Citrus canker detection using hyperspectral reflectance imaging and PCA-based image classification method

Citrus canker is one of the most devastating diseases that threaten marketability of citrus crops. Technologies that can efficiently identify citrus canker would assure fruit quality and safety and enhance the competitiveness and profitability of the citrus industry. This research was aimed to investigate the potential of using hyperspectral imaging technique for detecting canker lesions on citrus fruit. A portable hyperspectral imaging system consisting of an automatic sample handling unit, a light source, and a hyperspectral imaging unit was developed for citrus canker detection. The imaging system was used to acquire reflectance images from citrus samples in the wavelength range between 400 and 900 nm. Ruby Red grapefruits with normal and various diseased skin conditions including canker, copper burn, greasy spot, wind scar, cake melanose, and specular melanose were tested. Hyperspectral reflectance images were analyzed using principal component analysis (PCA) to compress the 3-D hyperspectral image data and extract useful image features that could be used to discriminate cankerous samples from normal and other diseased samples. Image processing and classification algorithms were developed based upon the transformed images of PCA. The overall accuracy for canker detection was 92.7%. Four optimal wavelengths (553, 677, 718, and 858 nm) were identified in visible and short-wavelength near-infrared region that could be adopted by a future multispectral imaging solution for detecting citrus canker on a sorting machine. This research demonstrated that hyperspectral imaging technique could be used for discriminating citrus canker from other confounding diseases.     

A strategy for molecular species detection in meat and meat products by PCR-RFLP and DNA sequencing using mitochondrial and chromosomal genetic sequences

Molecular species detection in food has become common in the last 10 years. The methods are sensitive enough to detect small, but relevant, amounts of one species in composed food. We have developed a strategy for detecting different animal species in food by molecular means. This strategy uses a combination of published PCR systems and new developed PCR primer systems for the detection of porcine, bovine, ovine, avian, cervine and equine DNA by PCR followed by restriction analysis (PCR-RFLP). In some cases, analysis is completed by DNA sequencing. The species detection system includes an amplification control and so is in accordance with the relevant food standards.     

Fabric defect detection using Gabor filters and defect classification based on LBP and Tamura method

This paper aims at investigating methods for solving the problem of automated fabric defect detection and classification, which are more essential and important in assuring the fabric quality. The work focuses on two aspects: fabric defect detection and classification. In the experiment, first, the detection texture features for texture defect are extracted using Gabor filters. The method would automatically segment defects from the regular texture. Second, texture features for classification use local binary patterns and Tamura method. Fabric samples are used in evaluation and the experimental results obtained further confirm the designed algorithm achieved a high detection success rate.     

大豆多肽发酵液中多肽测定方法的研究

研究了利用“纸层析-分光光度法”对大豆多肽发酵液中多肽的测定,确定了测定条件。实验表明,该方法对测定多肽的含量具有较高的准确度和精密度。与高效液相色谱法相比其测定结果基本一致,并且该法操作方便、易于掌握,适合于在发酵法大豆多肽生产中应用。     

A medium for the detection of yeasts using a conductimetric method

A new medium is described for the detection of yeasts using a Malthus microbial growth analyser which measures conductivity. This medium is superior to previous media devised for use in the Malthus, and allows the detection of a wide range of yeasts including those important in food spoilage. The new medium was inferior to existing media used to detect yeasts in the Bactometer 32 instrument which measures impedance.     

A new rapid technique for detection of microorganisms using bioluminescence and fluorescence microscope method

The MicroStar-RMDS-SPS (RMDS; R apid M icrobe D etection S ystem) enables detection and determination of the number of microorganisms trapped on a membrane filter based on the ATP-bioluminescence method. However, this system could not provide information about the identity of contaminating species based on the measurement results. Therefore, we developed a new technique for observing microcolonies of contaminants using a fluorescence microscope (Micro Scanner). The coordinates in the image data of the RMDS were converted to the coordinates of the sample stage of the microscope, and a microcolony could be easily observed. A single yeast cell and a microcolony consisting of 20-30 lactic acid bacterial cells could be observed on a membrane filter after measurement using the RMDS.     

肽类藻毒素液质联用检测研究进展

介绍了微囊藻毒素(MCs)和结球藻毒素(NOD)的结构与毒性.相比于其他方法,在检测肽类藻毒素的应用上,液质联用法(LC-MS)具有操作简单,检测限低,可有效分析组分结构等优点.对检测过程中提取、纯化、分离和检测等重要步骤的适合条件和方法特点以及质谱检测方法前景进行了评述.     

A method for broad spectrum classification of sunscreens

A method is described and evaluated for classifying sunscreen products into different broad spectrum categories. The method is based on spectrophotometric analysis of products applied to a suitable substrate and obviates the need for human or animal studies utilizing clinical endpoints which may be of dubious value in relation to protection from sun exposure. The absorbance spectrum obtained by spectrophotometric assay is reduced to a single index by determining that wavelength λ_c where the area under the spectrum from 290 nm (the approximate lower wavelength limit of terrestrial sunlight) to λ_c is 90% of the integral of the absorbance spectrum from 290 to 400 nm. A five-point scale is used to classify products as follows:

The method makes no underlying assumptions about the form of action spectra for either acute or chronic photobiological damage. However, acknowledgement is made of the fact that the efficiency of ultraviolet radiation to induce a given photobiological endpoint tends to decrease with increasing wavelength by adopting wavelength intervals for classifying the Broad Spectrum Rating which increase in an approximately logarithmic manner.     

