|
|
|
|
|
|
Effects of Different Fertilization Conditions on Canopy Spectral Characteristics of Winter Wheat Based on Hyperspectral Technique |
ZHANG Yue1, TIAN Yuan-sheng1, SUN Wen-yi1, 2*, MU Xing-min1, 2, GAO Peng1, 2, ZHAO Guang-ju1, 2 |
1. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China
2. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China |
|
|
Abstract Quantitative study of the relationship between soil nutrient content and canopy spectral characteristics of winter wheat based on hyperspectral techniques can provide theoretical basis and technical support for winter wheat nutrient abundance monitoring and scientific and rational guidance of fertilization programs. In a 35-year long-term positioning experiment, the effects of different fertilization treatments on the spectral characteristics of winter wheat canopy in different growth stages of Loess Plateau were studied. The results showed that under single fertilization conditions, compared with no fertilization (CK), from the jointing stage to the heading stage of the winter wheat, the CR500, CR670 and CR550 values of single P application were higher, while the spectral reflectance of single N and M application was significantly lower. The CR500 values of single P, N and M application in jointing stage were 1.2 times, 74.9% and 70.5% of CK; CR670 values were 1.2 times, 66.8% and 62.6% of CK; CR550 values were 1.2 times, 76.2% and 76.9% of CK, respectively. The peaks and valleys of the reflex characteristics of winter wheat were significantly enhanced at heading stage than those at jointing stage, at heading stage,the CR500 values of P, N and M application were 1.2 times, 81.0% and 53.5% of CK; the CR670 values were 1.3 times, 76.8% and 40.6% of CK; CR550 values were 1.2 times, 78.5% and 63.4% of CK, respectively. At the filling stage, the peaks and valleys of the reflex characteristics of each treatment were obviously weakened; to the maturity stage, the difference between the peaks and valleys of the winter wheat spectrum under different fertilization treatments was no longer obvious. The spectral characteristics of the red band position absorption valley under single fertilization conditions after enveloping line removal showed that, except for the maturity period, the red band absorption valley area (A), the red band absorption valley left area (AL) and the absorption peak symmetry (S) of winter wheat with single P application were higherthan CK, both with N and Mapplication were lower than CK. Under the combined fertilization conditions, the NMP, NP and NM of all nitrogen application combinations showed similar patterns, and the red, blue absorption depth and green reflection peak and the near-infrared spectral reflectance in the visible light range were significantly lower than CK; the spectral reflectance eigenvalue of the PM combined treatment was slightly lower than CK. Compared with CK, the characteristic value of spectral reflectance of PM combined treatment was slightly lower from the jointing stage to the heading stage; the difference between the spectral reflectance values of NM, NPM and NP treatment was small but significantly lower than CK. The CR500 values of NM, NPM and NP treatment were 25.85%, 27.99% and 26.07% of CK; CR670 values were 12.56%, 13.27% and 13.98% of CK; CR550 values were 33.39%, 35.38% and 37.04% of CK, respectively. The CR500, CR670 and CR550 values of PM treatment were 67.52%, 55.69% and 79.40% of CK, respectively. At grain filling stage, the peaks and valleys of each treatment were significantly weaker than those at heading stage. At maturity stage, the spectral reflectance absorption characteristics of different fertilization treatments were not significantly different, but they were significantly lower than CK. The spectral characteristics of red band absorption valley under combined fertilization conditions after enveloping line removal showed that the area of red band absorption valley (A) of the winter wheat was the largest in CK, followed by PM treatment and NM treatment.
|
Received: 2019-01-02
Accepted: 2019-05-10
|
|
Corresponding Authors:
SUN Wen-yi
E-mail: sunwy@ms.iswc.ac.cn
|
|
[1] ZHAO Jia-jia, FENG Mei-chen, YANG Wu-de,et al(赵佳佳,冯美臣,杨武德,等). Journal of Shanxi Agricultural Sciences(山西农业科学),2015,43(6):673.
[2] ZHANG Ying-shi(赵英时). Principle and Method of Analysis of Remote Sensing Application(遥感应用分析原理与方法). Beijing: Science Press(北京:科学出版社),2013. 36.
[3] HE Jia, LIU Bing-feng, LI Jun(贺 佳,刘冰锋,李 军). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2014,24(30): 141.
[4] WANG Fan, LI Min-yang(王 凡,李敏阳). Journal of Shanxi Agricultural Sciences(山西农业科学),2018, 46(5): 718.
[5] Fernandez S, Vidal D, Simon E, et al. International Journal of Remote Sensing, 2012, 15: 1867.
[6] YAO Fu-qi, CAI Huan-jie, SUN Jin-wei, et al(姚付启,蔡焕杰,孙金伟,等). Journal of Yangtze River Scientific Research Institute(长江学院院报),2015,32(3):95.
[7] LI Zhen-zhen, ZHENG Xiang, NIU De-kui, et al(李真真,郑 翔,牛德奎,等). Pratacultural Science(草业科学), 2016,33(8):1492.
[8] ZHAO Jun-wei, FENG Mei-chen, YANG WU-de(赵君伟,冯美臣,杨武德). Journal of Shanxi Agricultural Sciences(山西农业科学),2015,43(1):35.
[9] GAO Lin, WANG Xiao-fei, GU Xing-fa,et al(高 林,王晓菲,顾行发). Chinese Journal of Plant Ecology(植物生态学报),2017,41(12):1273.
