基于THz时域反射成像技术的玉米种子淀粉分布可视化研究

doi:10.3964/j.issn.1000-0593(2023)09-2722-07

摘要
参考文献
相关文章 (15)

全文: PDF (14734 KB)
输出: BibTeX | EndNote (RIS)

摘要：为无损探究种子成分分布与种子活力变化的内在关系，以玉米种子主要成分淀粉为研究对象，将太赫兹时域反射成像技术与移动窗口相关系数法相结合，无损可视化构建不同活力程度的玉米种子淀粉空间分布图。以郑单958玉米品种为例，实验通过人工老化方式(40 ℃，100%RH)制备老化0、18、36、54、72 h的种子样本，采用Terapluse 4000太赫兹时域光谱仪及反射成像附件扫描获取不同老化程度的样本和纯玉米淀粉样品的太赫兹光谱图像。以16.35 cm^-1下THz图像为基准，采用阈值分割法精确提取种子胚乳、种胚区域，通过对比不同组织区域内THz平均吸光度可得胚乳和种胚光谱明显差异，且胚乳和淀粉纯物质在51.96 cm^-1附近存在明显的共同吸收峰。应用移动窗口相关系数法(窗口宽度为20，移动步长为10)，逐像素点计算种子太赫兹时域光谱与纯玉米淀粉光谱的-相关系数，并根据相关系数值以及坐标信息绘制伪彩色热力图，可视化构建玉米种子淀粉分布图。实验统计5个老化阶段、6个谱区窗口的淀粉分布图中相关系数>0.8的像素点占比可得：在29.83～67.36 cm^-1区间内，种子胚乳和种子区域内的淀粉含量在种子活力下降过程中呈现总体下降趋势，即种子淀粉含量与活力呈现正相关关系。实验结果表明：太赫兹时域光谱反射成像技术结合移动窗口相关系数伪彩色成像分析方法可以初步实现种子活力变化过程中玉米种子淀粉空间分布特性的无损探测，该技术可为深入研究种子化学成分与其自身活力之间的制约关系，无损解析种子生命活动与自身生理生态规律变化提供崭新的视角和方法。

关键词：玉米种子；太赫兹时域光谱反射成像；相关系数成像法；移动窗口；淀粉

Abstract：To identify the intrinsic relationship between the distribution of seed composition and the change in seed vigour using a nondestructive testing method, this study chooses starch, a major component of corn seeds, as the research object. Combining the terahertz (THz) time-domain spectral reflection imaging technology with moving-window correlation coefficient imaging, a visualised map showing the spatial distribution of starch in corn seeds with different vigour degrees is constructed. Using the Zhengdan 958 corn variety as an example, a test is conducted to apply an artificial ageing method to prepare samples aged 0, 18, 36, 54 and 72 h. Then, the THz spectrometer is used to scan the reflection imaging attachments to obtain THz images of the samples. The THz image at 16.35 cm^-1 was used as a benchmark, and the endosperm and seed embryo regions of the seeds were accurately extracted using the threshold segmentation method. By comparing the average absorbance of THz in different tissue regions, it can be obtained that the endosperm and seed embryo spectra differ significantly, and there is an obvious common absorption peak near 51.96 cm^-1 for endosperm and starch pure substances. The moving window correlation coefficient method (window width 20, moving step 10) was applied to calculate the correlation coefficient between the terahertz time-domain spectrum of the seeds and the pure maize starch spectrum on a pixel-by-pixel basis and to construct a pseudo-colour heat map based on the correlation coefficient values and the coordinate information to visualise the maize seed starch distribution. Statistics on the percentage of pixel points with a correlation coefficient of >0.8 in the starch distribution map and covering five ageing stages and six spectral region windows lead to the conclusion that within the range of 29.83～67.36 cm^-1 of the starch in the endosperm area of the seed exhibits an overall downward trend in vigour decline, presenting a positive correlation with vigour. Test results show that the THz time-domain spectral imaging technology can preliminarily realise the nondestructive detection of the spatial distribution characteristics of starch in corn seeds as seed vigour changes when it is used with the moving-window correlation coefficient pseudo-colour imaging analysis method. This technique provides a new perspective and method for studying the relationship between the chemical composition of seeds and their vitality and for non-destructively analysing changes in the vital activity of seeds and their own physiological and ecological patterns.

