scholarly journals Biodiesel Synthesis Monitoring using Near Infrared Spectroscopy

2018 ◽  
Vol 12 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Estela Kamile Gelinski ◽  
Fabiane Hamerski ◽  
Marcos Lúcio Corazza ◽  
Alexandre Ferreira Santos
Keyword(s):  
Fossil Fuels ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Transesterification Reaction ◽  
Biodiesel Production ◽  
Molar Ratios ◽  
External Data ◽  
Biodiesel Synthesis ◽  
Biodiesel Production Monitoring

Objective: Biodiesel is a renewable fuel considered as the main substitute for fossil fuels. Its industrial production is mainly made by the transesterification reaction. In most processes, information on the production of biodiesel is essentially done by off-line measurements. Methods: However, for the purpose of control, where online monitoring of biodiesel conversion is required, this is not a satisfactory approach. An alternative technique to the online quantification of conversion is the near infrared (NIR) spectroscopy, which is fast and accurate. In this work, models for biodiesel reactions monitoring using NIR spectroscopy were developed based on the ester content during alkali-catalyzed transesterification reaction between soybean oil and ethanol. Gas chromatography with flame ionization detection was employed as the reference method for quantification. FT-NIR spectra were acquired with a transflectance probe. The models were developed using Partial Least Squares (PLS) regression with synthetic samples at room temperature simulating reaction composition for different ethanol to oil molar ratios and conversions. Model predictions were then validated online for reactions performed with ethanol to oil molar ratios of 6 and 9 at 55ºC. Standard errors of prediction of external data were equal to 3.12%, hence close to the experimental error of the reference technique (2.78%), showing that even without using data from a monitored reaction to perform calibration, proper on-line predictions were provided during transesterification runs. Results: Additionally, it is shown that PLS models and NIR spectra of few samples can be combined to accurately predict the glycerol contents of the medium, making the NIR spectroscopy a powerful tool for biodiesel production monitoring.

scholarly journals Bio-Derived Catalysts: A Current Trend of Catalysts Used in Biodiesel Production

Catalysts ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 812
Author(s):  
Hoang Chinh Nguyen ◽  
My-Linh Nguyen ◽  
Chia-Hung Su ◽  
Hwai Chyuan Ong ◽  
Horng-Yi Juan ◽  
...  
Keyword(s):  
Catalytic Activity ◽  
Fossil Fuels ◽  
Current Trend ◽  
Biodiesel Production ◽  
High Catalytic Activity ◽  
Promising Alternative ◽  
Advantages And Disadvantages ◽  
Biodiesel Synthesis ◽  
Alkali Catalysts ◽  
A Current

Biodiesel is a promising alternative to fossil fuels and mainly produced from oils/fat through the (trans)esterification process. To enhance the reaction efficiency and simplify the production process, various catalysts have been introduced for biodiesel synthesis. Recently, the use of bio-derived catalysts has attracted more interest due to their high catalytic activity and ecofriendly properties. These catalysts include alkali catalysts, acid catalysts, and enzymes (biocatalysts), which are (bio)synthesized from various natural sources. This review summarizes the latest findings on these bio-derived catalysts, as well as their source and catalytic activity. The advantages and disadvantages of these catalysts are also discussed. These bio-based catalysts show a promising future and can be further used as a renewable catalyst for sustainable biodiesel production.

scholarly journals A Comprehensive Review on Oil Extraction and Biodiesel Production Technologies

2021 ◽  
Vol 13 (2) ◽  
pp. 788
Author(s):  
Zulqarnain ◽  
Muhammad Ayoub ◽  
Mohd Hizami Mohd Yusoff ◽  
Muhammad Hamza Nazir ◽  
Imtisal Zahid ◽  
...  
Keyword(s):  
Energy Demand ◽  
Alternative Fuels ◽  
Fossil Fuels ◽  
Significant Proportion ◽  
Waste Cooking Oil ◽  
Oil Extraction ◽  
Biodiesel Production ◽  
Waste Oils ◽  
Biodiesel Synthesis ◽  
Production Technologies

Dependence on fossil fuels for meeting the growing energy demand is damaging the world’s environment. There is a dire need to look for alternative fuels that are less potent to greenhouse gas emissions. Biofuels offer several advantages with less harmful effects on the environment. Biodiesel is synthesized from the organic wastes produced extensively like edible, non-edible, microbial, and waste oils. This study reviews the feasibility of the state-of-the-art feedstocks for sustainable biodiesel synthesis such as availability, and capacity to cover a significant proportion of fossil fuels. Biodiesel synthesized from oil crops, vegetable oils, and animal fats are the potential renewable carbon-neutral substitute to petroleum fuels. This study concludes that waste oils with higher oil content including waste cooking oil, waste palm oil, and algal oil are the most favorable feedstocks. The comparison of biodiesel production and parametric analysis is done critically, which is necessary to come up with the most appropriate feedstock for biodiesel synthesis. Since the critical comparison of feedstocks along with oil extraction and biodiesel production technologies has never been done before, this will help to direct future researchers to use more sustainable feedstocks for biodiesel synthesis. This study concluded that the use of third-generation feedstocks (wastes) is the most appropriate way for sustainable biodiesel production. The use of innovative costless oil extraction technologies including supercritical and microwave-assisted transesterification method is recommended for oil extraction.

