光谱学与光谱分析最新文献_第5页

Prediction Model of Wood Absolute Dry Density by Near-Infrared Spectroscopy Based on IPSO-BP 基于IPSO-BP的近红外光谱木材绝对干密度预测模型

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2937-06

Lei Yu, Jin-hao Chen, Longbo Li, Chao Li, Yi-zhuo Zhang

引用次数: 1

Watercore Identification of Xinjiang Fuji Apple Based on Manifold Learning Algorithm and Near Infrared Transmission Spectroscopy 基于流形学习算法和近红外透射光谱的新疆富士苹果水核鉴定

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)08-2415-06

Juncheng Guo, Yongjie Ma, Zhiming Guo, Hua Huang, Shi Yong, Jun Zhou

引用次数: 1

The Content and Kinetics of Sucrose Hydrolysis Were Studied by Raman Spectroscopy 用拉曼光谱研究了蔗糖水解的含量和动力学

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2821-05

Hui Su, Jin-ge Ma, Xin Xin, Ying Han, Huo-lan Huang, Xiaofei Huang, Zhixiang Yao

引用次数: 0

Study on the Relationship Between Black Soil Emissivity Spectrum and Total Potassium Content Based on TASI Thermal Infrared Data 基于TASI热红外数据的黑土发射光谱与全钾含量关系研究

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2862-07

Ming Li, Kai Qin, Ning Zhao, Feng Tian

引用次数: 2

The Categories of the UV-Vis Reflectance Spectra of Seawater Cultured Black Pearl and Its Unique PL Spectral Characteristics 海水养殖黑珍珠紫外-可见光谱的分类及其独特的PL光谱特征

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2781-05

Yan Jun, S. Qing, Xueqing Yan, F. Shibin, Shen Jiawei, Zhang Jian

引用次数: 1

Identification Method of Imported Timber Species by Mid-Infrared Spectrum 进口木材品种的中红外光谱识别方法

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)07-2128-05

G. Feng, Yu-jie Zhu, Yao-xiang Li

引用次数: 2

Quantitative Analysis of Fuel Blends Based on Raman and Near Infrared Absorption Spectroscopy 基于拉曼光谱和近红外吸收光谱的燃料混合物定量分析

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)06-1889-06

Zhe Liu, N. Luo, Jiulin Shi, Yubao Zhang, Xingdao He

引用次数: 1

Study on Raman Spectra and Fluorescence Spectra of Dy3Al2(AlO4)3 in Aluminosilicate Substrates 硅酸铝衬底中Dy3Al2(AlO4)3的拉曼光谱和荧光光谱研究

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)03-0809-04

Bao-feng Zheng, Xiao-yun Yang, Chungang Min, Cui Xiaoying, Kun Dong

引用次数: 0

Development of Vehicle-Mounted in-situ Soil Parameters Detector Based on NIR Diffuse Reflection 基于近红外漫反射的车载原位土壤参数探测器的研制

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2856-06

Peng Zhou, Minzan Li, Wei Yang, Ronghua Ji, Chao Meng

引用次数: 5

Maize Root Phenotypic Detection Based on Thermal Imaging and Root Gap Repair Algorithm 基于热成像和根间隙修复算法的玉米根系表型检测

IF 0.7 4区化学

光谱学与光谱分析 Pub Date : 2020-01-01 DOI: 10.3964/J.ISSN.1000-0593(2020)09-2845-06

Wei Lu, Zhao Han, X. Jian, Ji Zhou, Dong Jiang, Yanfeng Ding

{"title":"Maize Root Phenotypic Detection Based on Thermal Imaging and Root Gap Repair Algorithm","authors":"Wei Lu, Zhao Han, X. Jian, Ji Zhou, Dong Jiang, Yanfeng Ding","doi":"10.3964/J.ISSN.1000-0593(2020)09-2845-06","DOIUrl":"https://doi.org/10.3964/J.ISSN.1000-0593(2020)09-2845-06","url":null,"abstract":"Aiming at the problem of incomplete root image information because of blocking by the soil, the paper proposed a root phenotypic method by using thermal image combined with improved Criminisi algorithm for root image repair, and studied the relationship between the root phenotype and seed vigor. First, an annular double-layer quartz culture device adapted to maize root configuration was designed to push maize roots to grow along the inner 3d and 6d were planted in the annular culture device respectively. Base on the significant difference of heat capacity between soil and water, water was used to irrigate the seedings along their stems followed by short time hot air thermal excitation, and then infrared thermal images were captured based on the temperature difference between the soil and interstitial water flow around the roots. Secondly, the endpoints of the root thermal images after preprocessed were selected and matched for connecting using improved Criminisi algorithm to repair root image. Finally, different aged-day maize seeds were applied for seeding root phenotyping detection to verify the mentioned method which results shown that the proposed thermal infrared imaging method can help to enhance the root phenotypic image information which improve the precision of phenotypic parameters about 0.5-10% compared with color image. The was no significant difference of Root Total Length (RTL) and Root Total Number (RTN) after 1 d aging, but there were remarkable difference of RTL and RTN after 3 d and 6 d aging which decreased about 20-35% and 10-55% respectively. In general, the maize root phenotypic parameters such as RTN and RTL were significantly negative with the aging-day which can be used as important index parameters of seed vigor. Furthermore, RTN is more sensitive to impress a seed vigor. Root number of 1d/3d and 6d aging days increasing delayed about 1day and 2 day compared with 0 aging-day seeds respectively. The proposed root phenotypic detection method based on the thermal infrared imaging combined with improved Criminisi algorithm for root image repair can be used in root high throughput nondestructive detection which has a broad application prospect.","PeriodicalId":21846,"journal":{"name":"光谱学与光谱分析","volume":"34 1","pages":"2845"},"PeriodicalIF":0.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87108795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1