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Relationships between Characteristics of Wheat Canopy and Leaf Spectral Reflectance and Yield under Different Nitrogen Treatments |
GENG Shi-ying, SUN Hua-lin, WANG Xiao-yan*, XIONG Qin-xue*, ZHANG Jing-lin |
Agricultrual College of Yangtze University/Hubei Collaborative Innovation Center for Grain Industry,Jingzhou 434025,China |
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Abstract The use of remote sensing spectroscopy in predicting the application of nitrogen fertilizer is of great importance in protecting the environment and improving fertilizer use efficiency and grain yiled. In this study, we used the FieldSpec 4 Wide-Res Field Spectrum radiometer to measure the spectral characteristics and red-edge parameters of wheat canopies and leaves under different nitrogen applications. We proposed a new spectral index - the Normalized Difference Maximum Index. We analyzed the correlations between Normalized Difference Maximum Index and leaf area index (LAI), SPAD (Soil and Plant Analyzer Development) value, MDA (Malondialdehyde) content, nitrogen content in flag leaf and yield. Twenty six days after flowering, the original spectrum of the spectral reflectance of leaves was the highest in the range of 800~1 330 nm for the N3 (1/3 starter fertilizer+1/3 pre-winter topdressing + 1/3 jointing stage topdressing) treatment, followed by the N1 treatment (1/2 starter fertilizer+1/2 pre-winter topdressing). The application of one-third of nitrogen fertilizer in both pre-winter and jointing stages enhanced the photosynthetic capacity of the leaves. The original spectrum of the spectral reflectance of canopies in the range of 400~700 nm was the lowest for the N2 (1/2 starter fertilizer+1/2 jointing stage topdressing) treatment. The spectral reflectance of the N1 treatment was the highest in the range of 760~1 368 nm followed by the N3 freatment. The canopy spectral reflectance of the N3 treatment was the highest at 26 d and 33 d after flowering. It is recommended to use the canopy raw spectral data in the ranges of 400~700 nm and 760~1 368 nm to measure flag leaf nitrogen content and to decide fertilizer application model. Two peaks were found in the range of 500~750 nm in the first-order differential spectrum of the leaf. The model of nitrogen application could be estimated by the degree of positional shift of the peaks and the offset periods. Of the canopy, the first-order differential spectral value in the range of 670~740 nm was the highest in flowering stage, and the lowest at 10th day after flowering. The first-order differential spectral value of the N1 treatment was higher than that of the N3 treatment for the first 10 days after flowering, but lower than the N3 treatment at late grain filling stage. Our results indicated that the first-order differential maximum value can be used to predict the growth stages and efficient fertilizer application. From flowering stage to mid-grain-filling stage, the highest first-order derivative (FD-Max) of canopy reflectance was the highest in the N1 treatment, followed by the N3 treatment 26 to 33d after flowering, the population structure of the N3 treatment is denser than the other treatments, resulting in the highest first-order derivation maximum. Less differences among different treatments were found on the maximum value of the first derivative of leaves. The red boundary position (REPFD-Max) of the N1, N3 canopy shifted significantly after the mid-grain-filling stage. 26 d to 33 d after flowering, the N3 treatment ended up with a dense upper structure and wide and thick leaves. Applying nitrogen fertilizer before winter affected the REPFD-Max migration. Based on the NDVI, we have developed a new index-the Normalized Difference Maximum Index (NDMI). The maximum canopy normalized index (CNDMI) showed a better correlation with agrochemical parameters than the leaf maximum normalized index (LNDMI). Similarly, a better correlation was also found between CNDMI and yiled. The maximum index of normalized canopy differences was significantly correlated with nitrogen content (r=0.81), SPAD value (r=0.92) and MDA content (r=-0.72) in flag leaves. In summary, the spectral data and red edge parameters can be used to predict nitrogen levels in leaves, growth stages and the model of nitrogen fertilizer application. It provides a basis for filed fertilization management and fertilization diagnosis. CNDMI has a better correlation with wheat yiled. CNDMI with a spectrum band falling into China’s resource satellites can be practically used in the diagnosis and management of fertilizer application.
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Received: 2018-02-05
Accepted: 2018-06-14
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Corresponding Authors:
WANG Xiao-yan, XIONG Qin-xue
E-mail: wamail_wang@163.com; 17646838@qq.com
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[1] Gajjar R B,Shekh A M,Dave A J,et al. Indian Soc. Remote Sens,2005,33(1):147.
[2] Shapira H U,Karnieli K A,Bonfil D J. Precision Agric,2013,14:637.
[3] LU Jun-jing,HUANG Wen-jiang,ZHANG Jing-cheng,et al(鲁军景,黄文江,张竞成,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2016,36(6):1854.
[4] HU Hao,BAI You-lu,YANG Li-ping,et al(胡 昊,白由路,杨俐苹,等). Plant Nutrition and Fertilizer Science(植物营养与肥料学报),2009,15(6):1317.
[5] Pradhan S,Bandyopadhyay K K,Sahoo R N,et al. Journal of the Indian Society of Remote Sensing,2014,42(4):711.
[6] Bowman B C,Chen J,Zhang J,et al. Crop Science,2015,55:1881.
[7] ZHANG Wei,PAN Jian-jun,LI Yong,et al(张 威,潘剑君,李 勇,等). Chinese Journal of Soil Science(土壤通报),2015,46(1):169.
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