基于近红外高光谱成像技术鉴别杂交稻品系

种子的筛选和鉴别是农业育种过程中的关键环节。该文基于近红外高光谱成像技术(874~1 734 nm)结合化学计量学方法以及图像处理技术实现杂交稻种的品系鉴别及可视化预测。采集了3类不同品系共2 700粒杂交水稻的高光谱图像,用SPXY算法,按照2∶1的比例划分建模集和预测集。基于水稻样本的光谱特征,采用主成分分析(PCA)方法初步探究3类样本的可分性。采用连续投影算法(SPA),提取出7个特征波长:985.08、1 106、1 203.55、1 399.04、1 463.19、1 601.81、1 645.82 nm。基于特征波长和全波段光谱,建立了偏最小二乘判别分析(PLS-DA)和支持向量机(SVM)模型。试验结果表明,所建模型判别效果较好,识别正确率均达到了90%以上,其中,SVM模型的判别效果优于PLS-DA模型,基于全谱的判别分析模型结果优于基于特征波长的判别模型。结合SPA-SVM校正模型和图像处理技术,生成样本预测伪彩图,可以直观的鉴别不同品系的水稻种子。结果表明,近红外高光谱成像技术可以实现杂交稻的品系识别及可视化预测,为农业育种过程中种子的快速筛选及鉴定提供了新思路。     

便携式X射线荧光光谱仪实验室异位检测法的实用性研究

采用分步取样法验证便携式X射线荧光光谱仪的实验室异位检测法的实用性,以ICP-AES法为基准,对土壤重金属Cr、Cu、As、Pb的含量进行测定,试验中选用70%土壤样品建立一元线性校准模型,30%土壤样品进行校准模型的验证。结果表明,便携式X射线荧光光谱仪实验室异位检测法的检出限分别为Cr 17.7 mg/kg,Cu 10.4 mg/kg,As 5.4 mg/kg,Pb 6.2 mg/kg,均低于国家土壤环境质量一级标准。对国内外标准物质进行多次重复测定,RPD在–8.9%~7.9%,说明仪器在异位测定重金属含量时具有较好的精密度与准确度。分析PXRF法与传统方法测定建立的拟合方程,其决定系数分别为0.817 3、0.787 0、0.673 3和0.722 1,表明PXRF室内异位法可用于土壤重金属Cr、Cu、As、Pb的快速测定;二次采样建立的验证模型R2分别为0.912 4、0.897 9、0.772 3、0.872 9,逐渐靠近理想模型,充分验证PXRF异位法的实用性和校准曲线的准确性,可适用于农田土壤Cr、Cu、As、Pb的快速测定、污染筛查,为土壤重金属速效测定提供有力依据;但仪器在异位测定As元素时准确性降低,建议异位测定时需进行数据校准。     

高寒草甸植物正构烷烃特征分析

为研究高寒草甸植物正构烷烃分布特征,对采自黄河源区高寒草甸的58种植物进行了测定和分析。结果表明,单种植物中正构烷烃的碳数在C₈和C₄₀之间,含量分布范围为0.81~22.88 mg/kg,其中碳数为C₂₇、C₂₉、C₃₁、C₃₃正构烷烃的含量均较高;总正构烷烃(C_total)含量变化范围为35.00~78.64 mg/kg,长链正构烷烃(C_25-36)含量范围为16.11~58.68 mg/kg,条叶垂头菊中总正构烷烃和长链正构烷烃含量最小,而阿尔泰狗娃花含量最大。58种植物中含量最高的正构烷烃(C_max)分布特征为:C₁₉有1种,C₂₂有2种,C₂₇有2种,C₂₉有23种,C₃₁有27种,C₃₂有1种,C₃₃有2种。植物中正构烷烃总正构烷烃碳优势指数(CPI_total)范围为1.07~4.32,CPI_25-36范围为1.12~8.20,总的正构烷烃平均碳链长度(ACL_total)范围为23.52~27.22,ACL_27-33范围为28.03~31.07,蜡质指数(P_wax)变化范围为0.60~0.92。植物中长链正构烷烃丰富,奇数碳含量分布优势明显。     

