Investigation of a LOCAL Calibration Procedure for near Infrared Instruments

1997 ◽  
Vol 5 (4) ◽  
pp. 223-232 ◽  
Author(s):  
John S. Shenk ◽  
Mark O. Westerhaus ◽  
Paolo Berzaghi
Keyword(s):  
Near Infrared ◽  
Calibration Procedure ◽  
Data Transformations ◽  
Calibration Equation ◽  
Acid Detergent Fibre ◽  
Infrared Instruments ◽  
Speed And Accuracy ◽  
Local Procedure ◽  
Small Advantage ◽  
Corn Grain

A new procedure (LOCAL) for local calibrations is presented. LOCAL selects spectra from a library of samples and computes a PLS calibration equation for each constituent of the sample. This study evaluated the performances of LOCAL on the prediction of ground corn grain and haylage using several different combinations of data transformations, wavelength segment reduction, number of PLS factors and samples used in calibration. LOCAL resulted in lower SEP values for all the constituents of corn and dry matter of haylage with improvements ranging between 6 to 13%. Global calibrations had only a small advantage over LOCAL (1–2%) in the prediction of acid detergent fibre and crude protein in haylage. The two most important variables controlling the accuracy of predictions were number of samples in the calibration and number of PLS factors in the solution. Best results were obtained using 150 to 225 samples and more than 20 PLS factors per calibration equation. The speed of the LOCAL procedure is 0.5–2 s per sample on a 90 MHz computer. With this speed and accuracy, LOCAL is now available for real-time routine operation on a Windows platform.

A Simple Testing Procedure for near Infrared Instruments

1998 ◽  
Vol 6 (A) ◽  
pp. A163-A170 ◽  
Author(s):  
B. Barabás
Keyword(s):  
Error Compensation ◽  
Near Infrared ◽  
Testing Procedure ◽  
Wheat Protein ◽  
Calibration Equation ◽  
Minimum Number ◽  
Mean Square Difference ◽  
Infrared Instruments ◽  
Protein Measurement

The testing and adjusting procedure of near infrared (NIR) spectrophotometers is based on the measurement of some standards and, if necessary, on the adjustment of the constants in the calibration equation. For this work some use few standards, whereas others use 20 or more. This work was aimed to determine the range of error compensation and the minimum number of standards required. The experiments were applied to wheat protein measurement using two scanning spectrophotometers. The errors in the NIR measurements were characterised as bias, skew, error derived from skew ( Eskew) and standard error of difference corrected for bias and skew ( SEDc) parameters and supposed that errors derived from the change in the wavelength or reflectance of the instrument. The confidence intervals of bias and skew, derived from duplicate measurements of various numbers of wheat standards, were used to determine the minimum number of standards required. The range of error compensation was defined with those bias values, where SEDc was smaller, than an acceptable limit. The range of compensation corresponded to a bias value of ± 8 g kg−1 for wheat protein measurements. The detection of error of measurements required 4 wheat standards. The elimination of errors of bias and skew required 9 standards within the above limits. The developed procedure was tested in case of real instrument error. Diminishing a bias from 5.2 g kg−1 to 0.7 g kg−1 and the root mean square difference ( RMSD) to an acceptable level required the use of 9 standards, similar to the model experiment. The simplicity and rapidity (about 10 min) of the procedure enabled the routine test of NIR instruments. The range of error compensation and the number of standards referred to wheat protein. The simple modelling procedure proved also suitable for the determination of these values for other components and under other measuring conditions.

