Factors affecting the prediction of organic matter Digestibility of grass silage by near infrared reflectance spectroscopy

Author(s):  
E. R. Deaville ◽  
D. L Givens

Earlier studies (Barber et al., 1990) showed the superiority of near infrared reflectance spectroscopy (NIRS) for predicting the organic matter digestibility (OMD) in vivo of grass silage over fibre and in vitro procedures. However, during routine application occasional erroneous values were predicted for which there were no obvious reasons. Baker and Barnes (1990) reported that the likely sources of the problems contributing to the errors were instrumental and environmental noise, sample particle size effects and variable moisture content of the samples. These authors also reported that standard normal variate - detrend (SNV-D) scatter correction procedure of Barnes et al. (1989) could be used to reduce the effects of particle size variation and they also emphasised the need to test NIRS calibrations for repeatability. The purpose of the present work was to evaluate the use of the SNV-D scatter correction procedure, the techniques for reducing the sensitivity of calibrations to residual moisture and methods to improve the repeatability of the predicted OMD in vivo values of grass silage. In addition, a further objective was to compare three calibration methods, namely modified stepwise regression (MSR), modified partial least squares (MPLS) and principal component analysis (PCA).

Author(s):  
C W Baker ◽  
D I Givens

Earlier studies showed the superiority of NIRS, over fibre measurements, for predicting organic matter digestibility (OMD) in vivo of grass silages. (Barber et al 1990). This system was put into routine use in ADAS in 1989 and after some initial doubts, due to the wider range of the predicted data seen, is now accepted as the best system available for routine use. However, occasional erroneous values were predicted for which there were no obvious explanations, and which resulted in occasional relatively poor repeatability. In common with all NIRS applications it was likely that the sources of the problems contributing to the errors were i) instrumental and environmental noise, ii) sample particle size effects and iii) variable moisture content of the samples. A course of investigation was undertaken with the objective of determining the effects of these on the predicted data.


2019 ◽  
Vol 4 (1) ◽  
pp. 578-587
Author(s):  
Masyitah Masyitah ◽  
Syahrul Syahrul ◽  
Zulfahrizal Zulfahrizal

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).


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