Scientia Agricultura Sinica ›› 2011, Vol. 44 ›› Issue (16): 3323-3332.doi: 10.3864/j.issn.0578-1752.2011.16.004

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Multi-Spectral Images Estimation Models for Nitrogen Contents of Rape

ZHANG  Xiao-Dong, MAO  Han-Ping, ZUO  Zhi-Yu, SUN  Jun, ZHANG  Hong-Tao   

  1. 江苏大学农业工程研究院/现代农业装备与技术省部共建教育部重点实验室
  • Received:2010-12-01 Revised:2011-02-28 Online:2011-08-15 Published:2011-03-09
  • Contact: Xiao-Dong ZHANG E-mail:zxd700227@126.com

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Abstract: 【Objective】Multi-spectral image analysis method was used to quantitatively analyze the rape total nitrogen content.【Method】The images of rape canopy were taken by the multi-spectral camera and were preprocessed by the median-filtering method. Two-dimensional maximum entropy segment method was used to complete background segmentation of multi-spectral images. 【Result】 By extracting mean and ratio of multi-spectral images of rape canopy , it was found that the features of ARV1, AVS560, ADV1, AVS660 and g are highly correlated with nitrogen content in the whole growth period. Considering the serious multicollinearity between multi-spectral variable, the prediction model of nitrogen content of rape at different growth stages was built by stepwise regression method. 【Conclusion】The reflection intensity distribution information of the visible light and the near infrared light is sufficiently utilized in this research to diagnose the nitrogen content of rape. The multi-spectral image features of the nitrogen content of rape at different growth stages were preliminarily verified. The result shows that the method of multi-spectral image analysis can be used to quantitatively analyze the rape total nitrogen content. This provides a theoretical basis and technical support for the scientific management of rape nutrition.

Key words: Rape, Nitrogen, Multi-spectral image, Stepwise regression

CLC Number: 

  • S121

[1]Ahmad I S, Reid J F. Evaluation of color representation for maize image. Journal of Agricultural Engineering Research, 1996, 63: 185-196.

[2]Goel P, Prasher S, Landry J, Patel R, Bonnell R, Viau A, Miller J. Potential of airborne hyperspectral remote sensing to detect nitrogen deficiency and weed infestation in corn. Computers and Electronics in Agriculture, 2003, 38: 99-124.

[3]Jia L L, Cheng X P. Use of digital camera to assess nitrogen status of winter wheat in the northern China plain. Journal of Plant Nutrition, 2004, 27 (3): 441-450.

[4]Mirik M, Michels G, Kassymzhanova M S, Elliott N, Catana V, Jones D, Bowling R. Using digital image analysis and spectral reflectance data to quantify damage by greenbug (Hemitera: Aphididae) in winter wheat. Computers and Electronics in Agriculture, 2006, 51: 86-98.

[5]Noh H, Zhang Q, Shin B, Han S, Feng L. A neural network model of maize crop nitrogen stress assessment for a multi-spectral imaging sensor. Biosystems Engineering, 2006, 94 (4): 477-485.

[6]Karimi Y, Prasher S, Patel R, Kimb S. Application of support vector machine technology for weed and nitrogen stress detection in corn. Computers and Electronics in Agriculture, 2006, 51: 99-109.

[7]Reum D, Zhang Q. Wavelet based multi-spectral image analysis of maize leaf chlorophyll content. Computers and Electronics in Agriculture, 2007, 56: 60-71.

[8]Wu J D, Wang D, Carl J, Marvin E. Comparison of petiole nitrate concentrations, SPAD chlorophyll readings, and QuickBird satellite imagery in detecting nitrogen status of potato canopies. Field Crops Research, 2007, 101: 96-103.

[9]Pagola M, Ortiz R, Irigoyen I. New method to assess barley nitrogen nutrition status based on image color analysis comparison with SPAD-502. Computers and Electronics in Agriculture, 2009, 65(3): 213-218.

[10]Wiwart M, Fordon G, Krystyna Z, Suchowilskaa E. Early diagnostics of macronutrient deficiencies in three legume species by color image analysis. Computers and Electronics in Agriculture, 2009, 65: 125-132.

[11]Liu J G, Elizabeth P. Retrieval of leaf area index from top-of-canopy digital photography over agricultural crops. Agricultural and Forest Meteorology, 2010, 150: 1485-1490.

[12]Vollmanna J, Waltera H, Satoa T, Schweigerb P. Digital image analysis and chlorophyll metering for phenotyping the effects of nodulation in soybean. Computers and Electronics in Agriculture, 2011, 75: 190-195.

[13]杨敏华, 赵春江, 赵永超, 刘良云, 王纪华. 用航空成像光谱数据获取小麦冠层信息的研究. 中国农业科学, 2002, 35(6):626-631.

Yang M H, Zhao C J, Zhao Y C, Liu L Y, Wang J H. Research on a method to derive wheat canopy informatien from airborne imaging spectrometer data. Scientia Agricultura Sinica, 2002, 35(6):626-631. (in Chinese)

[14]李少昆, 索兴梅, 白中英, 祁之力, 刘晓鸿, 高世菊, 赵双宁. 基于BP 神经网络的小麦群体图像特征识别. 中国农业科学, 2002, 35(6):616-620.