Prediction of Fatty Acid Content in Beef Neck Lean by near Infrared Reflectance Analysis

1998 ◽  
Vol 6 (1) ◽  
pp. 229-234 ◽  
Author(s):  
William R. Windham ◽  
W.H. Morrison
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Longissimus Dorsi ◽  
Near Infrared Reflectance ◽  
Total Fatty Acids

Near infrared (NIR) spectroscopy in the prediction of individual and total fatty acids of bovine M. Longissimus dorsi neck muscles has been studied. Beef neck lean was collected from meat processing establishments using advanced meat recovery systems and hand-deboning. Samples ( n = 302) were analysed to determine fatty acid (FA) composition and scanned from 400 to 2498 nm. Total saturated and unsaturated FA values ranged from 43.2 to 62.0% and 38.3 to 56.2%, respectively. Results of partial least squares (PLS) modeling shown reasonably accurate models were attained for total saturate content [standard error of performance ( SEP = 1.10%); coefficient of determination on the validation set ( r2 = 0.77)], palmitic ( SEP = 0.94%; r2 = 0.69), unsaturate ( SEP = 1.13%; r2 = 0.77), and oleic ( SEP = 0.97; r2 = 0.78). Prediction of other individual saturated and unsaturated FAs was less accurate with an r2 range of 0.10 to 0.53. However, the sum of individual predicted saturated and unsaturated FA was acceptable compared with the reference method ( SEP = 1.10 and 1.12%, respectively). This study shows that NIR can be used to predict accurately total fatty acids in M. Longissimus dorsi muscle.

scholarly journals Extraction Solvents Composition Effect In Biodiesel Production From Microalgae Consortium Botryococcus Braunii And Dunaliella Sp.

Khazanah ◽  
2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Tiara Nur Azizah ◽  
◽  
Alya Putri Ramadhanty ◽  
Nadya Feranika ◽  
◽  
...  
Keyword(s):  
Fossil Fuels ◽  
Production Capacity ◽  
Water Concentration ◽  
Soxhlet Extraction ◽  
Botryococcus Braunii ◽  
Solvent Mixture ◽  
Biodiesel Production ◽  
Solvent Ratio ◽  
Extraction Solvent ◽  
Biodiesel Synthesis

Indonesia has entered an energy emergency phase, proven that Indonesia is no longer a surplus oil producer due to the productivity of the wells decrease over the years and the pattern of people's consumption of fossil fuels has been exceeding the production capacity. Therefore, we need the right solution to overcome this problem, which is developing biodiesel as renewable energy based on microalgae oil. The microalgae used in this research is the consortium of microalgae Botryococcus braunii and Dunaliella sp. Microalgae were cultivated and harvested through the dewatering process with 1 g naoh/1 L water concentration. Water contents of cultivated Botryococcus braunii are 60.2505% while Dunaliella sp. Is 64.5002%. The oil from microalgae is obtained by extracted dry microalgae through the soxhlet extraction (leaching) method with mixed solvent n-hexane and ethanol as the co-solvent using a variety of solvent ratio 2:1 and 3:1. Pure microalgae consortium oil separated from the solvent using the distillation process then analyzed with GC-FID. The analysis result is trans-linoleic acid is the most dominant fatty acid contained in this oil. Transesterification process with cao (1.5% of oil weight) as a catalyst. The results obtained from this study are the oil yield 72% extracted with a solvent mixture of n-hexane and ethanol 2:1 and 60.4% for 3:1. The biodiesel synthesis resulted in the amount of yield obtained from the solvent ratio 2:1 extraction is 94.3%, while with solvent ratio 3:1 is 79.2%. The quality of both biodiesels has met the requirements of SNI 7182:2015 and ASTM D7467, except the density of biodiesel with extraction solvent composition 3:1 which is below the standard. Therefore, the best biodiesel quality is obtained from microalgae consortium’s oil with the composition of extraction solvent 2:1.

