scholarly journals The Potential of Spectroscopic Techniques in Coffee Analysis—A Review

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 71
Author(s):  
Leah Munyendo ◽  
Daniel Njoroge ◽  
Bernd Hitzmann
Keyword(s):  
Fluorescence Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Geographical Origin ◽  
Market Price ◽  
Spectroscopic Techniques ◽  
Analysis Techniques ◽  
Specialty Coffee ◽  
Robust Prediction

This review provides an overview of recent studies on the potential of spectroscopy techniques (mid-infrared, near infrared, Raman, and fluorescence spectroscopy) used in coffee analysis. It specifically covers their applications in coffee roasting supervision, adulterants and defective beans detection, prediction of specialty coffee quality and coffees’ sensory attributes, discrimination of coffee based on variety, species, and geographical origin, and prediction of coffees chemical composition. These are important aspects that significantly affect the overall quality of coffee and consequently its market price and finally quality of the brew. From the reviewed literature, spectroscopic methods could be used to evaluate coffee for different parameters along the production process as evidenced by reported robust prediction models. Nevertheless, some techniques have received little attention including Raman and fluorescence spectroscopy, which should be further studied considering their great potential in providing important information. There is more focus on the use of near infrared spectroscopy; however, few multivariate analysis techniques have been explored. With the growing demand for fast, robust, and accurate analytical methods for coffee quality assessment and its authentication, there are other areas to be studied and the field of coffee spectroscopy provides a vast opportunity for scientific investigation.

scholarly journals Rancidity Estimation of Perilla Seed Oil by Using Near-Infrared Spectroscopy and Multivariate Analysis Techniques

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Suk-Ju Hong ◽  
Shin-Joung Rho ◽  
Ah-Yeong Lee ◽  
Heesoo Park ◽  
Jinshi Cui ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Seed Oil ◽  
Prediction Models ◽  
Oxidation Process ◽  
Analysis Techniques ◽  
Peroxide Values ◽  
Perilla Seed

Near-infrared spectroscopy and multivariate analysis techniques were employed to nondestructively evaluate the rancidity of perilla seed oil by developing prediction models for the acid and peroxide values. The acid, peroxide value, and transmittance spectra of perilla seed oil stored in two different environments for 96 and 144 h were obtained and used to develop prediction models for different storage conditions and time periods. Preprocessing methods were applied to the transmittance spectra of perilla seed oil, and multivariate analysis techniques, such as principal component regression (PCR), partial least squares regression (PLSR), and artificial neural network (ANN) modeling, were employed to develop the models. Titration analysis shows that the free fatty acids in an oil oxidation process were more affected by relative humidity than temperature, whereas peroxides in an oil oxidation process were more significantly affected by temperature than relative humidity for the two different environments in this study. Also, the prediction results of ANN models for both acid and peroxide values were the highest among the developed models. These results suggest that the proposed near-infrared spectroscopy technique with multivariate analysis can be used for the nondestructive evaluation of the rancidity of perilla seed oil, especially the acid and peroxide values.

scholarly journals Near Infrared Hyperspectral Imaging in Transmission Mode: Assessing the Weathering of Thin Wood Samples

2016 ◽  
Vol 24 (6) ◽  
pp. 595-604 ◽  
Author(s):  
Knut Arne Smeland ◽  
Kristian Hovde Liland ◽  
Jakub Sandak ◽  
Anna Sandak ◽  
Lone Ross Gobakken ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Near Infrared ◽  
Prediction Models ◽  
Hyperspectral Image ◽  
Principal Component Regression ◽  
Principal Component ◽  
Transmission Mode ◽  
Infrared Wavelength ◽  
Robust Prediction ◽  
Wooden Surface

Untreated wooden surfaces degrade when exposed to natural weathering. In this study thin wood samples were studied for weather degradation effects utilising a hyperspectral camera in the near infrared wavelength range in transmission mode. Several sets of samples were exposed outdoors for time intervals from 0 days to 21 days, and one set of samples was exposed to ultraviolet (UV) radiation in a laboratory chamber. Spectra of earlywood and latewood were extracted from the hyperspectral image cubes using a principal component analysis-based masking algorithm. The degradation was modelled as a function of UV solar radiation with four regression techniques, partial least squares, principal component regression, Ridge regression and Tikhonov regression. It was found that all the techniques yielded robust prediction models on this dataset. The result from the study is a first step towards a weather dose model determined by temperature and moisture content on the wooden surface in addition to the solar radiation.

scholarly journals Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques

Foods ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 232
Author(s):  
Hanim Z. Amanah ◽  
Salma Sultana Tunny ◽  
Rudiati Evi Masithoh ◽  
Myoung-Gun Choung ◽  
Kyung-Hwan Kim ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Near Infrared ◽  
Prediction Models ◽  
Soybean Seed ◽  
Fourier Transform Infrared ◽  
Partial Least Square ◽  
Least Square ◽  
Calibration Model ◽  
Spectroscopic Techniques ◽  
Ft Ir

