scholarly journals Transformasi Attenuated Total Reflectance Untuk Prediksi Vitamin C Pada Buah Mangga Arumanis (Mangifera indica)

2019 ◽  
Vol 4 (3) ◽  
pp. 75-84
Author(s):  
Muslem Muslem ◽  
Sri Purnama Sari ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Vitamin C ◽  
Near Infrared ◽  
Mangifera Indica ◽  
Principal Component Regression ◽  
Principal Component ◽  
Attenuated Total Reflectance ◽  
Total Reflectance ◽  
Ft Ir ◽  
Pcr Method

Abstrak, Parameter yang digunakan dalam penilaian mutu buah mangga antara lain ukuran atau berat, kekerasan, tingkat ketuaan serta bebas dari cacat. Kekerasan pada buah mangga merupakan fungsi dari tingkat kematangan, sedangkan kematangan berhubungan dengan tingkat ketuaan yang dapat diduga melalui penampilan visual. Vitamin C merupakan vitamin yang larut dalam air dan esensial untuk biosintesis kolagen.pengukuran vitamin C pada buah mangga menggunkan metode tetrasi, dan penggunaan gelombang elektromaknetik seperti Near Infrared. Penelitian ini bertujuan untuk memprediksi kadar vitamin C dalam buah mangga menggunakan metode Spektrofotometri UV-Vis dan Iodimetri, serta membandingkan hasil dari kedua metode tersebut. Sampel yang diidentifikasi yaitu buah mangga yang sudah matang dengan menggunakan model transformasi Attenuated Total Reflectance dan menggunakan metode Principal Component Analysis (PCA) dan menggunakan metode Principal Component Regression  (PCR). Penelitian ini menggunakan buah mangga jenis Arumanis, yang berjumlah 30 sampel. Prediksi vitamin C dengan NIRS menggunakan alat FT-IR IPTEK T-1516. Pengolahan data menggunakan Unscramble software® X versi 10.5. Hasil penelitian menunjukkan prediksi vitamin C mangga dengan metode Principal Component Regression (PCR) menghasilkan sufficient performance dengan nilai RPD yang didapat yaitu 2,0083 (r) sebesar 0,8638 , (R2 ) sebesar 0,7463 dan (RMSEC) sebesar 5,1854 Transformation Of Attenuated Total Reflectance (ATR) Near Infrared for prediction of Vitamin C In Arumanis Mangoes (Mangifera Indica)Abstract. Parameters used in assessing the quality of mangoes are size or weight, hardness, age level and free from defects. Hardness in mangoes is a function of maturity level, while the maturity is related to the level of aging that can be predicted through visual appearance. Vitamin C is a water-soluble vitamin which is essential for collagen biosynthesis. The measurement of vitamin C in mangoes use tetration methods, and the using of electromagnetic waves such as Near Infrared. This study aims to predict vitamin C contains in mango fruit using the UV-Vis and Iodymetry Spectrophotometry method, and comparing the results of the two methods. The samples identified were mature mangoes using the attenuated total reflectance transformation model and using the Principal Component Analysis (PCA) method also using the Principal Component Regression (PCR) method. This study used Arumanis mangoes, which amounted to 30 samples. Prediction of vitamin C with NIRS using the FT-IR IPTEK T-1516. Data processing use the Unscramble software® X 10.5 version. The results showed that the prediction of vitamin C mango using the Principal Component Regression (PCR) method resulted in sufficient performance with the obtained RPD value of  2,0083, (r) of 0,8638, (R2) of 0,7463 and (RMSEC) of 5,1854.

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

scholarly journals Pengembangan Metode Pengujian Keaslian Beras Aceh Menggunakan Nirs Dengan Metode PCA

2019 ◽  
Vol 4 (1) ◽  
pp. 578-587
Author(s):  
Masyitah Masyitah ◽  
Syahrul Syahrul ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Principal Component Analysis ◽  
Protein Content ◽  
Near Infrared ◽  
Scatter Correction ◽  
Principal Component ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Ft Ir

