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    "title": "DEVELOPMENT OF A MACHINE AND DETECTION OF GLYCOALKALOIDS IN POTATO USING IMAGE PROCESSING TECHNIQUE",
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            "value": "Glycoalkaloids are secondary natural poisonous metabolites produced by plants of the Solanaceae family. Glycoalkaloids from solanaceous plants vary depending on species. The two major glycoalkaloids found in potatoes are Solanine and chaconine. The average potato contains 0.075 mg of solanine and chaconine. The doses of 200–400 mg for adult humans and 20–40 mg for children can cause toxic symptoms to human health. Commercial potatoes have GA content of less than 0.2 mg. This research aimed at determining the total glycoalkaloid content present in potatoes using image processing technique. It is one of the non-destructive method and images can be stored and retrieved easily. Potatoes were collected from local markets in Coimbatore. The major components used in this machine are Raspberry Pi, web camera, Lcd module, memory card. The Raspberry pi is powered up with 5V power supply through USB cable. The Button interfaced with raspberry pi is triggered to capture the image from camera to classify the level of glycoalkaloids and display the result in LCD module. Through this glycoalkaloid detector the amount of glycoalkaloid present in the potatoes can be determined by both milligram and percentage values. It is a cost-effective method and ensures food safety. Published by: Longman Publishers www.jst.org.in P age 315 | 7 www.jst.org.in DOI: https://doi.org/10.46243/jst.2022.v7.i02.pp315-321",
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                "unstructured": "K Przybyl, A Ryniecki, G Niedbala, W Mueller, P Boniecki,,M Zarborowicz, K Koszela, S kujawa, RJ Kozlowski “ Software supporting definition and extraction of the quality parameters of potatoes by using image analysis” Eighth international conference on digital image processing ( ICDIP 2016) 10033,100332L, 2016"
            },
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                "key": "ref2",
                "doi": "10.17221/427/2017-cjfs",
                "unstructured": "Krzysztof Pyrybyl, Piotr Bonieeki, Krzysztof Koszela, Lukasz Gierz, Mateusz Lukomski “ Computer vision and artificial neural network techniques for classification of damage in potato during storage process” Czech Journal of food science 37(2),135-140, 2019. 13.Machado, Rita MD, Maria Cecília F. Toledo, and Lucila C. Garcia. \"Effect of light and temperature on the formation of glycoalkaloids in potato tubers.\" Food Control 18, no. 5 (2019): 503-508"
            },
            {
                "key": "ref3",
                "doi": "10.1007/s00231-019-02771-2",
                "unstructured": "P Singh, P Talukdar “Determination of shrinkage characteristics of cylindrical potato during convective drying using novel image processing technique” Heat and mass transfer 56(4),1223-1235,2020"
            },
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                "key": "ref4",
                "doi": "10.5958/0976-4615.2021.00005.3",
                "unstructured": "Reinis zarins, Zanda karuma “Glycoakaloids in potatoes” Department of food technology, Lativa University of agriculture 2017. 23.Sanjeev, Kumar, Narendra Kumar Gupta, Rajendra Kumar Isaac, and Suneeta Paswan. A review on potato disease detection using image processing.\" Progressive Agriculture 21, no. 1 (2021): 23-30. 24.Siddique, Md Abu Bakar, and Nigel Brunton. \"Food Glycoalkaloids: distribution, structure, cytotoxicity, extraction, and biological activity.\" Alkaloids-their importance in nature and human life (2019): 13-5"
            },
            {
                "key": "ref5",
                "doi": "10.1007/s42853-020-00069-4",
                "unstructured": "Young-Joo Lee, Beom-Soo Shin “Development of potato yeild monitoring system using machine vision” Journal of Biosystems Engineering 45 (4), 282-290, 2020. 30.Wan, Libin, Haidong Gao, Huoliang Gao, Rui Du, Fayun Wang, Yong Wang, and Mantang Chen \"Selective extraction and determination of steroidal glycoalkaloids in potato tissues by electromembrane extraction combined with LC-MS/MS.\" Food Chemistry 367 (2021): 130724"
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