[10] WANG Le-hui, JI Yu, SHU Fang, et al(王乐辉,吉 宇,舒 芳,等). Guangdong Meteorology(广东气象),2016,38(1): 61.
[11] CUI Bei, HUANG Wen-jiang, YANG Wu-de, et al(崔 贝,黄文江,杨武德,等). Plant Nutrition and Fertilizer Science(植物营养与肥料学报),2013, 19(1): 11.
[12] ZHAO Gang-feng, LI Jun, LIU Bing-feng(赵刚峰,李 军,刘冰峰). Journal of Triticeae Crops(麦类作物学报),2012, 32(3): 530. |
[1] |
WANG Cai-ling1,ZHANG Jing1,WANG Hong-wei2*, SONG Xiao-nan1, JI Tong3. A Hyperspectral Image Classification Model Based on Band Clustering and Multi-Scale Structure Feature Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 258-265. |
[2] |
GAO Hong-sheng1, GUO Zhi-qiang1*, ZENG Yun-liu2, DING Gang2, WANG Xiao-yao2, LI Li3. Early Classification and Detection of Kiwifruit Soft Rot Based on
Hyperspectral Image Band Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 241-249. |
[3] |
WU Hu-lin1, DENG Xian-ming1*, ZHANG Tian-cai1, LI Zhong-sheng1, CEN Yi2, WANG Jia-hui1, XIONG Jie1, CHEN Zhi-hua1, LIN Mu-chun1. A Revised Target Detection Algorithm Based on Feature Separation Model of Target and Background for Hyperspectral Imagery[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 283-291. |
[4] |
CHU Bing-quan1, 2, LI Cheng-feng1, DING Li3, GUO Zheng-yan1, WANG Shi-yu1, SUN Wei-jie1, JIN Wei-yi1, HE Yong2*. Nondestructive and Rapid Determination of Carbohydrate and Protein in T. obliquus Based on Hyperspectral Imaging Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3732-3741. |
[5] |
HUANG You-ju1, TIAN Yi-chao2, 3*, ZHANG Qiang2, TAO Jin2, ZHANG Ya-li2, YANG Yong-wei2, LIN Jun-liang2. Estimation of Aboveground Biomass of Mangroves in Maowei Sea of Beibu Gulf Based on ZY-1-02D Satellite Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3906-3915. |
[6] |
ZHOU Bei-bei1, LI Heng-kai1*, LONG Bei-ping2. Variation Analysis of Spectral Characteristics of Reclaimed Vegetation in an Ionic Rare Earth Mining Area[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3946-3954. |
[7] |
YUAN Wei-dong1, 2, JU Hao2, JIANG Hong-zhe1, 2, LI Xing-peng2, ZHOU Hong-ping1, 2*, SUN Meng-meng1, 2. Classification of Different Maturity Stages of Camellia Oleifera Fruit
Using Hyperspectral Imaging Technique[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3419-3426. |
[8] |
FU Gen-shen1, LÜ Hai-yan1, YAN Li-peng1, HUANG Qing-feng1, CHENG Hai-feng2, WANG Xin-wen3, QIAN Wen-qi1, GAO Xiang4, TANG Xue-hai1*. A C/N Ratio Estimation Model of Camellia Oleifera Leaves Based on
Canopy Hyperspectral Characteristics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3404-3411. |
[9] |
SHEN Ying, WU Pan, HUANG Feng*, GUO Cui-xia. Identification of Species and Concentration Measurement of Microalgae Based on Hyperspectral Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3629-3636. |
[10] |
XIE Peng, WANG Zheng-hai*, XIAO Bei, CAO Hai-ling, HUANG Yi, SU Wen-lin. Hyperspectral Quantitative Inversion of Soil Selenium Content Based on sCARS-PSO-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3599-3606. |
[11] |
QIAN Rui1, XU Wei-heng2, 3 , 4*, HUANG Shao-dong2, WANG Lei-guang2, 3, 4, LU Ning2, OU Guang-long1. Tea Plantations Extraction Based on GF-5 Hyperspectral Remote Sensing
Imagery in the Mountainous Area[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3591-3598. |
[12] |
ZHU Zhi-cheng1, WU Yong-feng2*, MA Jun-cheng2, JI Lin2, LIU Bin-hui3*, JIN Hai-liang1*. Response of Winter Wheat Canopy Spectra to Chlorophyll Changes Under Water Stress Based on Unmanned Aerial Vehicle Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3524-3534. |
[13] |
YANG Lei1, 2, 3, ZHOU Jin-song1, 2, 3, JING Juan-juan1, 2, 3, NIE Bo-yang1, 3*. Non-Uniformity Correction Method for Splicing Hyperspectral Imager Based on Overlapping Field of View[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3582-3590. |
[14] |
SUN Lin1, BI Wei-hong1, LIU Tong1, WU Jia-qing1, ZHANG Bao-jun1, FU Guang-wei1, JIN Wa1, WANG Bing2, FU Xing-hu1*. Identification Algorithm of Green Algae Using Airborne Hyperspectral and Machine Learning Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3637-3643. |
[15] |
TAO Jing-zhe1, 3, SONG De-rui1, 3, SONG Chuan-ming2, WANG Xiang-hai1, 2*. Multi-Band Remote Sensing Image Sharpening: A Survey[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 2999-3008. |
|
|
|
|