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Multivariety and multimanufacturer drug identification based on near-infrared spectroscopy and recurrent neural network 被引量:1
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作者 Wenjie Zeng Yunqi Qiu +2 位作者 Yanting Huang Qingping Sun zhuoya luo 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2022年第4期86-96,共11页
Near-infrared(NIR)spectral analysis,which has the advantages of rapidness,nondestruction and high-efficiency,is widely used in the detection of feed,food and mineral.In terms of qualitative identification,it can also ... Near-infrared(NIR)spectral analysis,which has the advantages of rapidness,nondestruction and high-efficiency,is widely used in the detection of feed,food and mineral.In terms of qualitative identification,it can also be used for the discriminant analysis of medicines.Long short-term memory(LSTM)neural network,bidirectional long short-term memory(BiLSTM)neural network and gated recurrent unit(GRU)network are variants of the recurrent neural network(RNN).The potential relationship between nonlinear features learned from the sequence by these variants is used to complete the missions infields such as natural language processing,signal classification and video analysis.Since the effect of these variants in drug identification is still to be studied,this paper constructs a multiclassifier of these three variants,using compoundα-keto acid tablets produced by four manufacturers and repaglinide tablets produced by five manufacturers as the research object.Then,the paper analyzes the impacts of seven different preprocessed methods on the drug NIR data by constructing different layers of LSTM,BiLSTM and GRU networks and compares different classification model indicators and training time of each model.When the spectrum data are pre-processed by z-score normalization,the GRU-3 model has the best accuracy in all models.The BiLSTM models are better for analyzing high coincidence data.The method proposed in this paper can be further extended to other NIR spectroscopy data sets. 展开更多
关键词 Near-infrared spectroscopy long short-term memory bidirectional long short-term memory gated recurrent unit multiple classifiers.
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Effect of Water Chestnut Powder on Gel Properties of Silver Carp Surimi 被引量:1
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作者 Jialin XIE Qing GAN +4 位作者 Hui CHEN zhuoya luo Di TIAN Ruying HE Peng WU 《Agricultural Biotechnology》 CAS 2022年第6期103-108,共6页
[Objectives]The effects of water chestnut powder on the gel properties and quality of silver carp surimi were investigated.[Methods]The surimi gel was prepared by adding 0%,1%,2%,3%,4%and 5%of water chestnut powder to... [Objectives]The effects of water chestnut powder on the gel properties and quality of silver carp surimi were investigated.[Methods]The surimi gel was prepared by adding 0%,1%,2%,3%,4%and 5%of water chestnut powder to the surimi of silver carp.The gel properties,water-holding capacity,cooking loss,whiteness value,puncture and texture profile analysis(TPA)indexes of surimi products were determined to assess the effects of adding different amounts of water chestnut powder on surimi gel.[Results]The results showed that the gel strength,breaking force and depression distance of surimi products increased first and then decreased with the increase of the addition of water chestnut powder.Compared with the control group,the hardness and chewiness of surimi gel in TPA could be significantly improved by adding water chestnut powder.When the addition of water chestnut powder was 2%,the maximum water-holding capacity was 83.68%;the cooking loss rate was the lowest;and the whiteness value was the highest.Adding 2%of water chestnut powder could significantly improve the gel properties of silver carp surimi and obtain a good gel product.[Conclusions]This study provides a scientific basis for the effective utilization of water chestnut resources and the development of new fish surimi products. 展开更多
关键词 Silver carp Surimi gel Water chestnut powder TEXTURE
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