糜子叶片氮含量和籽粒蛋白质含量高光谱监测研究

doi:10.3864/j.issn.0578-1752.2019.15.004

Abstract

Abstract:

【Objective】The objective of the study was to explore the best spectral prediction model of protein content in the grain of broomcorn millet based on leaf nitrogen content, which provided theoretical basis for the management and regulation of high-quality production of broomcorn millet.【Method】Using experimental data and spectral data of nitrogen application in 2017 and 2018, the predicting models on grain protein content were constructed based on hyperspectral by linking the spectral models and grain protein content with leaf nitrogen content as intersection in broomcorn millet. 【Result】The support vector machine (SVM) which constructed monitoring model of leaf nitrogen content at full growth period was superior to stepwise multiple linear regression (SMLR) and partial least square (PLS), and R-SVM was superior to 1ST-SVM, the R ² of calibration set and validation set were 0.928 and 0.924, respectively, RMSE were 0.19 and 0.12, respectively, and RPD were 3.71 and 6.07, respectively. Leaf nitrogen content and grain protein content at heading, filling and maturing stages were significantly positively correlated, and their correlation coefficients were 0.48, 0.66 and 0.73, respectively. The R-SVM at filling stage could monitor the grain protein content accurately of broomcorn millet.【Conclusion】Establishing monitoring model of R-SVM based on grain protein content in broomcorn millet at filling stage, which could help to guide the field management, adjustment of planting structure and grain quality grading, and to provide technical basis for hyperspectral technology in the development of high quality and high yield cultivation and precision agriculture.

Key words: broomcorn millet, leaf nitrogen content, grain protein content, hyperspectral, model

WANG JunJie,CHEN Ling,WANG HaiGang,CAO XiaoNing,LIU SiChen,TIAN Xiang,QIN HuiBin,QIAO ZhiJun. Effects of Hyperspectral Prediction on Leaf Nitrogen Content and the Grain Protein Content of Broomcorn Millet[J].Scientia Agricultura Sinica, 2019, 52(15): 2593-2603.

