title: Identification of nitrogen, phosphorus, and potassium deficiencies in rice based on static scanning technology and hierarchical identification method.
abstract: Establishing an accurate, fast, and operable method for diagnosing crop nutrition is very important for crop nutrient management. In this study, static scanning technology was used to collect images of a rice sample's fully expanded top three leaves and corresponding sheathes. From these images, 32 spectral and shape characteristic parameters were extracted using an RGB mean value function and using the Regionprops function in MATLAB. Hierarchical identification was used to identify NPK deficiencies. First, the normal samples and non-normal (NPK deficiencies) samples were identified. Then, N deficiency and PK deficiencies were identified. Finally, P deficiency and K deficiency were identified. In the identification of every hierarchy, SVFS was used to select the optimal characteristic set for different deficiencies in a targeted manner, and Fisher discriminant analysis was used to build the diagnosis model. In the first hierarchy, the selected characteristics were the leaf sheath R, leaf sheath G, leaf sheath B, leaf sheath length, leaf tip R, leaf tip G, leaf area and leaf G. In the second hierarchy, the selected characteristics were the leaf sheath G, leaf sheath B, white region of the leaf sheath, leaf B, and leaf G. In the third hierarchy the selected characteristics were the leaf G, leaf sheath length, leaf area/leaf length, leaf tip G, difference between the 2nd and 3rd leaf lengths, leaf sheath G, and leaf lightness. The results showed that the overall identification accuracies of NPK deficiencies were 86.15, 87.69, 90.00 and 89.23% for the four growth stages. Data from multiple years were used for validation, and the identification accuracies were 83.08, 83.08, 89.23 and 90.77%.
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Lisu
authors.initials: L
authors.lastname: Chen
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Lin
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Guangzhe
authors.initials: G
authors.lastname: Cai
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Ke
authors.initials: K
authors.lastname: Wang
authors.affiliation: Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Jinsong
authors.initials: J
authors.lastname: Deng
mesh_terms: D007091:Image Processing, Computer-Assisted; D009584:Nitrogen / Q000032:analysis* / Q000172:deficiency; D009753:Nutritive Value; D012275:Oryza / Q000254:growth & development / Q000378:metabolism*; D010758:Phosphorus / Q000032:analysis* / Q000172:deficiency; D010788:Photosynthesis / Q000502:physiology; D018515:Plant Leaves / Q000254:growth & development / Q000378:metabolism*; D011188:Potassium / Q000032:analysis* / Q000378:metabolism; D012680:Sensitivity and Specificity; D013057:Spectrum Analysis / Q000379:methods
chemical_list: D010758:Phosphorus; D009584:Nitrogen; D011188:Potassium