Key words：Corn seeds; Terahertz time-domain spectral reflection imaging; Correlation coefficient imaging method; Moving window; Starch

收稿日期: 2022-05-27 修订日期: 2022-10-23

中图分类号:

O433.4

基金资助: 国家自然科学基金项目(61807001)资助

通讯作者: 吴静珠 E-mail: pubwu@163.com

作者简介: 李阳，1996年生，北京工商大学食品安全大数据技术北京市重点实验室硕士研究生 e-mail: liyang9218@163.com

引用本文:

李阳，李晓琪，杨佳滢，孙丽娟，陈媛媛，余乐，吴静珠. 基于THz时域反射成像技术的玉米种子淀粉分布可视化研究[J]. 光谱学与光谱分析, 2023, 43(09): 2722-2728.
LI Yang, LI Xiao-qi, YANG Jia-ying, SUN Li-juan, CHEN Yuan-yuan, YU Le, WU Jing-zhu. Visualisation of Starch Distribution in Corn Seeds Based on Terahertz Time-Domain Spectral Reflection Imaging Technology. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2722-2728.

链接本文:

https://www.gpxygpfx.com/CN/10.3964/j.issn.1000-0593(2023)09-2722-07 或 https://www.gpxygpfx.com/CN/Y2023/V43/I09/2722

[1] GUO Ai-liang, ZHOU Xiang-han, YAO Ya-ya, et al(郭爱良, 周湘寒, 姚亚亚, 等). Journal of The Chinese Cereals and Oils Association(中国粮油学报), 2022，(37)：5.
[2] WANG Xin-yu(王欣宇). Modern Animal Husbandry Science & Technology(现代畜牧科技), 2018, 40(4): 37.
[3] ZHAO Yan-hao, ZHANG Qian-xia, XIE Wei(赵燕昊, 张倩霞, 谢炜). Modern Agricultural Science and Technology(现代农业科技), 2019，(15): 1.
[4] LI Wen-bin, YU Xiu-qi, LIU Chun-yu, et al(李文彬, 于秀琪, 刘春宇, 等. ). Journal of Agricultural Catastrophology (农业灾害研究), 2021, 11(6): 3.
[5] Moreira J, Cardoso R R, Braga R A. Optics & Lasers in Engineering, 2014, 61: 8.
[6] Peiponen K E, Zeitler J A, Kuwata-Gonokami M. Terahertz Spectroscopy and Imaging. Berlin Heidelberg: Springer, 2012.
[7] LI Bin, LONG Yuan, LIU Huan, et al(李斌, 龙园, 刘欢, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2018, 34(2): 1.
[8] XIE Li-juan, XU Wen-dao, YING Yi-bin, et al(谢丽娟, 徐文道, 应义斌, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2013, 44(7): 246.
[9] Ge H, Jiang Y, Lian F, et al. Sensors, 2015, 15(6): 12560.
[10] Xu W, Xie L, Ye Z, et al. Scientific Reports, 2015, 5: 11115.
[11] Wei L, Liu C, Hu X, et al. Food Chemistry, 2016, 210: 415.
[12] Liu J, Li Z, Hu F，et al. Optical and Quantum Electronics, 2015, 47(2): 313.
[13] BU Zheng-yan, LI Zhen-feng, SONG Fei-hu, et al(步正延, 李臻峰, 宋飞虎, 等). Acta Agriculturae Zhejiangensis(浙江农业学报), 2018, 30(8): 1420.
[14] Nakajima S, Shiraga K, Suzuki T, et al. Food Chemistry, 2019, 294: 203.
[15] XU Hong-mei, WEN Jiang, ZHONG Wen-jie, et al(徐红梅, 文江, 钟文杰, 等). Journal of Jiangsu University (Natural Science Edition)[江苏大学学报(自然科学版)], 2017, 38(3): 295.
[16] ZHANG Ming-dan, WANG Min, CHEN Guang-xuan, et al(张明丹, 王敏, 陈光选, 等). Modern Food Science and Technology(现代食品科技), 2021, 37(2): 129.