The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Min Zhang - One of the best experts on this subject based on the ideXlab platform.
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detection of insect damaged vegetable Soybeans using hyperspectral transmittance image
Journal of Food Engineering, 2013Co-Authors: Min Huang, Min ZhangAbstract:Abstract Insects in vegetable soybean products pose potential hazard to consumers, thus making the food industry liable for economic losses. The objective of the current study is to develop a hyperspectral imaging technique for detecting insect-damaged vegetable Soybeans. Hyperspectral transmission images were acquired from normal and insect-damaged vegetable Soybeans over the spectral region between 400 nm and 1000 nm for 100 vegetable soybean pods (225 beans). Four statistical image features (minimum, maximum, mean, and standard deviation) were extracted from the images for classification and given as input to a discriminant classifier. The support vector data description (SVDD) classifier achieved 100% calibration accuracy. SVDD achieved 97.3% and 87.5% accuracies for normal and insect-damaged samples, respectively, with a 95.6% overall classification accuracy, for the investigated independent test samples. Therefore, the hyperspectral transmittance technique can discriminate insect-damaged vegetable Soybeans.
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Detection of insect-damaged vegetable Soybeans using hyperspectral transmittance image
Journal of Food Engineering, 2013Co-Authors: Min Huang, Xiangmei Wan, Min Zhang, Qibing ZhuAbstract:Insects in vegetable soybean products pose potential hazard to consumers, thus making the food industry liable for economic losses. The objective of the current study is to develop a hyperspectral imaging technique for detecting insect-damaged vegetable Soybeans. Hyperspectral transmission images were acquired from normal and insect-damaged vegetable Soybeans over the spectral region between 400 nm and 1000 nm for 100 vegetable soybean pods (225 beans). Four statistical image features (minimum, maximum, mean, and standard deviation) were extracted from the images for classification and given as input to a discriminant classifier. The support vector data description (SVDD) classifier achieved 100% calibration accuracy. SVDD achieved 97.3% and 87.5% accuracies for normal and insect-damaged samples, respectively, with a 95.6% overall classification accuracy, for the investigated independent test samples. Therefore, the hyperspectral transmittance technique can discriminate insect-damaged vegetable Soybeans. © 2012 Elsevier Ltd. All rights reserved.
Min Huang - One of the best experts on this subject based on the ideXlab platform.
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detection of insect damaged vegetable Soybeans using hyperspectral transmittance image
Journal of Food Engineering, 2013Co-Authors: Min Huang, Min ZhangAbstract:Abstract Insects in vegetable soybean products pose potential hazard to consumers, thus making the food industry liable for economic losses. The objective of the current study is to develop a hyperspectral imaging technique for detecting insect-damaged vegetable Soybeans. Hyperspectral transmission images were acquired from normal and insect-damaged vegetable Soybeans over the spectral region between 400 nm and 1000 nm for 100 vegetable soybean pods (225 beans). Four statistical image features (minimum, maximum, mean, and standard deviation) were extracted from the images for classification and given as input to a discriminant classifier. The support vector data description (SVDD) classifier achieved 100% calibration accuracy. SVDD achieved 97.3% and 87.5% accuracies for normal and insect-damaged samples, respectively, with a 95.6% overall classification accuracy, for the investigated independent test samples. Therefore, the hyperspectral transmittance technique can discriminate insect-damaged vegetable Soybeans.
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Detection of insect-damaged vegetable Soybeans using hyperspectral transmittance image
Journal of Food Engineering, 2013Co-Authors: Min Huang, Xiangmei Wan, Min Zhang, Qibing ZhuAbstract:Insects in vegetable soybean products pose potential hazard to consumers, thus making the food industry liable for economic losses. The objective of the current study is to develop a hyperspectral imaging technique for detecting insect-damaged vegetable Soybeans. Hyperspectral transmission images were acquired from normal and insect-damaged vegetable Soybeans over the spectral region between 400 nm and 1000 nm for 100 vegetable soybean pods (225 beans). Four statistical image features (minimum, maximum, mean, and standard deviation) were extracted from the images for classification and given as input to a discriminant classifier. The support vector data description (SVDD) classifier achieved 100% calibration accuracy. SVDD achieved 97.3% and 87.5% accuracies for normal and insect-damaged samples, respectively, with a 95.6% overall classification accuracy, for the investigated independent test samples. Therefore, the hyperspectral transmittance technique can discriminate insect-damaged vegetable Soybeans. © 2012 Elsevier Ltd. All rights reserved.
Qibing Zhu - One of the best experts on this subject based on the ideXlab platform.
