The Experts below are selected from a list of 9315 Experts worldwide ranked by ideXlab platform
Nobuyuki Hayashi - One of the best experts on this subject based on the ideXlab platform.
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Development of Expressed Sequence Tag (EST)-based Cleaved Amplified Polymorphic Sequence (CAPS) markers of tea plant and their application to Cultivar Identification.
Journal of Agricultural and Food Chemistry, 2011Co-Authors: Tomomi Ujihara, Fumiya Taniguchi, Junichi Tanaka, Nobuyuki HayashiAbstract:To develop cleaved amplified polymorphic sequence (CAPS) markers for Cultivar Identification of the tea leaf, 5 primer pairs designed on the basis of genes that encode proteins related to nitrogen assimilation and 26 primer pairs based on expressed sequence tag (EST) sequences of the root of tea plant were screened. From combinations of primer pair and restriction enzyme that showed polymorphism among tea plants, 16 markers were selected and applied to DNA fingerprinting of Japanese tea Cultivars. Sixty-three Cultivars, except for a bud sport (Kiraka) and its original Cultivar (Yabukita) and a pair that was the progeny of the same crossing parent (Harumoegi and Sakimidori), were distinguished from one another. By combining the 16 markers with previously developed CAPS markers and observing the physical appearance, 67 Cultivars were distinguishable. The Cultivars involve approximately 95% of total tea cultivating area in Japan; therefore, about 95% of tea leaves produced in Japan can be authenticated by labeling their Cultivars.
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Cultivar Identification and Analysis of the Blended Ratio of Green Tea Production on the Market Using DNA Markers
Food Science and Technology Research, 2005Co-Authors: Tomomi Ujihara, Nobuyuki Hayashi, Satoru Matsumoto, Katsunori KohataAbstract:Japanese green teas are produced by blending different materials and there are cases of discrepancy between the contents and the label of the product. Therefore, a technique for identifying tea Cultivars among product contents is strongly required. A simple CTAB (Cetyl trimethyl ammonium bromide) extraction method with a short time pre-incubation yielded DNA is suitable for Cultivar Identification by CAPS (cleaved amplified polymorphic sequence) analysis. The extracted DNA was analyzed with seven CAPS markers to identify Cultivars.
Yanjun Zhu - One of the best experts on this subject based on the ideXlab platform.
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toward good practices for fine grained maize Cultivar Identification with filter specific convolutional activations
IEEE Transactions on Automation Science and Engineering, 2018Co-Authors: Zhiguo Cao, Yang Xiao, Zhiwen Fang, Yanjun ZhuAbstract:Crop Cultivar Identification is an important aspect in agricultural systems. Traditional solutions involve excessive human interventions, which is labor-intensive and time-consuming. In addition, Cultivar Identification is a typical task of fine-grained visual categorization (FGVC). Compared with other common topics in FGVC, studies of this problem are somewhat lagging and limited. In this paper, targeting four Chinese maize Cultivars of Jundan No.20 , Wuyue No.3 , Nongda No.108 , and Zhengdan No.958 , we first consider the problem of identifying the maize Cultivar based on its tassel characteristics by computer vision. In particular, a novel fine-grained maize Cultivar Identification data set termed HUST-FG-MCI that contains 5000 images is first constructed. To better capture the textual differences in a weakly supervised manner, we proposed an effective deep convolutional neural network and Fisher vector (FV)-based feature encoding mechanism. The mechanism tends to highlight subtle object patterns via filter-specific convolutional representations and thus provides strong discrimination for Cultivar Identification. Experimental results demonstrate that our method outperforms other state-of-the-art approaches. We show also that FV encoding can weaken the linear dependency between convolutional activations, redundant filters exist in the convolutional layer, and high accuracy can be maintained with relatively low-dimensional convolutional features and one or two Gaussian components in FV. Note to Practitioners —In-field Cultivar Identification remains an open question for industrial applications in agriculture. This paper describes a practical computer vision system to explore the feasibility for automatic maize Cultivar Identification. Our system shows potentials to be applied in an embedded system as long as convolutional models could be compressed to address storage issues. Aside from using the fixed image acquisition device mentioned in this paper, another promising way is to integrate our system into an unmanned aircraft to achieve flexible field-based observations.
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ICIP - Fine-grained maize Cultivar Identification using filter-specific convolutional activations
2016 IEEE International Conference on Image Processing (ICIP), 2016Co-Authors: Zhiguo Cao, Yang Xiao, Zhiwen Fang, Yanjun ZhuAbstract:Cultivar Identification is an important aspect in agriculture and also a typical task of fine-grained visual categorization (FGVC). In comparison with other common topics in FGVC, studies on this problem are somewhat lagged and limited. In this paper, targeting four Chinese maize Cultivars of Jundan No.20, Wuyue No.3, Nongda No.108, and Zhengdan No.958, we first consider the problem of identifying the maize Cultivar based on its tassel characteristics. Technically, an effective convolutional neural network (CNN) based feature encoding pipeline that allows integration of deep CNN based column feature extraction, filter-specific Fisher vector (FV) encoding and mutual information (MI) based filter selection is proposed to better address this problem. In particular, a novel fine-grained maize Cultivar Identification dataset termed MCI-4000 that contains 4000 images is first constructed by our team. Experimental results demonstrate that our method outperforms other stat-of-the-art approaches by at least 5% in accuracy. We also show that, there exists redundant filters in the last convolutional layer, and high accuracy can be achieved with only relatively low-dimensional column features and a small number of Gaussian components in FV.
