作物学报 ›› 2013, Vol. 39 ›› Issue (02): 319-329.doi: 10.3724/SP.J.1006.2013.00319
陈兵1, 韩焕勇1,王方永1,刘政1,邓福军1,林海1,余渝1,李少昆2,3,王克如2,3,肖春华2,3
CHEN Bing1,HAN Huan-Yong1,WANG Fang-Yong1,LIU Zheng1,DENG Fu-Jun1,LIN Hai1,YU Yu1,LI Shao-Kun2,3,WANG Ke-Ru2,3,XIAO Chun-Hua2,3
摘要:
| [1]Chen B, Li S K, Wang K R, Zhou G Q, Bai J H. Evaluating the severity level of cotton Verticillium using spectral signature analysis. Int J Remote Sens, 2012, 33: 2706–2724[2]Reddy K R, Koti S, Davidonis G H, Reddy V R. Interactive effects of carbon dioxide and nitrogen nutrition on cotton growth, development, yield and fiber quality. Agron J, 2004, 96: 1148–1157[3]Lee Y J, Yang C M, Chang K W, Shen Y. A simple spectral index using reflectance of 735 nm to assess nitrogen status of rice canopy. Agron J, 2008, 100: 205–212[4]Hatfield J L. Remote detection of crop stress: application to plant pathology. Phytopathology, 1990, 80: 37–39[5]Liu W(刘炜), Chang Q-R(常庆瑞), Guo M(郭曼), Xing D-X(邢东兴), Yuan Y-S(员永生). Monitoring of leaf nitrogen content in summer corn with first derivative of spectrum based on modified red edge. J Northwest A&F Univ (Nat Sci Edn)(西北农林科技大学学报•自然科学版), 2010, 38(4): 91–98 (in Chinese with English abstract)[6]Smith K L, Steven M D, Colls J J. Use of hyperspectral derivative ratios in the red edge region to identify plant stress responses to gas leak. Remote Sens Environ, 2004, 92: 207–217[7]Jiang J-B(蒋金豹), Chen Y-H(陈云浩), Huang W-J(黄文江). Using hyper-spectral derivative index to monitor winter wheat diseases. Pectroscopy Spectral Anal (光谱学与光谱分析), 2007, 27(12): 2475–2479 (in Chinese with English abstract)[8]Broge N H, Mortensen J V. Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sens Environ, 2002, 81: 45–57[9]Ponzoni F J, Goncalves J L. Spectral features associated with nitrogen, phosphorus, and potassium deficiencies in Eucalyptus saligna seedling leaves. Int J Remote Sens, 1999, 20: 2249–2264[10]Schlemmer M R, Francis D D, Shanahan J F, Schepers J S. Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agron J, 2005, 97: 106–112[11]Blackburn G A. Quantifying chlorophylls and caroteniods at leaf and canopy scales: an evaluation of some hyperspectral approaches. Remote Sens Environ, 1998, 66: 273–285[12]Yoder B J, Pettigrew-Crosby R E. Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales. Remote Sens Environ, 1995, 53(3): 199–211[13]Haboudane D, Miller J R, Tremblay N, Zarco-Tejada P J, Dextraze L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sens Environ, 2002, 81: 416–426[14]Errmann I, Karnieli A, Bonfil D J, Cohen Y, Alchanatis V. SWIR-based spectral indices for assessing nitrogen content in potato fields. Int J Remote Sens, 2010, 31: 5127–5143[15]Huang W-J(黄文江), Wang J-H(王纪华), Liu L-Y(刘良云), Zhao C-J(赵春江), Wang J-D(王锦地), Du X-H(杜小鸿). The red edge parameters iversification disciplinarian and its application for nutrition diagnosis. Remote Sens Technol Appl (遥感技术与运用), 2003, 18(4): 206–211 (in Chinese with English abstract)[16]Lamb D W, Steyn-Ross M, Schaare P, Hanna M M, Silvester W, Steyn-Ross A. