Comparison of Commercial near Infrared Transmittance and Reflectance Instruments for Analysis of Whole Grains and Seeds

Near infrared transmittance and reflectance instruments were compared for the determination of protein, oil, moisture and some other constituents and parameters in several grains and seeds of commerce. Both approaches were comparable in accuracy and reproducibility. The importance of optimisation of the wavelength range in whole grain analysis is demonstrated for measurements in both the NIR and visible/NlR wavelength ranges. The RPD statistic, which relates the standard error of prediction to the standard deviation of the original data, is illustrated as a method for the evaluation of calibrations. The concept of monitoring the accuracy of analysis using whole grain calibrations with ground grain calibrations is introduced.

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Non-Destructive Determination of Sugar Content in Satsuma Mandarin Fruit by near Infrared Transmittance Spectroscopy

Journal of Near Infrared Spectroscopy ◽

10.1255/jnirs.73 ◽

1995 ◽

Vol 3 (4) ◽

pp. 227-237 ◽

Cited By ~ 43

Author(s):

Kumi Miyamoto ◽

Yoshinobu Kitano

Keyword(s):

Wavelength Range ◽

Near Infrared ◽

Sugar Content ◽

Satsuma Mandarin ◽

Infrared Transmittance ◽

Calibration Samples ◽

Sufficient Variation ◽

Non Destructive ◽

Calibration Equations

Using many samples of satsuma mandarins collected at random in packing houses, a method of establishing stable calibration equations to determine sugar content in the fruit by near infrared (NIR) transmittance spectroscopy was investigated. High accuracy in the determination of sugar content in the fruit could be obtained by multiple linear regression (MLR) using second derivative (D2) spectra in the 710–930 nm region. As a minimum, the four wavelengths mentioned below were needed as the predictor variables of the MLR equation. The D2 spectral change in the region of 900–910 nm was due to sugars (sucrose, glucose and fructose). A wavelength range of 880–890 nm and a wavelength range of 900–910 nm were selected as the best pair. A wavelength range of 740–755 nm region or 840–855 nm region compensated for the different optical pathlength of each fruit. One of the wavelengths around 794 nm or 835 nm was needed to compensate for the influence of fruit temperature. The influence of various factors such as fruit variety, growing location, harvest season and production year were investigated when the calibration was developed. When calibration samples had sufficient variation in fruit quality, it was possible to obtain a stable equation for all variations.

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Determination of Maximum Viscosity of Milled Rice Flours Using Near-Infrared Transmittance Spectroscopy.

Food Science and Technology Research ◽

10.3136/fstr.7.104 ◽

2001 ◽

Vol 7 (2) ◽

pp. 104-109 ◽

Cited By ~ 3

Author(s):

Naoto Shimizu ◽

Takashi Yanagisawa ◽

Hiroshi Okadome ◽

Hidechika Toyoshima ◽

Henrik Andren ◽

...

Keyword(s):

Near Infrared ◽

Milled Rice ◽

Infrared Transmittance ◽

Rice Flours

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Comparisons of Karl Fischer Method with Oven Methods for Determination of Water in Forages and Animal Feeds

Journal of AOAC International ◽

10.1093/jaoac/82.4.799 ◽

1999 ◽

Vol 82 (4) ◽

pp. 799-808 ◽

Cited By ~ 3

Author(s):

Nancy Thiex ◽

Terri Van Erem

Keyword(s):

Standard Error ◽

Near Infrared ◽

Corn Silage ◽

Infrared Reflectance ◽

Near Infrared Reflectance ◽

Karl Fischer ◽

Animal Feeds ◽

Karl Fischer Method ◽

Fischer Method

Abstract In a comparative study of the Karl Fischer method with oven methods for determination of water in forages and animal feeds, oven methods yielded the following relative recoveries (expressed as a percentage of the recovery obtained by the Karl Fischer method) for hay, haylage, and corn silage, respectively: (1) drying at 135°C for 2 h (AOAC 930.15), 113,162, and 133%; (2) drying at 104°C for 3 h (AOAC 935.29), 96,122, and 113%; and (3) drying at 104°C for 6 h, 97, 129, and 117%. Relative recoveries for nonurea-containing and urea-containing feed, respectively, were as fol lows: (1) drying at 135°C for 2 h (AOAC 930.15), 116 and 2746% (2) drying at 104°C for 3 h (AOAC 935.29), 88 and 239%; (3) drying at 95°C for 5 h under vacuum (AOAC 934.01), 83 and 727% (4) drying at 104°C for 6 h, 90 and 427%; and (5) drying at 110°C for 3 h, 94 and 425%. Preliminary near-infrared reflectance calibrations for water (moisture) based on the Karl Fischer method were promising (r2 = 0.98; standard error of calibration = 0.20).

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Development of a New Measurement Unit (MilkSpec-1) for Rapid Determination of Fat, Lactose, and Protein in Raw Milk Using Near-Infrared Transmittance Spectroscopy

Applied Spectroscopy ◽

10.1366/0003702021955150 ◽

2002 ◽

Vol 56 (5) ◽

pp. 599-604 ◽

Cited By ~ 29

Author(s):

Young-Ah Woo ◽

Yoko Terazawa ◽

Jie Yu Chen ◽

Chie Iyo ◽

Fuminori Terada ◽

...

