基于喷雾干燥覆盆子粉末颜色的人工神经网络载体识别

K. Przybył, J. Wawrzyniak, K. Samborska, Ł. Gierz, K. Koszela, M. Szychta
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引用次数: 1

摘要

果汁,蔬菜和果汁是产品,为我们的身体提供了许多有价值的营养成分,并在预防许多疾病方面发挥了重要作用。树莓是生物活性化合物的宝贵来源。作为保存食品的一部分,其主要目的是延长仅在季节获得的产品的稳定性,研究人员利用了喷雾干燥技术。在本研究的研究部分,以除湿喷雾干燥过程中获得的覆盆子粉的形式制备研究样品。为此,建立了一种神经网络模型,支持基于颜色的检测粉末样品质量评价。所设计的神经网络达到了0.924的分类准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of artificial neural networks in recognizing carrier based on the color of raspberry powders obtained in the spray-drying process
Fruit juices and vegetable and fruit juices are the products, which provide our bodies with a lot of valuable and nutritional ingredients and play a major role in prevention of numerous illnesses. Raspberries are the valuable source of bioactive compounds. As part of preserving food, whose main aim is to extend stability of products obtained only in season, the researchers took advantage of spray drying technique. In the research part of the study, research samples were prepared in the form of raspberry powders obtained from the process of dehumidified spray drying. Because of the research, a neural model was made, which supported the evaluation of the quality of detecting powder samples based on their color. The devised neural network reached classification accuracy at 0.924.
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