欢迎访问作物学报，今天是
作物学报

作物学报 ›› 2020, Vol. 46 ›› Issue (6): 950-959.doi: 10.3724/SP.J.1006.2020.94121

• 耕作栽培·生理生化 • 上一篇    下一篇

品种和生育时期对冠层光谱指数(NDVI)估测马铃薯植株氮素浓度的影响

杨海波,张加康,杨柳,贾禹泽,刘楠,李斐()   

  1. 内蒙古农业大学草原与资源环境学院 / 内蒙古自治区土壤质量与养分资源重点实验室, 内蒙古呼和浩特 010018
  • 收稿日期:2019-08-17 接受日期:2019-12-26 出版日期:2020-06-12 网络出版日期:2020-01-14
  • 通讯作者: 李斐
  • 作者简介:E-mail: hbyang93@163.com
  • 基金资助:
    2018年内蒙古自治区高等学校“青年科技英才支持计划”(NJYT-18-A08);国家自然科学基金项目(41361079)

Effect of variety and growth period on NDVI estimation of nitrogen concentration in potato plants

YANG Hai-Bo,ZHANG Jia-Kang,YANG Liu,JIA Yu-Ze, ,LI Fei()   

  1. Inner Mongolia Key Laboratory of Soil Quality and Nutrient Resource / College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010018, Inner Mongolia, China
  • Received:2019-08-17 Accepted:2019-12-26 Published:2020-06-12 Published online:2020-01-14
  • Contact: Fei LI
  • Supported by:
    “Youth Science and Technology Talents Support Program” (NJYT-18-A08) of Colleges and Universities of Inner Mongolia Autonomous Region in 2018(NJYT-18-A08);National Natural Science Foundation of China(41361079)

RichHTML

9

PDF

859

摘要：

NDVI是反映作物叶绿素相对含量及氮素水平的重要参数, 但是作物品种和生育时期的变化对NDVI估测氮素营养的能力有重要影响。本研究在内蒙古阴山北麓马铃薯主产区进行了多年多品种田间试验, 于2014—2016年7月上旬至8月中旬马铃薯关键生育时期, 利用便携式主动作物传感器GreenSeeker获取马铃薯冠层光谱指数NDVI, 对比了品种和生育时期对NDVI估测结果的影响。结果表明, 块茎形成期NDVI与马铃薯植株氮素浓度相关性较差, 随着生育时期的推进, NDVI与植株氮素浓度的线性相关性增强, 块茎膨大期与淀粉积累期组合会显著提高NDVI与植株氮素浓度的线性建模效果。品种混合会降低NDVI的灵敏性, 增加数据的离散性, 基于时间序列归一化的光谱指数TNDVI能够克服这些问题, 尤其是在块茎膨大期TNDVI与植株氮素浓度的拟合决定系数(R 2)能够由原来的0.13提高到0.47。TNDVI对块茎形成期、块茎膨大期和淀粉积累期组合的线性估测建模R 2为0.76, 显著高于NDVI。株型展开型的品种在块茎膨大期和淀粉积累期更具线性拟合趋势。研究表明, 马铃薯生育时期和品种对NDVI估测植株氮素浓度有显著影响, 且生育时期的影响更大。构建的TNDVI光谱指数能够克服品种差异导致的块茎膨大期、淀粉积累期数据分异及饱和现象, 为NDVI在马铃薯植株氮素浓度诊断应用的普适性上提供了理论依据与方法。

关键词: 马铃薯, 品种, 生育时期, 主动作物传感器, 归一化光谱指数, 植株氮素浓度

Abstract:

The normalized difference vegetation index (NDVI) is an important parameter to reflect relative chlorophyll content and nitrogen level of crops, but NDVI’s ability to estimate nitrogen nutrition is affected by varieties and growth period. The field experiments using several varieties were conducted in the main potato producing areas at the north foot of Yinshan mountain, Inner Mongolia. From early July to mid-august in 2014 to 2016, the canopy spectral index NDVI was measured by using the pocket active crop sensor GreenSeeker during potato critical growth period. The effects of cultivars and growth stages on NDVI estimation of nitrogen concentration in potato plants were compared. The linear correlation between NDVI and plant nitrogen concentration (PNC) was poor in tuber initiation, but increased in process of growth period. The combination of tuber bulking period and starch accumulation period significantly improved the linear modeling effect of NDVI and PNC. Variety combination reduced the sensitivity of NDVI and increased the discreteness of data, which could be offset by NDVI time series normalization (TNDVI), especially the fitting coefficient of determination (R 2) of TNDVI and PNC increased from 0.13 to 0.47 in the tuber bulking period. The R 2of linear estimation model of TNDVI for the combination of tuber initiation, tuber bulking and starch accumulation period was 0.76, which was significantly higher than that of NDVI. Plant-expanded varieties had a more linear fitting trend during tuber bulking and starch accumulation. The growth period and potato varieties had significant effects on NDVI estimation of PNC, and growth period had a greater effect. The established TNDVI spectral index overcame the data differentiation and saturation phenomenon during tuber bulking and starch accumulation caused by variety difference, which provides a theoretical basis and method for the application of NDVI in the diagnosis of nitrogen concentration in potato plants.

Key words: potato, varieties, growth stage, active crop sensor, NDVI, PNC

图1

试验地位置及试验小区分布 T1~T7分别代表由低到高的氮肥用量处理; a、b、c、d为4次重复。"

表1

NDVI与马铃薯植株氮素浓度的相关性(R2)"

时间
Year		 品种
Species		 函数类型
Function types		 块茎形成期
Tuber
initiation (A)		 块茎膨大期
Tuber
bulking (B)		 淀粉积累期
Starch
accumulation (C)		 A+B B+C A+B+C
2014 克新1号
Kexin 1		 线性函数 LF 0.04 0.83** 0.44** 0.38** 0.52** 0.52**
二次函数 QF 0.09 0.87** 0.44** 0.48** 0.52** 0.59**
幂函数 PF 0.04 0.85** 0.44** 0.45** 0.52** 0.55**
指数函数 EF 0.04 0.83** 0.44** 0.38** 0.52** 0.52**
2015 夏坡蒂Xiapodi 线性函数 LF 0.04 0.37** 0.36** 0.04 0.85** 0.52**
二次函数 QF 0.05 0.48** 0.40** 0.10 0.85** 0.67**
幂函数 PF 0.04 0.41** 0.35** 0.03 0.83** 0.58**
指数函数 EF 0.04 0.38** 0.35** 0.04 0.85** 0.53**
2016 荷兰14号
Holland 14		 线性函数 LF 0.07 0.44** 0.52** 0.01 0.72** 0.52**
二次函数 QF 0.08 0.56** 0.64** 0.15 0.76** 0.74**
幂函数 PF 0.07 0.45** 0.55** 0.01 0.74** 0.58**
指数函数 EF 0.08 0.44** 0.52** 0.01 0.72** 0.52**
全部All 线性函数 LF 0.03 0.07* 0.50** 0 0.48** 0.28**
二次函数 QF 0.06 0.13* 0.57** 0 0.58** 0.42**
幂函数 PF 0.03 0.08* 0.52** 0 0.50** 0.32**
指数函数 EF 0.03 0.07* 0.49** 0 0.48** 0.28**

图2

马铃薯块茎形成期、块茎膨大期、淀粉积累期NDVI与植株氮素浓度的估测模型"

图3

马铃薯组合生育时期NDVI与植株氮素浓度的估测模型 A, B和C分别代表马铃薯块茎形成期、块茎膨大期和淀粉积累期。"

图4

马铃薯品种混合条件下NDVI和植株氮素浓度估测模型的构建 A, B和C分别代表马铃薯块茎形成期、块茎膨大期和淀粉积累期。"

图5

品种混合时马铃薯块茎膨大期和淀粉积累期TNDVI与植株氮素浓度估测模型的构建"

图6

品种混合时马铃薯组合生育时期TNDVI与植株氮素浓度估测模型的构建"