Investigating the total antioxidant capacity of gluten-free grains with miniaturized near-infrared spectrometer

NIR news ◽  
2019 ◽  
Vol 30 (5-6) ◽  
pp. 35-38
Author(s):  
Verena Wiedemair ◽  
Christian Wolfgang Huck
Keyword(s):  
Antioxidant Capacity ◽  
Total Antioxidant Capacity ◽  
High Performance ◽  
Near Infrared ◽  
Least Squares Regression ◽  
Test Set ◽  
Total Antioxidant ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Infrared Instruments

The use of ever smaller near-infrared instruments is becoming more and more prevalent, since they are cheaper, more versatile and often advertised as high-performance spectrometer. The last claim is rarely verified by independent researchers, which is why the presented work evaluates the performance of three hand-held spectrometers in comparison to a benchtop instrument. Seventy-seven samples comprising buckwheat, millet and oat were investigated for their total antioxidant capacity using Folin–Ciocalteu and near-infrared spectroscopy. Partial least squares regression models were established using cross- and test set validation. Results showed that all instruments were able to predict total antioxidant capacity to some extent. The coefficients of determinations ranged from 0.823 to 0.951 for cross-validated and from 0.849 to 0.952 for test set validated models. Errors for cross-validated models ranged from 1.11 to 2.08 mgGAE/g and for test set validated models from 1.02 to 1.86 mgGAE/g.

scholarly journals Features of сalibration еequations for IR scanners in determining the amino acid composition of soy proteins

2020 ◽  
Author(s):  
С.Е. НИЗКИЙ ◽  
Г.А. КОДИРОВА ◽  
Г.В. КУБАНКОВА
Keyword(s):  
Amino Acids ◽  
Liquid Chromatography ◽  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
High Performance ◽  
Near Infrared ◽  
Soybean Proteins ◽  
Calibration Equation ◽  
Calibration Equations

Из 20 аминокислот, входящих в состав растительных белков, 17 лучше всего определяются с помощью высокоэффективной жидкостной хроматографии. Но эта технология затратна по времени, в том числе из-за подготовки проб, что делает ее малопригодной при проведении массовых анализов, например при оценке селекционного материала. В этом случае наиболее приемлемы технологии, основанные на сканировании в ближнем инфракрасном диапазоне излучения. Несмотря на то что ИК-сканеры способны по одному калибровочному уравнению выявлять большое количество компонентов, необходима постоянная коррекция при определении состава аминокислот и приведении его в процентное соотношение. В статье рассматриваются варианты создания калибровочных уравнений для расчета аминокислотного состава белков сои с помощью компьютерных программ (Nir 42, ISI), обеспечивающих работу ИК-сканеров типа NIR-4250 или FOSS NIRSystem 5000. Установлено, что при создании калибровочных уравнений содержание каждой аминокислоты наиболее корректно выражать в абсолютных единицах (г на 100 г белка), а не относительных (%). 17 of the 20 amino acids, included in the composition of plant proteins, are most effectively determined using liquid chromatography. The technology of high-performance liquid chromatography is to a certain extent costly in time, among other things because of sample preparation that makes it unsuitable for mass analysis, for example, when evaluating a breeding material. In this case, the technology based on scanning in the near infrared radiation band are the most acceptable. Despite the fact that IR scanners are able to determine a sufficiently large number of components on the basis of one calibration equation, a constant correction is required when determining the composition of amino acids and reducing it to a percentage ratio. The options for creating calibration equations for determining the amino acid composition of soybean proteins for computer programs (Nir 42, ISI), which provide the operation of IR scanners, such as NIR-4250 or FOSS NIRSystem 5000 are considered in the article. It was found that when creating calibration equations, it is most correct to set for each amino acid its mass content (g per 100 g of protein), and not the relative portion (in %).

Rapid evaluation of pasture quality for a critically endangered mammal, the northern hairy-nosed wombat (Lasiorhinus krefftii)

2002 ◽  
Vol 29 (1) ◽  
pp. 91 ◽  
Author(s):  
Andrew P. Woolnough ◽  
William J. Foley
Keyword(s):  
Large Scale ◽  
Nutritive Value ◽  
Near Infrared ◽  
Nitrogen Concentration ◽  
Water Soluble ◽  
Critically Endangered ◽  
Soluble Carbohydrates ◽  
Dry Matter Digestibility ◽  
Acid Detergent Fibre