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modeling and experimental observations. Int J Remote Sens, 2002, 23: 3619–3648[17]Jiang J-B(蒋金豹), Chen Y-H(陈云浩), Huang W-J(黄文江), Li J(李京). Hyperspectral estimation models for LTN content of winter wheat canopy under stripe rust stress. Trans CSAE (农业工程学报), 2008, 24(1): 35–39 (in Chinese with English abstract)[18]Ju C H, Tian Y C, Yao X, Cao W X, Zhu Y, Hannaway D B. Estimating leaf chlorophyll content using red edge parameters. Pedosphere, 2010, 20: 633–644[19]Xue L-H(薛利红), Yang L-Z(杨林章). Comparative study on estimation of chlorophyll content in spinach leaves using various red edge position extraction techniques. Trans CSAE (农业工程学报), 2008, 24(9): 165–169 (in Chinese with English abstract) [20]Yao X(姚霞), Tian Y-C(田永超), Liu X-J(刘小军), Cao W-X(曹卫星), Zhu Y(朱艳). Comparative study on monitoring canopy leaf nitrogen status on red edge position with different algorithms in wheat. Sci Agric Sin (中国农业科学), 2010, 43(13): 2661–2667 (in Chinese with English abstract)[21]Zhang Q-L(张清林), Chen W-H(陈文惠), Zhang Y-H(张永贺), Guo X-C(郭啸川), Chu W-D(褚武道), Xu W-M(许炜敏). Estimation m odels of chlorophyll contents in leaves of Acacia confusa based on the red edge position. J Subtrop Resour Environ (亚热带资源与环境学报), 2011, 6(3): 9–17 (in Chinese with English abstract)[22]Cho M A, Skidmore A K.A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method. Remote Sens Environ, 2006, 101: 181–193[23]Huang C-Y(黄春燕), Wang D-W(王登伟), Zhang Y-X(张煜星). Estimation of cotton canopy chlorophyll density and leaf area index based on red-edge parameters. Trans CSAE (农业工程学报), 2009, 25(S2): 137–141 (in Chinese with English abstract)[24]Tan C-W(谭昌伟), Wang J-H(王纪华), Guo W-S(郭文善), Lu J-F(陆建飞), Zhang H-C(张洪程), Jiang H-R(蒋海荣). Agronomy parameters of summer maize diagnosed by red edge parameters obtainable from remotely sensing data. J Fujian Agric For Univ (Nat Sci Edn)(福建农林大学学报•自然科学版), 2006, 35(2): 123–128 (in Chinese with English abstract)[25]Main R, Cho M A, Mathieu R, O’Kennedy M M, Ramoelo A, Koch S. An investigation into robust spectral indices for leaf chlorophyll estimation. ISPRS J Photogram Remote Sens, 2011, 66: 751–761[26]Huang J F, Wang X Z, Wang R C. The red edge parameters as indicators of rice nitrogen levels. Multispect Hyperspect Remote Sens Instr Appl, 2003, 4897: 311–317[27]Fang Z-D(方中达). Research Method for Plant Disease (植病研究方法). Beijing: Agriculture Press, 1979. pp 3–5 (in Chinese)[28]Danson F M. red edge response to leaf area index. Int J Remote Sens, 1995, 16: 183–188[29]Bao S-D(鲍士旦). Analysis for Soil and Agricultural Chemistry (土壤农化分析) 3rd edn. Beijing: