Nanchang Normal University, Nanchang, China
In order to better observe rice leaf color, and predict SPAD value, this paper will be based on computer vision analysis, analysis will elaborate computer vision technology, and then design computer vision observation scheme and SPAD value prediction model, through the scheme and model to obtain rice leaf color, predict SPAD value. The results can be used in the field of rice planting and provide support for rice planting technology.
Computer vision, Rice leaf color, SPAD value prediction
LIU Wang-qin. Prediction Model Analysis of Rice Leaf Color and SPAD Value Based on Computer Vision. The Frontiers of Society, Science and Technology (2020) Vol. 2 Issue 10: 58-61. https://doi.org/10.25236/FSST.2020.021014.
 Qiang W, Lei X,Yanna R, et al (2012). Determination of tobacco leaf maturity degree based on computer vision technology[J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol.28, no.4, pp.175-179.
 Wang Y, Wang D, Zhang G, et al (2012). Digital camera-based image segmentation of rice canopy and diagnosis of nitrogen nutrition [J].Transactions of the Chinese Society of Agricultural Engineering, vol. 28, no.17, pp.131-136.
 None (2014). A Review of Optical Methods for Assessing Nitrogen Contents During Rice Growth [J].Applied Engineering in Agriculture, vol.30, no.4, pp.657-669.
 Cavallo D P, Cefola M, Pace B, et al (2017). Contactless and non-destructive chlorophyll content prediction by random forest regression: A case study on fresh-cut rocket leaves[J].Computers and electronics in agriculture, no.140, pp.303-310.