图7

NDVI和TNDVI估测建模的敏感性分析 A、B、C分别代表块茎形成期、块茎膨大期和淀粉积累期。"

[1] 张晗, 赵小敏, 郭熙, 张佳佳, 叶春, 叶英聪, 李小毛 . 基于冠层高光谱信息的水稻生长监测应用研究进展. 江苏农业科学, 2018,46(12):1-9.
Zhang H, Zhao X M, Guo X, Zhang J J, Ye C, Ye Y C, Li X M . Advances in application of rice growth monitoring based on canopy layer spectral information, Jiangsu Agric Sci, 2018,46(12):1-9 (in Chinese).
[2] 张卫峰, 马林, 黄高强, 武良, 陈新平, 张福锁 . 中国氮肥发展贡献和挑战. 中国农业科学, 2013,46:3161-3171.
Zhang W F, Ma L, Huang G Q, Wu L, Chen X P, Zhang F S . The development and contribution of nitrogenous fertilizer in China and challenges faced by the country. Sci Agric Sin, 2013,46:3161-3171 (in Chinese with English abstract).
[3] 魏全全, 李岚涛, 任涛, 王振, 王少华, 李小坤, 鲁剑巍 . 基于数字图像技术的冬油菜氮素营养诊断. 中国农业科学, 2015,48:3877-3886.
Wei Q Q, Li F T, Ren T, Wang Z, Wang S H, Li X K, Lu J W . Diagnosing nitrogen nutrition status of winter rapeseed via digital Image processing technique. Sci Agric Sin, 2015,48:3877-3886 (in Chinese with English abstract).
[4] Nigon T J, Mulla D J, Rosen C J, Cohen Y, Alchanatis V, Rud R . Evaluation of the nitrogen sufficiency index for use with high resolution, broadband aerial imagery in a commercial potato field. Precision Agric, 2014,15:202-226.
doi: 10.1007/s11119-013-9333-6
[5] Wei W, Xia Y, Tian Y C, Liu X J, Jun N I, Cao W X, Yan Z H . Common spectral bands and optimum vegetation indices for monitoring leaf nitrogen accumulation in rice and wheat. J Integr Agric, 2012,11:2001-2012.
doi: 10.1016/S2095-3119(12)60457-2
[6] 卢艳丽, 白由路, 杨俐苹, 王磊 . N利用GreenSeeker法诊断春玉米氮素营养状况的研究. 玉米科学, 2008,16(1):111-115.
Lu Y L, Bai Y L, Yang L P, Wang L . Diagnos is on nitrogen status using GreenSeeker in spring maize. J Maize Sci, 2008,16(1):111-115 (in Chinese with English abstract).
[7] 郭建华, 王秀, 孟志军, 赵春江, 宇振荣, 陈立平 . 主动遥感光谱仪 Greenseeker与 SPAD 对玉米氮素营养诊断的研究. 植物营养与肥料学报, 2008,14(1):43-47.
doi: 10.11674/zwyf.2008.0107
Guo J H, Wang X, Meng Z J, Zhao C J, Yu Z R, Chen L P . Study on diagnosing nitrogen nutrition status of corn using GreenSeeker and SPAD meter. Plant Nutr Fert Sci, 2008,14(1):43-47 (in Chinese with English abstract).
doi: 10.11674/zwyf.2008.0107
[8] 张俊华, 张佳宝, 李立平 . 基于冬小麦植被指数的氮肥调控技术研究. 土壤学报, 2007,44:550-555.
Zhang J H, Zhang J B, Li L P . Nitrogen regulation technology based on canopy spectral property of winter wheat. Acta Pedol Sin, 2007,44:550-555 (in Chinese with English abstract).
[9] Raun W R, Solie J B, Johnson G V, Stone M L, Lukina E V, Thomason W E, Schepers J S . In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron J, 2001,93:131-138.
