scholarly journals Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics

Foods ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 851
Author(s):  
Mauricio Flores-Valdez ◽  
Ofelia Gabriela Meza-Márquez ◽  
Guillermo Osorio-Revilla ◽  
Tzayhri Gallardo-Velázquez
Keyword(s):  
Standard Error ◽  
Coffea Arabica ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quantitative Model ◽  
Economic Benefits ◽  
Production Volume ◽  
Mir Spectroscopy ◽  
Multiple Variables ◽  
Coffea Arabica L

Food adulteration is an illegal practice performed to elicit economic benefits. In the context of roasted and ground coffee, legumes, cereals, nuts and other vegetables are often used to augment the production volume; however, these adulterants lack the most important coffee compound, caffeine, which has health benefits. In this study, the mid-infrared Fourier transform spectroscopy (FT-MIR) technique coupled with chemometrics was used to identify and quantify adulterants in coffee (Coffea arabica L.). Coffee samples were adulterated with corn, barley, soy, oat, rice and coffee husks, in proportions ranging from 1–30%. A discrimination model was developed using the soft independent modeling of class analogy (SIMCA) framework, and quantitative models were developed using such algorithms as the partial least squares algorithms with one variable (PLS1) and multiple variables (PLS2) and principal component regression (PCR). The SIMCA model exhibited an accuracy of 100% and could discriminate among all the classes. The quantitative model with the highest performance corresponded to the PLS1 algorithm. The model exhibited an R2c: ≥ 0.99, standard error of calibration (SEC) of 0.39–0.82, and standard error of prediction (SEP) of 0.45–0.94. The developed models could identify and quantify the coffee adulterants, and it was considered that the proposed methodology can be applied to identify and quantify the adulterants used in the coffee industry.

scholarly journals Multivariate Method Based on Raman Spectroscopy for Quantification of Dipyrone in Oral Solutions

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luciana Lopes Guimarães ◽  
Letícia Parada Moreira ◽  
Bárbara Faria Lourenço ◽  
Walber Toma ◽  
Renato Amaro Zângaro ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Quality Control ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quantitative Model ◽  
Calibration Model ◽  
Analytical Methodology ◽  
Figures Of Merit ◽  
Model Based ◽  
Raman Probe

This work employed a quantitative model based on Raman spectroscopy and principal component regression (RS/PCR) to quantify the active ingredient dipyrone (metamizole) in commercially available formulations as an analytical methodology for quality control in the pharmaceutical industry. Raman spectra were collected using a dispersive Raman spectrometer (830 nm, 250 mW excitation, and 20 s exposure time) coupled to a Raman probe. Solutions of dipyrone diluted in water in the range of 80 to 120% of the concentration of commercial formulations (500 mg/mL) were used to develop a calibration model based on PCR to obtain the figures of merit for class I validation from the Brazilian Sanitary Surveillance Agency (ANVISA, RE no. 899/2003). This spectral model was then used to predict the concentration of dipyrone in commercial formulations from distinct brands with 500 mg/mL. A prediction error of 6.5 mg/mL (1.3%) was found for this PCR model using the diluted samples. Commercial formulations had predicted concentrations with a difference below 5.0% compared to the label concentration, indicating the applicability of Raman spectroscopy for quality control in the final product.

scholarly journals PENDUGAAN KANDUNGAN ENERGI BRUTO TEPUNG IKAN MENGGUNAKAN TEKNOLOGI Near Infrared (NIR) (Prediction of the Gross Energy for Fishmeal using Near Infrared Reflectant (NIR) Technology)

2016 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
Ati Atul Quddus
Keyword(s):  
Standard Error ◽  
Coefficient Of Variation ◽  
Near Infrared ◽  
Animal Feed ◽  
Principal Component Regression ◽  
Principal Component ◽  
Calibration Equation ◽  
Bomb Calorimeter ◽  
Gross Energy ◽  
Pcr Method

