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首页> 外文期刊>Journal of spectroscopy >Application of VIS/NIR Spectroscopy and SDAE-NN Algorithm for Predicting the Cold Storage Time of Salmon
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Application of VIS/NIR Spectroscopy and SDAE-NN Algorithm for Predicting the Cold Storage Time of Salmon

机译：VIS / NIR光谱和SDAE-NN算法在鲑鱼冷藏时间预测中的应用

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摘要

The cold storage time of salmon has a significant impact on its freshness, which is an important factor for consumers to evaluate the quality of salmon. The efficient, accurate, and convenient protocol is urgent to appraise the freshness for quality checking. In this paper, the ability of visibleear-infrared (VIS/NIR) spectroscopy was evaluated to predict the cold storage time of salmon meat and skin, which were stored at low-temperature box for 0~12 days. Meanwhile, a double-layer stacked denoising autoencoder neural network (SDAE-NN) algorithm was introduced to establish the prediction model without spectral pre-preprocessing. The results showed that, compared with the common methods such as partial least squares regression (PLSR) and back propagation neural network (BP-NN), the SDAE-NN method had a better performance due to its high efficiency in decreasing noise and optimizing the initial weights. The determination coefficient of test sets (R2test) and root mean square error of test sets (RMSEP) have been calculated based on SDAE-NN, for the salmon meat (skin), the R2test can reach 0.98 (0.92), and the RMSEP can reach 0.93 (1.75), respectively. It is highlighted that the algorithm is efficient and accurate and that the salmon meat would be more suitable for predicting freshness than the salmon skin. VIS/NIR spectroscopy combined with the SDAE-NN algorithm can be widely used to predict the freshness of various agricultural products.
机译：鲑鱼的冷藏时间对其新鲜度有重要影响，这是消费者评估鲑鱼质量的重要因素。高效，准确和方便的协议迫切需要评估质量检查的新鲜度。本文评估了可见/近红外（VIS / NIR）光谱的能力，以预测鲑鱼肉和皮肤在低温箱中保存0〜12天的冷藏时间。同时，引入了双层堆叠式去噪自动编码器神经网络（SDAE-NN）算法，建立了无需光谱预处理的预测模型。结果表明，与偏最小二乘回归（PLSR）和反向传播神经网络（BP-NN）等常规方法相比，SDAE-NN方法具有较高的降噪和优化噪声效率，因此具有更好的性能。初始权重。根据SDAE-NN计算出测试集的测定系数（R2test）和测试集的均方根误差（RMSEP），对于鲑鱼肉（皮肤），R2test可以达到0.98（0.92），并且RMSEP可以分别达到0.93（1.75）。需要强调的是，该算法高效且准确，鲑鱼肉比鲑鱼皮更适合预测新鲜度。 VIS / NIR光谱结合SDAE-NN算法可广泛用于预测各种农产品的新鲜度。

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