The presence of pesticide residues in pears is a serious health concern. This study presents the results from a 2-year investigation （2013-2014） that used gas chromatography, GS/MS and UPLC/MS-MS to measure the leve...The presence of pesticide residues in pears is a serious health concern. This study presents the results from a 2-year investigation （2013-2014） that used gas chromatography, GS/MS and UPLC/MS-MS to measure the levels of 104 pesti- cides in 310 pear samples. In 93.2% of the samples, 43 pesticides were detected, of which the maximum residue levels （MRLs） were exceeded in 2.6% of the samples. Multiple residues （two to eight compounds） were present in 69.7% of the samples; one sample contained nine pesticides and one sample contained 10. Only 6.8% of the samples did not contain residues. To assess the health risks, the pesticide residue data have been combined with daily pear consumption data for children and adult populations. A deterministic model was used to assess the chronic and acute exposures based on the Joint Meeting on Pesticide Residues （JMPR） method. A potential acute risk was demonstrated for children in the case of bifenthrin, which was found to be present at 105.36% of the acute reference dose （ARfD） value. The long- term exposure of the Chinese consumer to pesticide residues through the consumption of raw pears was far below the acceptable daily intake （ADI） criterion. Additionally, the matrix ranking scheme was used to classify risk subgroups of pesticides and pear samples. In general, 95.5% of samples were deemed to be safe and nine pesticides were classified as being of a relatively high risk. The findings indicated that the occurrence of pesticide residues in pears should not be considered a serious public health problem. Nevertheless, a more detailed study is required for vulnerable consumer groups, especially children. Continuous monitoring of pesticides in pears and tighter regulation of pesticide residue standards are recommended.展开更多
For a texture image, by recognizining the class of every pixel of the image, it can be partitioned into disjoint regions of uniform texture. This paper proposed a texture image classification algorithm based on Gabor ...For a texture image, by recognizining the class of every pixel of the image, it can be partitioned into disjoint regions of uniform texture. This paper proposed a texture image classification algorithm based on Gabor wavelet. In this algorithm, characteristic of every image is obtained through every pixel and its neighborhood of this image. And this algorithm can achieve the information transform between different sizes of neighborhood.Experiments on standard Brodatz texture image dataset show that our proposed algorithm can achieve good classification rates.展开更多
基金financially supported by the National Program for Quality and Safety Risk Assessment of Agricultural Products of China (GJFP2014002, GJFP2015002)the Core Research Budget of the Non-Profit Governmental Research Institution of China (0032014013)
文摘The presence of pesticide residues in pears is a serious health concern. This study presents the results from a 2-year investigation （2013-2014） that used gas chromatography, GS/MS and UPLC/MS-MS to measure the levels of 104 pesti- cides in 310 pear samples. In 93.2% of the samples, 43 pesticides were detected, of which the maximum residue levels （MRLs） were exceeded in 2.6% of the samples. Multiple residues （two to eight compounds） were present in 69.7% of the samples; one sample contained nine pesticides and one sample contained 10. Only 6.8% of the samples did not contain residues. To assess the health risks, the pesticide residue data have been combined with daily pear consumption data for children and adult populations. A deterministic model was used to assess the chronic and acute exposures based on the Joint Meeting on Pesticide Residues （JMPR） method. A potential acute risk was demonstrated for children in the case of bifenthrin, which was found to be present at 105.36% of the acute reference dose （ARfD） value. The long- term exposure of the Chinese consumer to pesticide residues through the consumption of raw pears was far below the acceptable daily intake （ADI） criterion. Additionally, the matrix ranking scheme was used to classify risk subgroups of pesticides and pear samples. In general, 95.5% of samples were deemed to be safe and nine pesticides were classified as being of a relatively high risk. The findings indicated that the occurrence of pesticide residues in pears should not be considered a serious public health problem. Nevertheless, a more detailed study is required for vulnerable consumer groups, especially children. Continuous monitoring of pesticides in pears and tighter regulation of pesticide residue standards are recommended.
基金Foundation item： Supported by the National Natural Science Foundation of China（61071189） Supported by the Key Project of Science and Technology of the Education Department of Henan Province（14A120009） Supported by the Program Young Scholar of the Peoples Republic of Henan Province China（2013GGJS-027）
文摘For a texture image, by recognizining the class of every pixel of the image, it can be partitioned into disjoint regions of uniform texture. This paper proposed a texture image classification algorithm based on Gabor wavelet. In this algorithm, characteristic of every image is obtained through every pixel and its neighborhood of this image. And this algorithm can achieve the information transform between different sizes of neighborhood.Experiments on standard Brodatz texture image dataset show that our proposed algorithm can achieve good classification rates.
