Rapid and Non-destructive measurement of moisture content of peanut (Arachis hypogaea L.) kernel using a near-infrared hyperspectral imaging technique

Rabanera, Jennyfer D.; Guzman, Jose Domingo; Yaptenco, Kevin F.

doi:10.1007/s11694-021-00894-x

Cited by 22 publications

(10 citation statements)

References 23 publications

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“…Near-infrared (NIR) spectroscopy has been extensively applied in plant growth, food quality analysis, environmental protection, medical diagnosis, night vision, and many other fields. − Disappointingly, the traditional NIR light sources including tungsten halogen lamps and NIR light-emitting diodes (LEDs) are deficient in satisfying the versatile applications in NIR spectroscopy because of their shortcomings, such as low efficiency, large size, high cost, or narrow emission bandwidth. − Recently, NIR phosphor-converted light-emitting diodes (pc-LEDs), which not only overcome the disadvantages of traditional NIR light sources but also show the characteristic of tunable broadband emission, have attracted considerable research interest. , As a crucial component of NIR pc-LEDs, the NIR phosphor determines the output spectrum, luminous flux, and efficiency of devices. Therefore, developing a broadband NIR phosphor with high performance is desired.…”

Section: Introductionmentioning

confidence: 99%

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors

Zhong

2022

Chem. Mater.

107

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Broadband near-infrared (NIR) light source based on phosphor-converted light-emitting-diode (pc-LED) is crucial for applications in medical diagnosis, food quality analysis, and night vision fields, motivating the development of highly efficient and thermal robust NIR phosphor materials. Herein, a novel Cr 3+ -doped garnet phosphor Y 3 In 2 Ga 3 O 12 :Cr 3+ emerges from a fundamental study of the Ln 3 In 2 Ga 3 O 12 (Ln = La, Gd, Y, and Lu) family. Upon 450 nm excitation, this material presents a broadband NIR emission covering 650−1100 nm with a peak located at 760 nm and a full width at half maximum of 125 nm. This material also possesses an ultrahigh internal quantum efficiency (IQE = 91.6%) and absorption efficiency (AE = 46.6%), resulting in an external quantum efficiency as high as 42.7%. Moreover, the emission intensity of this material at 150 °C maintains 100% of the initial intensity, showing a rare zero-thermalquenching property. Fabricating an NIR pc-LED device by using this material, an excellent NIR output power of 68.4 mW with a photoelectric efficiency of 15.9% under 150 mA driving current can be obtained, which exhibits much better performance than the devices fabricated by using some reported efficient NIR materials. Therefore, this work not only provides an ultraefficient and thermally robust broadband NIR material for spectroscopy application but also contributes to the foundation of design rules of NIR materials with high performance.

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Section: Introductionmentioning

confidence: 99%

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors

Zhong

2022

Chem. Mater.

107

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“…[36][37][38] In the spectral region of 950 nm to 1070 nm, the appearance of absorption valleys can be attributed to the third overtone C-H stretches. 39 Peanut oil composition contains a significant number of C-H groups, explaining the presence of these absorption valleys. Notably, Huayu 910 has a deeper spectral absorption valley than other peanut varieties, which indicates there is a higher oil content in Huayu 910 than others.…”

Section: Spectral Image Acquisition and Preprocessingmentioning

confidence: 99%

A hyperspectral band selection algorithm for identifying high oleic acid peanuts

Shao,

Li,

Sun

et al. 2024

Journal of Near Infrared Spectroscopy

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High oleic acid peanuts have higher oleic acid content and stronger oxidation stability than common peanuts, but their appearances are similar, which imposes difficulties for classifying. Based on this, the study aims to classify high oleic acid peanut to ensure its purity by using hyperspectral imaging technology. However, classification accuracy and efficiency are limited given the large amount of redundant information of hyperspectral images. The band iteration algorithm (BIA) is proposed to select characteristic bands by reducing the redundant information between spectral bands for the peanut classification. Hyperspectral images with 616 bands (from 400 nm to 1100 nm) of 126 high oleic acid peanuts and 126 common peanuts were collected. Then, BIA selected optimal bands as characteristic bands from adjacent bands according to the classification accuracy of each band subsets. Thirdly, three classification models, namely linear discriminant analysis (LDA), support vector machine (SVM), and partial least squares-discriminant analysis (PLS-DA), were employed to compare the performance of BIA with successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS), respectively. The experimental results show that BIA can effectively improve the classification ability of spectral data. The BIA-PLS-DA model had the best classification efficiency, and the accuracy of the test set reached 93.26%. For peanut individuals, only one peanut sample was misclassified with a classification error rate of 1.43%.

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“…The moisture content of peanuts was assessed using a Finnish HSI technology manufactured by Oulu company [ 64 ] according to several steps ( Figure 5 ). First, data were evaluated by Unscrambler X 10.5 and MatlabR2013a software using the PLSR regression model.…”

Section: Comparison Of Various Techniques For Prediction Of Moisture ...mentioning

confidence: 99%

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

2023

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Drying is one of the common procedures in the food processing steps. The moisture content (MC) is also of crucial significance in the evaluation of the drying technique and quality of the final product. However, conventional MC evaluation methods suffer from several drawbacks, such as long processing time, destruction of the sample and the inability to determine the moisture of single grain samples. In this regard, the technology and knowledge of hyperspectral imaging (HSI) were addressed first. Then, the reports on the use of this technology as a rapid, non-destructive, and precise method were explored for the prediction and detection of the MC of crops during their drying process. After spectrometry, researchers have employed various pre-processing and merging data techniques to decrease and eliminate spectral noise. Then, diverse methods such as linear and multiple regressions and machine learning were used to model and predict the MC. Finally, the best wavelength capable of precise estimation of the MC was reported. Investigation of the previous studies revealed that HSI technology could be employed as a valuable technique to precisely control the drying process. Smart dryers are expected to be commercialised and industrialised soon by the development of portable systems capable of an online MC measurement.

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Rapid and Non-destructive measurement of moisture content of peanut (Arachis hypogaea L.) kernel using a near-infrared hyperspectral imaging technique

Cited by 22 publications

References 23 publications

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors

A hyperspectral band selection algorithm for identifying high oleic acid peanuts

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

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Rapid and Non-destructive measurement of moisture content of peanut (Arachis hypogaea L.) kernel using a near-infrared hyperspectral imaging technique

Cited by 22 publications

References 23 publications

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y3In2Ga3O12:Cr3+ Phosphors

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y3In2Ga3O12:Cr3+ Phosphors

A hyperspectral band selection algorithm for identifying high oleic acid peanuts

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

Contact Info

Product

Resources

About

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors

Highly Efficient Broadband Near-Infrared Luminescence with Zero-Thermal-Quenching in Garnet Y₃In₂Ga₃O₁₂:Cr³⁺ Phosphors