1. Shihezi University，Key Laboratory of Oasis Ecology Agriculture of Xinjiang Construction Crops, Shihezi 832003, China 2. Chinese Academy of Agricultural Sciences，Key Laboratory of Crop Physiology and Production Ministry of Agriculture, Beijing 100081, China
摘要： 生物量、氮素含量和LAI(leaf area index)是生态系统中表征作物长势最重要的参数，叶干重、叶片氮素含量和LAI实时动态监测对小麦氮素营养诊断和管理调控具有重要意义。选用了五个小麦品种和四个氮素水平的比较实验，研究不同处理冬小麦抽穗到黄熟期氮素丰度(NR)与光谱反射率差值(ΔＲ)的关系，建立冬小麦后期氮素丰度监测模型。结果表明，不同品种的冬小麦冠层叶片氮素丰度随生育进程推进而增加，不同氮素处理氮素丰度大小为N0>N3>N1>N2，光谱参量TCARI和VD672与氮素丰度的相关性最好，相关系数(r)分别为0.870和0.855，其建立氮素丰度估测模型的决定系数分别为0.757和0.731，预测准确率达84.56%和80.13%。光谱参数TCARI和VD672可以有效地评价小麦后期冠层叶片氮素状况，可以对氮素丰度进行准确可靠的监测。
关键词：氮素丰度(NR);反射率差值(ΔR);冬小麦;模型;监测
Abstract：Biomass, leaf area index (LAI) and nitrogen status are important parameters for indicating crop growth potential and photosynthetic productivity in wheat. Nondestructive, quick assessment of leaf dry weight, LAI and nitrogen content is necessary for nitrogen nutrition diagnosis and cultural regulation in wheat production． In order to establish the monitoring model of nitrogen richness in winter wheat of growth anaphase, studying the relationship between the nitrogen richness (NR) containing nitrogen density, LAI and leaf dry weight and the difference of hyperspectral reflectance rates (ΔR), we conducted a comparable experiment with five winter wheat varieties under nitrogen application level of 0, 100, 200 and 400 kg·N·ha-1. The results indicated the NRs of the different varieties of winter wheat leaves increased with increasing growth stage while in the different nitrogen levels it was sequenced as: N0>N3>N1>N2. Twelve vegetation indices were compared with corresponding NR. The NR had significantly negative correlation to TCARI and VD672 in those vegetation indices, and their correlations (r) arrived at 0.870 and 0.855, respectively. The coefficients of determination (R2) of two models were 0.757 and 0.731 by erecting model with the two indexes and NR. Root mean square error (RMSE), relative error (RE) and determination coefficient between measured and estimated NR were employed to test the model reliability and predicting accuracy. Accuracy rates of the models based on TCARI and VD672 achieved 84.56% and 80.13%. The overall results suggested that leaf nitrogen status of growth anaphase in winter wheat has stable relationships with some vegetation indexes, especially index of TCARI and VD672.
[1] Scheumann V, Schoch S, Rüdiger W. Planta, 1999, 209(3): 364. [2] Lu C, Lu Q, Zhang J, et al. Journal Experim. Bot., 2001, 52(362): 1805. [3] Pefiuelas J, Filella I. Trends in Plant Science, 1998, 3(4): 151. [4] HUANG Wen-jiang, ZHAO Chun-jiang，WANG Ji-hua, et al(黄文江, 赵春江, 王纪华, 等). Transaction of the Chinese Society of Agricultural Engineering(农业工程学报), 2004, 20(6): 1. [5] ZHANG Liang-pei, ZHENG Lan-fen, TONG Qing-xi(张良培, 郑兰芬, 童庆禧). Journal of Remote Sensing(遥感学报), 1997, 1(2): 111. [6] LIU Wei-dong, XIANG Yue-qin, ZHENG Lan-fen, et al(刘伟东, 项月琴, 郑兰芬, 等). Journal of Remote Sensing (遥感学报), 2000, 4(4): 279. [7] WANG Xiu-zhen, HUANG Jing-feng, LI Yun-mei, et al(王秀珍, 黄敬峰, 李云梅, 等), Acta Agronomica Sinica(作物学报), 2003, 29(6): 815. [8] Serrano L, Filella I, Penuelas J. Crop Science, 2000, 40(3): 723. [9] Vaesen K, Gilliams S, Nackaerts K, et al. Field Crops Research, 2001, 69(1): 13. [10] Jensen R R, Binford M W. International Journal of Remote Sensing, 2004, 25(20): 4251. [11] Lu D S. International Journal of Remote Sensing, 2006, 27(7): 297. [12] ZHAO Du-li, Raja Reddy K, Gopal Kakani V, et al. European Journal of Agronomy, 2005, 22: 391. [13] Wright D L, Rasmussen V P, Ramsey R D. GIScience and Remote Sensing, 2004, 41(4): 287. [14] Peason R L, Miller D L. Proceedings of the Eighth International Symosium on Remote Sensing of Environment, 1972, 2: 1357. [15] Gamon J A, Penuelas J, Field C B. Remote Sens Environ., 1992, 41(1): 35. [16] Penuelas J, Baret F, Filella I. Photosynthetica, 1995, 31: 221. [17] Lyon J G, Yuan D, Lunetta R S. Photogrammetric Engineering and Remote Sensing, 1998, 64: 143. [18] Blackburn G A. International Journal of Remote Sensing, 1998, 19: 657. [19] Gitelson A A, Merzlyak M N . Journal of Plant Physiology, 1994, 143: 286. [20] Rondeaux G Steven，Baret M F. Remote Sensing of Environment, 1996, 55: 95. [21] Baret F, Guyot G, Major D J. Geoscience and Remote Sensing Society of Institute of Electrical and Electronics Enginess, 1989, 3: 1355. [22] Zarco-Tejada P J, Miller J R, Mohammed G H, et al. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39: 1491. [23] Rouse J W, Haas R H, Schell J A, et al. Third Earth Resources Technology Satellite Symposivm. Technical Presentations, Section A, 1973, (Ⅰ): 309. [24] ZHAO Quan-zhi, DING Yan-feng, WANG Qiang-sheng, et al(赵全志, 丁艳锋, 王强盛, 等). Scientia Agricultura Sinica(中国农业科学), 2006, 39(5): 916. [25] DUAN Jun, LIANG Cheng-ye, HUANG Yu-wen(段 俊, 梁承邺, 黄毓文). Acta Phytophysiologica Sinica(植物生理学报), 1997, 23(2): 139. [26] FENG Wei, ZHU Yan, YAO Xia, et al(冯 伟, 朱 艳, 姚 霞, 等). Chinese Journal of Plant Ecology(植物生态学报), 2009, 33(1): 34. [27] Rondeaux G, Steven M, Baret F. Remote Sensing of Environment, 1996, 55: 95. [28] Daughtry C S T, Walthall C L, Kin M S, et al. Remote Sensing of Environment, 2000, 74: 229. [29] LI Ying-xue, ZHU Yan, TIAN Yong-chao, et al(李映雪, 朱 艳, 田永超, 等). Scientia Agricultura Sinica(中国农业科学), 2005, 38(7): 1332.
