Near-infrared Spectroscopy for Determining Grain Constituent Contents at Grain Elevators

Li, Rui; Kawamura, Shuso; Fujita, Hideo; Fujikawa, Sakiko

doi:10.1016/s1881-8366(13)80013-4

Cited by 10 publications

(7 citation statements)

References 6 publications

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“…There are two methods for measuring the NIR: the transmission method (Delwiche et al, 1996;Li et al, 2013) and the reflection method (Hidaka et al, 2011;Priya et al, 2015). The transmission method applies to uniform or transparent samples, and the NIR absorbs the same proportion of light on each equivalent thickness medium on the optical path, that is, the absorbed amount of light is in direct proportion to the number of molecules that generate light absorption on the optical path.…”

Section: Measurement Principles Of the Sensormentioning

confidence: 99%

“…Using the Foss InfraXact™ Lab/Pro spectrometer (570-1850 nm), Arazuri et al (2012) collected the spectrum of wheat in the NIR area, analyzed the relationships of rheological parameters between spectrum and tenacity, extensibility, deformation energy of wheat, which provided technical support for obtaining the rheological parameters of wheat during harvest and transportation of wheat. In a study by Li et al (2013). a spectrometer was used to collect the transmitted spectrum (840-1,048 nm) of brown rice.…”

Section: Introductionmentioning

confidence: 99%

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Design of a Phenotypic Sensor About Protein and Moisture in Wheat Grain

Liu

et al. 2022

Front. Plant Sci.

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A near-infrared (NIR) spectrometer can perceive the change in characteristics of the grain reflectance spectrum quickly and nondestructively, which can be used to determine grain quality information. The full-band spectral information of samples of multiple physical states can be measured using existing instruments, yet it is difficult for the full-band instrument to be widely used in grain quality detection due to its high price, large size, non-portability, and inability to directly output the grain quality information. Because of the above problems, a phenotypic sensor about grain quality was developed for wheat, and four wavelengths were chosen. The interference of noise signals such as ambient light was eliminated by the phenotypic sensor using the modulated light signal and closed sample pool, the shape and size of the incident light spot of the light source were determined according to the requirement for collecting the reflectance spectrum of the grain, and the luminous units of the light source with stable light intensity and balanced luminescence were developed. Moreover, the sensor extracted the reflectance spectrum information using a weak optical signal conditioning circuit, which improved the resolution of the reflectance signal. A grain quality prediction model was created based on the actual moisture and protein content of grain obtained through Physico-chemical analyses. The calibration test showed that the R2 of the relative diffuse reflectance (RDR) of all four wavelengths of the phenotypic sensor and the reflectance of the diffusion fabrics were higher than 0.99. In the noise level and repeatability tests, the standard deviations of the RDR of two types of wheat measured by the sensor were much lower than 1.0%, indicating that the sensor could accurately collect the RDR of wheat. In the calibration test, the root mean square errors (RMSE) of protein and moisture content of wheat in the Test set were 0.4866 and 0.2161%, the mean absolute errors (MAEs) were 0.6515 and 0.3078%, respectively. The results showed that the NIR phenotypic sensor about grain quality developed in this study could be used to collect the diffuse reflectance of grains and the moisture and protein content in real-time.

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Section: Measurement Principles Of the Sensormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of a Phenotypic Sensor About Protein and Moisture in Wheat Grain

Liu

et al. 2022

Front. Plant Sci.

