Essential Oil Yield in Rosewood (Aniba Rosaeodora Ducke): Initial Application of Rapid Prediction by near Infrared Spectroscopy Based on Wood Spectra

2016 ◽  
Vol 24 (6) ◽  
pp. 507-515 ◽  
Author(s):  
Nadine Amusant ◽  
Jacques Beauchène ◽  
Alexis Digeon ◽  
Gilles Chaix
Keyword(s):  
Essential Oil ◽  
Near Infrared ◽  
Management Strategies ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Oil Yield ◽  
Yield Potential ◽  
Calibration Model ◽  
Wood Powder ◽  
Essential Oil Yield

Rosewood ( Aniba rosaeodora) essential oil is a valuable ingredient that has long been used in the perfume and cosmetic industries. The main rosewood timber quality parameters are its essential oil yield and quality. A hydrodistillation method has been developed for yield determination, but it is time consuming. Here we tested the applicability of near infrared (NIR) spectroscopy for determining essential oil yield directly from wood powder. Essential oil from 139 wood powders was extracted via hydrodistillation. The measurements were based on the ratio between the extracted essential oil mass and the oven-dried wood mass and were correlated with the wood powder NIR spectra. The calibration model statistical findings demonstrated that NIR could be a fast and feasible alternative method for selecting trees with a high essential oil yield potential. NIR-based predictions obtained in an independent validation set indicated a high correlation ( r2 = 0.92) with laboratory essential oil yield measurements. This NIR model could help wood managers in selecting trees with a high essential oil yield potential and in developing sustainable rosewood management strategies.

scholarly journals Near-Infrared Spectroscopy Combined with Multivariate Calibration to Predict the Yield of Sesame Oil Produced by Traditional Aqueous Extraction Process

2017 ◽  
Vol 2017 ◽  
pp. 1-5
Author(s):  
Yong-Dong Xu ◽  
Yan-Ping Zhou ◽  
Jing Chen
Keyword(s):  
Near Infrared ◽  
Multivariate Calibration ◽  
Nir Spectroscopy ◽  
Extraction Process ◽  
Sesame Oil ◽  
Aqueous Extraction ◽  
Oil Yield ◽  
Support Vector ◽  
Calibration Model ◽  
Aqueous Extraction Process

Sesame oil produced by the traditional aqueous extraction process (TAEP) has been recognized by its pleasant flavor and high nutrition value. This paper developed a rapid and nondestructive method to predict the sesame oil yield by TAEP using near-infrared (NIR) spectroscopy. A collection of 145 sesame seed samples was measured by NIR spectroscopy and the relationship between the TAEP oil yield and the spectra was modeled by least-squares support vector machine (LS-SVM). Smoothing, taking second derivatives (D2), and standard normal variate (SNV) transformation were performed to remove the unwanted variations in the raw spectra. The results indicated that D2-LS-SVM (4000–9000 cm−1) obtained the most accurate calibration model with root mean square error of prediction (RMSEP) of 1.15 (%, w/w). Moreover, the RMSEP was not significantly influenced by different initial values of LS-SVM parameters. The calibration model could be helpful to search for sesame seeds with higher TAEP oil yields.

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baselines for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non-destructive quantification of quality parameters in peanuts.

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Multiple Baseline ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baseline for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non destructive quantification of quality parameters in peanut.

Application of near Infrared Spectroscopy for the Quantification of Quality Parameters in Selected Vegetables and Essential Oil Plants

1998 ◽  
Vol 6 (A) ◽  
pp. A125-A130 ◽  
Author(s):  
H. Schulz ◽  
H.-H. Drews ◽  
R. Quilitzsch ◽  
H. Krüger
Keyword(s):  
Essential Oil ◽  
Oil Content ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Partial Least Square ◽  
Least Square ◽  
Total Carotenoids ◽  
Good Calibration

The use of near-infrared (NIR) spectroscopy for the prediction of the essential oil content and composition in various umbelliferae genotypes was investigated. Furthermore an NIR method was developed for the quantification of total carotenoids and sugars present in different carrot varieties. Applying partial least square algorithm very good calibration statistics ( SECV, R2) were obtained for the prediction of the essential oil content in fennel (0.47, 0.83), caraway (0.29, 0.93), dill (0.30, 0.96) and coriander (0.29, 0.93). Satisfactory calibration results were received for the NIR determination of total carotenoids (1.54, 0.80) and of saccharose(0.74, 0.76) in carrots. The performed study demonstrates that NIR can be used to rapidly and accurately predict secondary metabolites such as carotenoids, anethole, fenchone, estragole, limonene and carvone occurring in vegetables and in fruits of various essential oil plants.