Abstrak. Tujuan dari penelitian ini adalah membangun model pendugaan untuk menilai keaslian beras Aceh berdasarkan spektrum NIRS yang dihasilkan. Pendeteksian keaslian beras Aceh secara cepat dan efesien dapat diwujudkan melalui pengembangan teknologi Near Infrared Reflectance Spectroscopy (NIRS). Penelitian ini menggunakan beras varietas Sigupai (Aceh Barat Daya), varietas  Sanbay (Simeulue) dan varietas Ciherang. Jumlah sampel yang digunakan pada penelitian ini adalah 45 sampel. Pengukuran spektrum beras menggunakan Self developed FT-IR IPTEK T-1516. Klasifikasi data spektrum beras menggunakan Principal Component Analysis (PCA) dengan dua  pretreatment yaitu De-trending dan Multiplicative Scatter Correction. Hasil penelitian ini diperoleh yaitu: Spektrum NIRS beras menunjukkan keberadaan kandungan lemak pada panjang gelombang 2355 nm - 2462 nm. Kandungan karbohidrat pada panjang gelombang 2256 nm - 2321 nm.  Kandungan protein pada panjang gelombang 2056 nm - 2166 nm. Kandungan kadar air pada panjang gelombang 1910 nm-1980 nm dan panjag gelombang 1411 nm - 1492 nm menunjukkan kandungan protein dan kadar air. NIRS dengan metode PCA mampu membedakan pencampuran beras Sigupai dengan beras Ciherang dimana pembedaan terbaik terjadi dalam bentuk dua macam pengelompokan yaitu beras  Sigupai ≥ 75 dan beras Sigupai ≤50 dan pretreatment de-trending merupakan pretreatment terbaik dalam mengklasifikasi beras Aceh (Sigupai dan Sanbay) dengan beras Nasional (Ciherang).Development of Methods for Testing the Authenticity of Aceh Rice Using NIRS with the PCA MethodAbstract. The purpose of this study is to develop a prediction model to assess the authenticity of Aceh rice based on the NIRS spectrum produced. The detection of the authenticity of Aceh rice quickly and efficiently can be realized through technological development Near Infrared Reflectance Spectroscopy (NIRS). This study uses Sigupai rice varieties (Aceh Barat Daya), Sanbay (Simeulue) and Ciherang. The number of samples used in this study was 45 samples. Measurement of rice spectrum  using Self developed FT-IR IPTEK T-1516. Rice spectrum data classification uses the Principal Component Analysis (PCA) with two pretreatments, namely De-trending and Multiplicative Scatter Correction. The results of this study were obtained: NIRS spectrum of rice showed the presence of fat content at a wavelength of 2355 nm - 2462 nm. Carbohydrate content at wavelength 2256 nm - 2321 nm. Protein content at wavelength 2056 nm - 2166 nm. The content of water content at a wavelength of 1910 nm-1980 nm and wave length of 1411 nm - 1492 nm shows the protein content and water content. NIRS with the PCA method was able to distinguish the mixing of Sigupai rice from Ciherang rice where the best differentiation occurred in the form of two types of grouping namely Sigupai rice ≥ 75 and Sigupai rice ≤ 50 and de-trending pretreatment was the best pretreatment in classifying Aceh rice (Sigupai and Sanbay) with National rice (Ciherang).

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 Measurements of Urea and Glucose in Aqueous Solutions with Dual-Beam Near-Infrared Fourier Transform Spectroscopy

2002 ◽  
Vol 56 (12) ◽  
pp. 1593-1599 ◽  
Author(s):  
Peter Snoer Jensen ◽  
Jimmy Bak
Keyword(s):  
Aqueous Solutions ◽  
Near Infrared ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Single Beam ◽  
Dual Beam ◽  
Calibration Models ◽  
Ft Ir ◽  
Beam Technique

This study investigates the use of a dual-beam, optical null, FT-IR spectrometer to measure trace organic components in aqueous solutions in the combination band region 5000–4000 cm−1. The spectrometer may be used for both single- and dual-beam measurements, thereby facilitating comparison of these two modes of operation. The concentrations of aqueous solutions of urea and glucose in the ranges 0–40 mg/dL and 0–250 mg/dL, respectively, were determined by principal component regression using both modes. The dual-beam technique eliminated instrumental variations present in the single-beam measurements that must be taken into account when quantifying trace components from single-beam spectra. The data obtained with the dual-beam technique resulted in more stable calibration models based on principal component regression. These calibration models need fewer factors and yield lower prediction errors than those based on traditional single-beam data.

scholarly journals Klasifikasi Cepat dan Non-Destruktif Bubuk Biji Kakao Berdasarkan Tingkat Fermentasi Menggunakan Near Infrared Reflectance Spectroscopy

2016 ◽  
Vol 1 (1) ◽  
pp. 1046-1051
Author(s):  
Rita Zahara ◽  
Agus Arip Munawar ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Principal Component Analysis ◽  
Method Development ◽  
Near Infrared ◽  
Principal Component ◽  
Component Analysis ◽  
Accurate Estimate ◽  
Peak Performance ◽  
Cocoa Beans ◽  
Near Infrared Reflectance ◽  
Ft Ir