The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (R2p: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (R2p: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (R2p) of over 0.70. In addition, the result of the testing model proved the model’s performance by obtaining a similar R2 and error to the calibration model.

scholarly journals 379 ASAS-EAAP Talk: Precision Phenotyping using Infrared Spectroscopy to Improve the Quality of Animal Products

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 140-140
Author(s):  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Giovanni Bittante
Keyword(s):  
Gold Standard ◽  
Large Scale ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Parameters ◽  
Least Squares Regression ◽  
Animal Products ◽  
Precision Phenotyping ◽  
Definition Of

Abstract There is an ever-growing interest in research oriented towards the improvement of quality of animal products. In this context, one major operational bottleneck is the possibility to collect quality indicators over the meat and dairy chains and for selective breeding purposes. The use of near-infrared (NIR) and the Fourier-transformed infrared (FTIR) spectroscopy techniques have been proven to be powerful precision phenotyping tools for high-throughput meat and milk quality assessment. Such technologies allow scoring large number of animals and/or derived-products for novel (predicted) phenotypes and indicator traits to set-up potential new payment systems and boost the genetic improvement. One important step in the use of NIR and FTIR tools is the definition of the “gold standard” as the infrared-based predictions could act only as indicators traits. Indeed, the definition of a robust calibration set, the assessment of repeatability and reproducibility of the reference (i.e., gold standard) as well as the detection of random and systematic errors are crucial steps. Once the reference phenotype has been defined, different statistical methodologies could be applied to infrared spectra data. For instance, the partial least squares regression (PLS) is a multivariate regression method commonly used to build up prediction models using NIR and FTIR spectra data. However, the implementation of advanced statistical approaches, such as Bayesian approaches and machine learning methods, might allow us to achieve more robust and accurate predictions. In this talk, we will describe and discuss some of the challenges and potentials of NIR and FTIR tools for large-scale precision phenotyping. Some examples include the use of NIR and Visible-NIR (Vis-NIR) for assessing meat quality parameters (also using portable instruments able to collect spectra directly from the muscle surface at the slaughterhouse) and the use of FTIR for predicting several traits related to fine milk composition and technological traits in dairy cattle.

scholarly journals Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild Paris polyphylla var. yunnanensis

Molecules ◽  
2019 ◽  
Vol 24 (14) ◽  
pp. 2559 ◽  
Author(s):  
Pei ◽  
Zuo ◽  
Zhang ◽  
Wang
Keyword(s):  
Fourier Transform ◽  
Data Fusion ◽  
Near Infrared ◽  
Geographical Origin ◽  
Spectroscopic Techniques ◽  
Mid Infrared ◽  
Level Data ◽  
Paris Polyphylla ◽  
High Level ◽  
Geographical Origin Traceability

Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. Paris polyphylla var. yunnanensis is widely distributed and well-known all over the world. In our study, two spectroscopic techniques (Fourier transform mid-infrared (FT-MIR) and near-infrared (NIR)) were applied for the geographical origin traceability of 196 wild P. yunnanensis samples combined with low-, mid-, and high-level data fusion strategies. Partial least squares discriminant analysis (PLS-DA) and random forest (RF) were used to establish classification models. Feature variables extraction (principal component analysis—PCA) and important variables selection models (recursive feature elimination and Boruta) were applied for geographical origin traceability, while the classification ability of models with the former model is better than with the latter. FT-MIR spectra are considered to contribute more than NIR spectra. Besides, the result of high-level data fusion based on principal components (PCs) feature variables extraction is satisfactory with an accuracy of 100%. Hence, data fusion of FT-MIR and NIR signals can effectively identify the geographical origin of wild P. yunnanensis.

scholarly journals Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish

Molecules ◽  
2020 ◽  
Vol 25 (5) ◽  
pp. 1191 ◽  
Author(s):  
Abdo Hassoun ◽  
Karsten Heia ◽  
Stein-Kato Lindberg ◽  
Heidi Nilsen
Keyword(s):  
Hyperspectral Imaging ◽  
High Performance ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Ph Value ◽  
Raw Materials ◽  
Industrial Applications ◽  
Spectroscopic Techniques

