基于中红外光声光谱的梨树叶片氮含量的测定

doi:10.3864/j.issn.0578-1752.2012.04.011

摘要/Abstract

摘要： 【目的】利用光谱学手段，寻找一种快速、简单的梨树叶片中氮含量的诊断方法。【方法】应用傅里叶变换中红外光声光谱仪（FTIR-PAS）研究环渤海湾地区4个梨试验站200个梨园叶片的光声光谱特征，采用偏最小二乘法（PLSR）对叶片氮素含量进行建模和预测。【结果】通过分析PLSR中的主成分数和样本氮素浓度范围对PLSR定量预测能力的影响，当烟台、泰安、昌黎、营口试验站及综合的主成分数分别为6、6、6、4和8时，所建模型最优；用所建的5个模型预测了未知样品的氮素含量，发现预测误差（RMSEP）介于1.26—2.18 g•kg-1，预测相关系数（Rp）介于0.644—0.806。【结论】FTIR-PAS与PLSR相结合建立的预测模型可满足梨树叶片氮素含量快速、方便检测的需要。

关键词: 梨, 叶片氮含量, 中红外光声光谱, 偏最小二乘法

Abstract: 【Objective】 The aim was to find a fast and convenient method for prediction of the nitrogen status in pear leaves by technique of spectroscopy.【Method】Pear leaves were collected from 200 dominant pear orchards in four pear experimental stations scattered in three provinces (Shandong, Hebei and Liaoning) around the Bohai Gulf which is affiliated to National Pear Industrial Technology System. Fourier transform mid-infrared photoacoustic spectra (FTIR-PAS) of 200 pear leaf samples were recorded, and Partial Least Squares Regression (PLSR) was applied in the modelings of nitrogen content in pear leaf. 【Result】 The effects of the quantities of Principal Components (PCs) in PLSR and the scope of nitrogen concentrations in samples on the quantitative predicting capacity of PLSR were analyzed. It was found that the established model was of highest accuracy when the quantities of major ingredients in the respective experimental stations, which was referred to Yantai, Tai'an, Changli, Yingkou, and the total samples, as a whole were 6, 6, 6, 4 and 8, respectively. It was also found that when predicting the nitrogen contents in samples by the five established models, Root Mean Square Error of Prediction (RMSEP) was ranging from 1.26 g•kg-1 and 2.18 g•kg-1 and the correlation coefficient of Prediction(Rp) was between 0.644 and 0.806.【Conclusion】The results indicated that it is a new fast and convenient technique for predicting the leaf N status of fruit tree by using the Mid-Infrared Photoacoustic Spectroscopy.

Key words: pear, leaf nitrogen content, mid-infrared photoacoustic spectroscopy, partial least squares regression

赵化兵, 李艳丽, 谢凯, 宋晓晖, 董彩霞, 徐阳春. 基于中红外光声光谱的梨树叶片氮含量的测定[J]. 中国农业科学, 2012, 45(4): 706-713.

ZHAO Hua-Bing, LI Yan-Li, XIE Kai, SONG Xiao-Hui, DONG Cai-Xia, XU Yang-Chun. Fast Determination of Nitrogen Status in Pear Leaf Using Mid-Infrared Photoacoustic Spectroscopy[J]. Scientia Agricultura Sinica, 2012, 45(4): 706-713.

0
/ / 推荐

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2012.04.011

https://www.chinaagrisci.com/CN/Y2012/V45/I4/706

参考文献

[1]Curran P J. Remote sensing of foliar chemistry. Remote Sensing of Environment, 1989(3): 271-278.

[2]张继澍. 植物生理学. 北京: 高等教育出版社, 2006.

Zhang J S. Plant Physiology. Beijing: Higher Education Press, 2006.(in Chinese)

[3]蒋淑丽. 稻米矿质元素分析及其近红外测定技术的研究[D]. 杭州: 浙江大学, 2007.

Jiang S L. The study of determination and the calibration model optimization by near infrared reflectance spectroscopy (NIRS) for mineral element contents in rice (Oryza stativa L.)[D]. Hangzhou: Zhejiang University, 2007. (in Chinese)

[4]李静, 刘斌. 近红外光谱分析技术及其在食品中的应用. 农产品加工, 2007 (3): 44-47.