[10] Franzen D W. Nitrogen management in sugar beet using remote sensing and GIS. In: Francis J P, David C, eds. GIS Applications in Agriculture. New York: Taylor and Francis Group, 2007. pp 35-39.
[11] Li F, Gnyp M L, Jia L L, Miao Y X, Yu Z H, Koppe W, Chen X P, Zhang F S . Estimating N status of winter wheat using a handheld spectrometer in the North China Plain. Field Crops Res, 2008,106:77-85.
[12] Gnyp M L, Miao Y X, Yuan F, Ustin S L, Yu K, Yao Y K, Bareth G . Hyperspectral canopy sensing ofpaddy rice aboveground biomass at different growth stages. Field Crops Res, 2014,155:42-55.
[13] Xia T T, Miao Y X, Wu D L, Shao H . Active optical sensing of spring maize for in-season diagnosis of nitrogen status based on nitrogen nutrition index. Remote Sensing, 2016,8:605.
doi: 10.3390/rs8070605
[14] Yao Y K, Miao Y X, Cao Q, Wang H Y . In-season estimation of rice nitrogen status with an active crop canopy sensor. IEEE J Selected Top Appl Earth Observ Remote Sensing, 2014,7:4403-4413.
[15] 于静, 李斐, 秦永林, 樊明寿 . 应用主动作物冠层传感器对马铃薯氮素营养诊断. 光谱学与光谱分析, 2013,33:3092-3097.
Yu J, Li F, Qin Y L, Fan M S . Active crop canopy sensor-based nitrogen diagnosis for potato. Spectroscopy Spectral Anal, 2013,33:3092-3097 (in Chinese with English abstract).
[16] 高兴, 李斐, 杨海波, 黄绍福, 张加康, 苗杰, 黄伟杰 . 基于红边位置的马铃薯植株氮浓度估测方法研究. 植物营养与肥料学报, 2019,25:296-310.
Gao X, Li F, Yang H B, Huang S F, Zhang J K, Miao J, Huang W J . Appropriate calculation method for the use of red edge position to estimate potato nitrogen concentration. Plant Nutr Fert Sci, 2019,25:296-310 (in Chinese with English abstract).
[17] Wang W, Yao X, Yao X F, Tian Y C, Liu X J, Ni J, Cao W X, Zhu Y . Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Res, 2012,129:90-98.
[18] Mistele B, Schmidhalter U . Spectral measurements of the total aerial N and biomass dry weight in maize using a quadrilateral-view optic. Field Crops Res, 2008,106:94-103.
doi: 10.1016/j.fcr.2007.11.002
[19] 杨贵军, 邢著荣, 黄文江, 齐腊, 李伟国 . 不同株型冬小麦冠层结构特征多时相分析. 农业工程学报, 2010,26(7):227-234.
Yang G J, Xing Z R, Huang W J, Qi L, Li W G . Analysis of winter canopy structure for different plant types of growth period. Trans CSAE, 2010,26(7):227-234 (in Chinese with English abstract).
[20] Raun W R, Solie J B, Johnson G V, Stone M L, Lukina E V, Thomason W E, Schepers J S . In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron J, 2001,93:131-138.
