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Acta Agronomica Sinica ›› 2021, Vol. 47 ›› Issue (1): 177-184.doi: 10.3724/SP.J.1006.2021.03011

• RESEARCH NOTES • Previous Articles    

Remote sensing monitoring on maize flood stress and yield evaluation at different stages

SUI Xue-Yan1(), LIANG Shou-Zhen1(), ZHANG Jin-Ying2, WANG Meng1, WANG Yong1, HOU Xue-Hui1, ZHANG Xiao-Dong3,*()   

  1. 1Shandong Institute of Agricultural Sustainable Development / Key Laboratory of East China Urban Agriculture, Ministry of Agriculture and Shandong Rural Affairs, Jinan 250100, Shandong, China
    2Shandong Provincial Institute of Land Surveying and Mapping, Jinan 250013, Shandong, China
    3Shandong Center of Crop Germplasm Resources, Jinan 250100, Shandong, China
  • Received:2020-02-28 Accepted:2020-08-20 Online:2021-01-12 Published:2020-09-10
  • Contact: ZHANG Xiao-Dong E-mail:sdnkysxy@163.com;szliang_cas@163.com;zxdong2002@163.com
  • Supported by:
    Agricultural Great Application Technology Innovative Projects of Shandong Province(1-0504);Agricultural and Rural Resources Monitoring and Statistics Projects of Ministry of Agriculture and Rural Affairs(061721301112422018)

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Abstract:

In order to set up remote sensing monitoring and evaluation technology of maize flood stress and loss, a simulation experiment with different flood stress degrees was developed at different stages. Chlorophyll content, canopy spectral reflectance and coverage were monitored in vivo, and yield level was tested finally. The results showed that chlorophyll content decreased under flood stress at jointing and filling stages. The decreasing extend was significant at jointing stage and the value of maximal relative change reached -56.30%. There was little influence on chlorophyll at silking stage. Flood stress could reduce the coverage, especially at jointing stage, the most serious treatment was only 46.33%, followed by silking stage and filling stage. Flood stress reduced production at last, and the reduction was more serious in the early stage than in the later stage. There was a negative correlation between reflectance and flood stress degree at jointing stage and silking stage. It was extremely significantly difference at near infrared platform bands and significantly at green peak bands. There was no significant positive correlation between reflectance and flood stress degree at filling stage. Reflectance and spectral indexes with extremely significant correlation can be used to monitor flood. Two models with DSIPI were set up to evaluate flood loss at jointing and silking stage separately.

Key words: maize, flood stress, remote sensing, monitoring, evaluation

Table 1

Experimental design"

生长时期
Growing stage		 处理
Treatment		 胁迫持续天数
Flooding period (d)		 开始时间
Starting time (month/day)		 结束时间
Ending time (month/day)
拔节期
Jointing stage		 E-9 9 7/31 8/9
E-7 7 7/31 8/7
E-5 5 7/31 8/5
E-3 3 7/31 8/3
E-1 1 7/31 8/1
E-0 0 (CK)
吐丝期
Silking stage		 M-9 9 8/8 8/17
M-7 7 8/8 8/15
M-5 5 8/8 8/13
M-3 3 8/8 8/11
M-1 1 8/8 8/9
M-0 0 (CK)
灌浆期
Filling stage		 L-9 9 8/23 9/1
L-7 7 8/23 8/30
L-5 5 8/23 8/28
L-3 3 8/23 8/26
L-1 1 8/23 8/24
L-0 0 (CK)

Fig. 1

Chlorophyll content before and after flood stress in maize Treatments are the same as those given in Table 1. Different letters indicate significant differences among treatments at the 0.05 probability level."

Fig. 2

Effects of water stress on maize coverage degree Treatments are the same as those given in Table 1. Values marked with different letters indicate significant differences among treatments at the 0.05 probability level."

Fig. 3

Spectral reflectance curves of flooding stress treatments at jointing stage on August 14"

Fig. 4

Spectral reflectance curves of flooding stress treatments at silking stage on August 23"

Fig. 5

Spectral reflectance curves of flooding stress treatments at filling stage on September 3"

Fig. 6

Correlation between spectral reflectance and flooding stress period of treatments at different stages"

Table 2

Correlation of flooding stress period with spectral shape parameters and vegetation indexes"

