[1]李瑞鑫,张宝林,潘丽杰,等.不同无人机飞行高度下玉米叶片叶绿素相对含量的无人机遥感反演及其指示叶位的识别[J].江苏农业学报,2024,(07):1234-1244.[doi:doi:10.3969/j.issn.1000-4440.2024.07.010]
　LI Ruixin,ZHANG Baolin,PAN Lijie,et al.Unmanned aerial vehicle remote sensing inversion of relative chlorophyll content of maize leaves and identification of their indicator leaf at different flight altitudes[J].,2024,(07):1234-1244.[doi:doi:10.3969/j.issn.1000-4440.2024.07.010]
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不同无人机飞行高度下玉米叶片叶绿素相对含量的无人机遥感反演及其指示叶位的识别()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2024年07期
页码:
1234-1244
栏目:
农业信息工程
出版日期:
2024-07-30

文章信息/Info

Title:
Unmanned aerial vehicle remote sensing inversion of relative chlorophyll content of maize leaves and identification of their indicator leaf at different flight altitudes
作者:
李瑞鑫1; 张宝林1; 2; 3; 潘丽杰1; 牛潘婷1; 斯琴高娃1; 何美玲1
(1.内蒙古师范大学化学与环境科学学院,内蒙古呼和浩特010020；2.内蒙古自治区环境化学重点实验室,内蒙古呼和浩特010020；3.内蒙古节水农业工程研究中心,内蒙古呼和浩特010020)
Author(s):
LI Ruixin1; ZHANG Baolin1; 2; 3; PAN Lijie1; NIU Panting1; Siqingaowa1; HE Meiling1
(1.College of Chemistry and Environmental Science, Inner Mongolia Normal University, Hohhot 010020, China;2.Inner Mongolia Key Laboratory of Environmental Chemistry, Hohhot 010020, China;3.Inner Mongolia Water-saving Agriculture Engineering Research Center, Hohhot 010020, China)
关键词:
玉米; 叶绿素; 无人机; 遥感; 指示叶位; 智能
Keywords:
maize; chlorophyll; unmanned aerial vehicle; remote sensing; indicator leaf; intelligence
分类号:
X87
DOI:
doi:10.3969/j.issn.1000-4440.2024.07.010
文献标志码:
A
摘要:
玉米叶片叶绿素含量的空间异质性对其监测精度有影响。本研究旨在基于无人机遥感技术探究玉米叶片叶绿素相对含量(SPAD值)与植被指数间的关系,从而明确指示叶位、无人机的最佳飞行高度。采用随机森林法构建基于植被指数的叶绿素相对含量遥感估算模型,并进行模型的评价。结果表明,玉米灌浆期叶片的叶绿素相对含量高于乳熟期叶片的叶绿素相对含量,植株中部叶片的叶绿素相对含量高于上部、下部叶片的叶绿素相对含量。在玉米灌浆期与乳熟期,玉米叶片SPAD值的指示叶位为第5叶,当无人机飞行高度为20 m时,模型的精度最高[决定系数(R2)=0.94]。研究结果可为提高叶绿素相对含量遥感监测的精度提供技术支撑,并为农作物的田间智能化管理提供理论依据。
Abstract:
The detection accuracy of chlorophyll content in maize leaves is affected by spatial heterogeneity. The purpose of this study was to investigate the relationship between relative chlorophyll content (SPAD value) and vegetation indices of maize leaves based on unmanned aerial vehicle (UAV) remote sensing technology, so as to clarify the indicator leaf and the best UAV flying altitude. The remote sensing estimation model of relative chlorophyll content based on vegetation indices was constructed by random forest method, and the model was evaluated. The results showed that relative chlorophyll content in maize leaves at grain filling stage was higher than that at milking stage, and relative chlorophyll content of middle leaves was higher than that of upper and lower leaves. During the grain filling stage and milking stage, the SPAD value of maize leaves was indicated by the fifth leaf, and the best precision for the regression model (R2=0.94) was obtained when the flying altitude of UAV was 20 m. The results can provide technical support for improving the accuracy of remote sensing monitoring of relative chlorophyll content, and provide theoretical basis for crop smart management in the fields.