Abstrak.  Kakao merupakan salah satu komoditas perkebunan andalan di Provinsi Aceh. Hampir keseluruhan areal perkebunan kakao adalah perkebunan rakyat. Biji kakao dari perkebunan rakyat cenderung masih bermutu rendah yang disebabkan oleh pengolahan pascapanen yang kurang baik seperti masalah fermentasi biji kakao. Penjaminan mutu biji kakao melalui pengembangan metode pendugaan mutu yang cepat dan akurat menjadi kata kunci, peningkatan daya saing ekspor biji kakao Indonesia ditingkat dunia. Sampel biji kakao mentah varietas lindak. Sampel dibuat dalam  bentuk bubuk sebanyak 44 sample (10 gr per sampel) dengan penggunaan alat NIRS FT-IR IPTEK T-1516. Klasifikasi data spektrum menggunakan Principal Component Analysis (PCA) dengan tiga  pretreatment spektrum yaitu: de-trending, mean normalization dan standart normal variate. Hasil penelitian diperoleh yaitu Panjang gelombang 1910-2170 nm merupakan, panjang gelombang yang relevan untuk menduga procyanidin pada bubuk biji kakao. Penambahan pretreatment mampu memperbaiki tampilan puncak penanda procyanidin pada spektrum bubuk biji kakao, PCA tanpa pretreatment tidak mampu mengklasifikasi bubuk biji kakao berdasarkan tingkat fermentasi sedangkan dengan bantuan pretreatment mampu mengklasifikasi dengan tingkat keberhasilan diatas 85%, Pretreatment terbaik dalam meningkatkan kinerja PCA dalam klasifikasi bubuk biji kakao berdasarkan tingkat fermentasi yaitu SNV dengan tingkat keberhasilan  97,72 %.Abstract. Cocoa is one Aceh’s most  samples were beans plantation commodities. Most of cocoa belong to the small holder estates. Unfortunately cocoa beans owned by the locals, tend to have low quality as a result of poor postharvest management, such as a cocoa beans fermentation related issue. The assurance of cocoa beans quality through a rapid and accurate estimate method development will be a key in the efforts to promote global export competitions of Indonesia’s cocoa beans. The following sample is raw cocoa beans of lindak variety. Samples were made in the form of cocoa powder with a total of 44 samples (10 gr per samples) using an instrument of NIRS FT-IR IPTEK T-1516. The spectrum data classification uses the Principal Component Analysis  (PCA) three spectrum pretreatment, namely de-trending , mean normalization and standard normal variate. The result show that wavelength range of1910-2170 nm were considered as relevant wavelengths  to predict procyanidin on cocoa seed powder. The addition of the pretreatment will fix procyanidin peak performance on the cocoa beans powder based on the fermentation level of success over 85%. The best pretreatment to increase the PCA permonce classifying the cocoa beans powder according to fermentation level is SNV and the level of success is 97,72%.Keywords: 

scholarly journals Authenticity Determination of Greek-Cretan Mono-Varietal White and Red Wines Based on their Phenolic Content Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy and Chemometrics

2016 ◽  
Vol 4 (Special-Issue-October) ◽  
pp. 54-62 ◽  
Author(s):  
Marianthi Basalekou ◽  
Argiro Stratidaki ◽  
Christos Pappas ◽  
Petros Tarantilis ◽  
Yorgos Kotseridis ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Phenolic Content ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Critical Issue ◽  
Attenuated Total Reflectance ◽  
Fast Method ◽  
Total Reflectance ◽  
Ft Ir ◽  
Grape Varieties

The assessment of wine authenticity is a critical issue that has gained a lot of interest internationally. A simple and fast method was developed for the varietal classification of Greek wines according to grape cultivar using attenuated total reflectance (ATR) Fourier transform infrared (FT-IR) spectroscopy. The phenolic content and color parameters of wine samples (n=88) made by two white (Vilana and Dafni) and two red (Kotsifali and Mandilari) grape varieties were measured and their FT-IR spectra were recorded. Principal Component Analysis (PCA) of their chemical parameters indicated that the wines can be discriminated based on their different phenolic content. The spectroscopic analysis combined with discriminant analysis of the fingerprint region of the spectra (1800-900 cm-1) resulted in complete discrimination of the grape varieties. The proposed method in comparison with the rest analytical methods is simpler, less time consuming, more economical and requires reduced quantities of chemical reagents prior to analysis.

scholarly journals Pengembangan Metode Klasifikasi Biji Kopi Sangrai Arabika Gayo dan Robusta Gayo dengan Metode PCA (Principal Component Analysis) Berdasarkan Pengolahannya