Keyword(s):

Near Infrared ◽

Rapid Determination ◽

Scatter Correction ◽

Raw Milk ◽

Milk Composition ◽

Measurement Unit ◽

Calibration Model ◽

Transmittance Spectra ◽

Infrared Transmittance

A new measurement unit, the MilkSpec-1, has been developed to determine rapidly and nondestructively the content of fat, lactose, and protein in raw milk using near-infrared transmittance spectroscopy. The spectral range over 700 to 1100 nm was used. This unit was designed for general glass test tubes, 12 mm in diameter and 10 mL in volume. Al2O3 with a thickness of 2.5 mm was found to be optimum as a reference for acquiring the milk spectrum for this measurement. The NIR transmittance spectra of milk were acquired from raw milk samples without homogenization. The calibration model was developed and predicted by using a partial least-squares (PLS) algorithm. In order to reduce the scattering effect due to fat globules and casein micelles in NIR transmittance spectra, multiplicative scatter correction (MSC) and/or second derivative treatment were performed. MSC treatment proved to be useful for the development of calibration models for fat and protein. This study resulted in low standard errors of prediction (SEP), with 0.06, 0.10, and 0.10% for fat, lactose, and protein, respectively. It is shown that accurate, rapid, and nondestructive determination of milk composition could be successfully performed by using the MilkSpec-1, presenting the potential use of this method for real-time on-line monitoring in a milking process.

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Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy

Clinical Chemistry ◽

10.1093/clinchem/45.9.1651 ◽

1999 ◽

Vol 45 (9) ◽

pp. 1651-1658 ◽

Cited By ~ 125

Author(s):

Stephen F Malin ◽

Timothy L Ruchti ◽

Thomas B Blank ◽

Suresh N Thennadil ◽

Stephen L Monfre

Keyword(s):

Blood Glucose ◽

Wavelength Range ◽

Standard Error ◽

Diffuse Reflectance ◽

Near Infrared ◽

Diffuse Reflectance Spectroscopy ◽

Reflectance Spectroscopy ◽

Calibration Model ◽

Calibration Models ◽

Blood Glucose Concentrations

Abstract Background: Self-monitoring of blood glucose by diabetics is crucial in the reduction of complications related to diabetes. Current monitoring techniques are invasive and painful, and discourage regular use. The aim of this study was to demonstrate the use of near-infrared (NIR) diffuse reflectance over the 1050–2450 nm wavelength range for noninvasive monitoring of blood glucose. Methods: Two approaches were used to develop calibration models for predicting the concentration of blood glucose. In the first approach, seven diabetic subjects were studied over a 35-day period with random collection of NIR spectra. Corresponding blood samples were collected for analyte analysis during the collection of each NIR spectrum. The second approach involved three nondiabetic subjects and the use of oral glucose tolerance tests (OGTTs) over multiple days to cause fluctuations in blood glucose concentrations. Twenty NIR spectra were collected over the 3.5-h test, with 16 corresponding blood specimens taken for analyte analysis. Results: Statistically valid calibration models were developed on three of the seven diabetic subjects. The mean standard error of prediction through cross-validation was 1.41 mmol/L (25 mg/dL). The results from the OGTT testing of three nondiabetic subjects yielded a mean standard error of calibration of 1.1 mmol/L (20 mg/dL). Validation of the calibration model with an independent test set produced a mean standard error of prediction equivalent to 1.03 mmol/L (19 mg/dL). Conclusions: These data provide preliminary evidence and allow cautious optimism that NIR diffuse reflectance spectroscopy using the 1050–2450 nm wavelength range can be used to predict blood glucose concentrations noninvasively. Substantial research is still required to validate whether this technology is a viable tool for long-term home diagnostic use by diabetics.

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Rapid determination of oil content in dried-ground oil palm mesocarp and kernel using near infrared spectroscopy

Journal of Near Infrared Spectroscopy ◽

10.1177/0967033517732679 ◽

2017 ◽

Vol 25 (5) ◽

pp. 338-347 ◽

Cited By ~ 2

Author(s):

Sudarno ◽

Divo D Silalahi ◽

Tauvik Risman ◽

Baiq L Widyastuti ◽

F Davrieux ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Oil Palm ◽

Standard Error ◽

Oil Content ◽

Near Infrared ◽

Cross Validation ◽

Calibration Model ◽

Reliable Technique

Near infrared spectroscopy calibrations for rapid oil content determination of dried-ground oil palm mesocarp and kernel were developed. Samples were analyzed, one set using the Soxhlet extraction method for reference analysis and the other set scanned by near infrared spectroscopy instrument for calibration. Successful calibrations were obtained with good accuracy and precision for mesocarp and kernel, based on statistical models. Math treatment and scatter correction had significant effects on the fitting of the calibration model. The best obtained calibration models were demonstrated by multiple correlation coefficient (R2), standard error of calibration, standard error of cross validation, coefficient of determination in cross validation (1-VR) and relative predictive deviation of calibration, which respectively were 0.997, 1.21%, 1.23%, 0.997 and 17.89 for mesocarp and 0.952, 0.47%, 0.53%, 0.94 and 4.00 for kernel. The correlations between reference and predicted values for samples in the validation sets were in agreement with high linearity, high ratio performance to deviation of prediction (≥4.00) and low standard error of prediction samples for both samples. The results demonstrated that near infrared spectroscopy can be used as an alternative and reliable technique to estimate the mesocarp and kernel oil contents in dry matter basis accurately and rapidly.

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