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References 30

[1]	王绍华, 吉志军, 刘胜环, 丁艳峰, 曹卫星 . 水稻氮素供需差与不同叶位叶片氮转运和衰老的关系. 中国农业科学, 2003,36(11):1261-1265.
	WANG S H, JI Z J, LIU S H, DING Y F, CAO W X . Relationships between balance of nitrogen supply-demand and nitrogen translocation and senescence of leaves at different positions of rice. Scientia Agricultura Sinica, 2003,36(11):1261-1265. (in Chinese)
[2]	李刚华, 薛利红, 尤娟, 王绍华, 丁艳峰, 吴昊, 杨文祥 . 水稻氮素和叶绿素SPAD 叶位分布特点及氮素诊断的叶位选择. 中国农业科学, 2007,40(6):1127-1134.
	LI G H, XUE L H, YOU J, WANG S H, DING Y F, WU H, YANG W X . Spatial distribution of leaf N content and SPAD value and determination of the suitable leaf for N diagnosis in rice. Scientia Agricultura Sinica, 2007,40(6):1127-1134. (in Chinese)
[3]	李金梦, 叶旭君, 王巧男, 张初, 何勇 . 高光谱成像技术的柑橘植株叶片含氮量预测模型. 光谱学与光谱分析, 2014,34(1):212-216.
	LI J M, YE X J, WANG Q N, ZHANG C, HE Y . Development of prediction models for determining N content in citrus leaves based on hyperspectral imaging technology. Spectroscopy and Spectral Analysis, 2014,34(1):212-216. (in Chinese)
[4]	冯伟, 姚霞, 朱艳, 田永超, 曹卫星 . 基于高光谱遥感的小麦叶片含氮量监测模型研究. 麦类作物学报, 2008,28(5):851-860.
	FENG W, YAO X, ZHU Y, TIAN Y C, CAO W X . Monitoring leaf nitrogen concentration by hyperspectral remote sensing in wheat. Journal of Triticeae Crops, 2008,28(5):851-860. (in Chinese)
[5]	冯伟, 姚霞, 田永超, 朱艳, 刘小军, 曹卫星 . 小麦籽粒蛋白质含量高光谱预测模型研究. 作物学报, 2007,33(12):1935-1942.
	FENG W, YAO X, TIAN Y C, ZHU Y, LIU X J, CAO W X . Predicting grain protein content with canopy hyperspectral remote sensing in wheat. Acta Agronomica Sinica, 2007,33(12):1935-1942. (in Chinese)
[6]	张松, 冯美臣, 杨武德, 王超, 孙慧, 贾学勤, 武改红 . 基于近红外光谱的冬小麦籽粒蛋白质含量检测. 生态学杂志, 2018,37(4):1276-1281.
	ZHANG S, FENG M C, YANG W D, WANG C, SUN H, JIA X Q, WU G H . Detection of grain content in winter wheat based on near infrared spectroscopy. Chinese Journal of Ecology, 2018,37(4):1276-1281. (in Chinese)
[7]	乔瑶瑶, 赵武奇, 胡新中, 李小平 . 近红外光谱技术检测燕麦中蛋白质含量. 中国粮油学报, 2016,31(8):138-142.
	QIAO Y Y, ZHAO W Q, HU X Z, LI X P . Determination of protein content in oat using near-infrared spectroscopy. Journal of the Chinese Cereals and Oils Association, 2016,31(8):138-142. (in Chinese)
[8]	顾志宏 . 基于高光谱的大麦籽粒蛋白质含量遥感预测. 光谱学与光谱分析, 2012,32(2):435-438.
	GU Z H . The prediction of barley grain protein content based on hyperspectral data. Spectroscopy and Spectral Analysis, 2012,32(2):435-438. (in Chinese)
[9]	李振海, 徐新刚, 金秀良, 张竞成, 宋晓宇, 宋森楠, 杨贵军, 王纪华 . 基于氮素运转原理和GRA-PLS算法的冬小麦籽粒蛋白质含量遥感预测. 中国农业科学, 2014,47(19):3780-3790. doi: 10.3864/j.issn.0578-1752.2014.19.006
	LI Z H, XU X G, JIN X L, ZHANG J C, SONG X Y, SONG S N, YANG G J, WANG J H . Remote sensing prediction of winter wheat protein content based on nitrogen translocation and GRA-PLS method. Scientia Agricultura Sinica, 2014,47(19):3780-3790. (in Chinese) doi: 10.3864/j.issn.0578-1752.2014.19.006
[10]	贺佳, 刘冰峰, 黎世民, 郭燕, 王来刚, 张彦, 李军 . 不同生育时期冬小麦籽粒蛋白质含量的高光谱遥感监测模型. 中国生态农业学报, 2017,25(6):865-875.
	HE J, LIU B F, LI S M, GUO Y, WANG L G, ZHANG Y, LI J . Winter wheat grain protein content monitoring model driven by hyperspectral remote sensing images at different growth stages. Chinese Journal of Eco-Agriculture, 2017,25(6):865-875. (in Chinese)
[11]	陈鹏飞, 王吉顺, 潘鹏, 徐于月, 姚凌 . 基于氮素营养指数的冬小麦籽粒蛋白质含量遥感反演. 农业工程学报, 2011,27(9):75-80.
	CHEN P F, WANG J S, PAN P, XU Y Y, YAO L . Remote detection of wheat grain protein content using nitrogen nutrition index. Transactions of the Chinese Society of Agricultural Engineering, 2011,27(9):75-80. (in Chinese)
[12]	张新玉, 王颖杰, 刘若西, 申兵辉, 王皎月, 严衍禄, 康定明 . 近红外光谱技术应用于玉米单籽粒蛋白质含量检测分析的初步研究. 中国农业大学学报, 2017,22(5):25-31.
	ZHANG X Y, WANG Y J, LIU R X, SHEN B H, WANG J Y, YAN Y L, KANG D M . Application of near-infrared spectroscopy technology to analyze protein content in single kernel maize seed. Journal of China Agricultural University, 2017,22(5):25-31. (in Chinese)
[13]	张浩, 胡昊, 陈义, 唐旭, 吴春艳, 刘玉学, 杨生茂, 郑可锋 . 水稻叶片氮素及籽粒蛋白质含量的高光谱估测模型. 核农学报, 2012,26(1):135-140.
	ZHANG H, HU H, CHEN Y, TANG X, WU C Y, LIU Y X, YANG S M, ZHENG K F . Estimation nitrogen of rice leaf and protein of rice seed based on hyperspectral data. Journal of Nuclear Agricultural Sciences, 2012,26(1):135-140. (in Chinese)
[14]	李少昆, 谭海珍, 王克如, 肖春华, 谢瑞芝, 高世菊 . 小麦籽粒蛋白质含量遥感监测研究进展. 农业工程学报, 2009,25(2):302-307.