Application of near Infrared Spectroscopy On-Combine in Corn Grain Breeding

2005 ◽  
Vol 13 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Roland Welle ◽  
Willi Greten ◽  
Thomas Müller ◽  
Gary Weber ◽  
Hartwig Wehrmann
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Successful Implementation ◽  
Grain Moisture ◽  
Yield Determination ◽  
Corn Grain

Improving maize ( Zea mays L.) grain yield and agronomic properties are major goals for corn breeders in northern Europe. In order to facilitate field grain yield determination we measured corn grain moisture content with near infrared (NIR) spectroscopy directly on a harvesting machine. NIR spectroscopy, in combination with harvesting, significantly improved quality and speed of yield determination within the very narrow harvest time window. Moisture calibrations were developed with 2117 samples from the 2001 to 2003 crop seasons using six diode array spectrometers mounted on combines. These models were derived from databases containing spectra from all instruments. Spectrometer-specific calibrations cannot be used to predict samples measured on other instruments of the same type. Standard error of cross-validation ( SECV) and coefficient of determination ( R2) were 0.56 and 0.99%, respectively. Moisture standard errors of prediction ( SEPs) for the six instruments, using varying independent sample sets from the 2004 harvest, ranged between 0.59% and 0.99% with R2 values between 0.92 to 0.98. The six instruments produced the same dry matter predictions on a common sample set as indicated by high R2 and low biases among them, hence there was no need to apply specific standardisation algorithms. Moisture NIR spectroscopy determinations were significantly more precise than those obtained using the reference method. Analysis of variance revealed low least significant differences and high heritabilities. High precision and heritability demonstrate successful implementation of on-combine NIR spectroscopy for routine dry matter (yield) measurements.

scholarly journals A New Plant Indicator (Artemisia lavandulaefolia DC.) of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Lu Xu ◽  
Qiong Shi ◽  
Bang-Cheng Tang ◽  
Shunping Xie
Keyword(s):  
Support Vector Machine ◽  
Fourier Transform ◽  
Least Squares ◽  
Near Infrared ◽  
Mercury Level ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Classification Model ◽  
Support Vector ◽  
Reference Analysis

A rapid indicator of mercury in soil using a plant (Artemisia lavandulaefolia DC., ALDC) commonly distributed in mercury mining area was established by fusion of Fourier-transform near-infrared (FT-NIR) spectroscopy coupled with least squares support vector machine (LS-SVM). The representative samples of ALDC (stem and leaf) were gathered from the surrounding and distant areas of the mercury mines. As a reference method, the total mercury contents in soil and ALDC samples were determined by a direct mercury analyzer incorporating high-temperature decomposition, catalytic adsorption for impurity removal, amalgamation capture, and atomic absorption spectrometry (AAS). Based on the FT-NIR data of ALDC samples, LS-SVM models were established to distinguish mercury-contaminated and ordinary soil. The results of reference analysis showed that the mercury level of the areas surrounding mercury mines (0–3 kilometers, 7.52–88.59 mg/kg) was significantly higher than that of the areas distant from mercury mines (>5 kilometers, 0–0.75 mg/kg). The LS-SVM classification model of ALDC samples was established based on the original spectra, smoothed spectra, second-derivative (D2) spectra, and standard normal transformation (SNV) spectra, respectively. The prediction accuracy of D2-LS-SVM was the highest (0.950). FT-NIR combined with LS-SVM modeling can quickly and accurately identify the contaminated ALDC. Compared with traditional methods which rely on naked eye observation of plants, this method is objective and more sensitive and applicable.

scholarly journals Microalgae Cultivation in Photobioreactors Aiming at Biodiesel Production

2020 ◽  
Author(s):  
Mateus S. Amaral ◽  
Carla C.A. Loures ◽  
Fabiano L. Naves ◽  
Gisella L. Samanamud ◽  
Messias B. Silva ◽  
...  
Keyword(s):  
Fossil Fuels ◽  
Biomass Productivity ◽  
Raw Material ◽  
Biodiesel Production ◽  
Alternative Source ◽  
Biodiesel Synthesis ◽  
Microalgae Biomass ◽  
Increase Productivity ◽  
Bad Weather ◽  
Micro Organisms

The search for a renewable source as an alternative to fossil fuels has driven the research on new sources of biomass for biofuels. An alternative source of biomass that has come to prominence is microalgae, photosynthetic micro-organisms capable of capturing atmospheric CO2 and accumulating high levels of lipids in their biomass, making them attractive as a raw material for biodiesel synthesis. Thus, various studies have been conducted in developing different types of photobioreactors for the cultivation of microalgae. Photobioreactors can be divided into two groups: open and closed. Open photobioreactors are more susceptible to contamination and bad weather, reducing biomass productivity. Closed photobioreactors allow greater control against contamination and bad weather and lead to higher rates of biomass production; they are widely used in research to improve new species and processes. Therefore, many configurations of closed photobioreactors have been developed over the years to increase productivity of microalgae biomass.

scholarly journals Determination of Moisture, Starch, Protein, and Fat in Common Beans (Phaseolus vulgaris L.) by Near Infrared Spectroscopy

