scholarly journals Determination of Apparent Amylose Content in Japanese Milled Rice Using Near-Infrared Transmittance Spectroscopy.

1999 ◽  
Vol 5 (4) ◽  
pp. 337-342 ◽  
Author(s):  
Naoto SHIMIZU ◽  
Jyunji KATSURA ◽  
Takashi YANAGISAWA ◽  
Shigeru INOUE ◽  
Robin P. WITHEY ◽  
...  
Keyword(s):  
Near Infrared ◽  
Amylose Content ◽  
Milled Rice ◽  
Infrared Transmittance ◽  
Apparent Amylose Content

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

2001 ◽  
Vol 7 (2) ◽  
pp. 104-109 ◽  
Author(s):  
Naoto Shimizu ◽  
Takashi Yanagisawa ◽  
Hiroshi Okadome ◽  
Hidechika Toyoshima ◽  
Henrik Andren ◽  
...  
Keyword(s):  
Near Infrared ◽  
Milled Rice ◽  
Infrared Transmittance ◽  
Rice Flours

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

2002 ◽  
Vol 56 (5) ◽  
pp. 599-604 ◽  
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.

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

1993 ◽  
Vol 1 (1) ◽  
pp. 25-32 ◽  
Author(s):  
P. C. Williams ◽  
D.C. Sobering
Keyword(s):  
Standard Deviation ◽  
Wavelength Range ◽  
Standard Error ◽  
Near Infrared ◽  
Original Data ◽  
Whole Grains ◽  
Whole Grain ◽  
Infrared Transmittance

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.

scholarly journals Evaluation of Physicochemical and Cooking Characteristics of Rice (Oryza sativa L.) Landraces of Lamjung and Tanahun Districts, Nepal

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Amrit Pokhrel ◽  
Anup Dhakal ◽  
Shishir Sharma ◽  
Ankur Poudel
Keyword(s):  
Oryza Sativa ◽  
Principal Components ◽  
Amylose Content ◽  
Oryza Sativa L ◽  
Chemical Properties ◽  
Milled Rice ◽  
Cooking Properties ◽  
Rice Landraces ◽  
Apparent Amylose Content ◽  
Modern Varieties

After the Green Revolution, the increase in the choice of modern varieties at the expense of landraces has become a major cause of varietal loss. The preference, choice, and the economy of rice (Oryza sativa L.) largely depend on its physicochemical and cooking properties, which are found to be superior for landraces than modern varieties. In this study, we assessed and evaluated milled rice of 30 rice landraces on their physicochemical and cooking characteristics which aim to promote the revival of old landraces. Six parameters of physical properties, four parameters of chemical properties, and five parameters of cooking properties were evaluated based on the standard protocols. Significant variations (p<0.05) were found in all the properties that were evaluated. The result showed that the highest milling recovery was found in Indrabeli (75.55%) whereas the lowest was found in Kalo Masino (66.98%) and bulk density ranged from 0.81 g/cm3 to 0.88 g/cm3 showing not much variability. Although most of them were of medium grain type, their 1000 kernel weight varied between 12.62 g and 25.65 g. From the observed chemical properties, Pahelo Anadi (9.73±0.55 mm) showed the highest gel consistency and lowest apparent amylose content (7.23±0.36%). Also, 13% of landraces possessed strong aroma while noble cooking properties were showed by Thakali Lahare Marsi with the highest elongation ratio (2.41±0.05) and by Chiniya with the lowest gruel solid loss (0.033±0.03%) and minimum optimum cooking time (23.45±0.03 min). In the principal component analysis, the first four principal components retained 73.8% of the variance. The first and second principal components were mostly related with the physical and chemical characteristics while the third and fourth principal components were concerned with cooking characters. Superior characters possessed by rice landraces can be further assessed for the breeding programs so that the cultivation of these cherished rice landraces can be enhanced.

Evaluating Techniques for Rice Grain Quality Using near Infrared Transmission Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A111-A116 ◽  
Author(s):  
Naoto Shimizu ◽  
Jyunji Katsura ◽  
Takashi Yanagisawa ◽  
Bunji Tezuka ◽  
Yasuyuki Maruyama ◽  
...  
Keyword(s):  
Grain Quality ◽  
Near Infrared ◽  
Amylose Content ◽  
Rice Grain ◽  
Whole Grain ◽  
Infrared Transmission ◽  
Reliable Determination ◽  
Rice Quality ◽  
Head Rice ◽  
Apparent Amylose Content

The development of advanced evaluation techniques for rice quality has been a desire of the Japanese rice industry (breeding, distribution and processing). The objective of the present study is to develop novel techniques for evaluating rice grain quality. A reliable determination method for amylose in whole grain rice using near infrared transmission (NIT) is proposed, using Partial Least Squares (PLS) regression analysis. It was suggested from results based on two different validation methods that the PLS models have possibilities for determination of apparent amylose content using NIT spectroscopy. PLS modelling for constituents important in rice quality indicates that reasonably accurate models are attainable for moisture content and protein content in whole grain rice. However our PLS models were not sufficiently accurate for physical rice quality (head rice ratio, apparent density, whiteness) using NIT spectroscopy.

Determination of Adsorbed Protein Concentration in Aluminum Hydroxide Suspensions by Near-Infrared Transmittance Spectroscopy

2008 ◽  
Vol 62 (7) ◽  
pp. 784-790 ◽  
Author(s):  
Xuxin Lai ◽  
Yiwu Zheng ◽  
Susanne Jacobsen ◽  
Jørgen N. Larsen ◽  
Henrik Ipsen ◽  
...  
Keyword(s):  
Aluminum Hydroxide ◽  
Protein Concentration ◽  
Near Infrared ◽  
Adsorbed Protein ◽  
Infrared Transmittance

Determination of zeleny subsidence value of wheat based on Near Infrared Transmittance Spectroscopy

2011 ◽  
Author(s):  
Liu Hexiao ◽  
Sun Laijun ◽  
Liu Mingliang ◽  
Qian Haibo ◽  
Xululu ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Transmittance
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