, sensitivity and precision as well as minimum convergence epoch. The experimental implementation of the model was done using the MATLAB version R2015a platform. This study will help to standardize agarwood oil quality determination using intelligent modeling techniques and serve as a guide for future research in the essential oil industry.

Aquilaria oil, specifically agarwood oil, is esteemed for its unique fragrance and potential therapeutic qualities, primarily attributed to the presence of significant chemical compounds. These compounds play a vital role in shaping the quality and attributes of Aquilaria oil. The distinct aroma, characterized by intricate, woody, and multifaceted notes, originates directly from specific sesquiterpenes, with notable contributors like agarospirol defining this aromatic profile. The richness and complexity of the oil's scent are closely linked to the concentration and variety of noteworthy compounds within it. Oils containing a diverse range of sesquiterpenes are often considered superior, providing a more refined olfactory experience. This dataset presents a statistical analysis of the chemical compounds present in agarwood oil obtained through the hydrodistillation method from three distinct Aquilaria (A.) species: A. crassna, A. malaccensis, and A. subintegra. The analysis of these chemical compounds utilized Gas Chromatography-Mass Spectrometer (GC-MS) coupled with Gas Chromatography – Flame Ionization Detector (GC-FID). This study's data is crucial for highlighting compounds that contribute to the significance of agarwood oil as a valuable and versatile natural resource. This significance is emphasized by the oil's diverse applications and distinctive chemical composition.

Agarwood (Aquilaria malaccensis) is very well known as the most expensive wood in the world due to its wide applications in perfumery, cosmetic traditional medicine, and religious ceremonies. The study aimed to give an in-depth characterisation focusing on marker compounds in A. malaccensis from different places in Malaysia. The establishment of an oxygenated sesquiterpenes chemical profile of the fungus-infected agarwood oil was achieved by gas chromatography mass spectrometry (GC–MS) coupled with quadrupole time (QTOF) technique. Aroma compounds were identified as sesquiterpenes and oxygenated sesquiterpenes where agarospirol was found in samples of all locations (3.12%, 3.54%, 3.36% and 2.26% from Melaka, Pahang, Kelantan A and Kelantan B respectively) and also N-hexadecanoic acid as one of the major compounds. Both compounds were further isolated by Prep-GC and confirmed by NMR. This study provides a reference for agarwood oil analysis from different origins in Malaysia.

The inflammatory response is a central aspect of the human immune system that acts as a defense mechanism to protect the body against infections and injuries. A dysregulated inflammatory response is a major health concern, as it can disrupt homeostasis and lead to a plethora of chronic inflammatory conditions. These chronic inflammatory diseases are one of the major causes of morbidity and mortality worldwide and the need for them to be managed in the long term has become a crucial task to alleviate symptoms and improve patients' overall quality of life. Although various synthetic anti-inflammatory agents have been developed to date, these medications are associated with several adverse effects that have led to poor therapeutic outcomes. The hunt for novel alternatives to modulate underlying chronic inflammatory processes has unveiled nature to be a plentiful source. One such example is agarwood, which is a valuable resinous wood from the trees of Aquilaria spp. Agarwood has been widely utilized for medicinal purposes since ancient times due to its ability to relieve pain, asthmatic symptoms, and arrest vomiting. In terms of inflammation, the major constituent of agarwood, agarwood oil, has been shown to possess multiple bioactive compounds that can regulate molecular mechanisms of chronic inflammation, thereby producing a multitude of pharmacological functions for treating various inflammatory disorders. As such, agarwood oil presents great potential to be developed as a novel anti-inflammatory therapeutic to overcome the drawbacks of existing therapies and improve treatment outcomes. In this review, we have summarized the current literature on agarwood and its bioactive components and have highlighted the potential roles of agarwood oil in treating various chronic inflammatory diseases. [ABSTRACT FROM AUTHOR]

Agarwood is the commodity that has the highest economic value in the world, especially its oil. However, agarwood essential oils have a volatile compound component of almost 90%. To overcome this volatility, the agarwood oil can be changed into a solid dosage by encapsulation using maltodextrin and gum arabic through the freeze-drying method. Encapsulation is one solution that increases the efficiency of the packaging process and of the distribution of agarwood oil. Four different formulations of agarwood oil encapsulation were obtained that differed in the ratio of the active ingredient, agarwood oil, to the encapsulating materials, maltodextrin and gum arabic (MD-GA): F1 (2:10), F2 (5:10), F3 (10:10) and F4 (12:10). The highest loading capacity was 68.6%, obtained in the F2 sample. The surface oil content value of the four formulations ranged from 3% to 21%. The value of the encapsulation efficiency in the four formulations was between 82% and 96%. In the morphological test, all four formulations had pores on part of their surface. Overall, all samples showed good results for loading capacity, surface oil content percentage and encapsulation efficiency.