Ahmed Rebai - One of the best experts on this subject based on the ideXlab platform.
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OGDD (Olive Genetic Diversity Database): A microsatellite markers' genotypes database of worldwide olive trees for Cultivar Identification and virgin olive oil traceability
Database, 2016Co-Authors: Rayda Ben Ayed, Riadh Ben Marzoug, Karim Ennouri, Hanen Ben Hassen, Ahmed RebaiAbstract:Olive (Olea europaea), whose importance is mainly due to nutritional and health features, is one of the most economically significant oil-producing trees in the Mediterranean region. Unfortunately, the increasing market demand towards virgin olive oil could often result in its adulteration with less expensive oils, which is a serious problem for the public and quality control evaluators of virgin olive oil. Therefore, to avoid frauds, olive Cultivar Identification and virgin olive oil authentication have become a major issue for the producers and consumers of quality control in the olive chain. Presently, genetic traceability using SSR is the cost effective and powerful marker technique that can be employed to resolve such problems. However, to identify an unknown monovarietal virgin olive oil Cultivar, a reference system has become necessary. Thus, an Olive Genetic Diversity Database (OGDD) (http://www.bioinfo-cbs.org/ogdd/) is presented in this work. It is a genetic, morphologic and chemical database of worldwide olive tree and oil having a double function. In fact, besides being a reference system generated for the Identification of unkown olive or virgin olive oil Cultivars based on their microsatellite allele size(s), it provides users additional morphological and chemical information for each identified Cultivar. Currently, OGDD is designed to enable users to easily retrieve and visualize biologically important information (SSR markers, and olive tree and oil characteristics of about 200 Cultivars worldwide) using a set of efficient query interfaces and analysis tools. It can be accessed through a web service from any modern programming language using a simple hypertext transfer protocol call. The web site is implemented in java, JavaScript, PHP, HTML and Apache with all major browsers supported.Database URL: http://www.bioinfo-cbs.org/ogdd/.
Jinggui Fang - One of the best experts on this subject based on the ideXlab platform.
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Identification of apple Cultivars on the basis of simple sequence repeat markers.
Genetics and molecular research : GMR, 2014Co-Authors: G.s. Liu, Jinggui Fang, Y.g. Zhang, Ran Tao, H.y. DaiAbstract:DNA markers are useful tools that play an important role in plant Cultivar Identification. They are usually based on polymerase chain reaction (PCR) and include simple sequence repeats (SSRs), inter-simple sequence repeats, and random amplified polymorphic DNA. However, DNA markers were not used effectively in the complete Identification of plant Cultivars because of the lack of known DNA fingerprints. Recently, a novel approach called the Cultivar Identification diagram (CID) strategy was developed to facilitate the use of DNA markers for separate plant individuals. The CID was designed whereby a polymorphic maker was generated from each PCR that directly allowed for Cultivar sample separation at each step. Therefore, it could be used to identify Cultivars and varieties easily with fewer primers. In this study, 60 apple Cultivars, including a few main Cultivars in fields and varieties from descendants (Fuji x Telamon) were examined. Of the 20 pairs of SSR primers screened, 8 pairs gave reproducible, polymorphic DNA amplification patterns. The banding patterns obtained from these 8 primers were used to construct a CID map. Each Cultivar or variety in this study was distinguished from the others completely, indicating that this method can be used for efficient Cultivar Identification. The result contributed to studies on germplasm resources and the seedling industry in fruit trees.
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An Efficient Identification of 68 Apple Cultivars Using a Cultivar Identification Diagram (CID) Strategy and RAPD Markers
Korean Journal of Horticultural Science and Technology, 2012Co-Authors: Wenyan Wang, Kun Wang, Fengzhi Liu, Jinggui FangAbstract:The study aimed to establish an efficient tool for Cultivar Identification and characterization being the first steps of apple introduction and improvement program. We utilized a method to efficiently record DNA molecular fingerprints of plant individuals genotyped by RAPD, which could be used as efficient reference information for quick plant Identification. Ten of sixty 11-mer primers were screened to identify the 68 apple genotypes which could be distinguished by a combination of several primers. All Cultivars were easily identified by the corresponding primers marked on the Cultivar Identification diagram (CID). The results indicated that the CID strategy developed and employed in the apple Cultivar Identification could be vital in the utilization of DNA marker in other plants as well as the development of the apple industry.