scholarly journals Identification of VOCs in essential oils extracted using ultrasound- and microwave-assisted methods from sweet cherry flower

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Huimin Zhang ◽  
Hongguang Yan ◽  
Quan Li ◽  
Hui Lin ◽  
Xiaopeng Wen
Keyword(s):  
Essential Oil ◽  
Sweet Cherry ◽  
Dimethyl Sulfide ◽  
Solid Phase ◽  
Oil Yield ◽  
Gas Chromatography Mass Spectrometry ◽  
Process Conditions ◽  
Important Indicator ◽  
Microwave Assisted ◽  
Essential Oil Yield

AbstractThe floral fragrance of plants is an important indicator in their evaluation. The aroma of sweet cherry flowers is mainly derived from their essential oil. In this study, based on the results of a single-factor experiment, a Box–Behnken design was adopted for ultrasound- and microwave-assisted extraction of essential oil from sweet cherry flowers of the Brooks cultivar. With the objective of extracting the maximum essential oil yield (w/w), the optimal extraction process conditions were a liquid–solid ratio of 52 mL g−1, an extraction time of 27 min, and a microwave power of 435 W. The essential oil yield was 1.23%, which was close to the theoretical prediction. The volatile organic compounds (VOCs) of the sweet cherry flowers of four cultivars (Brooks, Black Pearl, Tieton and Summit) were identified via headspace solid phase microextraction (SPME) and gas chromatography–mass spectrometry (GC–MS). The results showed that a total of 155 VOCs were identified and classified in the essential oil from sweet cherry flowers of four cultivars, 65 of which were shared among the cultivars. The highest contents of VOCs were aldehydes, alcohols, ketones and esters. Ethanol, linalool, lilac alcohol, acetaldehyde, (E)-2-hexenal, benzaldehyde and dimethyl sulfide were the major volatiles, which were mainly responsible for the characteristic aroma of sweet cherry flowers. It was concluded that the VOCs of sweet cherry flowers were qualitatively similar; however, relative content differences were observed in the four cultivars. This study provides a theoretical basis for the metabolism and regulation of the VOCs of sweet cherry flowers.

scholarly journals Essential Oils of Four Virginia Mountain Mint (Pycnanthemum virginianum) Varieties Grown in North Alabama

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1397
Author(s):  
William N. Setzer ◽  
Lam Duong ◽  
Trang Pham ◽  
Ambika Poudel ◽  
Cuong Nguyen ◽  
...  
Keyword(s):  
Essential Oil ◽  
Essential Oils ◽  
University Research ◽  
Oil Yield ◽  
Research Station ◽  
Continuous Extraction ◽  
Chromatographic Techniques ◽  
Relative Differences ◽  
Essential Oil Yield ◽  
Very High

Virginia mountain mint (Pycnanthemum virginianum) is a peppermint-flavored aromatic herb of the Lamiaceae and is mainly used for culinary, medicinal, aromatic, and ornamental purposes. North Alabama’s climate is conducive to growing mint for essential oils used in culinary, confectionery, and medicinal purposes. There is, however, a need for varieties of P. virginianum that can be adapted and easily grown for production in North Alabama. Towards this end, four field-grown varieties with three harvesting times (M1H1, M1H2, M1H3; M2H1, M2H2, M2H3; M3H1, M3H2, M3H3, M4H1, M4H2, M4H3) were evaluated for relative differences in essential oil yield and composition. Thirty-day-old greenhouse-grown plants of the four varieties were transplanted on raised beds in the field at the Alabama A & M University Research Station in North Alabama. The plots were arranged in a randomized complete block with three replications. The study’s objective was to compare the four varieties for essential oil yield and their composition at three harvest times, 135, 155, and 170 days after planting (DAP). Essential oils were obtained by hydrodistillation with continuous extraction with dichloromethane using a Likens–Nickerson apparatus and analyzed by gas chromatographic techniques. At the first harvest, the essential oil yield of the four varieties showed that M1H1 had a yield of 1.15%, higher than M2H1, M3H1, and M4H1 with 0.91, 0.76, and 1.03%, respectively. The isomenthone concentrations increased dramatically through the season in M1 (M1H1, M1H2, M1H3) by 19.93, 54.7, and 69.31%, and M3 (M3H1, M3H2, M3H3) by 1.81, 48.02, and 65.83%, respectively. However, it increased only slightly in M2 and M4. The thymol concentration decreased slightly but not significantly in all four varieties; the thymol in M2 and M4 was very high compared with M1 and M3. The study showed that mountain mint offers potential for production in North Alabama. Two varieties, M1 and M3, merit further studies to determine yield stability, essential oil yield, composition, and cultivation development practices.

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