The Experts below are selected from a list of 24501 Experts worldwide ranked by ideXlab platform
Wenying Li - One of the best experts on this subject based on the ideXlab platform.
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prediction of elemental composition of coal using Proximate Analysis
Fuel, 2017Co-Authors: Lan Yi, Jie Feng, Wenying LiAbstract:Abstract Ultimate Analysis is an important property for fuel utilization. The experimental determination of ultimate Analysis is sophisticated, long time consumed, and expensive, on the contrary, the Proximate Analysis can be run rapidly and easily. A variety of correlations to predict the ultimate Analysis of biomass using the Proximate Analysis have been appeared, while there exists a few number of correlations to estimate the elemental compositions of coal using Proximate Analysis in the literature but were focused on the predicted model or dependent on the heating value of coal. According to the Proximate Analysis of four different ranks of coal, this study proposes a series of correlations which are classified to predict carbon, hydrogen, and oxygen compositions through using 300 data points and validated further by another set of 40 data points. These correlations have the R2 of 0.95, 0.91, and 0.65 corresponding to the measured contents of C, H, and O in anthracite, 0.93, 0.83, and 0.67 of C, H, and O in high-rank bituminous, 0.86, 0.61, and 0.71 of C, H, and O in subbituminous, and 0.92, 0.67, and 0.66 of C, H, and O in lignite, respectively. The main merit of the correlations is the ability to estimate elemental composition of different rank coals using the Proximate Analysis and thus offers a valuable tool to set up a coal-thermal-conversion-process model.
Kolawole O. Falade - One of the best experts on this subject based on the ideXlab platform.
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Production Proximate Analysis and shelf life studies of ready-to-eat rice and kilishi
African Journal of Food Science, 2010Co-Authors: Abel Olusola Idowu, T O Omobuwajo, Kolawole O. FaladeAbstract:Accelerated shelf life studies (50 ± 2°C, 27 ± 2°C) were carried out on meal -ready-to-eat (RTE) rice and “Kilishi” which were prepared and packaged in aluminum foil and high density polyethylene (50 µm gauge). Chemical, microbiological and Proximate Analysis of the product was carried out to ascertain the quality and safety of the meal. Total microbial load of the product at accelerated shelf life ranged from 2 x 102 - 4 x 102 CFU/g. FFA values, a measure of rancidity, were in the range of 1.2 and 2.1%. Proximate composition of Kilishi was: moisture (9.75), fat (18.10), ash (7.10), protein (57.02) and carbohydrate (8.05); and rice, moisture (10.8), fat (4.0) ash (3.3) protein (7.4) and carbohydrate (74.0). Also Proximate Analysis showed that rice and Kilishi are nutritionally complementary. Key words: Kilishi, rice, convenience, Proximate composition, shelf life.
Z. L. Yang - One of the best experts on this subject based on the ideXlab platform.
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Proximate Analysis and calorific value estimation of rice straw by near infrared reflectance spectroscopy
Journal of the Energy Institute, 2008Co-Authors: C. J. Huang, L. J. Han, L. Liu, Z. L. YangAbstract:AbstractExploitation of straw resources as renewable energy source has attracted increasing interest since the present global energy crisis. Determination of both the Proximate Analysis and the calorific value are required before the utilisation as a biomass energy source. A total of 172 rice straw samples were collected from 17 provinces of China, and the use of near infrared reflectance spectroscopy was investigated as an alternative rapid method for Proximate Analysis and calorific value estimation. Different pretreatments and regression methods were examined to obtain optimum calibrations. The constructed models showed satisfactory accuracy and it was concluded that near infrared reflectance spectroscopy can be used as a rapid predictive tool for rice straw Analysis.
Lan Yi - One of the best experts on this subject based on the ideXlab platform.
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prediction of elemental composition of coal using Proximate Analysis
Fuel, 2017Co-Authors: Lan Yi, Jie Feng, Wenying LiAbstract:Abstract Ultimate Analysis is an important property for fuel utilization. The experimental determination of ultimate Analysis is sophisticated, long time consumed, and expensive, on the contrary, the Proximate Analysis can be run rapidly and easily. A variety of correlations to predict the ultimate Analysis of biomass using the Proximate Analysis have been appeared, while there exists a few number of correlations to estimate the elemental compositions of coal using Proximate Analysis in the literature but were focused on the predicted model or dependent on the heating value of coal. According to the Proximate Analysis of four different ranks of coal, this study proposes a series of correlations which are classified to predict carbon, hydrogen, and oxygen compositions through using 300 data points and validated further by another set of 40 data points. These correlations have the R2 of 0.95, 0.91, and 0.65 corresponding to the measured contents of C, H, and O in anthracite, 0.93, 0.83, and 0.67 of C, H, and O in high-rank bituminous, 0.86, 0.61, and 0.71 of C, H, and O in subbituminous, and 0.92, 0.67, and 0.66 of C, H, and O in lignite, respectively. The main merit of the correlations is the ability to estimate elemental composition of different rank coals using the Proximate Analysis and thus offers a valuable tool to set up a coal-thermal-conversion-process model.
Abel Olusola Idowu - One of the best experts on this subject based on the ideXlab platform.
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Production Proximate Analysis and shelf life studies of ready-to-eat rice and kilishi
African Journal of Food Science, 2010Co-Authors: Abel Olusola Idowu, T O Omobuwajo, Kolawole O. FaladeAbstract:Accelerated shelf life studies (50 ± 2°C, 27 ± 2°C) were carried out on meal -ready-to-eat (RTE) rice and “Kilishi” which were prepared and packaged in aluminum foil and high density polyethylene (50 µm gauge). Chemical, microbiological and Proximate Analysis of the product was carried out to ascertain the quality and safety of the meal. Total microbial load of the product at accelerated shelf life ranged from 2 x 102 - 4 x 102 CFU/g. FFA values, a measure of rancidity, were in the range of 1.2 and 2.1%. Proximate composition of Kilishi was: moisture (9.75), fat (18.10), ash (7.10), protein (57.02) and carbohydrate (8.05); and rice, moisture (10.8), fat (4.0) ash (3.3) protein (7.4) and carbohydrate (74.0). Also Proximate Analysis showed that rice and Kilishi are nutritionally complementary. Key words: Kilishi, rice, convenience, Proximate composition, shelf life.
