Rapid Determination of Pentose and Hexose Sugars in Mixed Sugars by Multiple Linear Regression Calibration Method

2011 ◽  
Vol 145 ◽  
pp. 159-163
Author(s):  
Xiao Chen Liu ◽  
Ping Wang ◽  
Ying Long He ◽  
Yong Lei Kou ◽  
Biao Zhang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Rapid Determination ◽  
Calibration Method ◽  
Linear Regression Method ◽  
Regression Calibration ◽  
Mixed Sugars ◽  
Hexose Sugars ◽  
Pentose Sugar

This research provides an improvement for the method of Douglas to determine pentose and hexose sugars in mixed sugars. Specific absorption wave of 553 nm for pentose derivatives and 408 nm for hexose derivatives are selected for determination, and the interference from pentose sugar to hexose sugar is corrected with multiple linear regression method. The results show that the interference from pentose sugar is reduced greatly after multiple linear regression calibration; the error is lower than 5.0 %. The experimental results show a satisfying precision and accuracy, with a recovery range from 95.1 % to 106.8%. This method is suitable for simultaneously rapid determination of pentose and hexose sugars in practical application.

scholarly journals The Effect of Land Characteristics on Agricultural Productivity Using Multiple Linear Regression Method in Madiun Regency, East Java

2021 ◽  
Vol 325 ◽  
pp. 02005
Author(s):  
Elya Pratiwi Istifaroh ◽  
Rika Harini
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Agricultural Productivity ◽  
Secondary Data ◽  
Climatic Conditions ◽  
Linear Regression Method ◽  
Agricultural Commodities ◽  
Agricultural Commodity ◽  
Regression Methods

Agriculture is an important sector to support national food availability. Soil and climatic conditions in Indonesia are very suitable for agriculture. However, the land characteristics in each region are different, Especially in Madiun Regency, where this study is conducted. This study aims to determine what commodities are suitable for the characteristics of the land based on land suitability and how land characteristics influence agricultural productivity. The data used in this research is secondary data. Determination of agricultural commodities is carried out by cross-checking between land characteristics and guidelines for agricultural commodity land requirements. There are six types of agricultural commodities that are suitable for land characteristics in Madiun Regency. The effect of land characteristics consisting of several parameters on agricultural productivity was sought using multiple linear regression methods. The processing results are known that 8 variables of land characteristics significantly affect agricultural productivity by 93%. The independent variables were tested using the Simultaneous F-Test and were known to have a simultaneous (together) effect on agricultural productivity. In addition, a Partial T-Test was conducted, and it was found that there were only two variables that had a partial effect, namely the soil CEC characteristics and the sand characteristics.

Rapid determination of sulfamethoxazole and trimethoprim illegally added into health products using excitation-emission matrix fluorescence coupled with second-order calibration method

2021 ◽  
Author(s):  
Lu-Zhu Chen ◽  
Hai-Long Wu ◽  
WanJun Long ◽  
Tong Wang ◽  
Gao-Yan Tong ◽  
...  
Keyword(s):  
Analytical Method ◽  
Rapid Determination ◽  
Calibration Method ◽  
Trilinear Decomposition ◽  
Excitation Emission Matrix ◽  
Health Products ◽  
Alternating Trilinear Decomposition ◽  
Second Order Calibration ◽  
Eem Fluorescence

In this work, a simple and fast analytical method based on self-weighted alternating trilinear decomposition (SWATLD) algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the simultaneous determination of...

An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids

2019 ◽  
Vol 164 ◽  
pp. 681-689 ◽  
Author(s):  
Mariusz Zapadka ◽  
Mateusz Kaczmarek ◽  
Bogumiła Kupcewicz ◽  
Przemysław Dekowski ◽  
Agata Walkowiak ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

scholarly journals Chemometric approach in the development of the colorimetric method for the estimation of food colorants in meat products

2014 ◽  
Vol 68 (6) ◽  
pp. 781-791 ◽  
Author(s):  
Radivoj Petronijevic ◽  
Vesna Matekalo-Sverak ◽  
Aurelija Spiric ◽  
Ilija Vukovic ◽  
Jelena Babic ◽  
...  
Keyword(s):  
Linear Regression ◽  
Mathematical Models ◽  
Multiple Linear Regression ◽  
Linear Models ◽  
Colorimetric Method ◽  
Meat Products ◽  
Food Colorants ◽  
Food Colorant ◽  
Control Batch