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Identification of selected apricot Cultivars using RAPD and EST-SSR markers
Caryologia, 2012Co-Authors: Lingfei Shangguan, Yujuan Wang, Changnian Song, Yu-zhu Wang, Jinggui FangAbstract:Random amplified polymorphic DNA (RAPD) and expressed sequence tags–simple sequence repeats (EST-SSR) are useful for Cultivar Identification. In this study, we applied a new approach using RAPD fingerprints to distinguish 34 apricot Cultivars based on the optimization of RAPD by choosing 11-nucleotide (nt) primers and strict screening PCR annealing temperature. We further compared the discriminating ability of EST-SSR markers using the same number of primer pairs. The results showed that this new approach can clearly utilize and record the fingerprints generated from various RAPD primers during Cultivar Identification, and a Cultivar Identification diagram (CID) could be constructed. The CID approach can be used for efficient Identification of apricot Cultivars, providing information to separate groups of Cultivars. The reliability and efficiency of this method was checked and verified. Five RAPD primers clearly distinguished 34 apricot Cultivars, but five EST-SSR primer pairs could only identify 14 culti...
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A novel strategy for Identification of 47 pomegranate (Punica granatum) Cultivars using RAPD markers.
Genetics and molecular research : GMR, 2012Co-Authors: Y.p. Zhang, H.h. Tan, S.y. Cao, X.c. Wang, Guowu Yang, Jinggui FangAbstract:DNA marker can be used for precise plant Cultivar Identification. However, DNA markers have often not been used effectively for the Identification of plant Cultivars due to a lack of an effective analysis strategy. We used a novel strategy for effective Identification of plant individuals based on a new way of recording DNA fingerprints of the genotyped plants; a Cultivar Identification diagram can be manually generated and used as key reference information for quick Identification of plant and/or seed samples. Forty-seven pomegranate varieties popularly cultivated in various provinces of China were subjected to RAPD marker analysis. Using the Cultivar Identification diagram strategy, they were clearly separated by the fingerprints of 11 RAPD primers. The utility and accuracy of the Cultivar Identification diagram analysis results were confirmed by the Identification of three randomly chosen groups of Cultivars among the 47 varieties.
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Plant Variety and Cultivar Identification: Advances and Prospects
Critical reviews in biotechnology, 2012Co-Authors: Nicholas Kibet Korir, Jian Han, Lingfei Shangguan, Chen Wang, Emrul Kayesh, Yanyi Zhang, Jinggui FangAbstract:Plant variety and Cultivar Identification is one of the most important aspects in agricultural systems. The large number of varieties or landraces among crop plants has made it difficult to identify and characterize varieties solely on the basis of morphological characters because they are non stable and originate due to environmental and climatic conditions, and therefore phenotypic plasticity is an outcome of adaptation. To mitigate this, scientists have developed and employed molecular markers, statistical tests and software to identify and characterize the required plant Cultivars or varieties for cultivation, breeding programs as well as for Cultivar-right-protection. The establishment of genome and transcriptome sequencing projects for many crops has led to generation of a huge wealth of sequence information that could find much use in Identification of plants and their varieties. We review the current status of plant variety and Cultivar Identification, where an attempt has been made to describe th...
Sumiko Nakamura - One of the best experts on this subject based on the ideXlab platform.
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Cultivar Identification of Korean rice based on DNA markers for blast resistance.
Bioscience biotechnology and biochemistry, 2008Co-Authors: Masahiro Kishine, Sumiko Nakamura, Ushio Matsukura, Ken'ichi OhtsuboAbstract:Cultivar Identification of seven Korean domestic rice using DNA markers related to blast resistance was conducted. By PCR analyses using six markers, which we developed in a previous study, and one newly-developed marker for pib, it became possible to differentiate the seven Cultivars from each other. This result should contribute not only to Cultivar Identification but also, to molecular breeding of blast resistance for Korean rice.
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Cultivar Identification of rice oryza sativa l by polymerase chain reaction method and its application to processed rice products
Journal of Agricultural and Food Chemistry, 2007Co-Authors: Ken'ichi Ohtsubo, Sumiko NakamuraAbstract:As the Cultivars of rice markedly affect eating quality, processing suitability, and price, Identification or differentiation of rice Cultivar is very important. We developed suitable 14 STS (sequence-tagged site) primers for PCR (polymerase chain reaction), and it became possible to differentiate 60 Japanese dominant rice Cultivars from each other using template DNA extracted and purified from rice grains. A multiplex primer set was shown to be useful to effectively differentiate rice Cultivars produced in various countries by PCR. A novel multiplex primer set for PCR has been developed to differentiate KoshihikariBL, which is closely related with the premium Cultivar, Koshihikari, in Japan. The application of the Cultivar Identification method by PCR method to commercially processed rice products was investigated. We developed an enzyme treatment method, in which the gelatinized starch is decomposed by the heat-stable α-amylase at 80 °C, followed by the hydrolysis of proteins by proteinase K with sodium...