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作物学报 ›› 2020, Vol. 46 ›› Issue (12): 1979-1990.doi: 10.3724/SP.J.1006.2020.04023

• 耕作栽培·生理生化 • 上一篇    下一篇

不同光谱指数反演马铃薯叶片氮累积量的研究

韩康(), 于静, 石晓华, 崔石新, 樊明寿*()   

  1. 内蒙古农业大学农学院, 内蒙古呼和浩特 010019
  • 收稿日期:2020-02-05 接受日期:2020-08-19 出版日期:2020-09-02 网络出版日期:2020-09-02
  • 通讯作者: 樊明寿
  • 基金资助:
    国家自然科学基金项目(31960637);内蒙古自治区自然科学基金项目(2019BS03021)

Inversion of nitrogen accumulation in potato leaf with different spectral indices

HAN Kang(), YU Jing, SHI Xiao-Hua, CUI Shi-Xin, FAN Ming-Shou*()   

  1. College of Agronomy, Inner Mongolia Agricultural University, Hohhot 010019, Inner Mongolia, China
  • Received:2020-02-05 Accepted:2020-08-19 Published:2020-09-02 Published online:2020-09-02
  • Contact: FAN Ming-Shou
  • Supported by:
    National Natural Science Foundation of China(31960637);Natural Science Foundation of Inner Mongolia(2019BS03021)

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摘要：

光谱指数作为光谱衍生参数, 可用于反映作物叶片氮累积量状况, 但其因环境与作物而有所不同。本研究在内蒙古察右中旗和杭锦旗, 以马铃薯克新1号与夏波蒂品种为研究对象, 于2016—2018年进行了田间试验, 并在马铃薯生育期间, 用手持式光谱仪(SVC HR-1024i)获取了马铃薯冠层地面观测光谱信息。在前人光谱指数算法的基础上, 通过相关分析对比了22种光谱指数与马铃薯叶片氮累积量(LNA)之间的相关关系, 并利用线性与非线性回归分析建立了马铃薯关键生育时期的氮素营养诊断模型。结果表明, (1)红边区域是反演马铃薯叶片氮素累积量的主要波段, 以715、720、726、734、747 nm构成的Vogelmann红边指数2 (VOG2)、Vogelmann红边指数3 (VOG3)为内蒙古地区马铃薯LNA的敏感光谱指数。(2)苗期、块茎形成期与全生育时期VOG3与LNA的关系符合二次项模型(R 2>0.75), 以此可以较好地估算不同施氮水平下的马铃薯LNA状况。(3)上述3个模型的均方根误差(RMSE)范围分别为4.04~6.69、9.45~10.89、9.17~13.45 kg hm -2, 生育时期对马铃薯叶片氮累积量监测模型的准确性影响较大, 生育后期模型的预测性能变差, 但全生育时期监测模型准确度较高, 因此生育前期分阶段建模与生育后期统一建模可以准确估算马铃薯氮素营养状况, 为光谱指数在马铃薯氮素营养诊断应用提供了理论依据与方法。

关键词: 马铃薯, 叶片氮累积量, 光谱指数, 监测模型

Abstract:

As an important derivative parameter of optical spectrum, spectral index could reflect the leaf nitrogen accumulation of crops. However, the sensitive spectral index varies with different environments and crops. In order to obtain the sensitive spectral index for potato in Inner Mongolia, field experiments were conducted in Chayouzhongqi and Hangjinqi of Inner Mongolia from 2016 to 2018, and during the potato growth period, the canopy spectrum information of potato cultivars Kexin 1 and Shepody was obtained using a handheld spectrometer (SVC HR-1024i). Based on the previous spectral indices algorithm, the correlation coefficients between the leaves nitrogen accumulation of potato (LNA) and each of the 22 spectral indices were compared, and the nitrogen nutrition diagnosis models of potato at critical growth stages were established using linear and nonlinear regression analysis. The results were as follows: (1) the red edge area was the main spectral band for inverting the LNA of potato, and Vogelmann red edge index 2 (VOG2), Vogelmann red edge index 3 (VOG3) were the sensitive spectral indices for potato LNA in Inner Mongolia, which composed of 715, 720, 726, 734, and 747 nm of spectral bands. (2) At the seedling stage, tuber formation stage or whole growth stage, the quadratic regression models (R 2 > 0.75) between VOG3 and LNA could estimate better the LNA of potato under different nitrogen levels using VOG3. (3) The root mean square error (RMSE) of the models was 4.04-6.69, 9.45-10.89, 9.17-13.45 kg hm -2, indicating the accuracy of using the models to predict potato LNA varies with potato growth stage, and it was lower at late growth stages, while it is higher for whole growth duration. In summary, the staged modeling for potato early growth period and the unified modeling for potato later growth period could accurately estimate the potato LNA, which provides a theoretical basis and method for the application of spectral indices in the nitrogen nutrition diagnosis of potato.