The aim of this research was to develop a novel colorimetric method based on mathematical models, by multiple linear regression (MLR), from the CIE L*a*b* measurements and data of the HPLC determination of food colorants. Calibration set of 10 production batches of finely grinded cooked sausage with food colorants added was manufactured in industrial conditions as follows: one control batch and 9 products with various quantities of added food colorants: E120 (3.4, 7.5 and 12.5 mg/kg), E 124 (5.0, 15.0, 25.0 mg/kg) and E 129 (5.0, 15.0, 25.0 mg/kg). The estimation of the added food colorants was assessed by measuring L*, a*, b* parameters of cross-section. The quantification of food colorants was achieved by HPLC-PDA. Food colorants were extracted from meat products using Accelerated Solvent Extraction (ASE). Quantification of food colorants was achieved in the range from 1 to 100 mg / kg, and recovery values were from 76.15% to 107.04%, for E 120, from 97.61% to 101.03%, for E 124 and from 99.91% to 101.67%, for E 129. Correlation of the results obtained using HPLC and colorimetric measuring data was assessed by Multiple Linear Regression (MLR). The results from colorimetric and chromatographic determinations in four experimental batches (three batches with different quantities of food colorants and one control batch) were used for calibration. Coefficients of determination (R2) for linear models in experimental batches were 0.954, for E 124, 0.987, for E 120 and 0.993, for E 129. Correlation functions of food colorant quantities and corresponding L*a*b* values were established. The obtained mathematical models were tested for the estimation of the content of dyes in 21 samples of finely grinded cooked sausages purchased in retail stores. Food colorants were confirmed in 20 samples (95.24 %), and one sample (4.76 %) did not contain any of these compounds. Out of the positive samples, sixteen samples (80.00 %) contained E 120, while four samples (20.00 %) contained E 129. Food colorant E124 was not established in any of the analyzed samples. Colorimetric CIE L*a*b* method might be used during sensory evaluation of meat products for the assessment of the added food colorants.

scholarly journals Accident Prediction Model at Unsignalized Intersection Using Multiple Linear Regression Method

2017 ◽  
Vol 1 (2) ◽  
pp. 379-389
Author(s):  
N. K. Oghoyafedo ◽  
J. O. Ehiorobo ◽  
Ebuka Nwankwo
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Design Standards ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
Unsignalized Intersections ◽  
Multiple Linear Regression Method

The issue of road accidents is an increasing problem in developing countries. This could be due to increasing road traffic/vehicle occupancy, geometric characteristics and road way condition. The factors influencing accidents occurrence are to be analysed for remedies. The purpose of this research is to develop an accident prediction model as a measure for future study, aid planning phase preceding the designed intervention, enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. Five intersections were selected randomly within Benin City and traffic count carried out at these intersections as well as geometric characteristics and roadway conditions. The prediction model was developed using multiple linear regression method and the standard error of estimate was computed to show how close the observed value is to the regression line. The model was validated using coefficient of multiple determination. The establishment of the relationship between accidents and traffic flow site characteristics on the other hand would enable improvement to be more realistically accessed. This study will also enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PROFITABILITAS BANK UMUM SYARIAH DI INDONESIA

2020 ◽  
Vol 6 (8) ◽  
pp. 1607
Author(s):  
Dian Anggraini ◽  
Imron Mawardi
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Commercial Bank ◽  
Confidence Level ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Coefficient Of Determination

The purpose of this study is to analyze the factors that affect the profitability of Sharia Commercial Bank in Indonesia. The sampling technique used is saturated sampling, so the population and sample is the Sharia Commercial Bank periode October 2014-March 2018 which amounted to 42 months. This study uses a quantitative approach with multiple linear regression analysis technique.The result showed that with 95% confidence level partially variable Financing to Deposit Ratio have significant effect to profitability, while variable Natural Uncertainty Contract Financing, Non Performing Financing, and Equity have no significant effect on profitability of Sharia Commercial Bank in Indonesia. Nevertheless, Natural Uncertainty Contract Financing, Non Performing Financing, Financing to Deposit Ratio and Equity simultaneously have significant effect to the profitability of Sharia Commercial Bank in Indonesia. With the coefficient of determination of 33,2%.Keywords: Natural Uncertainty Contract, Non Performing Financing, Financing to Deposit Ratio, Equity

scholarly journals THE EFFECT OF LEADERSHIP, JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT ON EMPLOYEE PERFORMANCE AT RUMAH SAKIT UMUM DAERAH BESUKI SITUBONDO, INDONESIA