Lutefisk is a traditional Norwegian fish dish made from dried fish, such as cod or other whitefish. In Norway and other Nordic countries, lutefisk is considered among the most popular dishes served during Christmas or other festive occasions. However, to date, little attention has been paid to this product, and available research on the quality, processing, and chemistry of lutefisk is still limited. The quality of this very delicate product, with a high pH value, depends on many factors, such as the initial quality of raw materials (stockfish), the quantity of lye used during the preparation process of lutefisk, and time during soaking in the lye and water, among others, making it challenging to both optimize processing and monitor the quality of lutefisk. In this study, four commercially available lutefisk brands (labelled as A, B, C, and D) were characterized using two online spectroscopic techniques, namely fluorescence and diffuse reflectance hyperspectral imaging, implemented on conveyor belts to mimic industrial applications. The samples were also analyzed by the use of an offline laboratory instrument based on visible/near infrared diffuse reflectance spectroscopy. Three traditional measurements, including texture, water content, and pH, were also conducted on the same samples. Supervised classification PLS-DA models were built with each dataset and relationships between the spectroscopic measurements and the traditional data were investigated using canonical correlations. The spectroscopic methods, especially fluorescence spectroscopy, demonstrated high performance for the discrimination between samples of the different brands, with high correlations between the spectral and traditional measurements. Although more validations of the results of this study are still required, these preliminary findings suggest that the destructive, laborious, and time-consuming traditional techniques can be replaced by rapid and nondestructive online measurements based on hyperspectral imaging used in fluorescence or diffuse reflectance mode.

scholarly journals Prediction of wheat milling characteristics by near-infrared reflectance spectroscopy

2011 ◽  
Vol 23 (No. 4) ◽  
pp. 145-151 ◽  
Author(s):  
J. Blažek ◽  
O. Jirsa ◽  
M. Hrušková
Keyword(s):  
Near Infrared ◽  
Prediction Models ◽  
Nir Spectroscopy ◽  
Milling Process ◽  
Near Infrared Reflectance ◽  
Independent Validation ◽  
Milling Characteristics ◽  
Predicted Values ◽  
Calibration Equations

The aim of this study was to explore the use of NIR spectroscopy of laboratory milled flour to predict the milling characteristics of wheat. Quantitative traits of the milling process of wheat were predicted by analyses of NIR spectra of six sets consisting of 94 samples. Reference data were obtained by grinding the samples on the laboratory mill Chopin CD1-auto (France), spectral data were measured on spectrograph NIRSystem 6500. Commercial spectral analysis software WINISI II was used to collect spectra, develop calibration equations and evaluate calibration performance. The quality of prediction was evaluated by coefficients of correlation between the measured and the predicted values from cross and independent validation. MPLS/PLS regression and ANN methods were used. A statistically significant dependence (at the probability level of 99%) was determined for all traits studied in the case of cross-validation. Satisfactory accuracy of the prediction models by independent validation was achieved only for semolina extraction rate, models for other characteristics did not show acceptable precision.  

PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKTIF TEKNIK PEMESINAN BUBUT

2020 ◽  
Vol 6 (2) ◽  
pp. 169
Author(s):  
Philip Nababan ◽  
Efendi Napitupulu ◽  
R Mursid
Keyword(s):  
Student Learning ◽  
Learning Outcomes ◽  
Interactive Learning ◽  
Descriptive Analysis ◽  
Student Learning Outcomes ◽  
Field Trials ◽  
Student Responses ◽  
Analysis Techniques ◽  
Qualitative Descriptive

