[1]宋英博,贾立君,杜永生,等.利用叶片反射光谱预测大豆合交98-1667干物重模型[J].大豆科学,2010,29(03):429-432.[doi:10.11861/j.issn.1000-9841.2010.03.0429]
　SONG Ying-bo,JIA Li-jun,DU Yong-sheng,et al.Predicting Model of Dry Matter Accumulation of Dwarf Soybean Hybrid 98-1667 by Leaf Reflectance Spectra[J].Soybean Science,2010,29(03):429-432.[doi:10.11861/j.issn.1000-9841.2010.03.0429]
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利用叶片反射光谱预测大豆合交98-1667干物重模型

《大豆科学》[ISSN:1000-9841/CN:23-1227/S] 卷: 第29卷 期数: 2010年03期 页码: 429-432 栏目: 出版日期: 2010-06-25
Title:
Predicting Model of Dry Matter Accumulation of Dwarf Soybean Hybrid 98-1667 by Leaf Reflectance Spectra
文章编号:
1000-9841（2010）03-0429-04
作者:
宋英博1; 2; 贾立君2; 杜永生2; 王囡囡2; 邓际华3; 陈庆山1; 胡国华4
1.东北农业大学 农学院，黑龙江 哈尔滨 150030；
2.黑龙江省农业科学院 佳木斯分院，黑龙江 佳木斯 154007；
3.黑龙江省合江林业科学研究所，黑龙江 佳木斯 154002；
4.黑龙江省农垦科研育种中心，黑龙江 哈尔滨 150090
Author(s):
SONG Ying-bo1; 2;  JIA Li-jun2;  DU Yong-sheng2;  WANG Nan-nan2;  DENG Ji-hua3;  CHEN Qing-shan1; HU Guo-hua4
1.Agriculture College, Northest Agricultural University,Harbin 150030,Heilongjiang;
2.Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences,Jiamusi 154007,Heilongjiang;
3.Hejiang Forestry Institute of Heilongjiang Academy of Forestry Sciences,Jiamusi 154002,Heilongjiang;
4.The Crop Research and Breeding Center of land-Reclamation,Harbin 150090,Heilongjiang,China
关键词:
植被指数; 光谱反射率; 干物重; 估测模型
Keywords:
Vegetation index; Spectrum reflectance; Dry matter accumulation; Estimation model
分类号:
S565.1
DOI:
10.11861/j.issn.1000-9841.2010.03.0429
文献标志码:
A
摘要:
通过对不同波长光谱反射率的分析，确立大豆地上部干物重的敏感波段，计算出相应的植被指数，并建立植被指数与大豆地上部干物质量预测模型。结果表明：在可见光波段范围内，合交98-1667选取510 nm和680 nm 2个波段的光谱反射率与地上部干物重的相关性呈极显著；在近红外区域，选取800 nm、900 nm和1005 nm 3个波段，其中800 nm和900 nm的光谱反射率与合交98-1667地上部干物重的相关性均呈极显著，波长为1005 nm时呈显著相关。4种植被指数经过比较RVI相关性最好。通过RVI植被指数建立模型，Y= 4.0216×RVI2（900，680)-99.106×RVI（900，680) + 625.36，能较为准确预测大豆地上部干物重。
Abstract:
The sensitive wavebands were determined by analyzing relationship with spectra reflectance in different wavebands and the dry matter accumulation in above-ground part of soybean, and the prediction model was established. The results showed that there were highly significant correlations between spectra reflectance of 510 and 680 nm which selected from among visible light and the dry matter accumulation in the above-ground part of hybrid 98-1667, spectra reflectance of 800 and 900 nm in the range of near infrared light were highly significant correlated, and spectra reflectance of 1005 nm was significantly correlated with the above-ground weight. After compared with those four vegetation indices, the RVI has the best relativity. The corresponding prediction model established by vegetation indices of RVI was Y= 4.0216×RVI2（900,680)-99.106×RVI(900,680) + 625.36, and it could be accurate to predict the dry matter accumulation in above-ground part of soybean .

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备注/Memo

基金项目：黑龙江省国际合作资助项目（WB08C07）。

第一作者简介：宋英博（1979-），男，在读硕士，研究方向为植物营养。 E-mail: hjsyb@tom.com。

更新日期/Last Update: 2014-09-13