MRI evaluation of local expansion in bread crumb during baking

The aim of this study was to undertake a dynamic and quantitative evaluation of the local evolution of porosity in a section of bread using magnetic resonance imaging (MRI). A prototype of an oven compatible with continuous MRI acquisition had been previously developed and installed in the probe of the imager. Oil microcapsules, which provide a very different MRI signal to that obtained from the dough, were also incorporated in the dough before proving, and their position in the bread was monitored throughout baking. Microcapsules delimited dough layers of which initial thickness ranged from 7 to 20 mm. Monitoring of the expansion of these layers is presented and discussed.Local expansion of the lower part of the bread predominated, contributing to 82% of the overall expansion at an oven air temperature of 130 °C. This was related to a slight escape of gas in this region, favored by one-dimensional heat transport. When the crust was formed early, as for an oven air temperature of 182 °C, local expansion did not cease with the crust setting and occurred to the detriment of the other regions, which were compressed.     

Reliability of InGaAs focal plane array imaging of wheat germination at early stages

To assist our Kansas breeding program, we have developed nondestructive methods to test new lines of wheat for resistance to premature germination. The high sensitivity of subsurface imaging, compared with visual detection, α-amylase determination, or viscosity testing, permits germination detection at early stages. This report is concerned with detection reliability via chemical imaging of intact wheat kernels at early stages of germination by using an InGaAs focal plane detector array in the 1100–1700 nm range. Ninety kernels from each of six different cultivars, including HRW and HWW wheat, were exposed to moist conditions for 6, 12, 24, 36, and 48 h. Images of each 90 kernel group were examined, and images of those kernels exposed to moisture for 36 h were compared with images of kernels treated for 3 h as a control. Images of each were classified as sprouted or unsprouted. Criteria for classification included images of log 1/R at select wavelengths or images of select factors resulting from principle component analysis (PCA) treatment of reflectance intensity data from each pixel. Sprouted kernels determined by PCA factors 1 and 4 from 90 kernels tested in a 36-h moisture exposure numbered 87, 85, 80, 74, 70, 48 for six cultivars tested. Cultivar KS-2174 was shown to be distinctly more resistant to germination than the other cultivars. When KS-2174 was compared with Betty wheat, for all exposure times, Betty had approximately 45% more germinated kernels.     

Direct non-thermal plasma treatment for the sanitation of fresh corn salad leaves: Evaluation of physical and physiological effects and antimicrobial efficacy

Current problems with outbreaks of serious infections caused by human pathogens on fresh-cut greens highlight the need for new, optimized postharvest sanitation treatments to effectively meet recent food safety standards. In contrast to various chemical treatments, non-thermal plasma (NTP) has a high potential as a gentle target sanitation technique. However, possible interactions between NTP and the physiology of treated fresh products have not been investigated in detail. Here, chlorophyll fluorescence image analysis (CFIA) was used to study the potential impacts of non-thermal plasma on the photosynthetic activity of highly perishable corn salad leaves as a model produce. For this purpose, an atmospheric pressure plasma jet, driven at radio frequency, and transforming argon with flow rates of 20 L min⁻¹ into non-thermal plasma at 10, 20, 30, and 40 W generator power was applied for various times to the surface of corn salad leaves. Thermographic measurements indicated maximum temperatures of 39.0 °C, 44.4 °C, 60.1 °C, and 66.0 °C, respectively, on treated leaf surfaces. CFIA revealed that treatment at moderate generator power of 20 W for up to 1 min was the maximum setting for quality retention. Furthermore, the microbial inactivation efficiency of the plasma jet system at these operating parameters was successfully tested on Escherichia coli bacteria, inoculated on corn salad surface at 10⁷ cfu cm⁻² and 10⁴ cfu cm⁻². At 20 W, bacteria with lower initial load could be inactivated by 3.6 (±0.6) log-cycles within 15 s of treatment duration; whereas at the higher initial load of 10⁷ cfu cm⁻², bacteria were reduced by 2.1 (±0.2) log-cycles after 30 s.     