Key words: potato, leaf nitrogen accumulation, spectral index, monitoring models

表1

氮肥施用方案"

处理
Treatment		 基肥
Base fertilizer		 追肥Top dressing
出苗后10 d
10 days after emergence		 出苗后25 d
25 days after emergence
N0 0 0 0
N1 75 15 60
N2 75 45 180
N3 75 118.5 256.5
N4 75 150 375

表2

田间试验概况"

试验
Experiment		 年份
Year		 地点
Location		 品种
Variety		 播种日期
Sowing date
(month/day)		 收获日期
Harvest date
(month/day)		 出苗日期
Emergence date
(month/day)		 数据采集日期
Data collection date
(month/day)
Exp.1 2016 察右中旗
Chayouzhongqi		 克新1号
Kexin 1		 5/27 9/24 6/18 7/8, 7/23, 8/7, 8/22
Exp.2 2016 察右中旗
Chayouzhongqi		 夏波蒂
Shepody		 5/27 9/24 6/18 7/8, 7/23, 8/7, 8/22
Exp.3 2016 杭锦旗
Hangjinqi		 克新1号
Kexin 1		 5/27 9/24 6/20 7/10, 7/25, 8/9, 8/24
Exp.4 2017 察右中旗
Chayouzhongqi		 克新1号
Kexin 1		 5/11 9/20 6/13 7/3, 7/18, 8/2, 8/17
Exp.5 2018 察右中旗
Chayouzhongqi		 克新1号
Kexin 1		 5/3 9/28 6/10 6/30, 7/15, 7/30, 8/14

表3

SVC HR-1024i的光谱分辨率与采样间隔"

波长范围
Wavelength range (nm)		 光谱分辨率
Spectral resolution (nm)		 光谱采样间隔
Spectral sampling interval (nm)
350-1000 ≤3.3 ≤1.5
1000-1890 ≤9.5 ≤3.8
1890-2500 ≤6.5 ≤2.5

表4

光谱指数公式"

光谱指数
Spectral index		 计算公式
Calculation formula		 参考文献
References
1 Simple Ratio Index (SRI) R800 ? R680 Sim et al. [13]
2 Normalized Difference Vegetation (NDVI) (R800 - R680) ? (R800 + R680) Rouse et al. [14]
3 Difference Vegetation Index (DVI) R800 - R680 Richardson et al. [15]
4 Structure Insensitive Pigment Index (SIPI) (R800 - R445) ? (R800 + R680) Penuelas et al. [16]
5 Modified Red Edge Normalized Difference
Vegetation (mND705)		 (R750 - R705) ? (R750 + R705 - 2 × R445) Sims et al. [13]
6 Modified Simple Ratio Index (mSR705) (R750 - R445) ? (R705 - R445) Sims et al. [13]
7 Photochemical Reflectance Index (PRI) (R531 - R570) ? (R570 + R531) Gamon et al. [17]
8 Plant Senescence Reflectance Index (PSRI) (R680 - R500) ? R750 Merzlyak et al. [18]
9 The MERIS terrestrial Chlorophyll Index (MTCI) (R750 - R710) ? (R710 - R680) Dash et al. [19]
10 Modified Chlorophyll Absorption in Refectance
Index (MCARI)		 [(R700 - R670) - 0.2 × (R700 - R550)] × (R700 ? R670) Dash et al. [19]
11 Optimized Soil-adjusted Vegetation Index (OSAVI) (1 + 0.16) × (R800 - R670) ? (R800 + R670 + 0.16) Rondeaux et al. [20]
12 Transformed Chlorophyll Absorption In
Reflectance Index (TCARI)		 3 × [(R700 - R670) - 0.2 × (R700 - R550)] × (R700 ? R670) Haboudane et al. [21]
13 Enhanced Vegetation Index (EVI) 2.5 × (R800 - R680) ? (R800 + 6 × R680 - 7.5 × R450 + 1) Huete et al. [22]
14 Atmospherically Resistant Vegetation Index (ARVI) (R800 - 2 × R680 + R450) ? (R800 + 2 × R680 - R450) Kaufman et al. [23]
15 705nm Normalized Difference Vegetation (NDVI705) (R750 - R705) ? (R750 + R705) Gitelson et al. [24]
16 Vogelmann Red Edge Index 1 (VOG1) R740 ? R720 Zarco-Tejada et al. [25]
17 Vogelmann Red Edge Index 2 (VOG2) (R734 - R747) ? (R715 + R726) Zarco-Tejada et al. [25]
18 Vogelmann Red Edge Index 3 (VOG3) (R734 - R747) ? (R715 + R720) Zarco-Tejada et al. [25]
19 Carotenoid Reflectance Index 1 (CRI1) 1 ? R510 - 1 ? R550 Gitelson et al. [26]
20 Carotenoid Reflectance Index 2 (CRI2) 1 ? R510 - 1 ? R700 Gitelson et al. [26]
21 Anthocyanin Reflectance Index 1 (ARI1) 1 ? R550 - 1 ? R700 Gitelson et al. [27]
22 Anthocyanin Reflectance Index 2 (ARI2) R800 × (1 ? R550 - 1 ? R700) Gitelson et al. [28]

