机器学习在花果茶生产加工中的应用进展

Application progress of machine learning in the production and processing of flower and fruit tea

中文关键词:  花果茶  智能化  机器学习  花果茶加工

英文关键词:flower and fruit tea  intelligence  machine learning  flower and fruit tea processing

中文摘要:

      花果茶因其独特的口味和丰富的营养成分成为备受欢迎的新型饮品。然而, 在花果茶生产加工过程中, 仍存在原料溯源和品质控制方面的不足、质量安全控制标准化水平较低及加工工艺智能化不足等问题。传统分析手段对于花果茶有关数据的非线性信息挖掘和原料、成品传统分级方法的效率也较低。目前, 我国的花果茶产业正处于由传统加工向智能化转型的重要阶段, 机器学习在其中发挥着不可替代的重要作用。机器学习算法因其自主进行特征学习、强大的非线性拟合能力、端到端建模以及快速的特点, 成为花果茶加工中研究应用的热点。本文综述了机器学习算法在花果茶原料验收、原料加工、质量分级等方面的应用, 总结了机器学习算法在花果茶生产加工不同环节中的侧重点、优缺点和未来发展方向, 为花果茶加工的智能化发展提供了参考。

英文摘要:

      Flower and fruit tea has become a popular new beverage due to its unique flavor and rich nutritional content. However, in the production and processing of flower and fruit tea, there are issues such as insufficient traceability and quality control for raw materials, low standardization of quality and safety control, and inadequate intelligent processing technology. Traditional analytical methods also have low efficiency in nonlinear information mining related to flower and fruit tea data and traditional grading methods for raw materials and finished products. Currently, China’s flower and fruit tea industry is in an important stage of transformation from traditional processing to intelligent processing, in which machine learning plays an irreplaceable role. Due to its ability to autonomously learn features, strong nonlinear fitting capability, end-to-end modeling, and fast computation, machine learning algorithms have become a research hotspot in flower and fruit tea processing. This article reviewed the applications of machine learning algorithms in flower and fruit tea raw material inspection, raw material processing, and quality grading, summarizes the focus, advantages, and limitations of machine learning algorithms in different stages of flower and fruit tea production and processing, so as to provide a reference for the intelligent development of flower and fruit tea processing.