Near-infrared spectroscopy (NIRS) was used to predict the nutritive value of forage species available to the critically endangered northern hairy-nosed wombat (Lasiorhinus krefftii). Nutritive attributes of the forage successfully estimated included total nitrogen concentration, fibre (including neutral detergent fibre, acid detergent fibre and acid lignin), organic matter, water soluble carbohydrates and in vitro dry matter digestibility. The reported results demonstrate the seasonal variability of the forage resource available to L. krefftii in its tropical savanna habitat. Multivariate modelling of the spectra enabled the nutritive value of forage samples to be estimated with coefficients of determination (r2) of 0.770–0.995 and standard errors of the cross-validation of 0.070–2.850 using a modified partial least-squares analysis technique. The standard error of the laboratory was 0.02–1.42. This study demonstrates that broad-based NIRS predictive equations can be used to predict the nutritive value of a number of plant types available to a herbivore over time. By using NIRS the analyst can rapidly analyse large numbers of samples with limited reduction of precision, thereby enabling large-scale ecological applications that may have previously been impeded by time and costs.

Application of near Infrared Spectroscopy On-Combine in Corn Grain Breeding

2005 ◽  
Vol 13 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Roland Welle ◽  
Willi Greten ◽  
Thomas Müller ◽  
Gary Weber ◽  
Hartwig Wehrmann
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Successful Implementation ◽  
Grain Moisture ◽  
Yield Determination ◽  
Corn Grain

Improving maize ( Zea mays L.) grain yield and agronomic properties are major goals for corn breeders in northern Europe. In order to facilitate field grain yield determination we measured corn grain moisture content with near infrared (NIR) spectroscopy directly on a harvesting machine. NIR spectroscopy, in combination with harvesting, significantly improved quality and speed of yield determination within the very narrow harvest time window. Moisture calibrations were developed with 2117 samples from the 2001 to 2003 crop seasons using six diode array spectrometers mounted on combines. These models were derived from databases containing spectra from all instruments. Spectrometer-specific calibrations cannot be used to predict samples measured on other instruments of the same type. Standard error of cross-validation ( SECV) and coefficient of determination ( R2) were 0.56 and 0.99%, respectively. Moisture standard errors of prediction ( SEPs) for the six instruments, using varying independent sample sets from the 2004 harvest, ranged between 0.59% and 0.99% with R2 values between 0.92 to 0.98. The six instruments produced the same dry matter predictions on a common sample set as indicated by high R2 and low biases among them, hence there was no need to apply specific standardisation algorithms. Moisture NIR spectroscopy determinations were significantly more precise than those obtained using the reference method. Analysis of variance revealed low least significant differences and high heritabilities. High precision and heritability demonstrate successful implementation of on-combine NIR spectroscopy for routine dry matter (yield) measurements.

scholarly journals Analysis of the Acid Detergent Fibre Content in Turnip Greens and Turnip Tops (Brassica rapa L. Subsp. rapa) by Means of Near-Infrared Reflectance

Foods ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 364 ◽  
Author(s):  
Sara Obregón-Cano ◽  
Rafael Moreno-Rojas ◽  
Ana María Jurado-Millán ◽  
María Elena Cartea-González ◽  
Antonio De Haro-Bailón
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
Mathematical Treatment ◽  
Second Derivative ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
First Derivative ◽  
Acid Detergent Fibre ◽  
Turnip Greens ◽  
Turnip Tops

Standard wet chemistry analytical techniques currently used to determine plant fibre constituents are costly, time-consuming and destructive. In this paper the potential of near-infrared reflectance spectroscopy (NIRS) to analyse the contents of acid detergent fibre (ADF) in turnip greens and turnip tops has been assessed. Three calibration equations were developed: in the equation without mathematical treatment the coefficient of determination (R2) was 0.91, in the first-derivative treatment equation R2 = 0.95 and in the second-derivative treatment R2 = 0.96. The estimation accuracy was based on RPD (the ratio between the standard deviation and the standard error of validation) and RER (the ratio between the range of ADF of the validation as a whole and the standard error of prediction) of the external validation. RPD and RER values were of 2.75 and 9.00 for the treatment without derivative, 3.41 and 11.79 with first-derivative, and 3.10 and 11.03 with second-derivative. With the acid detergent residue spectrum the wavelengths were identified and associated with the ADF contained in the sample. The results showed a great potential of NIRS for predicting ADF content in turnip greens and turnip tops.