[21] Sharma L K, Franzen D W . Use of corn height to improve the relationship between active optical sensor readings and yield estimates. Precision Agric, 2014,15:331-345.
[22] Walsh O S, Klatt A R, Solie J B, Godsey C B, Raun W R . Use of soil moisture data for refined GreenSeeker sensor based on nitrogen recommendations in winter wheat ( Triticum aestivum L.). Precision Agric, 2013,14:343-356.
doi: 10.1007/s11119-012-9299-9
[23] Viña A, Gitelson A A, Nguy-Robertson A L, Peng Y, . Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sensing Environ, 2011,115:3468-3478.
[24] 任建强, 陈仲新, 周清波, 唐华俊 . 基于叶面积指数反演的区域冬小麦单产遥感估测. 应用生态学报, 2010,21:2883-2888.
Ren J Q, Chen Z X, Zhou Q B, Tang J H . LAI-based regional winter wheat yield estimation by remote sensing. Chin J Appl Ecol, 2010,21:2883-2888 (in Chinese with English abstract).
[1] 王丹, 周宝元, 马玮, 葛均筑, 丁在松, 李从锋, 赵明. 长江中游双季玉米种植模式周年气候资源分配与利用特征[J]. 作物学报, 2022, 48(6): 1437-1450.
[2] 徐田军, 张勇, 赵久然, 王荣焕, 吕天放, 刘月娥, 蔡万涛, 刘宏伟, 陈传永, 王元东. 宜机收籽粒玉米品种冠层结构、光合及灌浆脱水特性[J]. 作物学报, 2022, 48(6): 1526-1536.
[3] 王海波, 应静文, 何礼, 叶文宣, 涂卫, 蔡兴奎, 宋波涛, 柳俊. rDNA和端粒重复序列鉴定马铃薯和茄子体细胞杂种染色体丢失和融合[J]. 作物学报, 2022, 48(5): 1273-1278.
[4] 石艳艳, 马志花, 吴春花, 周永瑾, 李荣. 垄作沟覆地膜对旱地马铃薯光合特性及产量形成的影响[J]. 作物学报, 2022, 48(5): 1288-1297.
[5] 柯健, 陈婷婷, 吴周, 朱铁忠, 孙杰, 何海兵, 尤翠翠, 朱德泉, 武立权. 沿江双季稻北缘区晚稻适宜品种类型及高产群体特征[J]. 作物学报, 2022, 48(4): 1005-1016.
[6] 冯亚, 朱熙, 罗红玉, 李世贵, 张宁, 司怀军. 马铃薯StMAPK4响应低温胁迫的功能解析[J]. 作物学报, 2022, 48(4): 896-907.
[7] 张霞, 于卓, 金兴红, 于肖夏, 李景伟, 李佳奇. 马铃薯SSR引物的开发、特征分析及在彩色马铃薯材料中的扩增研究[J]. 作物学报, 2022, 48(4): 920-929.
[8] 谭雪莲, 郭天文, 胡新元, 张平良, 曾骏, 刘晓伟. 黄土高原旱作区马铃薯连作根际土壤微生物群落变化特征[J]. 作物学报, 2022, 48(3): 682-694.
[9] 闫岩, 张钰石, 刘础荣, 任丹阳, 刘洪润, 刘雪晴, 张明才, 李召虎. 冬小麦-夏玉米轮作“双晚”种植模式下的品种匹配与资源效率[J]. 作物学报, 2022, 48(2): 423-436.
[10] 陈新宜, 宋宇航, 张孟寒, 李小艳, 李华, 汪月霞, 齐学礼. 干旱对不同品种小麦幼苗的生理生化胁迫以及外源5-氨基乙酰丙酸的缓解作用[J]. 作物学报, 2022, 48(2): 478-487.
[11] 余慧芳, 张卫娜, 康益晨, 范艳玲, 杨昕宇, 石铭福, 张茹艳, 张俊莲, 秦舒浩. 马铃薯CrRLK1Ls基因家族的鉴定及响应晚疫病菌信号的表达分析[J]. 作物学报, 2022, 48(1): 249-258.
[12] 荐红举, 尚丽娜, 金中辉, 丁艺, 李燕, 王季春, 胡柏耿, Vadim Khassanov, 吕典秋. 马铃薯PIF家族成员鉴定及其对高温胁迫的响应分析[J]. 作物学报, 2022, 48(1): 86-98.
[13] 许德蓉, 孙超, 毕真真, 秦天元, 王一好, 李成举, 范又方, 刘寅笃, 张俊莲, 白江平. 马铃薯StDRO1基因的多态性鉴定及其与根系性状的关联分析[J]. 作物学报, 2022, 48(1): 76-85.
[14] 傅华英, 张婷, 彭文静, 段瑶瑶, 许哲昕, 林艺华, 高三基. 甘蔗新品种(系)苗期白条病人工接种抗性鉴定与评价[J]. 作物学报, 2021, 47(8): 1531-1539.
[15] 习玲, 王昱琦, 朱微, 王益, 陈国跃, 蒲宗君, 周永红, 康厚扬. 78份四川小麦育成品种(系)条锈病抗性鉴定与抗条锈病基因分子检测[J]. 作物学报, 2021, 47(7): 1309-1323.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2