scholarly journals Improved prediction of protein content in wheat kernels with a fusion of scatter correction methods in NIR data modelling

2021 ◽  
Vol 203 ◽  
pp. 93-97
Author(s):  
Puneet Mishra ◽  
Santosh Lohumi
Keyword(s):  
Protein Content ◽  
Scatter Correction ◽  
Data Modelling ◽  
Wheat Kernels

COMPARATIVE ASSESSMENT OF VARIOUS METHODS OF PROTEIN CONTENT PREDICTION IN WHEAT KERNELS

2021 ◽  
pp. 22-27
Author(s):  
A.V. PASYNKOV ◽  
◽  
A.A. ZAVALIN ◽  
E.N. PASYNKOVA ◽  
V.L. ANDREEV ◽  
...  
Keyword(s):  
Protein Content ◽  
Comparative Assessment ◽  
Wheat Kernels

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).

A multispectral sorting device for isolating single wheat kernels with high protein content

2013 ◽  
Vol 7 (4) ◽  
pp. 149-157 ◽  
Author(s):  
Ron P. Haff ◽  
Tom C. Pearson ◽  
Elizabeth Maghirang
Keyword(s):  
Protein Content ◽  
High Protein ◽  
High Protein Content ◽  
Wheat Kernels

Detection of the Protein Content of Ningxia Tan Sheep Using Hyperspectral Reflectance Imaging

2014 ◽  
Vol 513-517 ◽  
pp. 4235-4238
Author(s):  
Song Lei Wang ◽  
Gui Shan Liu ◽  
Xue Fu Li ◽  
Rui Ming Luo
Keyword(s):  
Protein Content ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Mean Squared Error ◽  
Imaging Technique ◽  
Linear Regression Analysis ◽  
Scatter Correction ◽  
Squared Error ◽  
Tan Sheep ◽  
Well Correlation

Near-infrared (NIR) hyperspectral imaging technique (900-1700nm) was evaluated to predict the protein content of Tan sheep. This research adopted NIR hyperspectral imaging to get imaging information of 72 mutton samples, multiplicative scatter correction was used to spectral data preprocessing. The optimal wavelengths were obtained through linear-regression analysis, BP neural network combined with actual measured values were established the prediction model and verified this model. The results showed that the prediction effect of model was very well. Correlation coefficient (Rp) and root mean squared error of prediction (RMSEP) of the protein were 0.87 and 1.19. The results indicated that it is feasible to predict the protein content of Tan sheep for NIR hyperspectral imaging technique.

scholarly journals Protein content prediction in single wheat kernels using hyperspectral imaging

2018 ◽  
Vol 240 ◽  
pp. 32-42 ◽  
Author(s):  
Nicola Caporaso ◽  
Martin B. Whitworth ◽  
Ian D. Fisk
Keyword(s):  
Protein Content ◽  
Hyperspectral Imaging ◽  
Wheat Kernels

Protein Content of Wheat Kernels from Different Parts of the Spike 1

1966 ◽  
Vol 58 (6) ◽  
pp. 635-636 ◽  
Author(s):  
F. H. McNeal ◽  
D. J. Davis
Keyword(s):  
Protein Content ◽  
Wheat Kernels ◽  
Different Parts

scholarly journals EFFICIENCY OF RAW GLUTEN CONTENT PREDICTION IN WHEAT KERNELS

2019 ◽  
pp. 19-26
Author(s):  
A. V. Pasynkov ◽  
E. N. Pasynkova
Keyword(s):  
Experimental Data ◽  
Protein Content ◽  
Dry Matter ◽  
Kernel Weight ◽  
Climatic Conditions ◽  
Independent Data ◽  
Wheat Varieties ◽  
Climatic Zones ◽  
Gluten Content ◽  
Wheat Kernels

The conducted regression analysis allowed us to obtain the equation of multiple nonlinear regression, which reflects the dependence of the raw gluten content in wheat kernels (Y, %) on the protein content (X1 = Ntotal · 5.7, %) and 1000-kernel weight (X2, g): Y = -41.928 + 0.081Х1 2 + 2.548Х2 - 0.028Х2 2. In the presented equation, all quality indicators are given at 12% humidity. If protein content and/or 1000-kernel weight are determined for absolutely dry matter (a.d.m.), the developed equation to predict raw gluten content in wheat kernels is recalculated with the use of coefficients of 0.88 and 1.136, respectively. The purpose of the research is to identify the effectiveness of raw gluten content prediction in wheat kernels using the developed regression equation, which reflects its dependence on protein content and 1000-kernel weight. There have been developed and presented an algorithm and results of testing the predictive capabilities of the equation based on independent data. That is, using experimental data on protein and gluten content, and 1000-kernel weight obtained by other researchers in the experiments with different wheat varieties and in other soil and climatic conditions. The summarized experimental data of 124 Soviet, Russian and foreign literary references with a total number of observations n = 2485 on more than a hundred wheat varieties grown from 1959 to 2019 in various soil and climatic zones of the USSR, Russia and abroad have shown that the number of values beyond the limits regulated by GOST R 54478 - 2011 (± 2%) was 462 or 18.6% of the total number of observations. The accuracy of the raw gluten content prediction in wheat kernels was 81.4%. The developed equation can be used to predict raw gluten content in kernels of various winter and spring soft and durum wheat varieties.

Protein content of 5 algae from Persian gulf and Arabian sea

Planta Medica ◽  
2010 ◽  
Vol 76 (12) ◽  
Author(s):  
N Ebrahimi ◽  
M Moein ◽  
S Moein
Keyword(s):  
Protein Content ◽  
Persian Gulf ◽  
Arabian Sea
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