吴婷婷,ARMSTRONG P R,张海辉,杨玲,高维瑞.全包围光源结构的单粒小麦蛋白质含量检测装置研究[J].农业机械学报,2018,49(10):363-369.
WU Tingting,ARMSTRONG P R,ZHANG Haihui,YANG Ling,GAO Weirui.Investigation on Individual Wheat Kernel Quality Prediction Device with Stereoscopic Light Source[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(10):363-369.
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全包围光源结构的单粒小麦蛋白质含量检测装置研究   [下载全文]
Investigation on Individual Wheat Kernel Quality Prediction Device with Stereoscopic Light Source   [Download Pdf][in English]
投稿时间:2018-06-05  
DOI:10.6041/j.issn.1000-1298.2018.10.041
中文关键词:  小麦籽粒  品质检测  全包围光源  光谱分析
基金项目:陕西省科技重点研发计划项目(2018GY-051)
作者单位
吴婷婷 西北农林科技大学 
ARMSTRONG P R 美国农业部农业研究局 
张海辉 西北农林科技大学 
杨玲 西北农林科技大学 
高维瑞 西北农林科技大学 
中文摘要:针对单粒小麦蛋白质含量等内部表型的实时检测需求,设计了基于近红外漫反射光谱的无损定量检测装置,阐述了光源结构设计、硬件系统设计和软件系统构建。选用近红外LED微型灯珠,以6行8列形式均匀分布于圆柱形铝合金灯筒壁上,形成向心全包围的物理结构,LED灯珠引脚通过16根导电铜柱并联连接,灯筒上顶部设有红外对射传感器,当检测到谷物经由灯筒内的玻璃滑道时,光谱仪通过一分二型光纤分别从灯筒上顶部和下底部收集漫反射光谱,基于C++语言的上位机软件将其转换为吸光度,再根据嵌入模型进行实时预测。获取了300粒单粒小麦900~1700nm范围的全包围漫反射光谱,进行归一化处理后,分别建立了基于全光谱(FS)和连续投影算法(SPA)提取特征波长的单粒蛋白质含量预测模型。试验结果表明,两个模型校正集的R2分别为0.9604和0.8446,验证集R2分别为0.8016和0.819;从实用性和预测效果出发,选择基于SPA特征波长的蛋白质模型作为嵌入式预测模型;分别验证了该装置的波长重复性、吸光度重复性和预测重复性,结果表明,本装置可以用于单粒谷物内部表型的实时、无损、定量检测。
WU Tingting  ARMSTRONG P R  ZHANG Haihui  YANG Ling  GAO Weirui
Northwest A&F University,USDA-ARS,Northwest A&F University,Northwest A&F University and Northwest A&F University
Key Words:wheat seed  quality detection  stereoscopic light source  spectral analysis
Abstract:For the real-time compositional endophenotype detection of individual wheat kernel, a quantitative and non-destructive device based on near infrared diffuse reflectance was designed and developed. The hardware consisted of a novel stereoscopic light source unit, spectrum acquisition unit and control unit, also the corresponding detection software were presented. NIR miniature LED lamps were placed in six rows multiple eight columns along an aluminum cylindrical tube to provide a constant centripetal light and the 48 lamps were connected in parallel by 16 copper conductor to inform a physically stereoscopic light structure. A pair of infrared radiation sensor was adopted on the top of the cylindrical tube to trigger the NIR spectrometer for spectra collection as a seed fell through the borosilicate glass tubing inside the light source. The spectrometer of Ocean Optics was connected to a PC with its standard interface and pin definitions, which was used to collect spectrum from the top and bottom of the light source in real-time through a bifurcate structure fiber. All the soft functions were designed in C++ language of Visual Studio platform. The real time diffuse reflectance spectrum of each seed was transferred to absorbance via PC and predicted its real protein content according to a model embedded in the program. In order to set up a reliable prediction model, totally 300 individual wheat samples were collected to acquire absorbance spectra in the range of 900~1700nm, and pretreated with standard normal variate correction (SNV) algorithm. Two calibration models were established based on full spectra (FS) and feature wavelengths optimized by successive projections algorithm (SPA) respectively. Data showed that the calibration model based on SPA had a relatively lower determination coefficient (R2) of 0.8446 in contrast to the R2 value of 0.9604 based on FS, but the validation model based on SPA had relatively equal prediction accuracy with the model based on FS. For the nine feature wavelengths selected by SPA eliminated the collinearity relationship in spectral data but preserved characteristic of protein on spectrum band with a concise model equation, it was chosen as a superior model and developed in software to predict individual seed protein content online. To verify system design and performance, a series of experiment was conducted for wavelength repeatability, absorbance repeatability and protein predictive repeatability. The results indicated that the compositional detection device based on stereoscopic light source was able to realize fast, nondestructive and real-time detection of protein content for individual seed, also had certain applications potential on other compositional endophenotype detection for wheat and other crop seeds.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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