Acta Optica Sinica, Volume. 35, Issue 10, 1012001(2015)

Study on Infrared Thermal Prediction Model of Rice Seed Germination Rate Based on Multi-Scale Wavelet Transform and Grey Neural Network

Fang Wenhui1、*, Lu Wei1,2, Hong Delin3, Dang Xiaojing3, and Liang Kun1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    References(26)

    [1] [1] Chen Nianwei, Zhang Tigang. Influencing factors in germination percentage of hybrid rice seeds[J]. Hybrid Rice, 2009, 24(3): 23-26.

    [3] [3] Zhao Zhongliang, Zhang Lianping, Zhang Bei, et al.. Influence of ultrasonic stimulation on the germination and take root of rice seed[J]. Journal of Agricultural Mechanization Research, 2011, (6): 122-124.

    [5] [5] Zhou Jianmin, Zhou Qixian, Liu Yande. Application of infrared thermography techniques in agricultural production[J]. Journal of Agricultural Mechanization Research, 2010, (2): 1-4.

    [6] [6] Yu Zheng, Fang Fang, Peng Zuodeng, et al.. New technologies for detecting seed vigor[J]. Seed, 2012, 31(8): 52-55.

    [7] [7] Chen Bin, Tian Guihua. Application of infrared thermal imaging in the detection of plant disease progression[J]. Jiangsu Agricultural Sciences, 2014, 42(9): 1-4.

    [8] [8] Li Xiaolong, Wang Ku, Ma Zhanhong, et al.. Early detection of wheat disease based on thermal infrared imaging[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(18): 183-189.

    [9] [9] Jamil N, Bejo S K. Husk detection using thermal imaging technology[J]. Agriculture & Agricultural Science Procedia, 2014, 2: 128–135.

    [10] [10] Kranner I, Kastberger G, Hartbauer M, et al.. Noninvasive diagnosis of seed viability using infrared thermography[J]. Proceedings of the National Academy of Sciences of the United States of America, 2010, 107(8): 3912-3917.

    [11] [11] Gong Fang, Zhang Xuewu, Sun Hao. Detection system for solar module surface defects based on constrained ICA model and PSO method [J]. Acta Optica Sinica, 2012, 32(4): 0415002.

    [12] [12] Zhi Juzhen, Bi Xinhua, Du Kemin, et al.. Rules for agricultural seed testing - germination test[S]. Beijing: Chinese Standard Press, 1995.

    [13] [13] Zhu Jin, Sun Dongmei, Chen Ling. Study of concentration retrieving algorithm for ammonia based on differential optical absorption spectroscopy[J]. Acta Optica Sinica, 2013, 33(2): 0230004.

    [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] Yang Yaping, Jiang Xiaocheng, Chen Liangbi, et al.. Study on physiological mechanism in aging of rice seeds[J]. Journal of Hunan Agricultural University (Natural Sciences), 2008, 34(3): 265-269.

    [16] [16] Ji Junjie, Luo Yonghao. The combustion instability detection using the wavelet detail of pressure fluctuations[J]. Journal of Shanghai Jiao Tong University, 2007, 41(3): 342-346.

    [17] [17] Duan Yali, Su Rongguo, Shi Xiaoyong, et al.. Differentiation of phytoplankton populations by in vivo fluorescence based on high-frequency component of wavelet[J]. Chinese J Lasers, 2012, 39(7): 0715003.

    [18] [18] Wu Long, Xing Likun, Chen Shuai. Determination algorithm of optimal decomposition level based on singular spectrum analysis[J]. Computer Engineering and Applications, 2012, 48(36): 137-141.

    [19] [19] Lu Shizeng, Jiang Gangshun, Sui Qingmei, et al.. Identification of impact location by using fiber Bragg grating based on wavelet transform and support vector classifiers[J]. Chinese J Lasers, 2014, 41(3): 0305006.

    [20] [20] Zhang Leijie, Zhang Min, Yang Le, et al.. Using BP neural networks to predict specific heat capacity of food[J]. Journal of Anhui Agricultural Sciences, 2009, 37(17): 8296-8297.

    [21] [21] Jin Wen, Zhang Lailin, Li Guangtao, et al.. Study on the thermal conductivity of paddy[J]. Foodstuffs Technology, 2010, 18(2): 1-3.

    [22] [22] Plans M, Simó J, Casaas F, et al.. Estimating sensory properties of common beans (Phaseolus vulgaris L.) by near infrared spectroscopy [J]. Food Research International, 2014, 56: 55-62.

    [24] [24] Moody J, Darken C J. Fast learning in networks of locally-tuned processing units[J]. Neural Computation, 1989, 1(2): 281-294.

    [25] [25] Chen Shuyan, Wang Wei. Grey neural network forecasting for traffic flow[J]. Journal of Southeast University (Natural Science Edition), 2004, 34(4): 541-544.

    [26] [26] Yang Jian, Pan He, Li Taihao, et al.. Study on non-destructive detection method for fresh degree of eggs based on grey neural network [J]. Journal of Chinese Agricultural Mechanization, 2014, 35(1): 229-234.

    [27] [27] Zhang Hongliang, Li Jie, Zhang Wengen, et al.. Application of grey GM(1,1) model to alumina concentration estimation in aluminum electrolysis[J]. Chinese Journal of Scientific Instrument, 2008, 29(4): 883-887.

    Tools

    Get Citation

    Copy Citation Text

    Fang Wenhui, Lu Wei, Hong Delin, Dang Xiaojing, Liang Kun. Study on Infrared Thermal Prediction Model of Rice Seed Germination Rate Based on Multi-Scale Wavelet Transform and Grey Neural Network[J]. Acta Optica Sinica, 2015, 35(10): 1012001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Apr. 28, 2015

    Accepted: --

    Published Online: Oct. 8, 2015

    The Author Email: Wenhui Fang (fwhnjau@126.com)

    DOI:10.3788/aos201535.1012001

    Topics