Abstrak Penelitian ini bertujuan untuk menduga kandungan energi bruto tepung ikan untuk bahan pakan ternak menggunakan teknologi Near Infrared (NIR). Tepung ikan yang digunakan dalam penelitian ini diperoleh dari poultry shop yang ada di beberapa daerah di Indonesia dan industri pakan ternak. Penelitian ini menggunakan 50 tepung ikan. Tiga puluh lima sampel digunakan untuk kalibrasi, sedangkan 15 sampel digunakan untuk validasi. Pengukuran NIR reflektan menggunakan sistem NIR. Energi bruto diukur menggunakan bomb calorimeter. Data dianalisis dengan menggunakan regresi linier berganda (RLB) dan Principal Component Regression (PCR). Persamaan kalibrasi dari reflektan dianalisis menggunakan 29 panjang gelombang untuk memprediksi energi bruto. Hasil dari validasi menunjukkan akurasi yang tinggi dengan standar eror dan koefisien variasi untuk energi bruto yaitu 6,6 Kkal/Kg dan 0,2%. Persamaan kalibrasi dari metode PCR menggunakan data absorban. Hasil dari validasinya menunjukkan kurang akurasi dengan nilai standar eror dan koefisien variasi yaitu 119,2 Kkal/kg dan 4,16%. Kata kunci : energi bruto, NIR, RLB, PCR Abstract This experiment was aimed to predict gross energy (GE) content of fishmeal by using Near Infrared (NIR) technology. Fishmeal that was used in this experiment was obtained from the poultry shop in several regions in Indonesia and from animal feed industries. This experiment was conducted by using 50 fishmeals. Thirty five samples out of 50 samples fishmeal was used to develop the NIR of calibration and the rest 15 samples was used to test the accuracy of the calibration. NIR reflectant was measured by NIR system. Gross energy was measured by bomb calorimeter. Collected data were analyzed by using multivariate linier regression (MLR) and principal component regression (PCR). Calibration equation of reflectant was analyzed by using 29 wavelengths for predicting GE. The results of the validation indicated high accuracy with standard error and coefficient of variation for GE: SEp = 6.6 Kkal/Kg, CV = 0.2 % . Calibration equation was obtained from PCR method by using absorbent data. The result of the validation indicated less accuracy with standard error and coefficient of variation for GE: SEp = 119.92 Kkal/Kg, CV = 4.16% . Keywords : Gross Energy, Near infrared Reflectant (NIR), fishmeal, Multivariate Linier Regression (MLR), Principal Component Regression (PCR)

scholarly journals Analisis Kadar Air dan Aroma Blending Kopi Arabika (Coffea arabica L) dan Robusta(Coffea canephora L) Selama Penyimpanan Dengan Principal Component Analisys (PCA)

2019 ◽  
Vol 6 (1) ◽  
pp. 23
Author(s):  
Surya Abdul Muttalib ◽  
Joko Nugraha WK ◽  
Nursigit Bintoro
Keyword(s):  
Coffea Arabica ◽  
Principal Component ◽  
Coffea Canephora ◽  
Electric Nose ◽  
Coffea Arabica L

Kopi merupakan komoditas pertanian yang menyumbang devisa terbesar bagi Indonesia dan menjadi komoditas perdagangan nomor dua di dunia. Ekspor kopi Indonesia masih terbatas pada kopi kering gelondongan, belum diolah menjadi barang jadi berupa kopi bubuk. Proses pengolahan menjadi kopi bubuk melalui serangkaian proses penyangraian yang didalamnya terjadi proses fisik dan kimia yang sangat komplek yang mempengaruhi cita rasa dan aroma. Terdapat dua jenis kopi yang berkembang di Indonesia yakni Kopi Arabika dan Robusta dengan karakteristik yang berbeda. Arabika memiliki rasa yang kuat sedangkat robusta memiliki kelebihan dari segi aroma. Jika kedua jenis kopi ini dipadukan maka akan menghasilkan cita rasa dan aroma yang kuat. Penelitian ini bertujuan untuk mengidentifikasi kadar air dan aroma blending kopi arabika dan robusta menggunakan Principal Component Analisys (PCA). PCA pada dasarnya bertujuan untuk menyederhanakan variabel yang diamati dengan cara menyusutkan (mereduksi) dimensinya. Hal ini dilakukan dengan cara menghilangkan korelasi diantara variabel bebas melalui transformasi variabel bebas asal ke variabel baru yang tidak berkorelasi.Identifikasi Aroma blending kopi Arabika dan Robusta dilakukan menggunakan empat buah sensor aroma (electric Nose) yang dipasang secara bersamaan yakni sensor TGS822, TGS825, TGS826 dan TGS2602. Hasil analisis menujukkan PCA mampu mereduksi data dan mengklasifikasi kopi sesuai input kadar air dan aroma selama penyimpanan.