	LI S K, TAN H Z, WANG K R, XIAO C H, XIE R Z, GAO S J . Research progress in wheat grain protein content monitoring using remote sensing. Transactions of the Chinese Society of Agricultural Engineering, 2009,25(2):302-307. (in Chinese)
[15]	妙佳源, 张钰玉, 王孟, 张盼盼, 李夏, 韩浩坤, 刘凤琴, 冯佰利 . 旱区糜子农田冠层高光谱反射特征研究初报. 黑龙江八一农垦大学学报, 2015,27(5):6-9.
	MIAO J Y, ZHANG Y Y, WANG M, ZHANG P P, LI X, HAN H K, LIU F Q, FENG B L . Characteristics of hyperspectral reflectance of broomcorn millet canopy in semi-arid region. Journal of Heilongjiang Bayi Agricultural University, 2015,27(5):6-9. (in Chinese)
[16]	韩浩坤, 妙佳源, 张钰玉, 张大众, 宗国豪, 宫香伟, 李境, 冯佰利 . 基于高光谱反射率的糜子冠层叶片叶绿素含量估算. 干旱地区农业研究, 2018,36(1):164-170.
	HAN H K, MIAO J Y, ZHANG Y Y, ZHANG D Z, ZONG G H, GONG X W, LI J, FENG B L . Estimating chlorophyll content of proso millet canopy by hyperspectral reflectance. Agricultural Research in the Arid Areas, 2018,36(1):164-170. (in Chinese)
[17]	YANG H F, LI J L . Predictions of soil organic carbon using laboratory-based hyperspectral data in the northern Tianshan mountains, China. Environmental Monitoring and Assessment, 2013,185(5):3897-3908.
[18]	GAYDOU V, KISTER J, DUPUY N . Evaluation of multiblock NIR/ MIR PLS predictive models to detect adulteration of diesd/biodiesel blends by vegetal oil. Chemometrics and Intelligent Laboratory Systems, 2011,106(2):190-197.
[19]	VOHLAND M, BESOLD J, HILL J, FRVND H C . Comparing different multivariate calibration methods for the determination of soil organic carbon pools visible to near infrared spectroscopy. Geoderma, 2011,166:198-205.
[20]	陆景陵, 胡霭堂 . 植物营养学. 北京: 高等教育出版社, 2006.
	LU J L, HU A T . Plant Nutrition. Beijing: Higher Education Press, 2006. (in Chinese)
[21]	吴巍, 赵军 . 植物对氮素吸收利用的研究进展. 中国农学通报, 2010,26(13):75-78.
	WU W, ZHAO J . Advances on plants′ nitrogen assimilation and utilization. Chinese Agricultural Science Bulletin, 2010,26(13):75-78. (in Chinese)
[22]	王莉雯, 卫亚星 . 植被氮素浓度高光谱遥感反演研究进展. 光谱学与光谱分析, 2013,33(10):2823-2827.
	WANG L W, WEI Y X . Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing. Spectroscopy and Spectral Analysis, 2013,33(10):2823-2827. (in Chinese)
[23]	薛利红, 曹卫星, 罗卫红, 张宪 . 小麦叶片氮素状况与光谱特性的相关性研究. 植物生态学报, 2004,28(2):172-177.
	XUE L H, CAO W X, LUO W H, ZHANG X . Correlation between leaf nitrogen status and canopy spectral characteristics in wheat. Acta Phytoecologica Sinica, 2004,28(2):172-177. (in Chinese)
[24]	SELLERS P J . Canopy reflectance, photosynthesis, and transpiration, II. The role of biophysics in the linearity of their interdependence. Remote Sensing of Environment, 1987,21:143-183.
[25]	李冬梅, 田纪春, 翟红梅, 张永祥 . 小麦蛋白质含量测定方法比较. 山东农业科学, 2006(3):83-84.
	LI D M, TIAN J C, ZHAI H M, ZHANG Y X . Methods comparison of determining wheat protein. Shandong Agricultral Sciences, 2006(3):83-84. (in Chinese)
[26]	李振海, 杨贵军, 王纪华, 徐新刚, 宋晓宇 . 作物籽粒蛋白质含量遥感监测预报研究进展. 中国农业信息, 2018,30(1):46-54.
	LI Z H, YANG G J, WANG J H, XU X G, SONG X Y . Remote sensing of grain protein content in cereal: A review. China Agricultural Informatics, 2018,30(1):46-54. (in Chinese)
[27]	李映雪, 朱艳, 田永超, 姚霞, 秦晓东, 曹卫星 . 小麦叶片氮含量与冠层反射光谱指数的定量关系. 作物学报, 2006,32(3):358-362.
	LI Y X, ZHU Y, TIAN Y C, YAO X, QIN X D, CAO W X . Quantitative relationship between leaf nitrogen concentration and canopy reflectance spectra. Acta Agronomica Sinica, 2006,32(3):358-362. (in Chinese)
[28]	王纪华, 黄文江, 赵春江, 杨敏华, 王之杰 . 利用光谱反射率估算叶片生化组分和籽粒品质指标研究. 遥感学报, 2003,7(4):277-284. doi: 10.11834/jrs.20030408
	WANG J H, HUANG W J, ZHAO C J, YANG M H, WANG Z J . The inversion of leaf biochemical components and grain quality indicators of winter wheat with spectral reflectance. Journal of Remote Sensing, 2003,7(4):277-284. (in Chinese) doi: 10.11834/jrs.20030408
[29]	李映雪, 朱艳, 田永超, 尤小涛, 周冬琴, 曹卫星 . 小麦冠层反射光谱与籽粒蛋白质含量及相关品质指标的定量关系. 中国农业科学, 2005,38(7):1332-1338.
	LI Y X, ZHU Y, TIAN Y C, YOU X T, ZHOU D Q, CAO W X . Relationship of grain protein content and relevant quality traits to canopy reflectance spectra in wheat. Scientia Agricultura Sinica, 2005,38(7):1332-1338. (in Chinese)
[30]	屈莎, 李振海, 邱春霞, 杨贵军, 宋晓宇, 陈召霞, 刘畅 . 基于开花期氮素营养指标的冬小麦籽粒蛋白质含量遥感监测. 农业工程学报, 2017,33(12):186-193.
	QU S, LI Z H, QIU C X, YANG G J, SONG X Y, CHEN Z X, LIU C . Remote sensing prediction of winter wheat grain protein content based on nitrogen nutrition index at anthesis stage. Transactions of the Chinese Society of Agricultural Engineering, 2017,33(12):186-193. (in Chinese)