2018 ◽  
Vol 6 (6) ◽  
pp. 322-334
Author(s):  
Amrozi ◽  
Zarah Puspitaningtyas ◽  
Djoko Poernomo
Keyword(s):  
Job Satisfaction ◽  
Organizational Commitment ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Employee Performance ◽  
Sampling Technique ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

This study is to examine the influence of leadership, job satisfaction and organizational commitment on employee performance. Population in this research was the entire employees of Rumah Sakit Umum Daerah (RSUD) Besuki, Situbondo, Indonesia which was about 295 peoples. Then, the researcher applied probability random sampling technique to select 170 respondents as the sampling. The researcher analyzed the data by applying multiple linear regression method. The result shows that leadership and job satisfaction contribute positive and significant effect on employee performance, while organizational commitment has no effect on employee performance.

scholarly journals Pengaruh Disiplin Kerja dan Pemberian Insentif terhadap Kinerja Karyawan PT Putra Karisma Palembang

2021 ◽  
Vol 2 (1) ◽  
pp. 25-42
Author(s):  
Andini Dwi Saputri ◽  
Susi Handayani ◽  
Muhammad Kurniawan DP
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Employee Performance ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method ◽  
Sample Technique ◽  
Saturated Sample ◽  
Analyze Data

This study aims to analyze the effects of work discipline and incentives on the performance of employees of PT Putra Karisma Palembang. The sample was selected using the saturated sample technique. Data from 57 respondents were collected through interviews, documentation, and questionnaires. This study implemented the multiple linear regression method to analyze data. The results prove that partially each of work discipline and incentives has no significant effect on employee performance. However, simultaneously work discipline and incentives have a significant effect on employee performance. This insight is beneficial for PT Putra Karisma Palembang. To improve employees' performance, the company should consider both work discipline and incentives factors together.   Penelitian ini bertujuan untuk menganalisis pengaruh disiplin kerja dan pemberian insentif terhadap kinerja karyawan PT Putra Karisma Palembang. Sampel dipilih menggunakan teknik sampel jenuh. Data 57 responden dikumpulkan melalui wawancara, dokumentasi, dan kuesioner. Studi ini mengimplementasikan metode regresi linier berganda untuk menganalisis data. Hasil investigasi membuktikan bahwa secara parsial baik disiplin kerja maupun pemberian insentif masing-masing tidak berpengaruh signifikan terhadap kinerja karyawan. Tetapi, secara simultan disiplin kerja dan pemberian insentif berpengaruh signifikan terhadap kinerja karyawan. Fakta ini bermanfaat bagi PT Putra Karisma Palembang. Untuk meningkatkan kinerja karyawan, maka perusahaan harus mempertimbangkan faktor disiplin kerja dan pemberian insentif secara bersama-sama.

scholarly journals ANALYSIS OF FACTORS AFFECTING THE PRICE FLUCTUATION OF CAYENNE PEPPER IN MALANG REGENCY

2021 ◽  
Vol 5 (1) ◽  
pp. 19-26
Author(s):  
Nurul Laili ◽  
Sri Hindarti ◽  
Dwi Susilowati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Commodity Prices ◽  
Secondary Data ◽  
Regression Method ◽  
Linear Regression Method ◽  
Factors Affecting ◽  
Independent Variables ◽  
Multiple Linear Regression Method

 This study aims to 1) Analyze the pattern of changes in commodity prices for spanish pepper in Malang District. 2) Analyzing the factors that influence fluctuations in the price of spanish pepper in Malang District. The research method used is quantitative method that uses secondary data in the form of time series obtained from several related agencies, namely the Central Statistics Agency of Malang District, Department of Industry and Trade, and Department of food crops, horticulture, and plantation in Malang District. Analysis of the data used is multiple linear regression with the dependent variable is the price at the consumer level from 2009-2018, while the independent variables use the data of the price of spanish pepper at the producer level, the amount of production, and the amount of consumption from 2009-2018. The study found that: 1) The development of the price of spanish pepper had a trend that tended to increase during the last 10 years. 2) From the results of data processing using multiple linear regression method with Eviews 9.0 application, it is found that the factor that significantly influences changes in the price of spanish pepper is the price at the producer level, while the amount of production of spanish pepper and the number of requests does not significantly affect the change in spanish pepper prices in Malang District. 

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