Li S K, Suo X M, Bai Z Y, Qi Z L, Liu X H, Gao S J, Zhao S N. The machine recognition for population feature of wheat images based on BP neural network. Scientia Agricultura Sinica, 2002, 35(6): 616-620. (in Chinese)

[15]张彦娥, 李民赞, 张喜杰, 张建平, 徐增辉. 基于计算机视觉技术的温室黄瓜叶片营养信息检测. 农业工程学报, 2005, 21(8): 102-105.

Zhang Y E, Li M Z, Zhang X J, Zhang J P, Xu Z H. Nitrogen status diagnosis by using digital photography analysis for organic fertilized maize. Transactions of the Chinese Society of Agricultural Engineering, 2005, 21(8): 102-105. (in Chinese)

[16]鲍艳松, 王纪华, 刘良云, 李小文, 李 翔, 黄文江, 唐 怡. 不同尺度冬小麦氮素遥感监测方法及其应用研究. 农业工程学报, 2007, 23(2): 139-145.

Bao Y S, Wang J H, Liu L Y, Li X W, Li X, Huang W J, Tang Y. Approach to estimation of winter wheat nitrogen by using remote sensing technology on diverse scale and its application. Transactions of the Chinese Society of Agricultural Engineering, 2007, 23(2): 139-145. (in Chinese)

[17]张 浩, 姚旭国, 张小斌, 祝利莉, 叶少挺, 郑可锋, 胡为群. 基于多光谱图像的水稻叶片叶绿素和籽粒氮素含量检测研究. 中国水稻科学, 2008, 22(5) : 555- 558.

Zhang H, Yao X G, Zhang X B, Zhu L L, Ye S T, Zheng K F, Hu W Q. Measurement of rice leaf chlorophyll and seed nitrogen contents by using multi-spectral imagine. Chinese Journal of Rice Science, 2008, 22(5) : 555- 558. (in Chinese)

[18]宋述尧, 王秀峰. 数字图像技术在黄瓜氮素营养诊断上的应用研究. 吉林农业大学学报, 2008, 30(4):460-465.

Song S R, Wang X F. Diagnosis of N status of cucumber using digital image processing technique. Journal of Jilin Agricultural University, 2008, 30(4):460-465. (in Chinese)

[19]雷 彤, 赵庚星, 朱西存, 战 冰, 张洋洋. 基于高光谱和数码照相技术的苹果花期光谱特征研究. 中国农业科学, 2009, 42(7): 2481- 2490.

Lei T, Zhao G X, Zhu X C, Zhan B, Zhang Y Y. Research of apple florescence spectral features based on hyperspectral data and digital photos. Scientia Agricultura Sinica, 2009,42(7):2481-2490. (in Chinese)

[20]张东彦, 宋晓宇, 马智宏, 杨贵军, 黄文江, 王纪华. 扫描成像光谱仪和地物光谱仪在单叶尺度上的对比研究. 中国农业科学, 2010,43(11):2239-2245.

Zhang D Y, Song X Y, Ma Z H, Yang G J, Huang W J, Wang J H. Assessment of the developed pushbroom imaging spectrometer in single leaf scale. Scientia Agricultura Sinica, 2010,43(11): 2239- 2245. (in Chinese)

[21]唐华俊, 吴文斌, 杨 鹏, 周清波, 陈仲新. 农作物空间格局遥感监测研究进展. 中国农业科学, 2010,43(14):2879-2888.

Tang H J, Wu W B, Yang P, Zhou Q B, Chen Z X. Recent progresses in monitoring crop spatial patterns by using remote sensing technologies. Scientia Agricultura Sinica, 2010,43(14):2879-2888. (in Chinese)

[22]孙钦平, 李吉进, 邹国元, 向成材, 罗一鸣, 刘本生. 应用数字图像技术对有机肥施用后玉米氮营养诊断研究. 光谱学与光谱分析, 2010,30(9):2447-2450.

Sun Q P, Li J J, Zou G Y, Xiang C C, Luo Y M, Liu B S. Nitrogen status diagnosis by using digital photography analysis for organic fertilized maize. Spectroscopy and Spectral Analysis, 2010,30(9): 2447-2450. (in Chinese)

[23]张晓东, 毛罕平, 倪 军, 程秀花. 作物生长多传感信息检测系统设计与应用. 农业机械学报, 2009, 40(9):164-170.

Zhang X D, Mao H P, Ni J Cheng X H. Intelligent detection system of multi-sensor information for growing crops. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(9):164-170. (in Chinese)

[24]张晓东, 毛罕平, 程秀花. 基于PCA_SVR的油菜氮素光谱特征定量分析模型. 农业机械学报, 2009, 40(4):161-165.

 

Zhang X D, Mao H P, Cheng X H. Rape nitrogen content spectral character models based on PCA_SVR method. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(4):161-165. (in Chinese)

[25]Neter J, Li W, Kutner M H, Nachtsheim C J. Applied linear statistical models//Statistical Probability Stochastics, 2005: 475-518.

[26]苏金明, 傅荣华, 周建斌. 统计软件SPSS for Windows实用指南.  北京: 电子工业出版社, 2000.

Su J M, Fu R H, Zhou J B. Statistical Software SPSS for Windows Practical Guide. Beijing: Electronic Industry Press, 2000.(in Chinese)

[27]冯 力. 回归分析方法原理及SPSS实际操作. 北京: 中国金融出版社, 2004.

Feng L. Regression Analysis Method and SPSS Practical. Beijing: China Financial Press, 2004. (in Chinese)
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