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样本类型 Type of sample	样本数 Number of sample	全距 Total distance	极小值 Mix	极大值 Max	均值 Mean	标准差 Standard deviation
建模集 Calibration set	122	2.900	1.090	3.990	2.974	0.724
验证集 Validation set	39	2.660	1.270	3.930	3.007	0.722

预处理 Pretreatment	光谱特征 Spectral characteristics (nm)
R	418	697	2274
1ST	534	683	2084

模型类型 Model type	建模集 Calibration set			验证集 Validation set			变量个数 Number of variable
模型类型 Model type	决定系数 R²	均方根误差 RMSE	预测残差 RPD	决定系数 R²	均方根误差 RMSE	预测残差 RPD	变量个数 Number of variable
R-SMLR	0.754	0.85	0.85	0.790	0.44	1.63	3
1ST-SMLR	0.858	0.27	2.65	0.882	0.15	4.65	3
R-PLS	0.829	0.30	2.42	0.894	0.14	5.05	4
1ST-PLS	0.957	0.15	4.80	0.885	0.14	5.09	4
R-SVM	0.928	0.19	3.71	0.924	0.12	6.07	3
1ST-SVM	0.900	0.23	3.14	0.911	0.12	5.87	2

生育时期 Growth stage	拔节期 Jointing	抽穗期 Booting	开花期 Heading	灌浆期 Filling	成熟期 Maturity	籽粒蛋白质含量 GPC
拔节期Jointing	1.00
抽穗期Booting	0.55**	1.00
开花期Heading	0.40*	0.31	1.00
灌浆期Filling	0.45**	0.35*	0.58**	1.00
成熟期Maturity	0.26	0.07	0.63**	0.61**	1.00
籽粒蛋白质含量 GPC	0.10	0.22	0.48**	0.66**	0.73**	1.00

生育时期 Growth stage	拟合方程 Equation	决定系数 R²
开花期 Heading	y=2.5509x+5.1857	0.631
灌浆期 Filling	y=1.8327x+8.8819	0.872
成熟期 Maturity	y=1.1921x+11.789	0.900

Effects of Hyperspectral Prediction on Leaf Nitrogen Content and the Grain Protein Content of Broomcorn Millet

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