Abstract : A rapid and nondestructive way to measure protein
and amylose content of rice was put forward based on near infrared(NIR)
spectral technology. The NIR spectra were acquired from 13 varieties of
rice with the wavelength from700 to 1100nm. The objectives of the
present study were to establish forecasting model to find out the
relationship between the absorbance of the spectrum and the main
components of rice. By using the machine vision-based method, the rice
appearance quality can be studied. On the basis of the evaluation
criteria, 13 different kinds of rice were classified. And according to
the usage of neural network, the detection model was established, so it
can lay the foundation for the prediction grade of the unknown kinds of
rice in the future.
Daoliang Li; Chunjiang Zhao. Third IFIP TC 12 International Conference on Computer and Computing Technologies in Agriculture III (CCTA), Oct 2009, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-317, pp.523-531, 2010, Computer and Computing Technologies in Agriculture III. 〈10.1007/978-3-642-12220-0_76〉
https://hal.inria.fr/hal-01055403
Contributeur : Hal Ifip
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Soumis le : mardi 12 août 2014 - 17:42:51
Dernière modification le : mardi 8 août 2017 - 17:16:46
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 23:12:22
Ruokui Chang, Weiyu Zhang, Jing Cui, Yuanhong Wang, Yong Wei, et al.. Research of Rice-Quality Based on Computer
Vision and Near Infrared Spectroscopy. Daoliang Li; Chunjiang Zhao. Third IFIP TC 12 International Conference on Computer and Computing Technologies in Agriculture III (CCTA), Oct 2009, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-317, pp.523-531, 2010, Computer and Computing Technologies in Agriculture III. 〈10.1007/978-3-642-12220-0_76〉. 〈hal-01055403〉