China Agriculture Press, 2000. pp 14–38 (in Chinese)[30]Demetrialdes-Shan T H, Steven M D, Clark J A. High resolution derivative spectra in remote sensing. Remote Sens Environ, 1990, 33: 55–64[31]Chen B(陈兵), Li S-K(李少昆), Wang K-R(王克如), Wang F-Y(王方永), Tan H-Z(谭海珍), Liu G-Q(刘国庆), Chen J-L(陈江鲁). Spectrum characteristics of cotton single leaf infected by Verticillium wilt and estimation on severity level of disease. Sci Agric Sin (中国农业科学), 2007, 40(12): 2709–2715 (in Chinese with English abstract)[32]Jing X(竞霞), Wang J-H(王纪华), Song X-Y(宋晓宇) , Xu X-G(徐新刚), Chen B(陈兵), Huang W-J(黄文江). Continuum removal method for cotton Verticillium wilt severity monitoring with hyperspectral data. Transact CSAE (农业工程学报), 2010, 26(1): 193–198 (in Chinese with English abstract)[33]Liang S-Z(梁守真), Shi P(施平), Ma W-D(马万栋), Xing Q-G(邢前国), Yu L-J(于良巨). Relational analysis of spectra and red-edge characteristics of plant leaf and leaf biochemical constituent. Chin J Eco Agric (中国生态农业学报), 2010, 18(4): 804–809 (in Chinese with English abstract)[34]Lu Y-L(卢艳丽), Li S-K(李少昆), Bai Y-L(白由路), Xie R-Z(谢瑞芝), Gong Y-M(宫永梅). Spectral red edge parametric variation and correlation analysis with n content in winter wheat. Remote Sens Technol Appl (遥感技术与应用), 2007, 21(1): 1–7 (in Chinese with English abstract) |
| [1] | 梁进宇, 尹嘉德, 王红丽, 张国平, 侯慧芝, 董博, 马明生. 基于无人机高光谱和机器学习的旱地饲用玉米叶片氮含量估测[J]. 作物学报, 2026, 52(6): 1788-1801. |
| [2] | 赵佳雪, 周龙昊, 郭岂源, 尚伦霄, 王涵, 刘志涛, 陈曦, 张晓佩, 宋宪亮, 毛丽丽. 长期秸秆还田与深松通过改善土壤环境与棉花光合特性提高滨海盐碱地棉花产量[J]. 作物学报, 2026, 52(5): 1548-1560. |
| [3] | 张曦, 王广恩, 李邵琦, 刘祎, 李俊兰, 钱玉源. 基于转录组测序解析陆海杂交姊妹系马克隆值差异的形成机制[J]. 作物学报, 2026, 52(5): 1442-1458. |
| [4] | 杨月, 张新新, 贺增辉, 李瑞东, 潘昱洁, 李嘉康, 杜薇, 徐大勇, 堵劲松. 基于高光谱成像的烟叶主要化学成分无损检测与可视化[J]. 作物学报, 2026, 52(3): 922-935. |
| [5] | 周琦翔, 朱艳, 汪楚博, 朱柏林, 李俊博, 宋利兵. 基于DSSAT模型模拟气候变化对新疆棉花物候期及产量的影响[J]. 作物学报, 2026, 52(2): 590-602. |
| [6] | 郭栋财, 吕涛, 蔡永生, 买吾鲁达·艾合买提, 全家, 曲延英, 郑凯. 棉花纤维品质相关性状QTL元分析及候选基因鉴定[J]. 作物学报, 2025, 51(6): 1445-1466. |
| [7] | 王亚雯, 戚正阳, 尤佳琦, 聂新辉, 曹娟, 杨细燕, 涂礼莉, 张献龙, 王茂军. 棉花60K功能位点基因芯片的制备及应用[J]. 作物学报, 2025, 51(5): 1178-1188. |
| [8] | 王清华, 朱格格, 方雯, 刘诗诗, 鲁剑巍. 基于高光谱遥感的油菜叶片氮磷养分含量诊断[J]. 作物学报, 2025, 51(5): 1326-1337. |
| [9] | 丁俊沣, 许映飞, 张祥, 陈媛, 陈德华. 生长调节剂吲哚丁酸对移栽棉苗成活及生长发育的影响[J]. 作物学报, 2025, 51(12): 3331-3341. |
| [10] | 哈丽哈什·依巴提, 张炎, 李青军, 徐新朋, 何萍. 基于产量反应和农学效率的棉花智能化推荐施肥方法研究[J]. 作物学报, 2025, 51(11): 3052-3064. |
| [11] | 李亚玮, 徐盈盈, 左春阳, 刘若男, 梁亚军, 孔杰, 张献龙, 闵玲. 棉花减数分裂进程鉴定体系构建及其对高温胁迫的响应分析[J]. 作物学报, 2025, 51(10): 2570-2580. |
| [12] | 陈佳伟, 林艳, 张明星, 周诗晶, 饶力群, 周池, 李鑫. 贝莱斯芽孢杆菌YCH92对棉花根际土壤微生物群落及棉花产量的影响[J]. 作物学报, 2025, 51(10): 2821-2835. |
| [13] | 谢章书, 谢学方, 屠小菊, 刘爱玉, 董合忠, 周仲华. 植物激素对棉花蕾铃脱落的调控研究进展[J]. 作物学报, 2025, 51(1): 1-29. |
| [14] | 辛明华, 秘雅迪, 王国平, 李小飞, 李亚兵, 董合林, 韩迎春, 冯璐. 行距配置和种植密度对棉花干物质生产及产量的影响[J]. 作物学报, 2025, 51(1): 221-232. |
| [15] | 李超, 付小琼. 基于GYT双标图综合评价黄河流域中熟杂交棉花区域试验品种[J]. 作物学报, 2025, 51(1): 30-43. |
|
||