A preprocessing method for inferring genetic interaction from gene expression data using Boolean algorithm

Unknown genetic regulation mechanisms are expected to be discovered by information technology using large amount of biological data especially for gene expression data. In this study, we propose a novel inferring method for genetic interactions that combines our original preprocessing method and the Boolean algorithm. First, the performance of our method was evaluated using artificial data. The results showed that our method was able to infer genetic interactions with high specificity (specificity=0.629). Then, using our method, the genetic interaction was inferred from the experimental time course data collected using microarray on 69 genes of cell cycle for Saccharomyces cerevisiae. Our method estimated about 80% of all genetic interactions in Kyoto Encyclopedia Genes and Genomes (KEGG) for these genes. Furthermore, our method was able to infer several other genetic interactions that are not included in KEGG but whose existence is supported by other biological reports.     

Controlling inbreeding and maximizing genetic gain using semi-definite programming with pedigree-based and genomic relationships

Because of the relatively high levels of genetic relationships among potential bull sires and bull dams, innovative selection tools should consider both genetic gain and genetic relationships in a long-term perspective. Optimum genetic contribution theory using official estimated breeding values for a moderately heritable trait (production index, Index-PROD), and a lowly heritable functional trait (index for somatic cell score, Index-SCS) was applied to find optimal allocations of bull dams and bull sires. In contrast to previous practical applications using optimizations based on Lagrange multipliers, we focused on semi-definite programming (SDP). The SDP methodology was combined with either pedigree (a_ij) or genomic relationships (f_ij) among selection candidates. Selection candidates were 484 genotyped bulls, and 499 preselected genotyped bull dams completing a central test on station. In different scenarios separately for PROD and SCS, constraints on the average pedigree relationships among future progeny were varied from a_ij = 0.08 to a_ij = 0.20 in increments of 0.01. Corresponding constraints for single nucleotide polymorphism-based kinship coefficients were derived from regression analysis. Applying the coefficient of 0.52 with an intercept of 0.14 estimated for the regression pedigree relationship on genomic relationship, the corresponding range to alter genomic relationships varied from f_ij = 0.18 to f_ij = 0.24. Despite differences for some bulls in genomic and pedigree relationships, the same trends were observed for constraints on pedigree and corresponding genomic relationships regarding results in genetic gain and achieved coefficients of relationships. Generally, allowing higher values for relationships resulted in an increase of genetic gain for Index-PROD and Index-SCS and in a reduction in the number of selected sires. Interestingly, more sires were selected for all scenarios when restricting genomic relationships compared with restricting pedigree relationships. For example, at constraint of f_ij = 0.185 and selection on Index-PROD, the number of selected sires was 35. In contrast, only 21 sires were selected at the comparable constraint on additive genetic relationship of a_ij = 0.09. A further reduction in relationships is possible when using SDP output (i.e., suggested genetic contributions of selected parents) and applying a simulated annealing algorithm to define specific mating plans. However, the advantage of this strategy is limited to a short-term perspective and probably not successful in the period of genomic selection allowing a substantial reduction of generation intervals.     

基于改进CNN的草莓成熟度分类方法

目的:提高草莓分类准确率。方法:通过混合池化方法对CNN进行改进,提出基于改进CNN的草莓分类方法。通过最大池化和平均池化技术组合,得到混合池化方法;通过混合池化方法对CNN进行改进,提高CNN模型的泛化能力;进行图像数据采集、图像预处理和提取图像特征;并利用灵敏度、特异度、精确度、召回率和F₁分数对训练好的草莓分类方法进行分类效果评估。结果:试验方法对16像素×16像素图像中草莓分类的灵敏度、特异度、精确度、召回率和F₁分数分别达到0.993,0.993,0.994,0.992,0.991;与其他5种分类方法相比,试验方法对草莓分类的灵敏度、特异度、精确度、召回率和F₁分数分别平均提高了3.44%,3.96%,4.26%,3.92%,4.08%。结论:该方法可实现不同成熟度草莓的准确分类。     

纸病图像检测与分割的二阶段方法

提出了纸张表面纸病检测与分割的二阶段新方法.通过对纸张微观结构中纤维分布的分析,由统计学分析原理建立了纸病图像的二阈值分割法,利用质量控制图结合具体纸样进行了纸病特征的提取,利用数学形态学操作对二值图像进行了滤波和分割检测.结果表明:二阶段分割阈值检测方法对纸病图像的分析十分简单、有效.     