参考文献/References:

[1]张国庆,黄楠,宋茜,等. 基于叶绿素含量的玉米长势遥感监测的研究[J]. 黑龙江科技信息,2013(19):6.
[2]谢东辉,朱启疆,王锦地,等. 基于真实三维结构的玉米冠层生化参数垂直分布的定量化分析[J]. 北京师范大学学报(自然科学版),2007,43(3):337-342.
[3]潘丽杰,张宝林,李瑞鑫,等. 玉米不同叶位叶片叶绿素含量垂直分布研究进展[J]. 北方农业学报,2023,51(4):28-37.
[4]王群瑛,胡昌浩. 玉米不同叶位叶片叶绿体超微结构与光合性能的研究[J]. 植物学报,1988,30(2):146-150.
[5]童淑媛,宋凤斌,徐洪文. 玉米不同叶位叶片SPAD值的变化及其与生物量的相关性[J]. 核农学报,2008,22(6):869-874.
[6]HUANG W J, WANG Z J, HUANG L S, et al. Estimation of vertical distribution of chlorophyll concentration by bi-directional canopy reflectance spectra in winter wheat[J]. Precision Agriculture,2011,12(2):165-178.
[7]朱延姝,郭丽丽,崔震海,等. 光强对玉米幼苗不同叶位叶片叶绿素荧光参数的影响[J]. 吉林农业科学,2013,38(4):1-4,14.
[8]王丹,赵朋,孙家波,等. 基于无人机多光谱的夏玉米叶绿素含量反演研究[J]. 山东农业科学,2021,53(6):121-126,132.
[9]郭铌. 植被指数及其研究进展[J]. 干旱气象,2003,21(4):71-75.
[10]徐晋,蒙继华. 农作物叶绿素含量遥感估算的研究进展与展望[J]. 遥感技术与应用,2016,31(1):74-85.
[11]敖登,杨佳慧,丁维婷,等. 54种植被指数研究进展综述[J]. 安徽农业科学,2023,51(1):13-21,28.
[12]田婷,张青,张海东. 无人机遥感在作物监测中的应用研究进展[J]. 作物杂志,2020(5):1-8.
[13]WU B, YE H C, HUANG W J, et al. Monitoring the vertical distribution of maize canopy chlorophyll content based on multi-angular spectral data[J]. Remote Sensing,2021,13(5):987.
[14]何勇,杜晓月,郑力源,等. 无人机飞行高度对植被覆盖度和植被指数估算结果的影响[J]. 农业工程学报,2022,38(24):63-72.
[15]井宇航,郭燕,张会芳,等. 无人机飞行高度对冬小麦植株氮积累量预测模型的影响[J]. 河南农业科学,2022,51(2):147-158.
[16]刘涛,张寰,王志业,等. 利用无人机多光谱估算小麦叶面积指数和叶绿素含量[J]. 农业工程学报,2021,37(19):65-72.
[17]郭松,常庆瑞,郑智康,等. 基于无人机高光谱影像的玉米叶绿素含量估测[J]. 江苏农业学报,2022,38(4):976-984.
[18]张银杰,王磊,白由路,等. 玉米不同层位叶片生理生化指标与SPAD值的关系[J]. 植物营养与肥料学报,2020,26(10):1805-1817.
[19]马明洋,许童羽,周云成,等. 东北粳稻叶绿素相对含量的无人机高清影像检测方法[J]. 沈阳农业大学学报,2017,48(6):757-762.
[20]WOEBBECKE D M, MEYER G E, VON BARGEN K, et al. Color indices for weed identification under various soil,residue,and lighting conditions[J]. Transactions of the ASAE,1995,38(1):259-269.
[21]王方永,王克如,李少昆,等. 利用数码相机和成像光谱仪估测棉花叶片叶绿素和氮素含量[J]. 作物学报,2010,36(11):1981-1989.
[22]PEUELAS J, GAMON J A, FREDEEN A L, et al. Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves[J]. Remote Sensing of Environment,1994,48(2):135-146.
[23]魏全全,李岚涛,任涛,等. 基于数字图像技术的冬油菜氮素营养诊断[J]. 中国农业科学,2015,48(19):3877-3886.
[24]SELLARO R, CREPY M, TRUPKIN S A, et al. Cryptochrome as a sensor of the blue/green ratio of natural radiation in Arabidopsis[J]. Plant Physiology,2010,154(1):401-409.
[25]VERRELST J, SCHAEPMAN M E, KOETZ B, et al. Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data[J]. Remote Sensing of Environment,2008,112(5):2341-2353.
[26] KAWASHIMA S, NAKATANI M. An algorithm for estimating chlorophyll content in leaves using a video camera[J]. Annals of Botany,1998,81(1):49-54.
[27]汪小钦,王苗苗,王绍强,等. 基于可见光波段无人机遥感的植被信息提取[J]. 农业工程学报,2015,31(5):152-157,159,158.
[28]PEUELAS J, GAMON J A, FREDEEN A L, et al. Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves[J]. Remote Sensing of Environment,1994,48(2):135-146.
