Laser & Optoelectronics Progress, Volume. 52, Issue 11, 113005(2015)
Rapid Testing Method of Brown Rice Germination Rate Based on Characteristic Spectrum and General Regression Neural Network
[1] [1] Xin Liangjie, Li Xiubin. Changes of multiple cropping in double cropping rice area of southern China and its policy implications[J]. Journal of Natural Resources, 2009, 24(1): 58-65.
[2] [2] Sun Qun, Wang Qing, Xue Weiqing, et al.. Advances in nondestructive detection of seed quality[J]. Journal of China Agricultural University, 2012, 17(3): 1-6.
[3] [3] Guo Peiyuan, Lin Yan, Fu Yan, et al.. Research on freshness level of meat based on near- infrared spectroscopic technique[J]. Laser & Optoelectronics Progress, 2013, 50(3): 033002.
[4] [4] Zhao Jiewen, Bi Xiakun, Lin Hao, et al.. Visible-near-infrared transmission spectra for rapid analysis of the freshness of eggs[J]. Laser & Optoelectronics Progress, 2013, 50(5): 053003.
[7] [7] Xu Lei, Xia Haiping. Multi-metal sulfide for absorbing near infrared light[J]. Chinese J Lasers, 2013, 40(6): 0606001.
[9] [9] Rudolphi S, Becker H C, Schierholt A, et al.. Improved estimation of oil, linoleic and oleic acid and seed hull fractions in safflower by NIRS[J]. Journal of the American Oil Chemists' Society, 2012, 89(3): 363-369.
[11] [11] Agelet L E, Ellis D D, Duvick S, et al.. Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels[J]. Journal of Cereal Science, 2012, 55(2): 160-165.
[12] [12] Xie L H, Tang S Q, Chen N, et al.. Optimisation of near-infrared reflectance model in measuring protein and amylose content of rice flour[J]. Food Chemistry, 2014, 142: 92-100.
[13] [13] Zhi Juzhen, Bi Xinhua, Du Kemin, et al.. GB/T3543.4-1995 Rules for agricultural seed testing - germination test[S]. Beijing: Chinese Standard Press, 1995.
[14] [14] Xu Huibin, Wei Yidong, Lian Ling, et al.. Comparative analysis of artificial aging and natural aging with rice seeds[J]. Molecular Plant Breeding, 2013, 11(5): 552-556.
[15] [15] Christy C D. Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy[J]. Computers and Electronics in Agriculture, 2008, 61(1): 10-19.
[16] [16] Brunet D, Barthès B G, Chotte J L, et al.. Determination of carbon and nitrogen contents in alfisols, oxisols and ultisols from Africa and Brazil using NIRS analysis: Effects of sample grinding and set heterogeneity[J]. Geoderma, 2007, 139(1): 106- 117.
[17] [17] Gong Huili. Feature Extraction and Similarity Measure on Tobacco Near Infrared Spectra[D]. Qingdao: Ocean University of China, 2014.
[18] [18] Sinelli N, Limbo S, Torri L, et al.. Evaluation of freshness decay of minced beef stored in high-oxygen modified atmosphere packaged at different temperatures using NIR and MIR spectroscopy[J]. Meat Science, 2010, 86(3): 748-752.
[19] [19] Balabin R M, Lomakina E I, Safieva R Z. Neural network (ANN) approach to biodiesel analysis: Analysis of biodiesel density, kinematic viscosity, methanol and water contents using near infrared (NIR) spectroscopy[J]. Fuel, 2011, 90(5): 2007-2015.
[20] [20] Zhang W J, Liu R, Zhang W, et al.. Net analyte signal with floating reference theory in non-invasive blood glucose sensing by near-infrared spectroscopy[J]. Chinese Optics Letters, 2012, 10(8): 70-73.
[21] [21] Chen K J, Huang M. Prediction of milled rice grades using Fourier transform near-infrared spectroscopy and artificial neural networks[J]. Journal of Cereal Science, 2010, 52(2): 221-226.
[22] [22] Liu Boping, Qin Huajun, Luo Xiang, et al.. Multicomponent quantitative analysis using near infrared spectroscopy by building PLS-GRNN model[J]. Spectroscopy and Spectral Analysis, 2007, 27(11): 2216-2220.
[23] [23] Han Rui. Studies on Physio- Biochemical Changes, DNA Damages and Invigoration in Artificial Aged Rice Seeds[D]. Hangzhou: Zhejiang University, 2012.
[24] [24] Xu Pengyu, Deng Hongping, Zhang Jiahui, et al.. Analysis of differential expression of seed embryo protein in the artificial aging process in rice[J]. Journal of Southwest University (Natural Science Edition), 2010, 32(12): 1-7.
Get Citation
Copy Citation Text
Li Huanhuan, Lu Wei, Hong Delin, Dang Xiaojing, Liang Kun. Rapid Testing Method of Brown Rice Germination Rate Based on Characteristic Spectrum and General Regression Neural Network[J]. Laser & Optoelectronics Progress, 2015, 52(11): 113005
Category: Spectroscopy
Received: Jun. 15, 2015
Accepted: --
Published Online: Nov. 9, 2015
The Author Email: Huanhuan Li (hhlnjau@126.com)