2020 ◽  
Vol 4 (4) ◽  
pp. 562-571
Author(s):  
Cut Faradilla Zha Zha Maura ◽  
Rahmat Fadhil ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Principal Component Analysis ◽  
Near Infrared ◽  
Principal Component ◽  
Component Analysis ◽  
Roasted Coffee ◽  
Near Infrared Reflectance ◽  
Coffee Beans ◽  
Medium Level ◽  
Pca Method ◽  
Ft Ir

Abstrak. Tanaman kopi merupakan suatu tanaman yang dapat meningkatkan sumber devisa negara lewat ekspor biji mentah maupun olahan dari biji kopi. Pengolahan kopi yang berbeda maka akan menghasilkan mutu kopi yang berbeda juga, semakin bagus prosesnya maka akan semakin tinggi mutu dan harga dari kopi. Pendeteksian perbedaan proses pengolahannya yang cepat dan efisien dapat diwujudkan dengan teknologi Near Infrared Reflectance Spectroscopy (NIRS). Tujuan yang ingin dicapai dalam penelitian ini adalah untuk membangun metode klasifikasi kopi arabika dan robusta Gayo menggunakan pengolahan full wash dan semi wash dalam bentuk biji kopi yang telah disangrai. Kopi disangrai pada tingkat medium (200-205ºC) dalam waktu 16 menit. Akuisisi spektrum kopi menggunakan Self developed FT-IR IPTEK T-1516. Selanjutnya data spektrum diolah menggunakan unscrambler software® X version 10.1 dengan metode PCA (Principal Component Analysis). Hasil penelitian menunjukkan bahwa NIRS dengan metode PCA mampu mengklasifikasikan biji kopi sangrai berdasarkan pengolahannya yaitu Semi wash dan Full wash. Melalui studi ini ditemukan juga selang panjang gelombang yang dapat mengidentifikasikan kualitas kopi sehingga dapat digunakan untuk penelitian selanjutnya dalam pengembangan model identifikasi kualitas kopi.Development of Classification Methods for Gayo Roasted Arabica Coffee and Gayo Robusta by PCA Method (Principal Component Analysis)Abstract. Coffee crop is a plant that can increase the country's foreign exchange source through the export of raw beans and processed coffee beans. Different coffee processing will produce different coffee quality as well, the better the process then the quality and price of the coffee is more higher. Therefore, alternative rapid and efficiently method is needed to detect differences in the processing of coffee. Near Infrared Spectroscopy (NIRS) can be considered to be used due to its advantages. The main objective of this study is to build classification method of Gayo Arabica and Robusta coffee using fullwash and semiwash processing in form of roasted. Coffee is roasted at a medium level (200-205ºC) within 16 minutes. Acquisition of the coffee spectrum using Self-developed FT-IR IPTEK T-1516. Furthermore, the spectrum data is processed using unscrambler software ® X version 10.1 with the PCA (Principal Component Analysis) method. The results showed that NIRS with the PCA method was able to classify roasted coffee beans based on its processing, namely Semi wash and Full wash. Through this study, it was also found that wavelength intervals can identify coffee quality so that it can be used for further research in developing coffee quality identification models

Attenuated total reflectance/Fourier transform infrared (ATR/FTIR) mapping coupled with principal component analysis for the study of in vitro degradation of porous polylactide/hydroxyapatite composite material

2014 ◽  
Vol 6 (15) ◽  
pp. 5590-5595 ◽  
Author(s):  
Nan Jing ◽  
Xiaoting Jiang ◽  
Qian Wang ◽  
Yongjiao Tang ◽  
Pudun Zhang
Keyword(s):  
Principal Component Analysis ◽  
Composite Material ◽  
Fourier Transform ◽  
Principal Component ◽  
Component Analysis ◽  
Attenuated Total Reflectance ◽  
In Vitro Degradation ◽  
Total Reflectance ◽  
Hydroxyapatite Composite

We proposes coupling ATR/FTIR mapping with principal component analysis for the biomimetic degradation of poly(l-lactide)/hydroxyapatite composite material.

scholarly journals Analysis of ‘legal high’ substances and common adulterants using handheld spectroscopic techniques

2015 ◽  
Vol 7 (2) ◽  
pp. 736-746 ◽  
Author(s):  
S. Assi ◽  
A. Guirguis ◽  
S. Halsey ◽  
S. Fergus ◽  
J. L. Stair
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Near Infrared ◽  
Fourier Transform Infrared ◽  
Attenuated Total Reflectance ◽  
Spectroscopic Techniques ◽  
Total Reflectance ◽  
Legal High ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Three handheld spectrometers, near-infrared (NIR), Raman and attenuated total reflectance Fourier transform-infrared (ATR-FT-IR) spectroscopy, were used for the identification of ‘legal high’ model mixtures and Internet products.

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