Ｒapid Diagnosis Technology of Wheat Stem Number
 Based on Canopy Image Processing

LIU Jiahuan, ZHENG Chengjuan, LI Yun, LI Zengyuan, FU Haoran, ZHANG Weifeng

doi:10.15933/j.cnki.1004-3268.2019.11.024

Journal of Henan Agricultural Sciences >

2019 , Vol. 48 >Issue 11: 174 - 180

DOI: https://doi.org/10.15933/j.cnki.1004-3268.2019.11.024

Agricultural Information and Engineering and Agricultural Product Processing

Ｒapid Diagnosis Technology of Wheat Stem Number Based on Canopy Image Processing

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( 1.College of Ｒesources and Environmental Sciences,China Agricultural University,Beijing 100094,China; 2.Beijing Xingnong Fenghua Technology Co.,Ltd.,Beijing 100094,China)

Received date: 2018-12-23

Online published: 2019-11-15

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Abstract

In order to improve the diagnostic efficiency of wheat population,the feasibility of using image recognition instead of manual sampling counting was studied.The number of stems in the four stages of seedling,pre-wintering,reviving and jointing at 105 wheat fields in Yangxin County,Shandong Province were diagnosed from 2016 to 2017 by smart phone,UAV and manual sampling counting,respectively.The results showed that,the correlations of smart phone image recognition and manual sampling counting in the four growth stages were pre-wintering stage(^Ｒ2=0.900，P＜0.001 0)＞jointing stage (Ｒ²=0. 240,P＜0.001 0)＞reviving stage (Ｒ²=0.130，P＜0.001 0)＞seedling stage (Ｒ²=0.010,P＜0.290 0);The correlations of UAV image recognition and manual sampling counting in the three growth stages were pre-wintering stage(Ｒ²=0.760,P＜0.001 0)reviving stage(Ｒ²=0.320,P＜0.010 0)＞seedling stage (Ｒ²=0.005，P＜0.880 0).In terms of diagnostic efficiency,manual sampling counting unit took about 100.0 min/ha,smart phone image recognition unit took about 5.0 min/ha,while UAV image recognition took about 1.5 min/ha.The results show that smart phone image recognition can be used for wheat population size diagnosis in pre-wintering to jointing stage,and the diagnosis accuracy is highest in the pre-wintering stage.For large-area wheat fields，the method of UAV image recognition can be used for wheat population size diagnosis in pre-winterring and reviving stage．

Key words： Wheat stems number; Canopy image; Ｒapid diagnosis; Population; Smart phone; UAV

Cite this article

LIU Jiahuan, ZHENG Chengjuan, LI Yun, LI Zengyuan, FU Haoran, ZHANG Weifeng . Ｒapid Diagnosis Technology of Wheat Stem Number Based on Canopy Image Processing[J]. Journal of Henan Agricultural Sciences, 2019 , 48(11) : 174 -180 . DOI: 10.15933/j.cnki.1004-3268.2019.11.024

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