Sensing of Moisture Content of In-Shell Peanuts by NIR Reflectance Spectroscopy

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"Sensing of Moisture Content of In-Shell Peanuts by NIR Reflectance Spectroscopy"
written by Jaya Sundaram, Chari V. Kandala, Konda Naganathan Govindarajan, Jeyam Subbiah,
published by Journal of Sensor Technology, Vol.2 No.1, 2012

has been cited by the following article(s):

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[1]	Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies
	Sensors, 2022

[2]	Non-Destructive Quality Monitoring of Flaxseed During Storage
	Journal of Food …, 2022

[3]	Rapid and Non-destructive measurement of moisture content of peanut (Arachis hypogaea L.) kernel using a near-infrared hyperspectral imaging technique
	2021

[4]	Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds
	2020

[5]	Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectroscopy
	2020

[6]	Selecting key wavelengths of hyperspectral imagine for nondestructive classification of moldy peanuts using ensemble classifier
	2020

[7]	The universal emergence of self-affine roughness from deformation
	arXiv preprint arXiv:1901.03236, 2019

[8]	EXPRESS: Use of Visible–Near-Infrared (Vis–NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels
	2019

[9]	Use of Visible–Near-Infrared (Vis-NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels
	2019

[10]	Determination of Moisture Content of Peanut (Arachis hypogaea Linn.) Kernel Using Near-Infrared Hyperspectral Imaging Technique
	2019

[11]	Potential of near-infrared hyperspectral imaging in discriminating corn kernels infected with aflatoxigenic and non-aflatoxigenic Aspergillus flavus
	2019

[12]	Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectra
	2019

[13]	Rapid and Non-destructive Prediction of Protein Content in Peanut Varieties Using Near-infrared Hyperspectral Imaging Method
	2018

[14]	Rapid measurement of moisture content in groundnut kernels using non-destructive near infrared reflectance spectroscopy
	2018

[15]	Связь показателя Хёрста и эффективности самоорганизации деформируемой системы
	Журнал технической физики, 2018

[16]	Rapid and non-destructive detection of aflatoxin contamination of peanut kernels using visible/near-infrared (Vis/NIR) spectroscopy
	Proceedings Volume 10665, Sensing for Agriculture and Food Quality and Safety X, 2018

[17]	Optical Sensing Technologies in Seed Science Research-A Review
	2017

[18]	Dynamic spectrum extraction method based on independent component analysis combined dual-tree complex wavelet transform
	RSC Advances, 2017

[19]	Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms
	Infrared Physics & Technology, 2017

[20]	Yerfıstığı (Arachis hypogaea L.)'nda bazı kalite özelliklerinin Yakın Kızılötesi Spektroskopi (NIRS) ile belirlenmesi
	DER?M, 2017

[21]	3 种不同红枣水分检测方法的比较
	江苏农业科学, 2016

[22]	近红外光谱技术在食品产地溯源中的应用研究进展
	农产品加工(上), 2016

[23]	Effect of Aspergillus flavus on groundnut seed quality and its management
	Thesis, 2016

[24]	Mısırda Nem İçeriğinin Yakın Kızıl Ötesi (NIR) Spektroskopisi ile Tespitinde Farklı Kemometrik Yöntemlerin Etkisinin Belirlenmesi
	2016

[25]	Near Infrared Imaging As a Method of Studying Tsetse Fly (Diptera: Glossinidae) Pupal Development
	2016

[26]	Density Independent and Temperature Compensated Moisture Prediction Model for Agricultural Products Using Impedance Analyzer: A Review
	International Journal of Advanced Engineering, Mana gement and Science (IJAEMS) , 2016

[27]	Calibration set selection method based on the “M+ N” theory: application to non-invasive measurement by dynamic spectrum
	RSC Advances, 2016

[28]	Survey Anomali Magnetik Bijih Besi di Pesisir Pantai Marina Kabupaten Bantaeng Berdasarkan Metode Geomagnetik
	2016