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Detection of insect-damaged vegetable Soybeans using hyperspectral transmittance image
Journal of Food Engineering, 2013Co-Authors: Min Huang, Xiangmei Wan, Min Zhang, Qibing ZhuAbstract:Insects in vegetable soybean products pose potential hazard to consumers, thus making the food industry liable for economic losses. The objective of the current study is to develop a hyperspectral imaging technique for detecting insect-damaged vegetable Soybeans. Hyperspectral transmission images were acquired from normal and insect-damaged vegetable Soybeans over the spectral region between 400 nm and 1000 nm for 100 vegetable soybean pods (225 beans). Four statistical image features (minimum, maximum, mean, and standard deviation) were extracted from the images for classification and given as input to a discriminant classifier. The support vector data description (SVDD) classifier achieved 100% calibration accuracy. SVDD achieved 97.3% and 87.5% accuracies for normal and insect-damaged samples, respectively, with a 95.6% overall classification accuracy, for the investigated independent test samples. Therefore, the hyperspectral transmittance technique can discriminate insect-damaged vegetable Soybeans. © 2012 Elsevier Ltd. All rights reserved.
S Degrandis - One of the best experts on this subject based on the ideXlab platform.
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effects of processing on the content and composition of isoflavones during manufacturing of soy beverage and tofu
Process Biochemistry, 2002Co-Authors: Chungja C Jackson, J P Dini, Catherine Lavandier, H.p. Vasantha Rupasinghe, H Faulkner, Vaino Poysa, Drew Buzzell, S DegrandisAbstract:Isoflavones present in soybean (Glycine max) have been credited with performing several health-promoting functions, such as, prevention of cardiovascular diseases, cancers, and menopausal symptoms. In this study, the effect of the processing of soybean on the total content of isoflavones (including aglycones and glucosides) and the relative concentrations of 12 isoflavone compounds during the preparation of soy beverage and tofu were investigated. The mean recoveries of isoflavones in soy beverage and tofu in relation to their initial concentration in the raw Soybeans were 54 and 36%, respectively. The estimated percentage of total isoflavones lost in the water used to soak raw Soybeans, the okara (waste from heat-treated slurry), and whey were 4, 31, and 18%, respectively. The isoflavone profile of raw Soybeans was altered as a result of processing. During processing, the detectable levels of aglycones, glucosides, and acetyl glycoside groups increased, whilst the corresponding malonyl glucosides decreased. The loss of isoflavones through the by-products, such as, okara and whey, was considerable. Appropriate techniques should be developed to recover and utilize these functional constituents from soybean by-products. In addition, processing techniques have to be optimized, so that the final products contain the nutrient and nutraceutical content of the starting material as much as possible.
Stephen R. Padgette - One of the best experts on this subject based on the ideXlab platform.
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Compositional analysis of glyphosate-tolerant Soybeans treated with glyphosate
Journal of Agricultural and Food Chemistry, 1999Co-Authors: Nancy B. Taylor, Azizul Rahman Mohd Shariff, John Macdonald, Roy L. Fuchs, Stephen R. PadgetteAbstract:The compositional analyses and safety assessment of glyphosate-tolerant Soybeans (GTS) were previously described. These analyses were extensive and included addressing the potential effects on seed composition from the genetic modification. Detailed compositional analyses established that GTS, which had not been treated with glyphosate, were comparable to the parental soybean line and to other conventional Soybeans. In this study, two GTS lines, 40-3-2 and 61-67-1, were treated with commercial levels of glyphosate, the active ingredient in Roundup herbicide. The composition of the seed from Soybeans sprayed with glyphosate was compared to that of a nonsprayed parental control cultivar, A5403. The nutrients measured in the seed included protein, oil, ash, fiber, carbohydrates, and amino acids. The concentration of isoflavones (also referred to as phytoestrogens) was also measured as these compounds are derived from the same biochemical pathway that was engineered for glyphosate tolerance. The analytical results from these studies demonstrate that the GTS Soybeans treated with glyphosate were comparable to the parental soybean cultivar, A5403, and other conventional soybean varieties.
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the composition of glyphosate tolerant soybean seeds is equivalent to that of conventional Soybeans
Journal of Nutrition, 1996Co-Authors: Stephen R. Padgette, John Macdonald, Nancy Taylor, Debbie L Nida, Michele R Bailey, Larry R Holden, Roy L. FuchsAbstract:One important aspect of the safety assessment of genetically engineered crops destined for food and feed uses is the characterization of the consumed portion of the crop. One crop currently under development, glyphosate-tolerant Soybeans (GTS), was modified by the addition of a glyphosate-tolerance gene to a commercial soybean cultivar. The composition of seeds and selected processing fractions from two GTS lines, designated 40-3-2 and 61-67-1, was compared with that of the parental soybean cultivar, A5403. Nutrients measured in the soybean seeds included macronutrients by proximate analyses (protein, fat, fiber, ash, carbohydrates), amino acids and fatty acids. Antinutrients measured in either the seed or toasted meal were trypsin inhibitor, lectins, isoflavones, stachyose, raffinose and phytate. Proximate analyses were also performed on batches of defatted toasted meal, defatted nontoasted meal, protein isolate, and protein concentrate prepared from GTS and control soybean seeds. In addition, refined, bleached, deodorized oil was made, along with crude soybean lecithin, from GTS and control Soybeans. The analytical results demonstrated that the GTS lines are equivalent to the parental, conventional soybean cultivar.
