机器学习在食品贮藏品质预测中的应用

Application of Machine Learning on Food Storage Quality Prediction

食品贮藏和流通过程中会出现不同程度的品质劣变现象。随着人们对食品品质和安全重视程度的不断提高,开展食品贮运过程中的品质预测研究,对食品品质调控具有重要意义。本文综述机器学习在食品贮藏品质预测中的研究进展,包括常规的品质预测方法及其局限性。重点介绍近年发展快、应用广的集成学习和人工神经网络算法以及预测性能评估方法,展望机器学习在食品领域的未来发展趋势,为开展食品科学的交叉研究提供参考。

During the process of food storage and circulation,there will be different degrees of quality deterioration.With the improvement of people's attention to food quality and safety,it is of great significance to carry out quality prediction research in the process of food storage and transportation for quality control.This paper reviews the research progress of machine learning in food storage quality prediction,including conventional quality prediction methods and limitations,and then focuses on the rapid development and wide application of integrated learning and artificial neural network algorithms,and prediction performance evaluation methods in recent years.Finally,it summarizes and looks forward to the future development trend of machine learning in the food field,and provides relevant references for the development of food science cross research.