[29]	VIS/NIR spectral signature for the identification of peanut contamination of powder foods
	AgricEngInt: CIGR Journal, 2015

[30]	干燥过程中玉米水分质量分数均匀度的高光谱图像无损检测
	食品与生物技术学报, 2015

[31]	近红外光谱定性与定量分析技术在莲子无损检测中的应用
	2015

[32]	赵伟彦, 黄敏 41, 张 2
	2015

[33]	Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy
	Journal of Food Measurement and Characterization, 2014

[34]	基于近红外光谱的南疆温185 核桃水分无损检测的研究
	安徽农业科学, 2014

[35]	近红外光谱在南疆红枣糖度无损检测中的应用
	农机化研究, 2014

[36]	小麦品质近红外检测系统的设计与试验研究
	光谱学与光谱分析, 2013

[37]	Design and Experiment of NIR Wheat Quality Quick Detection System
	Computer and Computing Technologies in Agriculture VI. Springer Berlin Heidelberg, 2013

[38]	近红外光谱对南疆红枣水分无损检测的研究
	食品科技, 2013

[39]	Food, nutrition and agrobiodiversity under global climate change
	Adv Agron, 2013

[40]	Emergence of surface and interface structure from friction, fracture and deformation
	J Kermode, L Pastewka, G Moras

[1]	Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies Sensors, 2022 DOI:10.3390/s22134864

[2]	Non-Destructive Quality Monitoring of Flaxseed During Storage Journal of Food Measurement and Characterization, 2022 DOI:10.1007/s11694-022-01464-5

[3]	Rapid and Non-destructive measurement of moisture content of peanut (Arachis hypogaea L.) kernel using a near-infrared hyperspectral imaging technique Journal of Food Measurement and Characterization, 2021 DOI:10.1007/s11694-021-00894-x

[4]	Potential of near-infrared hyperspectral imaging in discriminating corn kernels infected with aflatoxigenic and non-aflatoxigenic Aspergillus flavus Sensing for Agriculture and Food Quality and Safety XI, 2019 DOI:10.1117/12.2521654

[5]	Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectra Journal of Near Infrared Spectroscopy, 2019 DOI:10.1177/0967033519895686

[6]	Use of Visible–Near-Infrared (Vis-NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels Applied Spectroscopy, 2019 DOI:10.1177/0003702819829725

[7]	Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms Infrared Physics & Technology, 2018 DOI:10.1016/j.infrared.2017.11.018

[8]	Rapid and non-destructive detection of aflatoxin contamination of peanut kernels using visible/near-infrared (Vis/NIR) spectroscopy Sensing for Agriculture and Food Quality and Safety X, 2018 DOI:10.1117/12.2304399

[9]	Dynamic spectrum extraction method based on independent component analysis combined dual-tree complex wavelet transform RSC Adv., 2017 DOI:10.1039/C6RA28647J

[10]	Optical remote sensor for peanut kernel abortion classification Applied Optics, 2016 DOI:10.1364/AO.55.004005

[11]	Near Infrared Imaging As a Method of Studying Tsetse Fly (Diptera: Glossinidae) Pupal Development Journal of Insect Science, 2016 DOI:10.1093/jisesa/iew047

[12]	Calibration set selection method based on the “M + N” theory: application to non-invasive measurement by dynamic spectrum RSC Adv., 2016 DOI:10.1039/C6RA19272F

[13]	Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy Journal of Food Measurement and Characterization, 2014 DOI:10.1007/s11694-014-9173-8

[14]	Advances in Agronomy, 2013 DOI:10.1016/B978-0-12-407686-0.00001-4

[15]	Computer and Computing Technologies in Agriculture VI IFIP Advances in Information and Communication Technology, 2013 DOI:10.1007/978-3-642-36137-1_17

[16]	New trends in the multidisciplinary treatment of liver tumors Future Oncology, 2013 DOI:10.2217/fon.13.127

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	+86 18163351462(WhatsApp)
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