表5

建模集与验证集的样本数量"

生育时期
Growth stage		 样本数量Number of samples
建模集Modeling set 验证集Validation set
苗期Seedling stage 45 30
块茎形成期Tuber formation stage 45 30
块茎膨大期Tuber expansion stage 45 30
淀粉积累期Starch accumulation stage 45 30
全生育时期Total growth stages 180 120

图2

不同施氮水平对叶片氮累积量的影响(Exp.1) LNA为叶片氮累积量。处理同表1。不同小写字母表示在0.05水平上显著差异。"

图3

不同施氮水平对冠层反射率的影响 a: 全波段; b: 可见光波段; c: 红边波段。处理同表1。"

表6

光谱指数与叶片氮累积量的回归模型"

生育时期
Growth stage		 监测模型方程式
Monitoring model equation		 R2
苗期Seedling stage LNA = - 269.271 × VOG3 - 16.5 0.882**
LNA = 1976.733 × VOG32 + 211.143 × VOG3 + 11.236 0.913**
LNA = 1.712 × e-17.519 × VOG3 0.908**
块茎形成期Tuber formation stage LNA = - 323.22 × VOG3 - 21.257 0.771**
LNA = 1393.778 × VOG32 + 162.368×VOG3 + 17.484 0.790**
LNA = 4.841 × e-10.411 × VOG3 0.740**
块茎膨大期Tuber expansion stage LNA = - 403.678 × VOG3 - 34.233 0.723**
LNA = 1020.908 × VOG32 - 20.441 × VOG3 - 0.711 0.741**
LNA = 4.249 × e-11.184 × VOG3 0.741**
淀粉积累期Starch accumulation stage LNA = - 279.991 × VOG2 - 8.249 0.550**
LNA = - 654.51 × VOG22 - 464.961 × VOG2 - 20.102 0.555**
LNA = 4.894 × e-11.837 × VOG2 0.570**
全生育时期Total growth stages LNA = - 328.711 × VOG3 - 21.683 0.765**
LNA = 832.343 × VOG32 - 46.576 × VOG3 - 0.242 0.778**
LNA = 3.867 × e-11.534 × VOG3 0.773**

图5

光谱指数与叶片氮累积量的关系 LNA为叶片氮累积量。a: 苗期; b: 块茎形成期; c: 全生育时期。**表示在0.01水平上显著差异。"

表7

马铃薯叶片氮累积量监测模型的检验"

生育时期
Growth stage		 均方根误差RMSE (kg hm-2)
Exp.2 Exp.3
苗期Seedling stage 6.69 4.04
块茎形成期Tuber formation stage 9.45 10.89
块茎膨大期Tuber expansion stage 13.38 9.12
淀粉积累期Starch accumulation stage 16.18 14.13
全生育时期Total growth stages 13.45 9.17

图6

叶片氮累积量估测值与观察值之间的关系 a: 苗期; b: 块茎形成期; c: 块茎膨大期; d: 淀粉积累期; e: 全生育时期。"

图4

光谱指数与叶片氮累积量的相关性 a: 苗期; b; 块茎形成期; c块茎膨大期; d: 淀粉积累期; e: 全生育时期。缩写同表4。"

图1

试验地位置及试验小区分布 N0~N4分别代表0、150、300、450、600 kg hm-2 的氮肥水平; a、b、c为3次重复。"

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