Estimating fatty acid content and related nutritional indexes in ewe milk using different near infrared instruments

2020 ◽  
Vol 88 ◽  
pp. 103427
Author(s):  
Nieves Núñez-Sánchez ◽  
Gabriele Acuti ◽  
Raffaella Branciari ◽  
David Ranucci ◽  
Naceur Mohamed Haouet ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Acid Content ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Infrared Instruments

scholarly journals Fast prediction of quality parameters in whole seeds of oilseed rape (Brassica napus L.)

2011 ◽  
Vol 49 (No. 4) ◽  
pp. 141-145 ◽  
Author(s):  
V. Míka ◽  
P. Tillmann ◽  
R. Koprna ◽  
P. Nerušil ◽  
V. Kučera
Keyword(s):  
Prediction Accuracy ◽  
Near Infrared ◽  
Quality Parameters ◽  
Breeding Cycle ◽  
Brassica Napus L ◽  
Calibration Equation ◽  
Whole Seed ◽  
Fast Prediction ◽  
Short Time ◽  
Non Destructive

A calibration equation for NIRSystems 6500 instrument was derived at VSTE Jevíčko using the measurement of broad collection of Czech samples of winter rape, allowing sufficiently accurate prediction of content of dry matter (DM), crude protein (XP), crude fat (XL), glucosinolates (GSL), oleic and linoleic acids in an extremely short time. The prediction accuracy was verified on a validation file (n = 60). The coefficients of determinance (R2) were 0.83 for XP, 0.71 for XL, and 0.84 for GSL. The prediction accuracy according to the VSTE equation was compared to the prediction accuracy according to the VDLUFA calibration equation (Kassel, FRG) used in EU near infrared spectroscopy network. It was stated that the former was not distinctly worse. Non-destructive NIR-analysis of the whole seed also allows sowing selected seeds in the year of harvest and thus accelerates the breeding cycle.

scholarly journals Diffuse transmitted spectroscopy in conjunction with spectral peak averaging as a potential tool for noninvasive creatinine screening

2020 ◽  
Vol 13 (06) ◽  
pp. 2050028
Author(s):  
Zvi Hai Barnea (Burbea) ◽  
Shmuel Zimlichman ◽  
David Abookasis
Keyword(s):  
Kidney Function ◽  
Near Infrared ◽  
Muscle Metabolism ◽  
Peak Level ◽  
Calibration Procedure ◽  
Rapid Screening ◽  
Simple Method ◽  
Intensity Index ◽  
Screening Platform ◽  
Cr Concentration

Creatinine (Cr) is a biochemical waste molecule generated from muscle metabolism and primarily cleared from the bloodstream by the kidneys. If kidney function declines, Cr levels in the blood tend to increase. Therefore, Cr serves as an indicator of kidney function. In this work, we present a simple method for the rapid screening for impaired renal function based on the subject’s Cr concentration. In our setup, broadband white light is delivered to a finger clamp through a fiber-optic cable to illuminate the patient’s finger. The light is transmitted through the finger and collected by a second optical fiber coupled to a visible–near-infrared (VisNIR) spectrometer which covers the spectral range from 400[Formula: see text]nm to 1100[Formula: see text]nm. During the calibration process, the transmitted spectra acquired from 60 patients were measured. An average was calculated using the peak level of the transmitted, diffused intensity at three different wavelengths to create a “Cr intensity index”. Patients were divided into five groups according to their Cr concentration levels, ranging from 1[Formula: see text]mg/dL to 13[Formula: see text]mg/dL. Our observations indicated that each group featured a unique spectral fingerprint. Next, we tested the index on 20 patients not included in the calibration procedure (unknown samples). We were able to classify patients into groups according to their Cr level with moderate prediction accuracy ([Formula: see text]) and mean screening error of up to 16%. Future efforts will evaluate the accuracy of this approach with larger patient populations representing a broad range of Cr concentration. Still, this preliminary work is an essential step toward developing this useful noninvasive Cr screening platform using NIR light spectroscopy.

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