A primary study on forecasting the days before decay of peach fruit using near-infrared spectroscopy and electronic nose techniques
A primary study on forecasting the days before decay of peach fruit using near-infrared spectroscopy and electronic nose techniques
复制标题
利用近红外光谱和电子鼻技术预测桃果实腐烂前几天的初步研究
DOI：
10.1016/j.postharvbio.2017.07.014
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发表时间：
2017-11-01
影响因子：
7
通讯作者：
Wu, Di
中科院分区：
文献类型：
--
作者：
Huang, Lingxia;Meng, Liuwei;Wu, Di
预测桃子腐烂的天数不仅对消费者决定什么时候吃桃子很重要，对销售商决定他们的销售策略也很重要。然而，传统的目视观察，化学和解剖-数字卡尺方法仅适用于已经开始腐烂的情况。本文探讨了利用近红外光谱（NIR）和电子鼻（e-nose）技术预测桃果实腐烂前天数（DBD）的可能性。采用偏最小二乘回归、最小二乘支持向量机和多重高斯拟合回归对模型进行校正。采用逐次投影法、无信息变量消去法和竞争性自适应重加权抽样法进行变量选择。最佳DBD预测模型的正确率为82.26%。结果表明，利用近红外光谱和电子鼻数据相结合的方法预测桃果的DBD是一种可靠、快速的方法。本研究揭示了无损评估桃果在腐烂前可食用时间的诱人前景，这对提高人们的日常生活和桃树产业的管理效率具有重要意义。
Forecasting the number of days until peach fruit decay is important not only for consumers to determine when to eat the fruit, but also for sellers to determine their sale strategies. However, traditional visual observation, chemical and anatomy-digital caliper methods are applicable only when the decay has already begun. In this work, the possibility of forecasting the days before decay (DBD) of peach fruit was explored by means of near-infrared (NIR) spectroscopy and an electronic nose (e-nose). Partial least squares regression, least-squares support vector machines, and multiple Gaussian fitting regressions were used for model calibration. Successive projections algorithm, uninformation variable elimination, and competitive adaptive reweighted sampling were used for variable selection. The best DBD prediction model had a correct answer rate of 82.26%. The results show that the combination of NIR spectroscopy and e-nose data holds promise as a reliable and rapid alternative to forecasting the DBD of peach fruit. This study reveals the attractive prospect of non-destructively estimating how long peach fruit can be edible before decaying, which is important for improving both the daily lives of people and management efficiency in the peach industry.