Detection of the protein content of Ningxia Tan sheep using hyperspectral reflectance imaging

被引:0
|
作者
Wang, Songlei [1 ]
Liu, Guishan [1 ]
Li, Xuefu [1 ]
Luo, Ruiming [1 ]
机构
[1] Ningxia Univ, Sch Agr, Ningxia 750021, Peoples R China
关键词
Near-infrared hyperspectral imaging; Tan sheep; Protein; Detection;
D O I
10.4028/www.scientific.net/AMM.513-517.4235
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Near-infrared (NIR) hyperspectral imaging technique (900-1700nm) was evaluated to predict the protein content of Tan sheep. This research adopted NIR hyperspectral imaging to get imaging information of 72 mutton samples, multiplicative scatter correction was used to spectral data preprocessing. The optimal wavelengths were obtained through linear-regression analysis, BP neural network combined with actual measured values were established the prediction model and verified this model. The results showed that the prediction effect of model was very well. Correlation coefficient(Rp) and root mean squared error of prediction(RMSEP) of the protein were 0.87 and 1.19. The results indicated that it is feasible to predict the protein content of Tan sheep for NIR hyperspectral imaging technique.
引用
收藏
页码:4235 / 4238
页数:4
相关论文
共 50 条
  • [1] Non-destructive assessment of the myoglobin content of Tan sheep using hyperspectral imaging
    Cheng, Lijuan
    Liu, Guishan
    He, Jianguo
    Wan, Guoling
    Ma, Chao
    Ban, Jingjing
    Ma, Limin
    MEAT SCIENCE, 2020, 167
  • [2] Nondestructive detection for internal qualities of Tan-sheep meat using NIR hyperspectral imaging technique
    Wang, Jia-Yun
    Wang, Song-Lei
    He, Xiao-Guang
    He, Jian-Guo
    Wu, Long-Guo
    Liu, Gui-Shan
    Modern Food Science and Technology, 2014, 30 (06) : 257 - 262
  • [3] Rapid and Non-Destructive Detection of Tan Sheep Meat MetMb Contents Using Hyperspectral Imaging
    Cheng Li-juan
    Liu Gui-shan
    He Jian-guo
    Wan Guo-ling
    Ma Chao
    Ban Jing-jing
    Ma Li-min
    Yang Guo-hua
    Yuan Rui-rui
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40 (04) : 1263 - 1269
  • [4] Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging
    Mo, Changyeun
    Kim, Giyoung
    Lim, Jongguk
    Kim, Moon S.
    Cho, Hyunjeong
    Cho, Byoung-Kwan
    SENSORS, 2015, 15 (11) : 29511 - 29534
  • [5] Detection of common defects on oranges using hyperspectral reflectance imaging
    Li, Jiangbo
    Rao, Xiuqin
    Ying, Yibin
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2011, 78 (01) : 38 - 48
  • [6] Molecular cloning and polymorphism analysis of the prion protein gene in Tan sheep of Ningxia, China
    Xu, Lihua
    Zhang, Zhuming
    Zhou, Xiangmei
    Yin, Xiaomin
    Yang, Lifeng
    Zhao, Deming
    GENE, 2011, 485 (02) : 102 - 105
  • [7] Non-destructive detection of protein content in mulberry leaves by using hyperspectral imaging
    Li, Xunlan
    Peng, Fangfang
    Wei, Zhaoxin
    Han, Guohui
    Liu, Jianfei
    FRONTIERS IN PLANT SCIENCE, 2023, 14
  • [8] Detection of Soybean Protein Content in Fresh Minced Chicken Meat Using Hyperspectral Imaging
    Wang W.
    Jiang H.
    Jia B.
    Lu Y.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50 (12): : 357 - 364
  • [9] Prediction of soluble solids content of jujube fruit using hyperspectral reflectance imaging
    He, Jian Guo
    Luo, Yang
    Liu, Gui Shan
    Xu, Shuang
    Si, Zhen Hua
    He, Xiao Guang
    Wang, Song Lei
    MECHATRONICS AND INTELLIGENT MATERIALS III, PTS 1-3, 2013, 706-708 : 201 - +
  • [10] Detection of moisture content of edamame based on the fusion of reflectance and transmittance spectra of hyperspectral imaging
    Li, Bin
    Su, Cheng-tao
    Yin, Hai
    Zou, Ji-ping
    Liu, Yan-de
    JOURNAL OF CHEMOMETRICS, 2024, 38 (09)