光谱学与光谱分析 |
|
|
|
|
|
Response of Winter Wheat (Triticum aestivum L. ) Hyperspectral Characteristics to Low Temperature Stress |
REN Peng, FENG Mei-chen*, YANG Wu-de, WANG Chao, LIU Ting-ting, WANG Hui-qin |
Institute of Dry Farming Engineering, Shanxi Agricultural University, Taigu 030801, China |
|
|
Abstract The simple winter wheat variety was conducted under the low temperature treatment at -2, -4, and -6 ℃, the canopy reflectance was measured and the red edge parameters were extracted to study the winter wheat canopy spectral characteristics effected by the low temperature stress and the hyperspectral response to the low temperature stress of winter wheat at jointing stage. The results showed that the canopy reflectance decreased in visible region and increases at near infrared band with the high intensively low temperature stress, and "green peak" was weakened and “red well” was not distinctive. Moreover, the derivate spectrum had the trend of shift to short wavelength direction with the strengthening of low temperature stress and the red edge presented the blue shift. The area of red edge and red edge amplitude exhibit increase. It indicated that the canopy spectrum of winter wheat is sensitive to the low temperature stress, and the hyperspectral technology can be used to monitor the low temperature stress of winter wheat at jointing stage.
|
Received: 2014-01-24
Accepted: 2014-04-18
|
|
Corresponding Authors:
FENG Mei-chen
E-mail: fmc101@163.com
|
|
[1] Sofalian O, Mohammadi S A, Aharizad S, et al. J. Turkish Journal of Agriculture and Forestry, 2006, 30(6): 399. [2] Romanov P J. NATO Science for Peace and Security Series C: Environmental Security. Dordrecht: Springer 2011. 81. [3] FENG Meichen, YANG Wude, CAO Liangliang, et al. Agricultural Science in China, 2009, 8(9): 1053. [4] QI Ya-qin, Lü Xin, CHEN Guan-wen, et al(祁亚琴, 吕 新, 陈冠文,等). Cotton Science(棉花学报), 2011, 23(2): 167. [5] Starks P J, Zhao D, Brown M A. Grass and Forage Science, 2008, 63(2): 168. [6] Arafat S M, Aboelghar M A, Ahmed E F. Advances in Remote Sensing, 2013, 2(2): 63. [7] Vane G. Remote Sensing of Environment, 1993, 44(2): 109. [8] LI Zhang-cheng, ZHOU Qing-bo, Lü Xin, et al(李章成, 周清波, 吕 新, 等). Acta Agronomica Sinica(作物学报), 2008, 34(5): 831. [9] CHEN Bing, HAN Huan-yong, WANG Fang-yong, et al(陈 兵, 韩焕勇, 王方永, 等). Acta Agronomica Sinica(作物学报), 2013, 39(2): 319. [10] Horler D N H, Barber J, Barringer A R. International Journal of Remote Sensing, 1980, 1(2): 121. [11] Boochs F, Kupfer G. International Journal of Remote Sensing, 1990, 11(10): 1741. [12] XIE Xiao-jin, SHEN Shuang-he, LI Ying-xue, et al(谢晓金, 申双合, 李映雪,等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2010, 26(3): 183. [13] Stroppiana D, Boschetti M, Brivio A P, et al. International Journal of Remote Sensing, 2009, 30(18): 4643. [14] Song Shalei, Gong Wei, Zhu Bo, et al. Journal of Photogrammetry and Remote Sensing, 2011, 66(5): 56. [15] HUANG Jing-feng, WANG Yuan, WANG Fu-min, et al(黄敬峰, 王 渊, 王福民,等). Transactions of the Chinese Society of Agriculutral Engineering(农业工程学报), 2006, 22(8): 22. |
[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. |
|
|
|
|