Abstrak: Penelitian ini bertujuan untuk: (1) Mengetahui tanggapan siswa terhadap kualitas media pembelajaran interaktif pada pembelajaran Teknik Pemesinan Bubut. (2) Mengetahui keefektifan media pembelajaran interaktif pada pembelajaran Teknik Pemesinan Bubut pada siswa program keahlian Teknik Pemesinan. Jenis penelitian ini adalah penelitian pengembangan. Data tentang kualitas produk pengembangan ini dikumpulkan dengan angket dan dianalisis dengan teknik analisis deskriptif kualiatatif. Hasil penelitian menunjukkan bahwa; (1) uji ahli materi pelajaran Teknik Pemesinan Bubut berada pada kualifikasi sangat baik (88,92%), (2) uji ahli desain pembelajaran berada pada kualifikasi sangat baik (85,21%), (3) uji ahli rekayasa perangkat lunak berada pada kualifikasi sangat baik (84,03%), (4) uji coba perorangan berada pada kualifikasi sangat baik (88,75%), (5) uji coba kelompok kecil berada pada kualifikasi sangat baik (91,35%) dan (5) uji coba lapangan berada pada kualifikasi sangat baik (88,31%). Hasil pengujian hipotesis membuktikan bahwa terdapat perbedaan antara hasil belajar siswa yang menggunakan media pembelajaran interaktif  dengan hasil belajar siswa yang menggunakan buku teks. Hal ini ditunjukkan dengan hasil pengolahan data diperoleh  thitung sebesar 4,68 dan ttabel sebesar 1,67 pada taraf kepercayaan 95 persen. Maka diperoleh bahwa thitung> ttabel. Disimpulkan bahwa  hasil belajar siswa yang menggunakan media pembelajaran interaktif dengan efektifitas sebesar 72,77 %. lebih tinggi dari hasil belajar siswa yang diajar dengan pembelajaran menggunakan buku teks dengan efektifitas sebesar 62,13%. Kata Kunci: media pembelajaran interaktif, teknik pemesinan bubut Abstract: This study aims to: (1) Determine student responses to the quality of interactive learning media on learning Lathe Machining Techniques. (2) Knowing the effectiveness of interactive learning media on learning of Machining Lathe in students of Machining Engineering expertise program. This type of research is development research. Data about the quality of this development product was collected by a questionnaire and analyzed by qualitative descriptive analysis techniques. The results showed that; (1) Lathe machining engineering subject matter expert test is in very good qualification (88.92%), (2) learning design expert test is in very good qualification (85.21%), (3) software engineering expert test is in in very good qualifications (84.03%), (4) individual trials were in very good qualifications (88.75%), (5) small group trials were in very good qualifications (91.35%) and (5 ) field trials are in very good qualifications (88.31%). Hypothesis testing results prove that there are differences between student learning outcomes using interactive learning media with student learning outcomes using textbooks. This is indicated by the results of data processing obtained by tcount of 4.68 and ttable of 1.67 at a confidence level of 95 percent. Then it is obtained that tcount> ttable. It was concluded that student learning outcomes using interactive learning media with an effectiveness of 72.77%. higher than student learning outcomes taught by learning to use textbooks with an effectiveness of 62.13%. Keywords: interactive learning media, lathe machining techniques

The Links between the Companies Market Price Quality and that of its Management and Business Quality: A System Panel Data Approach

GIS Business ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. 28-38
Author(s):  
Dinis Daniel Santos ◽  
Elias Soukiazis
Keyword(s):  
Panel Data ◽  
Business Performance ◽  
Market Price ◽  
Equation System ◽  
Simultaneous Equation ◽  
System Equation ◽  
Simultaneous Equation System ◽  
Management Quality ◽  
The Relationship

This work uses a simultaneous equation system approach to analyze the relationship between the management and business quality of companies and their market price quality. Using panel data we found that both the management and the business quality of companies positively influence the market price quality of the studied American companies. Additionally, variables like the actual position of the company price quality compared to the industry average, being on the top or the bottom, or the beta value of a company, also influence the market price quality of the respective company. It is shown that the system equation approach is the most appropriate to explain the linkages between price, business, and management quality providing consistent estimates. Also, using ratings to express the three core variables in the system is the most adequate way to define the quality characteristics in terms of price, management, and business performance of the companies considered in this study.

UPAYA MENINGKATKAN KOMPETENSI GURU DALAM MENYUSUN RENCANA PELAKSANAAN PEMBELAJARAN MELALUI BIMBINGAN BERKELANJUTAN DI SD NEGERI 017 KUNTO DARUSSALAM TAHUN 2017

2020 ◽  
Author(s):  
Sri Winarsih
Keyword(s):  
Learning Strategies ◽  
Learning Process ◽  
School Principal ◽  
Initial Condition ◽  
Research Subjects ◽  
Analysis Techniques ◽  
Pedagogical Competence ◽  
Treatment Data ◽  
The Subject

This study aims to determine the appropriate steps in carrying out academic supervision so as to be able to improve the pedagogical competence of teachers, especially in the learning process which in turn will affect the improvement of the quality of education.The study was conducted in two cycles. Each cycle has different planning, implementation, observation and reflection. Research subjects of the principal and teacher. The school principal with his academic supervision measures, while the Kunto Darussalam Elementary School 017 teacher as an object as well as the subject in providing academic supervision treatment. Data collection techniques through class supervision with stages of supervising teachers in the learning process and observation of classroom learning, to record important events related to research, especially at the time of the processlearning takes place.Data analysis techniques that guide data processing using a percentage (%) of achievement with 100 constants. And to see the interpertation using score interpertation criteria to strengthen the interpretation in conclusions as follows: 80% - 100% (Very Good), 66% - 79 % (Good), 56% - 65% (Enough), and 40% - 55% (Less).The results showed that the ability of teachers in the implementation of the learning process experienced an increase in the percentage at each stage, from the first cycle reached an average of 63% (sufficient) and in the second cycle reached an average of 68% (good). There is an increase in teacher's ability by 5% from cycle I. In detail there is a significant increase in the initial condition of the school when compared to the final condition in the second cycle. The accuracy of teachers entering the class increased by 48%, the use of learning media increased by 32%, varied methods increased by 31%, and learning strategies increased by 36%.

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