2006 ◽  
Vol 89 (4) ◽  
pp. 1039-1041 ◽  
Author(s):  
MarÍa Hermida ◽  
Natalia Rodriguez ◽  
Jose L Rodriguez-Otero
Keyword(s):  
Phaseolus Vulgaris ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Sample Pretreatment ◽  
Common Beans ◽  
Least Squares Regression ◽  
Phaseolus Vulgaris L ◽  
Previous Sample ◽  
Validation Set

Abstract The presence of moisture, starch, protein, and fat was determined in common beans (Phaseolus vulgaris L.) by near infrared (NIR) spectroscopy without any previous sample pretreatment except grinding. A set of 96 samples was used to calibrate the instrument by modified partial least-squares regression. The following statistical results were achieved: standard error of calibration (SEC) = 0.31 and square correlation coefficient (R2) = 0.96 for moisture; SEC = 0.76 and R2 = 0.92 for starch; SEC = 0.39 and R2 = 0.98 for protein; and SEC = 0.14 and R2 = 0.80 for fat. To validate the calibration, a set of 25 bean samples was used. Standard errors of prediction were 0.39, 0.90, 0.56, and 0.13 for moisture, starch, protein, and fat, respectively, and R2 for the regression of measurements by the reference method versus NIR analysis were 0.94, 0.88, 0.94, and 0.74 for moisture, starch, protein, and fat, respectively. To compare the results obtained for all 4 components of the validation set by NIR spectroscopy with those obtained by the reference methods, linear regression and paired t tests were applied, and the methods did not give significantly different results, P = 0.05.

scholarly journals Nondestructive Discrimination of Lead (Pb) in Preserved Eggs (Pidan) by Near-Infrared Spectroscopy and Chemometrics

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Lu Xu ◽  
Si-Min Yan ◽  
Chen-Bo Cai ◽  
Xiao-Ping Yu
Keyword(s):  
Least Squares ◽  
Inductively Coupled Plasma ◽  
Near Infrared ◽  
Safety Concern ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Nonlinear Least Squares ◽  
Classification Performance ◽  
Nondestructive Method ◽  
Support Vector

A major safety concern with pidan (preserved eggs) has been the usage of lead (II) oxide (PbO) during its processing. This paper develops a rapid and nondestructive method for discrimination of lead (Pb) in preserved eggs with different processing methods by near-infrared (NIR) spectroscopy and chemometrics. Ten batches of 331 unleaded eggs and six batches of 147 eggs processed with usage of PbO were collected and analyzed by NIR spectroscopy. Inductively coupled plasma mass spectrometry (ICP-MS) analysis was used as a reference method for Pb identification. The Pb contents of leaded eggs ranged from 1.2 to 12.8 ppm. Linear partial least squares discriminant analysis (PLSDA) and nonlinear least squares support vector machine (LS-SVM) were used to classify samples based on NIR spectra. Different preprocessing methods were studied to improve the classification performance. With second-order derivative spectra, PLSDA and LS-SVM obtained accurate and reliable classification of leaded and unleaded preserved eggs. The sensitivity and specificity of PLSDA were 0.975 and 1.000, respectively. Because the strictest safety standard of Pb content in traditional pidan is 2 ppm, the proposed method shows the feasibility for rapid and nondestructive discrimination of Pb in Chinese preserved eggs.

scholarly journals BIODIESEL PRODUCTION AND PAPER CHROMATOGRAPHY IN ORGANIC CHEMISTRY TEACHING

2016 ◽  
Vol 13 (26) ◽  
pp. 52-58
Author(s):  
Juliana Almeida ROCHA ◽  
Vanessa de Andrade ROYO ◽  
Elytania Veiga MENEZES
Keyword(s):  
Soybean Oil ◽  
Paper Chromatography ◽  
Fossil Fuels ◽  
Chemical Properties ◽  
Transesterification Reaction ◽  
Biodiesel Production ◽  
Chemistry Teaching ◽  
Basic Principles ◽  
Oil Reserves ◽  
Teaching Content

Biodiesel is important renewable energy that stands out mainly due to the possible reduction of oil reserves and environmental impacts intensified by the use of fossil fuels. This biofuel is produced from various oily materials, catalysts, and alcohols. Generates glycerin as a byproduct, which is used in different kinds of industries. Given the importance of the fuel and the need to integrate the theoretical content with the practical application of knowledge, this article aims to describe an experiment that can be used for teaching content such as chromatography and transesterification reaction in graduation courses. For biodiesel production were used: soybean oil, methanol, and potassium hydroxide, and analysis on paper chromatography were employed: filter paper and the solvents hexane, ethyl ether, and acetic acid as eluants. The viscosity and specific gravity of soybean oil and biodiesel were measured. With experiments, the academics observed that the transesterification reaction changes the physical-chemical properties of oil when it is converted into biodiesel and understand basic principles governing the chromatographic techniques and organic reactions.

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