A simple HPLC-UVD method for detection of etofenprox in green tea using sample hydration

Residue levels were estimated using HPLC-UV detection. Samples were hydrated and extracted using acetonitrile. Analytical linearity in the range of 0.02 to 2.0 mg/kg was excellent with a determination coefficient (R ²) of 1.0. Recovery at levels of 0.2 and 1.0 mg/kg ranged from 89.9 to 94.6% with a relative standard deviation <5%. Sufficient sensitivity was achieved. The limits of detection and quantification were 0.006 and 0.02 mg/kg, respectively. The method was successfully applied to analysis of field samples. This method was effective and can be used for routine analysis of etofenprox in tea samples at low concentrations.     

A histochemical method using a substrate of beta-glucuronidase for detection of genetically modified papaya

A histochemical assay for detecting genetically modified (GM) papaya (derived from Line 55-1) is described. GM papaya, currently undergoing a safety assessment in Japan, was developed using a construct that included a beta-glucuronidase (GUS) reporter gene linked to a virus coat protein (CP) gene. Histochemical assay was used to visualize the blue GUS reaction product from transgenic seed embryos. Twelve embryos per fruit were extracted from the papaya seeds using a surgical knife. The embryos were incubated with the substrate 5-bromo-4-chloro-3-indolyl-beta-D-glucuronide (X-Gluc) in a 96-well microtiter plate for 10-15 hours at 37 degrees C. Seventy-five percent of GM papaya embryos should turn blue theoretically. The histochemical assay results were completely consistent with those from a qualitative polymerase chain reaction (PCR) method developed by this laboratory. Furthermore, the method was validated in a five-laboratory study. The method for detection of GM papaya is rapid and simple, and does not require use of specialized equipment.     

用演化方法反演抛物型方程系数的数值算法

给出了一种利用演化计算方法求解抛物型方程中的一次项参数反问题的方法．该方法把参数识别问题转化为泛函的优化问题,用演化算法求解,用演化计算（Genetic Algorithms）演化待求参数的最优估计值,并将该方法运用于一类方程反问题的数值模拟中．数值结果显示数值解与理论解吻合很好．     

阻抗生物传感器连续叠加法检测毒死蜱研究

目的 研究微电极阻抗生物传感器快速检测农药以及回归模型建立。方法 用蛋白A修饰叉指微电极, 把5个不同浓度的毒死蜱样品依次滴加到已经制备好的阻抗生物传感器上进行检测, 分析6个特定频率下毒死蜱浓度与阻抗信号的相关性。结果 在10 Hz频率下, 毒死蜱浓度在0.01 μg/mL~100 μg/mL范围内, 建立的回归模型方程为: Y=136.4Ln(X)+2075, 相关系数R2为0.961。结论 该方法具有操作简单、检测速度快等优点, 可以适用于其他生物传感器研究。     

A new selection index percent emphasis method using subindex weights and genetic evaluation accuracy

The current international standard methodology to quantify trait percent emphasis in selection indexes is based on a simple multiplication of the relative contribution of each trait's economic value (converted to absolute value) and its genetic standard deviation. This method does not reflect the actual selection emphasis applied when the index is used in practice. The economic value does not reflect selection effort when traits differ considerably in their accuracy of evaluation, and no account is taken for either favorable or antagonistic correlations among traits. A new emphasis method adjusted by both accuracy and genetic correlation is proposed. Genetically highly correlated traits are grouped into subindexes by applying a hierarchical clustering method to the genetic correlation matrix. Then each trait's subindex emphasis is calculated within its subindex group, with a weighting included for trait accuracy. Finally, each subindex emphasis is converted to a full index emphasis according to the conventional relative emphasis of its corresponding subgroup. The method can also be applied to sets of breeding values and their economic weights. When applied to a New Zealand sheep breeding selection index where trait genetic correlations are distinct across subindex groups, the new method shrank the emphasis on low-heritability traits, including survival, from 51% to 19%; and expanded that on growth traits from 30% to 49%, better reflecting the selection pressure applied in reality. When genetic correlations across traits were similar, clustering became difficult. Accounting for accuracy affected traits' within-subindex group rankings, whereas the clustering to account for correlations affected all traits within a subgroup equally. Accounting for differences in trait accuracy when describing percent emphasis within selection indexes gives a more practical indication of the likely outcome of selecting on the index. Accounting for correlations among traits when defining percent emphasis made a significant difference only in a subset of case study examples.     

A method for the determination of fungicide residues in citrus and other fruit using HPLC and selective detection

A HPLC-method is described for the determination of diphenyl, o-phenylphenol, thiabendazole, diphenylamine, and ethoxiquin in different fruits (detection limits: 0.1 mg/kg). The compounds are extracted with dichloromethane, and after concentration and filtration steps the determination is carried out by HPLC with selective detection. Chromatographic separation of fungicides is achieved by use of a RP-18 column with a methanolic formic acid buffer as eluent. The working parameters of three different HPLC-detectors (UV-, fluorimetric-, and electrochemical detector) are optimized, and it is shown that residues of the fungicides in plant materials can be determinated at least by two detectors without interferences.