The inflammatory response is a central aspect of the human immune system that acts as a defense mechanism to protect the body against infections and injuries. A dysregulated inflammatory response is a major health concern, as it can disrupt homeostasis and lead to a plethora of chronic inflammatory conditions. These chronic inflammatory diseases are one of the major causes of morbidity and mortality worldwide and the need for them to be managed in the long term has become a crucial task to alleviate symptoms and improve patients’ overall quality of life. Although various synthetic anti-inflammatory agents have been developed to date, these medications are associated with several adverse effects that have led to poor therapeutic outcomes. The hunt for novel alternatives to modulate underlying chronic inflammatory processes has unveiled nature to be a plentiful source. One such example is agarwood, which is a valuable resinous wood from the trees of Aquilaria spp. Agarwood has been widely utilized for medicinal purposes since ancient times due to its ability to relieve pain, asthmatic symptoms, and arrest vomiting. In terms of inflammation, the major constituent of agarwood, agarwood oil, has been shown to possess multiple bioactive compounds that can regulate molecular mechanisms of chronic inflammation, thereby producing a multitude of pharmacological functions for treating various inflammatory disorders. As such, agarwood oil presents great potential to be developed as a novel anti-inflammatory therapeutic to overcome the drawbacks of existing therapies and improve treatment outcomes. In this review, we have summarized the current literature on agarwood and its bioactive components and have highlighted the potential roles of agarwood oil in treating various chronic inflammatory diseases.

Aquilaria oil, specifically agarwood oil, is esteemed for its unique fragrance and potential therapeutic qualities, primarily attributed to the presence of significant chemical compounds. These compounds play a vital role in shaping the quality and attributes of Aquilaria oil. The distinct aroma, characterized by intricate, woody, and multifaceted notes, originates directly from specific sesquiterpenes, with notable contributors like agarospirol defining this aromatic profile. The richness and complexity of the oil's scent are closely linked to the concentration and variety of noteworthy compounds within it. Oils containing a diverse range of sesquiterpenes are often considered superior, providing a more refined olfactory experience. This dataset presents a statistical analysis of the chemical compounds present in agarwood oil obtained through the hydrodistillation method from three distinct Aquilaria (A.) species: A. crassna, A. malaccensis, and A. subintegra. The analysis of these chemical compounds utilized Gas Chromatography-Mass Spectrometer (GC-MS) coupled with Gas Chromatography - Flame Ionization Detector (GC-FID). This study's data is crucial for highlighting compounds that contribute to the significance of agarwood oil as a valuable and versatile natural resource. This significance is emphasized by the oil's diverse applications and distinctive chemical composition., (© 2024 The Author(s).)

Agarwood (Aquilaria malaccensis) is very well known as the most expensive wood in the world due to its wide applications in perfumery, cosmetic traditional medicine, and religious ceremonies. The study aimed to give an in-depth characterisation focusing on marker compounds in A. malaccensis from different places in Malaysia. The establishment of an oxygenated sesquiterpenes chemical profile of the fungus-infected agarwood oil was achieved by gas chromatography mass spectrometry (GC–MS) coupled with quadrupole time (QTOF) technique. Aroma compounds were identified as sesquiterpenes and oxygenated sesquiterpenes where agarospirol was found in samples of all locations (3.12%, 3.54%, 3.36% and 2.26% from Melaka, Pahang, Kelantan A and Kelantan B respectively) and also N-hexadecanoic acid as one of the major compounds. Both compounds were further isolated by Prep-GC and confirmed by NMR. This study provides a reference for agarwood oil analysis from different origins in Malaysia. [ABSTRACT FROM AUTHOR]

Incubation with microbial culture supernatants improved essential oil yield from Aquilaria subintegra woodchips. The harvested woodchips were incubated with de man, rogosa and sharpe (MRS) agar, yeast mold (YM) agar medium and six different microbial culture supernatants obtained from Lactobacillus bulgaricus, L. acidophilus, Streptococcus thermophilus, Lactococcus lactis, Saccharomyces carlsbergensis and S. cerevisiae prior to hydrodistillation. Incubation with lactic acid bacteria supernatants provided higher yield of agarwood oil (0.45% w/w) than that obtained from yeast (0.25% w/w), agar media (0.23% w/w) and water (0.22% w/w). The composition of agarwood oil from all media and microbial supernatant incubations was investigated by using gas chromatography-mass spectrometry. Overall, three major volatile profiles were obtained, which corresponded to water soaking (control), as well as, both YM and MRS media, lactic acid bacteria, and yeast supernatant incubations. Sesquiterpenes and their oxygenated derivatives were key components of agarwood oil. Fifty-two volatile components were tentatively identified in all samples. Beta-agarofuran, α-eudesmol, karanone, α-agarofuran and agarospirol were major components present in most of the incubated samples, while S. cerevisiae-incubated A. subintegra provided higher amount of phenyl acetaldehyde. Microbial culture supernatant incubation numerically provided the highest yield of agarwood oil compared to water soaking traditional method, possibly resulting from activity of extracellular enzymes produced by the microbes. Incubation of agarwood with lactic acid bacteria supernatant significantly enhanced oil yields without changing volatile profile/composition of agarwood essential oil, thus this is a promising method for future use. [ABSTRACT FROM AUTHOR]

Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.

Established in the year 1979 by the Assam Science Society and subsequently supported by the Assam government, IASST was adopted as an autonomous R&D institute by the Department of Science and Technology in March 2009. Research achievement during the year 2014 has been highlighted under its various programmes. [ABSTRACT FROM AUTHOR]

Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples. [ABSTRACT FROM AUTHOR]