Comprehensive Evaluation of Urban Land Use in Wuhan City

2014 ◽  
Vol 1073-1076 ◽  
pp. 1401-1406
Author(s):  
Zheng Xiong ◽  
Bing Tan ◽  
Cheng Shun Song
Keyword(s):  
Land Use ◽  
Principal Component ◽  
Quantitative Model ◽  
Economic Benefits ◽  
Urban Land Use ◽  
Environmental Benefits ◽  
Environmental Benefit ◽  
Land Utilization ◽  
Ecological Civilization ◽  
Wuhan City

At present, that is the inevitable requirement of sustainable development and the construction of ecological civilization society, to keep comprehensive land use benefits increasing. Based on the relevant research, combined with the Wuhan city land utilization state and the status of land use, this paper establish two kinds of index system which are socio-economic benefit and eco-environmental benefit, in the balance of comprehensive benefit of land output angle. And this paper also uses the principal component analysis to analyze the land use socio-economic benefits and eco-environmental benefits of Wuhan city, with quantitative model. The result shows that: during the period of 1996~2010, the socio-economic benefits and eco-environmental benefits of Wuhan city land use are on the rise, but the fluctuation characteristics are quite different. At the end, this paper put forward some policy proposals to promote the development sustainable utilization of land resources and to realize the best benefit of Wuhan City land-use in the field of technique, management and utilization.

SISTEMA DE PRODUCCIÓN DE CAFÉ (Coffea arabica L.) EN LA COMUNIDAD DEL CERRO CUATE, ILIATENCO, GUERRERO

2018 ◽  
Vol 11 (10) ◽  
Author(s):  
A. Delgado-Alvarado
Keyword(s):  
Coffea Arabica ◽  
El Sistema ◽  
Coffea Arabica L

Objetivo: Analizar el proceso de producción y comercialización de café en la comunidad del Cerro Cuate, Iliatenco, en la región de la Montaña de Guerrero, México.Diseño/Metodología/aproximación: el trabajo se realizó por; 1) investigación documental), 2) selección del área de estudio, 3) Entrevista estructurada con preguntas abiertas a 22 cafeticultores, soportada con la técnica de encuesta seccional y la herramienta de cédulas de entrevistas, y 4) análisis de la información. El tamaño de muestra se definió por el método de muestreo por conveniencia, y la selección de las unidades de análisis por la técnica bola de nieve. Resultados: El sistema de producción de café que predominó fue el sistema rústico de montaña, intercalado con plátano y frutales. La máxima productividad de las plantaciones se alcanza de 5.5 a 7.5años de edad, la renovación de plantas la hacen a los 12 años. El rendimiento de café fue de 3.7 kg por planta por año. La producción del café la realizan principalmente hombres (77.3%), entre 56 y 70años de edad. La venta se realiza en la presentación de café capulín a granel a intermediarios, a la ARIC, a CAFECO, a la Unión de Ejidos y a la Organización Mixtrui.Limitaciones del estudio/implicaciones: Se da una propuesta de mejora para favorecer el proceso de producción, beneficio y comercialización del café.Hallazgos/conclusiones: Coffea arabica es el principal café que se cultiva, con las variedades Typica, Caturra, Mundo Novo, Garnica y Bourbón. Los factores que limitan su producción y calidad son faltade planeación en manejo del cultivo y no contar con asesoría técnica.

Deposição da calda de pulverização em diferentes volumes vegetativos de Coffea arabica L.

2017 ◽  
Vol 12 (1) ◽  
pp. 69 ◽  
Author(s):  
Felipe Santinato ◽  
Renato Adriane Alves Ruas ◽  
Carlos Diego Silva ◽  
Rouverson Pereira Da Silva ◽  
Victor Afonso Reis Gonçalves ◽  
...  
Keyword(s):  
Coffea Arabica ◽  
Para Determinar ◽  
Coffea Arabica L

