|
|
|
|
|
|
Feasibility Study of Dividing Maize Heterotic Group Based on Near Infrared Spectroscopy |
JIA Shi-qiang1, LI Hao-chuan2, AN Dong1,3*, LIU Zong-hua2* |
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. College of Agronomy, Henan Agricultural University, Collaborative Innovation Center of Henan Grain Crops, National Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450002, China
3. Key Laboratory of Agricultural Information Acquisition Technology (Beijing), Ministry of Agriculture, Beijing 100083, China |
|
|
Abstract Accurate division of heterotic group in maize can provide effective information on germplasm improvement, heterosis mode construction, and development of new varieties. The main methods used at present to divide maize heterotic group are pedigree, combining ability test, isozyme markers, and molecular markers. These methods are inferior because of their high cost and operational complexity. Some of them even have to destroy the seeds. This study explored novel method feasibility of near infrared (NIR) spectroscopy in quick nondestructive heterotic grouping of maize. The near infrared diffuse reflection spectra of maize seeds were collected and preprocessed using smoothing, first derivative, and vector normalization. The features of these spectra were extracted through principal component analysis (PCA). Twelve Chinese maize inbred line samples were selected, including six leading inbred lines (Part A) and six excellent self-selection lines (Part B). Part A was divided into three groups with NIR spectroscopy, namely, A1 (Zheng58) and A2 (Ye478), A3 (Chang7-2) and A4 (Huangzaosi), and A5 (Mo17) and A6 (SiF1). This division was in accordance with pedigree analysis. Part B was also divided into three groups by NIR spectroscopy: B1 and B2, B3 and B4, as well as B5 and B6. This division conforms to clustering analysis based on SSR molecular marker. These processes confirm that NIR spectroscopy is a convenient, highly efficient, and feasible heterotic grouping method of maize.
|
Received: 2015-09-08
Accepted: 2016-02-05
|
|
Corresponding Authors:
AN Dong, LIU Zong-hua
E-mail: andong@cau.edu.cn; zhliu100@163.com
|
|
[1] Yao W H, Tan J, Chen H M. Journal of Maize Sciences, 2006, 14: 30.
[2] şuteu D, Bǎcilǎ I, Haş V. PLoS ONE, 2013, 8(12): e85501.
[3] Romay M C, Millard M J, Glaubitz J C. Genome Biology, 2013, 14(6): R55.
[4] Swarts K, Li H H, Navarro J A R. The Plant Genome, 2014, 7(3): 1.
[5] Pojic M M, Mastilovic J S. Food and Bioprocess Technology, 2012, 6(2): 330.
[6] Munck L, MФlle B, Jacobsen S. Journal of Cereal Science, 2004, 40: 213.
[7] Jones R W, Reinot T, Frei U K. Applied spectroscopy, 2013, 66: 447.
[8] Jia S Q, An D, Liu Z. Journal of Cereal Science, 2015, 63: 21.
[9] Saleh B. Journal of Plant Biology Research, 2012, 1: 1.
[10] Osorno J M, Carena M J. Maydica, 2008, 53: 131.
[11] Wang F G, Tian H L, Zhao J R. Maydica, 2011, 56(1): 1693.
[12] Lima D C, Santos A M P, Araujo R G O. Microchemical Journal, 2010, 95: 222.
[13] Wang R, Yu Y, Zhao J. Theoretical and Applied Genetics, 2008, 117(7): 1141.
[14] Yang X, Yan J, Shah T. Theoretical and Applied Genetics, 2010, 121(3): 417.
[15] Teng W T, Cao J S, Chen Y H. Scientia Agricultura Sinica, 2004, 37(12): 1804. |
[1] |
WANG Wen-xiu, PENG Yan-kun*, FANG Xiao-qian, BU Xiao-pu. Characteristic Variables Optimization for TVB-N in Pork Based on Two-Dimensional Correlation Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2094-2100. |
[2] |
LE Ba Tuan1, 3, XIAO Dong1*, MAO Ya-chun2, SONG Liang2, HE Da-kuo1, LIU Shan-jun2. Coal Classification Based on Visible, Near-Infrared Spectroscopy and CNN-ELM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2107-2112. |
[3] |
CHEN Sheng, ZHANG Xun, XU Feng*. Study on Cell Wall Deconstruction of Pinus Massoniana during Dilute Acid Pretreatment with Confocal Raman Microscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2136-2142. |
[4] |
YANG Ke-ming, ZHANG Wei, WANG Xiao-feng, SUN Tong-tong, CHENG Long. Differentiation and Level Monitoring of Corn Leaf Stressed by Cu and Pb Derived from Spatial Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2200-2208. |
[5] |
LIU Jin, LUAN Xiao-li*, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2274-2278. |
[6] |
YU Hui-ling1, MEN Hong-sheng2, LIANG Hao2, ZHANG Yi-zhuo2*. Near Infrared Spectroscopy Identification Method of Wood Surface Defects Based on SA-PBT-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1724-1728. |
[7] |
XU Wei-jie1, WU Zhong-chen1, 2*, ZHU Xiang-ping2, ZHANG Jiang1, LING Zong-cheng1, NI Yu-heng1, GUO Kai-chen1. Classification and Discrimination of Martian-Related Minerals Using Spectral Fusion Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1926-1932. |
[8] |
LI Ying1, LI Yao-xiang1*, LI Wen-bin2, JIANG Li-chun3. Model Optimization of Wood Property and Quality Tracing Based on Wavelet Transform and NIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1384-1392. |
[9] |
DU Jian1, 2, HU Bing-liang1*, LIU Yong-zheng1, WEI Cui-yu1, ZHANG Geng1, TANG Xing-jia1. Study on Quality Identification of Macadamia nut Based on Convolutional Neural Networks and Spectral Features[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1514-1519. |
[10] |
HAN Guang, LIU Rong*, XU Ke-xin. Extraction of Effective Signal in Non-Invasive Blood Glucose Sensing with Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1599-1604. |
[11] |
WANG Li-shuang, ZHANG Wen-bo*, TONG Li. Studies on Dimensional Stability of Wood under Different Moisture Conditions by Near Infrared Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1066-1069. |
[12] |
HUANG Hua1, WU Xi-yu2, ZHU Shi-ping1*. Feature Wavelength Selection and Efficiency Analysis for Paddy Moisture Content Prediction by Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1070-1075. |
[13] |
LI Hao-guang1,2, YU Yun-hua1,2, PANG Yan1, SHEN Xue-feng1,2. Study of Maize Haploid Identification Based on Oil Content Detection with Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1089-1094. |
[14] |
PENG Cheng1, FENG Xu-ping2*, HE Yong2, ZHANG Chu2, ZHAO Yi-ying2, XU Jun-feng1. Discrimination of Transgenic Maize Containing the Cry1Ab/Cry2Aj and G10evo Genes Using Near Infrared Spectroscopy (NIR)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1095-1100. |
[15] |
XIA Ji-an1, YANG Yu-wang1*, CAO Hong-xin2, HAN Chen1, GE Dao-kuo2, ZHANG Wen-yu2. Classification of Broad Bean Pest of Visible-Near Infrared Spectroscopy Based on Cloud Computing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 756-760. |
|
|
|
|