Effects of PEG priming and water uptake pattern of maize seeds based on low-field nuclear magnetic resonance

被引:0
|
作者
Zhang, Chunmei [1 ,2 ]
Meng, Jingwu [1 ]
Luo, Bin [1 ]
Kang, Kai [1 ]
Gu, Ying [1 ]
Sun, Qun [2 ]
Zhang, Han [1 ]
机构
[1] Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing,100097, China
[2] College of Agriculture, China Agricultural University, Beijing,100093, China
关键词
Polyethylene glycol (PEG) is one of the most commonly used seed initiators; in order to regulate the seed water uptake during seed priming. This study aims to investigate the effect of seed water uptake on the priming behavior under different PEG concentrations and priming times using low-field nuclear magnetic resonance (LF-NMR) technology. The aqueous phase state of maize seeds was dynamically monitored to be initiated by the different PEG concentrations. A prediction model of maize seed germination was constructed to clarify the relationship between seed water uptake and priming effect using machine learning. LF-NMR data was collected from the maize seeds at each node of priming time. A systematic analysis was carried out to determine the effects of PEG priming on seed germination and seedling growth. The optimal conditions of priming treatment were determined to evaluate the physical and chemical indicators; such as the vigor index of maize seeds. The pattern of water uptake was obtained in the maize seeds during priming. A regression model was also constructed to predict the priming effect of maize seeds. The main findings were summarized as follows: Firstly; there were some effects of PEG priming on the germination and seedling growth of maize seeds. Two-way ANOVA analysis showed that there were highly significant effects of PEG priming time and priming concentration on the germination indexes of maize seeds. Among them; the effect of priming time on the germination indexes of maize was much larger than that of priming concentration. With the increase of priming time (0-48 h); the viability of maize seeds showed a tendency to increase and then decrease; where the most suitable priming time was 16 h. Secondly; the water uptake of maize seed was elucidated during priming. The internal water of maize seeds was divided into two kinds of water components: bound water (0.1 ms 21 22 2 relaxation time. With the increase of priming time (0-48 h); the content of bound water increased and then gradually stabilized; while the content of free water continued to rise. The total water content increased and then gradually slowed down. The content of bound water had just entered the stagnation stage; while the increasing trend of A21 signal amplitude decreased basically without increase; indicating an appropriate indicator to judge the priming time of maize seeds. Finally; the medium Gaussian support vector machine (SVM) model and exponential gaussian process regression (GPR) model were constructed to assess the priming effect of maize seeds; respectively; according to the data before and after the screening of LF-NMR feature parameters. Among them; the exponential GPR model was achieved in the validation set R2 of 0.920 for maize seed germination after feature screening; which was better than 0.900 before that. The water absorption kinetics of the seed was elucidated to verify the priming efficacy. The experiment proved that the moisture variations during seed priming detected by LF-NMR can be expected for the rapid screening of the optimal priming conditions. The finding can also provide a new idea for the parameters setting and rapid evaluation during corn seed priming. © 2024 Chinese Society of Agricultural Engineering. All rights reserved;
D O I
10.11975/j.issn.1002-6819.202405167
中图分类号
学科分类号
摘要
引用
收藏
页码:292 / 299
相关论文
共 50 条
  • [1] LOW-FIELD NUCLEAR MAGNETIC RESONANCE SPECTROMETER
    MITCHELL, RW
    EISNER, M
    REVIEW OF SCIENTIFIC INSTRUMENTS, 1957, 28 (08): : 624 - 628
  • [2] Static weak magnetic field measurements based on low-field nuclear magnetic resonance
    Wang, Xiaofei
    Zhu, Maohua
    Xiao, Kangda
    Guo, Jun
    Wang, Li
    JOURNAL OF MAGNETIC RESONANCE, 2019, 307
  • [3] Low-field nuclear magnetic resonance for the in vivo study of water content in trees
    Yoder, Jacob
    Malone, Michael W.
    Espy, Michelle A.
    Sevanto, Sanna
    REVIEW OF SCIENTIFIC INSTRUMENTS, 2014, 85 (09):
  • [4] Progress in miniaturization and low-field nuclear magnetic resonance
    Anders, Jens
    Dreyer, Frederik
    Krueger, Daniel
    Schwartz, Ilai
    Plenio, Martin B.
    Jelezko, Fedor
    JOURNAL OF MAGNETIC RESONANCE, 2021, 322
  • [5] Study of the method of water-injected meat identifying based on low-field nuclear magnetic resonance
    Xu, Jianmei
    Lin, Qing
    Yang, Fang
    Zheng, Zheng
    Ai, Zhujun
    2017 3RD INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION (ESMA2017), VOLS 1-4, 2018, 108
  • [6] Characterization of water state and distribution in fibre materials by low-field nuclear magnetic resonance
    Ji, Peng
    Jin, Jin
    Chen, Xianglin
    Wang, Chaosheng
    Wang, Huaping
    RSC ADVANCES, 2016, 6 (14) : 11492 - 11500
  • [7] 1D magnetic resonance imaging and low-field nuclear magnetic resonance relaxometry of water-based silica nanofluids
    Gholinezhad, Sajjad
    Kantzas, Apostolos
    Bryant, Steven L.
    COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS, 2022, 640
  • [8] Low-field nuclear magnetic resonance for petroleum distillate characterization
    Barbosa, Lucio L.
    Kock, Flavio V. C.
    Almeida, Vinicius M. D. L.
    Menezes, Sonia M. C.
    Castro, Eustaquio V. R.
    FUEL PROCESSING TECHNOLOGY, 2015, 138 : 202 - 209
  • [9] On the feasibility of neurocurrent imaging by low-field nuclear magnetic resonance
    Burghoff, Martin
    Albrecht, Hans-Helge
    Hartwig, Stefan
    Hilschenz, Ingo
    Koerber, Rainer
    Hoefner, Nora
    Scheer, Hans-Juergen
    Voigt, Jens
    Trahms, Lutz
    Curio, Gabriel
    APPLIED PHYSICS LETTERS, 2010, 96 (23)
  • [10] Distribution Characteristics and Backflow Flow Pattern of a Slickwater Fracturing Fluid in Shale Based on Low-Field Nuclear Magnetic Resonance
    Liu, Jiawei
    Zhang, Jian
    Yang, Yue
    Liu, Dongchen
    Jiang, Rui
    Huang, Shan
    Sun, Yongpeng
    Dai, Caili
    Energy and Fuels, 2024, 38 (03): : 2001 - 2009