A disposição dos ramos e sobreposição das folhas em plantas de café dificultam a penetração da calda pulverizada. Portanto, para determinar o volume de calda adequado, é importante verificar o estado de enfolhamento da lavoura antes da aplicação. Objetivou-se com este trabalho, avaliar a deposição de caldas de pulverização em lavouras de café aplicadas em diferentes volumes vegetativos. Os tratamentos foram dispostos seguindo esquema de parcelas subdivididas em cada volume vegetativo (5.000; 7.500; 10.000 e 17.500 m<sup>3</sup> ha<sup>-1</sup>). Sendo as parcelas cinco volumes de calda (150, 300, 450, 600 e 750 L ha<sup>-1</sup>) e as subparcelas três posições no dossel do cafeeiro (terço superior, médio e inferior) com quatro repetições. Nos quatro volumes vegetativos estudados, não ocorreu interação significativa (p&gt;0,05) entre o volume aplicado e os diferentes volumes vegetativos. Porém, os volumes vegetativos de 5.000,0 e 17.500,0 m<sup>3</sup> ha<sup>-1</sup> a deposição foi crescente com aumento das vazões, o que pode ser atribuído a densidade foliar. Não foi verificada diferença estatística (p&gt; 0,05), entre as médias de deposição nos diferentes terços (alturas) no dossel das plantas de café, nos volumes vegetativos 5.000,0 m<sup>3 </sup>ha<sup>-1</sup>, 10.000,0 m<sup>3 </sup>ha<sup>-1</sup> e 17.500,0 m<sup>3 </sup>ha<sup>-1</sup>. Contudo, no volume de 7.500,0 m<sup>3 </sup>ha<sup>-1</sup> houve maior deposição no terço mediano em relação ao terço inferior. A deposição é maior à medida que aumenta o volume de calda aplicado. Em plantas com menor densidade foliar, há incremento na deposição. A deposição é maior no terço mediano em relação ao terço inferior.

Pengelolaan Pemangkasan Tanaman Kopi Arabika (Coffea arabica L.) di Kebun Blawan, Bondowoso, Jawa Timur

2016 ◽  
Vol 4 (3) ◽  
pp. 266
Author(s):  
Vinsensia Febrina Sianturi ◽  
Ade Wachjar
Keyword(s):  
Coffea Arabica ◽  
Coffea Arabica L

<p><em>Kopi merupakan salah satu komoditas perkebunan yang memiliki nilai ekonomi yang cukup tinggi</em><em>. </em><em>Kegiatan magang bertujuan mempelajari teknik budidaya</em><em> </em><em>tanaman</em><em> </em><em>dan</em><em> p</em><em>engelolaan</em><em> </em><em>perkebunan kopi, mempelajari dan menganalisis permasalahan yang dihadapi di lapangan mengenai pengelolaan pemangkasan serta solusi mengatasinya.</em><em> P</em><em>emangkasan </em><em>bertujuan </em><em>agar pohon tetap rendah sehingga mudah perawatannya, </em><em>dan </em><em>membentuk cabang-cabang produksi yang baru.</em><em> </em><em>Kegiatan magang dilaksanakan di Kebun Blawan, Bondowoso, Jawa Timur</em><em>,</em><em> mulai bulan Februari sampai dengan Juni 2014.</em><em> </em><em>Pengumpulan data </em><em>primer diperoleh melalui </em><em>pengamatan dan praktik kerja secara langsung meliputi kegiatan pemeliharaan tanaman yaitu pemangkasan lepas panen (pengamatan cabang-cabang tanaman, tinggi tanaman, jumlah tunas yang tumbuh)</em><em>, sedangkan data sekunder </em><em>diperoleh melalui </em><em>laporan manajemen perusahaan. </em><em>A</em><em>nalisis </em><em>data </em><em>yang dilakukan secara</em><em> deskriptif, rata-rata dan persentase</em><em>. Pemangkasan yang dilakukan</em><em> </em><em>termasuk dalam kategori pemangkasan ringan.</em><em> Tanaman kopi </em><em>yang memiliki kondisi cabang yang merata dan seimbang sangat mempengaruhi </em><em>hasil </em><em>taksasi</em><em> produksi</em><em>.</em><em> Banyak cabang harus dipangkas karena cabang-cabang yang sudah tua dan terserang penyakit. Setelah melakukan pemangkasan, tanaman menghasilkan tunas-tunas baru</em><em>.</em><em></em></p>

Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Khairunnisa Khairunnisa ◽  
Rizka Pitri ◽  
Victor P Butar-Butar ◽  
Agus M Soleh
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Principal Component Regression ◽  
Circulation Model ◽  
Principal Component ◽  
Meteorological Station ◽  
Grid Size ◽  
Partial Least Square ◽  
Least Square ◽  
Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

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