Mekkerdchoo, Orachorn

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Preferred name
Mekkerdchoo, Orachorn
Alternative Name
Mekkerdchoo, O.
Mekkerdchoo, Orachon
Main Affiliation
Email
orachorn.me@kmitl.ac.th

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    Item type:Publication,
    Tracing the evolution and economic potential of konjac glucomannan in Amorphophallus species (Araceae) using molecular phylogeny and RAPD markers
    (2016-10-27)
    Mekkerdchoo, Orachorn
    ;
    Borompichaichartkul, Chaleeda
    ;
    Perrigo, Allison L.
    ;
    Srzednicki, George
    ;
    Prakitchaiwattana, Cheunjit
    The genus Amorphophallus is an economically important taxon that is abundant in Old World tropical forests (Asia, Oceania and Africa). It includes many species that are used with increasing frequency as a source of food and pharmaceutical products worldwide. Amorphophallus konjac is an important economic crop and has been used widely in China and Japan for commercial konjac glucomannan (KGM) production. However, the species’ range does not extend to Thailand, where other closely related species may be more suitable for commercial KGM production. Present understanding of genetic relaionships among Thai Amorphophallus species is still limited, and the connection between evolutionary history and KGM content is unknown. Here, the genetic relationships among various accessions of Amorphophallus spp. collected in Thailand are investigated using the chloroplast trnL-trnF spacer, nuclear ribosomal internal transcribed spacer (ITS) region and the second intron of LEAFY (FLint2) together with genome-wide DNA variation analysis, Randomly Amplified Polymorphic DNA (RAPD) technique. RAPD primers are also developed to quickly and efficiently identify species producing high levels of KGM. This study finds that two monophyletic clades include high KGM content species. RAPD analyses indicate that primer AC-10 generates specific bands identifying species belonging only to the high and medium KGM content clades. These primers can be used as a screening tool for economical species, aiming at improving the industrial production of KGM in Thailand and the world.
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    Item type:Publication,
    A soft computing tool for species classification and prediction of glucomannan content in Amorphophallus genus
    (2017-12-01)
    Banerjee, Anupam
    ;
    Das, Priti
    ;
    Mekkerdchoo, Orachorn
    ;
    Borompichaichartkul, Chaleeda
    ;
    Basu, Subhadip
    The proposed work aims at designing a classification system for automatic identification of A. muelleri species, grown as a potential cash crop in many Asian countries, from the DNA fingerprints of Amorphophallus genus. Four sets of 48 DNA fingerprints belonging to 37 species of the Amorphophallus genus, developed with the help of four different primers are considered for the experiment, with an objective to identify only the fingerprints of the species of interest. A second experimental setup deals with the automatic classification of species containing high amounts of glucomannan from the same set of DNA fingerprints of the Amorphophallus genus. For each set of 48 DNA fingerprints generated with a specific primer, the DNA fingerprints are preprocessed to extract a 42 dimensional feature vector which is used to generate a k-Nearest Neighbor based classifier based on the Leave One Out Cross Validation protocol. Final classification based on outputs from individual classifiers constructed with respect to the four different primers is performed according to a n-star consensus strategy. The n-star consensus predicts species A. muelleri with cent per cent accuracy while it predicts species containing glucomannan with a more modest accuracy of 81.25%.