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“…Using the convection oven to dry the grain and measuring the loss of mass to determine the grain moisture is the standard method of grain moisture measurement in several countries because of its high precision and high reliability [3,4,5], however, it has obvious disadvantages of being time-consuming and cumbersome. In order to achieve fast and precise moisture determination, many studies have been conducted to determine the moisture of grains by using near-infrared reflection methods [6,7,8]. However, the penetration depth of infrared is shallow, and the measured result is easily affected by ambient light and impurities attached to the grain particles, therefore, the method is most often applied to grain moving on a conveyor belt in a processing plant, where the layer of grain is thin and the environment is relatively clean [9].…”

Section: Introductionmentioning

confidence: 99%

A Novel, Portable and Fast Moisture Content Measuring Method for Grains Based on an Ultra-Wideband (UWB) Radar Module and the Mode Matching Method

Zhang

Shi

Yang

et al. 2019

Sensors

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To perform fast and portable grain moisture measurements under field conditions, a novel moisture sensor was designed, which consisted of a coaxial waveguide, a circular waveguide, and an isolation layer. The electromagnetic characteristics of the sensor were simulated and measured. The analytical model, which represented the relationship between the reflection coefficient of the sensor and the complex permittivity of grain, was established by using the mode matching method. The reflection coefficient of the sensor was measured by using an ultra-wideband (UWB) radar module, and the moisture content of grains was calculated from the complex permittivity by using density-independent model. To verify the performance of the proposed method, wheat, rough rice, and barley were taken as examples. The measured results in the range from 1.0% to 26.0%, wet basis, agreed well with the reference values (R2 was more than 0.99), and the maximum absolute errors for wheat, rough rice, and barley were 1.1%, 1.0%, and 1.4%, respectively. In addition, the effect of isolation layer was discussed. Both the simulation results and the experimental results showed that the isolation layer improved the stability of sensor.

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“…For example, it is used for determination of proteins, fats and moisture in cookies and cakes, and also for detection of starch, protein, water, ash, colour and grain size in flour (Porep et al, 2015). NIR spectroscopy is also used for monitoring the breadcrumb mixing process, for monitoring cereals and cereal products (Aït Kaddour and Cuq, 2011a), for agglomeration of flour (Aït Kaddour and Cuq, 2011b), for determination of moisture in pasta after extrusion (De Temmerman and sur., 2007) and for determination of moisture and protein in rice and wheat in the wavelength range of 840 nm to 1048 nm (Li et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Application of NIR spectroscopy in gluten detection as a cross-contaminant in food

Radman

Jurina

Benković

et al. 2018

Hrvat. čas. prehrambenu tehnol. biotehnol. nutr. (Online)

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The determination of gluten is of critical importance when food screening is intended for special groups such as food ingredient intolerant and allergic persons. Cross-contamination of food that does not contain gluten is also possible in the sales chain. The aim of this study was to determine the applicability of Near-Infrared Spectroscopy (NIRs) for the detection of gluten traces in rice, rice flour, corn flour and corn grits. In the cross-contamination simulation, two types of wheat flour were used. They were added to rice, rice flour, corn flour and corn grits in a range from 5 % to 30 %. Apart from the spectra of pure and contaminated samples, conductivity and total dissolved solids were monitored to determine changes in the samples. NIR spectroscopy was combined with chemometric techniques to determine at which wavelengths a glutenfree fingerprint can be detected. Although experiments were carried out with a NIR instrument that monitors molecular vibrations in the range of λ= 904-1699 nm, the gluten fingerprint was successfully determined, regardless of the type of flour that was added to the rice, rice flour, corn flour and corn grits. All concentrations of the added flours were successfully determined and models were developed to detect the concentrations of the added flours. Even the conductivity showed good prediction potential in gluten determination. Regardless if the investigated samples were contaminated or not, the determination coefficient R2 was over 0.9. Developed models could be used to predict possible wheat flour contamination of any rice or corn product samples or samples prepared for cooking in water.

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Near-infrared Spectroscopy for Determining Grain Constituent Contents at Grain Elevators

Cited by 10 publications

References 6 publications

Design of a Phenotypic Sensor About Protein and Moisture in Wheat Grain

Design of a Phenotypic Sensor About Protein and Moisture in Wheat Grain

A Novel, Portable and Fast Moisture Content Measuring Method for Grains Based on an Ultra-Wideband (UWB) Radar Module and the Mode Matching Method

Application of NIR spectroscopy in gluten detection as a cross-contaminant in food

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