[1]苗梦珂,王宝山,李长春,等.基于连续小波变换的冬小麦叶片最大净光合速率遥感估算[J].江苏农业学报,2020,(03):544-552.[doi:doi:10.3969/j.issn.1000-4440.2020.03.003]
　MIAO Meng-ke,WANG Bao-shan,LI Chang-chun,et al.Remote sensing estimation of maximum net photosynthetic rate of winter wheat leaves based on continuous wavelet transform[J].,2020,(03):544-552.[doi:doi:10.3969/j.issn.1000-4440.2020.03.003]
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基于连续小波变换的冬小麦叶片最大净光合速率遥感估算()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年03期
页码:
544-552
栏目:
遗传育种·生理生化
出版日期:
2020-06-30

文章信息/Info

Title:
Remote sensing estimation of maximum net photosynthetic rate of winter wheat leaves based on continuous wavelet transform
作者:
苗梦珂1; 2; 3; 4; 王宝山1; 李长春1; 龙慧灵2; 3; 4; 杨贵军2; 3; 4; 冯海宽2; 3; 4; 翟丽婷2; 3; 4; 刘明星2; 3; 4; 吴智超2; 3; 4
（1.河南理工大学，河南焦作454000；2.农业部农业遥感机理与定量遥感重点实验室/北京农业信息技术研究中心，北京100097；3.国家农业信息化工程技术研究中心，北京100097；4.北京市农业物联网工程技术研究中心，北京100097）
Author(s):
MIAO Meng-ke1; 2; 3; 4; WANG Bao-shan1; LI Chang-chun1; LONG Hui-ling2; 3; 4; YANG Gui-jun2; 3; 4; FENG Hai-kuan2; 3; 4; ZHAI Li-ting2; 3; 4; LIU Ming-xing2; 3; 4; WU Zhi-chao2; 3; 4
(1.Henan Polytechnic University, Jiaozuo 454000, China;2.Key Laboratory of Quantitative Remote Sensing in Agriculture, Ministry of Agriculture/ Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;3.National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China;4.Beijing Engineering Research Center for Agriculture Internet of Things, Beijing 100097, China)
关键词:
连续小波变换; 最大净光合速率; 植被指数; 高光谱
Keywords:
continuous wavelet transform; maximum net photosynthetic rate; vegetation index; hyper-spectrum
分类号:
S512
DOI:
doi:10.3969/j.issn.1000-4440.2020.03.003
文献标志码:
A
摘要:
已有研究发现，植物的最大净光合速率（Amax）决定了其潜在的光合能力。以冬小麦为研究对象，以2017年、2018年4-6月获取的拔节期、挑旗期、开花期和灌浆期4个重要生育期的不同叶位叶片的原始光谱（350～1 350 nm）与气体交换数据为基础，旨在建立基于连续小波变换的冬小麦叶片最大净光合速率估算模型。结果表明，基于连续小波变换方法估算的模型，2017年、2018年的建模决定系数（R2）分别为0.62、0.77，验证R2分别为0.65、0.77，其估算模型的精度远高于基于植被指数建立的模型。通过对比分析几种植被指数与高光谱数据对最大净光合速率的估算结果发现，植被指数对小麦叶片Amax的解释能力较低，无法对光合能力作出正确且精确的估算。基于连续小波变换方法对冬小麦叶片Amax的估算精度较高，可以作为预估冬小麦生长状况、产量的依据。
Abstract:
Present studies have shown that the maximum net photosynthetic rate (Amax) of a plant determines its potential capacity in photosynthesis. Winter wheat was taken as the research object， the data of original spectra (350-1 350 nm) and gas exchange in different leaf positions in four important growth periods such as elongation stage, flagging stage, flowering stage and filling stage were obtained from April to June in 2017 and 2018. The estimation model for Amax of winter wheat leaves was established based on continuous wavelet transform. The results showed that determination coefficients (R2) of the model established by continuous wavelet transform in 2017 and 2018 were 0.62 and 0.77 respectively, while the determination coefficients in the verification were 0.65 and 0.77 respectively. The accuracy of the estimation model based on continuous wavelet transform was much higher than that based on the vegetation index. By comparing and analyzing several Amax results estimated by vegetation indices and hyperspectral data, it was found that the vegetation index showed a low ability in explaining Amax, and it couldn’t make a correct and accurate estimation of photosynthetic capacity. The method based on continuous wavelet transform is more accurate in the estimation of Amax, which can be used as the basis for predicting the growth status and yield of winter wheat.

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备注/Memo

备注/Memo:
收稿日期：2019-12-05基金项目：：国家重点研发计划项目（2018YFF0213602）；国家自然科学基金项目（41301475、41601346）；北京市农林科学院博士后基金项目；河南省科技攻关项目（1821021101186）作者简介：苗梦珂（1994-），女，河南永城人，硕士，研究实习员，主要从事生态遥感研究。（E-mail）Mengkemiao17@163.com通讯作者：龙慧灵，（E-mail）longhl@nercita.org.cn
更新日期/Last Update: 2020-07-14