Examination of the quality of spinach leaves using hyperspectral imaging

The present research is focused on the application of hyperspectral images for the supervision of quality deterioration in ready to use leafy spinach during storage (Spinacia oleracea). Two sets of samples of packed leafy spinach were considered: (a) a first set of samples was stored at 20 °C (E-20) in order to accelerate the degradation process, and these samples were measured the day of reception in the laboratory and after 2 days of storage; (b) a second set of samples was kept at 10 °C (E-10), and the measurements were taken throughout storage, beginning the day of reception and repeating the acquisition of Images 3, 6 and 9 days later. Twenty leaves per test were analyzed. Hyperspectral images were acquired with a push-broom CCD camera equipped with a spectrograph VNIR (400–1000 nm). Calibration set of spectra was extracted from E-20 samples, containing three classes of degradation: class A (optimal quality), class B and class C (maximum deterioration). Reference average spectra were defined for each class. Three models, computed on the calibration set, with a decreasing degree of complexity were compared, according to their ability for segregating leaves at different quality stages (fresh, with incipient and non-visible symptoms of degradation, and degraded): spectral angle mapper distance (SAM), partial least squares discriminant analysis models (PLS-DA), and a non linear index (Leafy Vegetable Evolution, LEVE) combining five wavelengths were included among the previously selected by CovSel procedure. In sets E-10 and E-20, artificial images of the membership degree according to the distance of each pixel to the reference classes, were computed assigning each pixel to the closest reference class. The three methods were able to show the degradation of the leaves with storage time.     

二维结合彩色多普勒超声对诊断乳腺肿块的价值

目的探讨二维及彩色多普勒超声(CDFI)对乳腺肿块鉴别诊断的价值。方法120例女性患者,术前应用二维超声观察乳腺肿块的大小、形态、位置、边界、包膜、内部回声;采用CDFI检测肿块周边及内部的血流形态、特点,并将彩色血流分为0~Ⅲ级。结果超声诊断乳腺肿块检出率为100%,良、恶性肿瘤超声诊断符合率分别为88.5%、85.7%。良性肿瘤多表现为边界光滑,侧缘回声减弱,CDFI血流分级以Ⅰ~Ⅱ级为主;恶性肿瘤多表现为形态不规则,边界不清,内部回声不均,CDFI血流分级以Ⅱ~Ⅲ级为主。恶性组的收缩期峰值流速(Vmax)、阻力指数(RI)、搏动指数(PI)分别为(28.2±7.3)cm/s、(0.78±0.09)、(1.8±0.3),良性组则分别为(13.5±6.7)cm/s、(0.63±0.07)、(1.2±0.2),差异均有统计学意义(P<0.01)。结论二维超声联合CDFI在乳腺良恶性肿瘤的鉴别诊断中有较高的应用价值。     

Examining brain oedema through brain electrical impedance topographic mapping

Change of Brain Electrical Impedance has great relations with brain oedema and brain block, a new method of Examining Brain Oedema through Brain Electrical Impedance Topographic Mapping(BEITM)is reviewed. Network topology structure that used in BEITM are also presented. According to topology, we discuss the drawing algorithm that based on triangle element. Some patients have been measured to make clinical data, according to this data Brain Electrical Impedance topographic come into being by computer at last, functional imaging has been implemented. Clinical case analysis compared with change state of an illness and repeatability of steady patient's data has proved the method is feasible.     

全方位高速瓜果图像采集系统的研究

快速可靠的图像采集系统是实现对瓜果进行准确分拣的基础。介绍了一种全方位高速瓜果图像采集系统。该系统实现了果实多个表面图像的同步采集，采用多线程程序结构提高图像采集速度，采用单场提取模式提高图像质量。利用开发的智能瓜果精选分级试验样机对图像采集系统的性能进行了试验，试验结果证明获得的图像质量和采集速度可以满足实时瓜果分级系统的需要。