名称
Parameters		 缩写
Abbreviation		 作者及年代
Author and year		 拔节期
Jointing stage		 吐丝期
Silking stage		 灌浆期
Filling stage
差值植被指数
Difference vegetation index		 DVI [867, 671] Richardso et al. (1977) [22] -0.9491** -0.8220* -0.3405
DVI [550, 464] -0.8906* -0.2548 -0.7216
DVI [550, 671] -0.9515** -0.6641 -0.6018
比值植被指数
Ratio vegetation index		 RVI [867, 671] -0.9274** -0.9373** 0.7446
归一化差值植被指数
Normalization difference
vegetation index		 NDVI [550, 671] Rouse et al. (1974) [23] 0.9635** 0.7552 -0.5113
NDVI [671, 867] -0.9432** -0.9481** 0.6828
红谷位置
Location of red valley		 λ0 Liu (2002) [24] -0.9660** -0.8396* 0.6613
红边峰值
Maximum value of the first
derivative at the red edge		 RFDMax -0.9614** -0.7990 -0.2701
吸收谷红谷深度
Depth of red absorption valley		 Depth [670] -0.9384** -0.7593 0.6003
反射峰绿峰深度
Depth of green peak		 P_Depth [540] -0.9378** -0.5346 0.5522
吸收谷红谷面积
Area of red absorption valley		 Area [670] -0.9378** -0.6942 0.6217
反射峰绿峰面积
Area of green reflectance peak		 P_Area [540] -0.9220** -0.5719 0.5028
红边位置
Red edge position		 λp -0.9194** -0.8586* 0.7817
红边宽度
Red edge width		 σ -0.7454 -0.7925 0.8302*
归一化反射峰绿峰深度
Normalized depth of green
reflectance peak		 P_ND [540] 0.5344 0.6719 0.7217
归一化吸收谷红谷深度
Normalized depth of red
absorption valley		 ND [670] 0.9020* 0.0476 -0.6463
抗大气植被指数
Visible atmospherically resistant index		 Vari700 Singh et al. (2002) [25] -0.9442** -0.8037 0.6074
VariGreen -0.9695** -0.8293* 0.5179
光化学反射指数
Photochemical reflectance index		 PRI [570, 531] Gamom et al. (1992) [26] -0.9546** -0.8661* 0.5112
最优土壤调节植被指数
Optimization of soil-adjusted
regulatory vegetation index		 OSAVI Rondeaux et al. (1996) [27] -0.9527** -0.8567* 0.2736
土壤调整植被指数
Soil-adjusted vegetation index		 SAVI Huete et al. (1988) [28] -0.9493** -0.8384* -0.1070
转化型叶绿素吸收反射指数
Tidal constituent and residual interpolation		 TCARI Haboudane et al. (2002) [29] -0.5457 -0.3166 -0.7241
叶绿素含量指数
Canopy chlorophyll inversion index		 CCII Haboudane et al. (2002) [29] 0.5441 0.6918 -0.7130
绿度指数
Green normalization difference vegetation index		 GreenNDVI Baret et al. (1991) [30] 0.8977* 0.8795* 0.8039
结构不敏感色素指数
Structure insensitive pigment index		 SIPI Penuelas et al. (1995) [31] 0.9514** 0.9564** -0.5422

Table 3

Model of maize yield loss rate under flooding stress at jointing stage and silking stage"

参数
Parameter		 参数计算公式
Parameter calculation
formula		 拔节期洪涝胁迫玉米产量损失率模型
Model of maize yield loss rate under flooding stress at jointing stage		 吐丝期洪涝胁迫玉米产量损失率模型
Model of maize yield loss rate under flooding stress at silking stage
DNDVI NDVIafter - NDVIbefore y = -86.051 x2 + 470.53 x + 9.5564
(-0.04 < x < 0.14, 0 < y < 75%)
R2 = 0.8969		 y = -2803.8 x2 - 586.71 x + 13.8
(-0.07 < x < 0.03, 0 < y < 45%)
R2 = 0.9337
DRVI RVIafter - RVIbefore y = -1163.9 x2 - 855.71 x + 9.8187
(-0.09 < x < 0.02, 0 < y < 75%)
R2 = 0.8951		 y = -9118.2 x2 + 1024.7 x + 13.888
(-0.02 < x < 0.05, 0 < y < 45%)
R2 = 0.9320
DSIPI SIPIafter - SIPIbefore y = -19600 x2 - 1985.3 x +15.814
(-0.06 < x < 0.01, 0 < y < 75%)
R2 = 0.9433		 y = -13599 x2 -814.11 x + 26.53
(-0.03 < x < 0.03, 0 < y < 45%)
R2 = 0.9697

Fig. 7

Fitting chart of maize yield loss rate with DSIPI under flooding stress at jointing stage"

Fig. 8

Fitting chart of maize yield loss rate with DSIPI under flooding stress at silking stage"

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