Li J, Liu B. Applications of near infrared spectroscopy to foods. Academic Periodical of Farm Products Processing, 2007(3): 44-47. (in Chinese)

[5]Yang H, Irudayaraj J. Characterization of beef and pork using fourier-transform infrared photoacoustic spectroscopy. Food Science and Technology, 2001, 34(6): 402-409.

[6]Irudayaraj J, Yang H. Depth profiling of a heterogeneous food-packaging model using step-scan fourier transform infrared photoacoustic spectroscopy. Journal of Food Engineering, 2002, 55(1): 25-33.

[7]Fan M H, Brown R C. Precision and accuracy of photoacoustic measurements of unburned carbon in fly ash. Fuel, 2001, 80(11): 1545-1554.

[8]Janusz R. Infrared photoacoustic spectroscopy in catalysis and surface science. Applied Surface Science, 2010, 256(17): 5545-5550.

[9]Ravikumar V. Cure characterization of carbon fiber reinforced phenyl-ethynyl terminated oligoamic acid by FTIR–photoacoustic spectroscopy. Applied Science and Manufacturing, 2009, 40(12): 2054-2063.

[10]Koskinen V, Fonsen J. Extremely sensitive trace gas analysis with modern photoacoustic spectroscopy. Vibrational Spectroscopy, 2006, 42(2): 239-242.

[11]杜昌文, 周健民. 傅里叶变换红外光声光谱法测定土壤中有效磷. 分析化学, 2007, 35(1): 119-122.

Du C W, Zhou J M. Prediction of soil available phosphorus using Fourier transform infrared-photoacoustic spectroscopy. Chinese Journal of Analytical Chemistry, 2007, 35(1): 119-122. (in Chinese)

[12]Du C W. Determination of soil properties using Fourier transform mid-infrared photoacoustic spectroscopy. Vibrational Spectroscopy, 2009, 49(1): 32-37.

[13]赵聪, 申亚珍. 基于傅里叶变换红外光声光谱的包膜控释肥料聚合物膜疏水性的表征. 分析化学, 2010, 38(8): 1186-1190.

Zhao C, Shen Y Z. Hydrophobicity characterization of polymer coating for controlled-release fertilizer using Fourier transform infrared photoacoustic spectroscopy. Chinese Journal of Analytical Chemistry, 2010, 38(8): 1186-1190. (in Chinese)

[14]Cecilia S, Luis R S. Application of NIR and MIR spectroscopy in quality control of potato chips. Journal of Food Composition and Analysis, 2009, 22(6): 596-605.

[15]鲍士旦. 土壤农化分析. 第3版. 北京: 中国农业出版社, 2000.

Bao S D. Soil and Chemical Alanalysis. Third Edition. Beijing: China Agriculture Press, 2000. (in Chinese)

[16]Vlachos N, Skopelitis1 Y, Psaroudaki M, Konstantinidou V, Chatzilazarou A, Tegou E. Applications of fourier transform-infrared spectroscopy to edible oils. Analytica Chimica Acta, 2006, 573-574: 459-465.

[17]李港丽, 苏润宇, 沈隽. 几种落叶果树叶内矿质元素含量标准值的研究. 园艺学报, 1987,14 (2): 81-89.

Li G L, Su R Y, Shen J. Studies on the nutritional ranges in some deciduous fruit trees. Acta Horticulturae, 1987, 14(2): 81-89. (in Chinese)

[18]姜远茂, 彭福田, 巨晓棠. 果树施肥新技术. 北京: 中国农业出版社, 2002.

Jiang Y M, Peng F T, Ju X T. New Techniques in Fruit Tree Fertilization. Beijing: China Agriculture Press, 2002. (in Chinese)

[19]李民赞. 光谱分析技术及其应用. 北京:科学出版社, 2006.

Li M Z. Spectroscopy and Its Applications. Beijing: Science Press, 2006. (in Chinese)

[20]赵文萃, 窦英. 偏最小二乘-近红外漫反射光谱法测定西米替丁药片. 分析试验室, 2004, 23(10): 85-87.

Zhao W C, Dou Y. Determination of Cimetidine in Tablets by Near-infrared Spectroscopy and PLSR. Analysis Laboratory, 2004, 23(10): 85-87. (in Chinese)

[21]李卫东. 应用多元统计分析. 北京: 北京大学出版社, 2008.