[29]HUNT E R, CAVIGELLI M, DAUGHTRY C S T, et al. Evaluation of digital photography from model aircraft for remote sensing of crop biomass and nitrogen status[J]. Precision Agriculture,2005,6(4):359-378.
[30]SHIBAYAMA M, SAKAMOTO T, TAKADA E, et al. Estimating rice leaf greenness (SPAD) using fixed-point continuous observations of visible red and near infrared narrow-band digital images[J]. Plant Production Science,2012,15(4):293-309.
[31]井然,邓磊,赵文吉,等. 基于可见光植被指数的面向对象湿地水生植被提取方法[J]. 应用生态学报,2016,27(5):1427-1436.
[32]马红雨,李仙岳,孙亚楠,等. 基于无人机遥感的不同控释肥夏玉米SPAD差异性[J]. 排灌机械工程学报,2023,41(12):1261-1267.
[33]李靖言,颜安,宁松瑞,等. 基于高光谱植被指数的春小麦LAI和SPAD值及产量反演模型研究[J]. 江苏农业科学,2023,51(20):201-210.
[34]李皓轩,朱杰,周勇,等. 叶面肥与穗肥互作对稻虾共作水稻抽穗后光合特性、产量性状及稻米品质的影响[J]. 南方农业学报,2023,54(4):1095-1105.
[35]吴秀宁,张军,王凤娟,等. 肥密互作对旱地冬小麦商麦1619旗叶光合特性、干物质积累和产量的影响[J]. 江苏农业学报,2022,38(4):924-930.
[36]李雪梅,黄禹翕,蔡晓婧,等. 外源氯化钙对铅胁迫下水稻幼苗生长、SPAD值和荧光特性的影响[J]. 江苏农业科学,2022,50(14):73-79.
[37]刘玲,冯乃杰,郑殿峰,等. 不同微生物菌剂对水稻幼苗形态建成和生理特性的影响[J]. 南方农业学报,2022,53(1):88-95.
[38]胡昌浩,王群瑛. 玉米不同叶位叶片叶绿素含量与光合强度变化规律的研究[J]. 山东农业大学学报,1989,20(1):43-47.
[39]陈岭,孙耀邦,崔绍平. 玉米穗部性状的基因效应分析[J].华北农学报,1996,11(2):28-32.
[40]姜上川. 玉米单叶面积生长变化曲线研究[J]. 现代化农业,2009(2):12-15.
[41]CIGANDA V S, GITELSON A A, SCHEPERS J. How deep does a remote sensor sense?Expression of chlorophyll content in a maize canopy[J]. Remote Sensing of Environment,2012,126:240-247.
[42]刘燕婕,李建设,高艳明. 可见光波段不同氮处理生菜叶片光谱反射率与叶片全氮、叶绿素的相关性研究[J]. 北方园艺,2015(22):12-16.
[43]LIVESLEY S J, MCPHERSON E G, CALFAPIETRA C. The urban forest and ecosystem services:impacts on urban water,heat,and pollution cycles at the tree,street,and city scale[J]. Journal of Environmental Quality,2016,45(1):119-124.
[44]ZHU W X, SUN Z G, YANG T, et al. Estimating leaf chlorophyll content of crops via optimal unmanned aerial vehicle hyperspectral data at multi-scales[J]. Computers and Electronics in Agriculture,2020,178:105786.
[45]王方永. 基于近地可见光成像传感器的棉花生长信息监测研究[D]. 石河子:石河子大学,2011.
[46]LI F, MIAO Y X, HENNIG S D, et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages[J]. Precision Agriculture,2010,11(4):335-357.
[47]冯浩,杨祯婷,陈浩,等. 基于无人机多光谱影像的夏玉米SPAD估算模型研究[J]. 农业机械学报,2022,53(10):211-219.
[48]袁媛,瑚波,武兴厚,等. 基于植被指数的夏玉米不同生育期叶绿素含量遥感估算[J]. 中国农学通报,2015,31(15):254-259.
[49]LUNDBERG S M, LEE S I. A unified approach to interpreting model predictions[C]. Long Beach:NIPSF,2017.
[50]贺英,邓磊,毛智慧,等. 基于数码相机的玉米冠层SPAD遥感估算[J]. 中国农业科学,2018,51(15):66-77.
[51]刘启兴,景海涛,董国涛. 无人机高分辨率遥感影像分类方法研究[J]. 计算机与数字工程,2019,47(3):638-642,727.

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备注/Memo

备注/Memo:
收稿日期：2024-03-22基金项目：内蒙古自然科学基金项目(2022LHMS03009)；内蒙古自治区科技重大专项(2021ZD0003-1)；内蒙古师范大学基本科研业务费专项(2022JBTD009)作者简介：李瑞鑫(1998-),男,内蒙古巴彦淖尔人,硕士研究生,研究方向为环境遥感。(E-mail)1443637569@qq.com通讯作者：张宝林,(E-mail)zhangbl@imnu.edu.cn
更新日期/Last Update: 2024-09-14