Li W D. Applied Multivariate Statistical Analysis. Beijing: Peking University Press,2008. (in Chinese)

[22]王磊, 白由路. 不同氮处理春玉米叶片光谱反射率与叶片全氮和叶绿素含量的相关研究. 中国农业科学, 2005, 38(11): 2268-2276.

Wang L, Bai Y L. Correlation between corn leaf spectral reflectance and leaf total nitrogen and chlorophyll content under different nitrogen level. Scientia Agricultura Sinica, 2005, 38(11): 2268-2276. (in Chinese)

[23]姚霞, 朱艳, 田永超, 冯伟, 曹卫星. 小麦叶层氮含量估测的最佳高光谱参数研究. 中国农业科学, 2009, 42(8): 2716-2725.

Yao X, Zhu Y, Tian Y C, Feng W, Cao W X. Research of the optimum hyperspectral vegetation indices on monitoring the nitrogen content in wheat leaves. Scientia Agricultura Sinica, 2009, 42(8): 2716-2725. (in Chinese)

[24]陈青春, 田永超, 姚霞, 朱艳, 曹卫星. 基于冠层反射光谱的水稻追氮调控效应研究. 中国农业科学, 2010, 43(20): 4149-4157.

Chen Q C, Tian Y C, Yao X, Zhu Y, Cao W X. Effects of nitrogen fertilizer top-dressing based on canopy reflectance spectra in rice. Scientia Agricultura Sinica, 2010, 43(20): 4149-4157. (in Chinese)

[25]朱西存, 赵庚星, 王凌, 董芳, 雷彤, 战兵. 基于高光谱的苹果花氮素含量预测模型研究. 光谱学与光谱分析, 2010, 30(2): 416-420.

Zhu X C, Zhao G X, Wang L, Dong F, Lei T, Zhan B. Hyperspectrum based prediction model for nitrogen content of apple flowers. Spectroscopy and Spectral Analysis, 2010, 30(2): 416-420. (in Chinese)

[26]易时来, 邓烈, 何绍兰, 郑永强, 张璇. 锦橙叶片氮含量可见近红外光谱模型研究. 果树学报, 2010, 27 (1): 13-17.

Yi S L, Deng L, He S L, Zheng Y Q, Zhang X. Research on nitrogen content of leaf of Jincheng orange cultivar using visible near infrared spectroscopy model. Journal of Fruit Science, 2010, 27(1): 13-17. (in Chinese)

[27]易时来, 邓烈, 何绍兰, 郑永强, 毛莎莎. 锦橙叶片钾含量光谱监测模型研究. 中国农业科学, 2010, 43(4): 780-786.

Yi S L, Deng L, He S L, Zheng Y Q, Mao S S. A spectrum based models for monitoring leaf potassium content of Citrus sinensis (L)cv.Jincheng orange. Scientia Agricultura Sinica, 2010, 43(4): 780-786. (in Chinese)

[28]赵扬辉, 汤亮, 曹卫星, 朱艳. 小麦生长模拟模型(WheatGrow)的适应性评价. 麦类作物学报, 2010, 30(3): 443-448.

Zhao Y H, Tang L, Cao W X, Zhu Y. Adaptability evaluation of a wheat growth model (WheatGrow). Journal of Triticeae Crops, 2010, 30(3): 443-448. (in Chinese)

[29]Du C W, Linker R, Shaviv A. Characterization of soils using photoacoustic mid-infrared spectroscopy. Applied Spectroscopy, 2007, 61(10): 1063-1067.

[30]Du C W, Zhou G Q, Zhou J M, Wang H M, Chen X Q, Dong Y H, Wang H. Characterization of animal manures using mid-infrared photoacoustic spectroscopy. Bioresource Technology, 2010, 101(15): 6273-6277.

[31]杜浩, 方健文. 植物叶片的光声光谱. 生物化学与生物物理进展, 1991, 18(1): 53-55.

Du H, Fang J W. The photoacoustic spectroscopy of plant leaf. Progress in Biochemistry and Biophysics, 1991, 18(1): 53-55. (in Chinese)

[32]伍荣护, 苏佳. 植物色素的光声光谱研究. 光谱学与光谱分析, 2002, 22(3): 378-380.

Wu R H, Su J. Study on plant pigments by photoacoustic spectroscopy. Spectroscopy and Spectral Analysis, 2002, 22(3): 378-380. (in Chinese)