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?;钸\(yùn)輸河蟹品質(zhì)感知生物信號(hào)檢測(cè)與建模
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國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2017YFE0111200)、博士后創(chuàng)新人才支持計(jì)劃項(xiàng)目(BX20180362)和中國(guó)博士后科學(xué)基金項(xiàng)目(2018M641535)


Quality Inspection and Modeling for Crab Transportation
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    摘要:

    針對(duì)河蟹運(yùn)輸過(guò)程中營(yíng)養(yǎng)下降快,、品質(zhì)流失嚴(yán)重以及有效監(jiān)測(cè)難的問(wèn)題,,基于STM32芯片設(shè)計(jì)河蟹生物信號(hào)檢測(cè)裝置,實(shí)現(xiàn)對(duì)運(yùn)輸或貯藏環(huán)境中的氣體和河蟹阻抗信息數(shù)據(jù)實(shí)時(shí)獲取,。利用生物信號(hào)檢測(cè)裝置獲取了河蟹在4,、15、25℃下氣體和生物阻抗的變化信息,,通過(guò)化學(xué)實(shí)驗(yàn)檢測(cè)了相同環(huán)境下作為河蟹傳統(tǒng)品質(zhì)指示指標(biāo)的河蟹揮發(fā)性鹽基氮含量的變化,根據(jù)河蟹貯藏時(shí)感官的變化將品質(zhì)變化階段粗劃分為新鮮到瀕死(S1),、瀕死到死亡(S2)和死亡后腐?。⊿3)3個(gè)變化階段。利用遺傳算法(GA)對(duì)BP神經(jīng)網(wǎng)絡(luò)進(jìn)行參數(shù)優(yōu)化,,分別建立了阻抗-揮發(fā)性鹽基氮含量,、氣體-揮發(fā)性鹽基氮含量、阻抗-氣體-揮發(fā)性鹽基氮含量的耦合模型,,并檢驗(yàn)了這3種耦合模型的預(yù)測(cè)精度,。結(jié)果表明:這3種耦合模型在4、15,、25℃下的預(yù)測(cè)精度均不低于86.32%,。該耦合模型基本滿足河蟹品質(zhì)預(yù)測(cè)的需要,,通過(guò)耦合揮發(fā)性化合物、生物阻抗和化學(xué)指標(biāo)之間的變化關(guān)系,,實(shí)現(xiàn)了通過(guò)生物信號(hào)對(duì)河蟹品質(zhì)的監(jiān)測(cè),,降低了河蟹品質(zhì)獲取的難度。

    Abstract:

    In view of the rapid decline in nutrition during transportation of crabs and the serious loss of quality, the problem of effective monitoring is difficult. The biosignal detection device was used to obtain the changes of gas and bioimpedance of crabs at 4℃, 15℃ and 25℃. The chemical experiment was used to detect the changes of volatile base nitrogen in crabs in the same environment. According to the change of sensory acquisition during crab storage, the quality change stage was roughly divided into three stages: fresh to sudden death (S1), sudden death to death (S2) and postmortem corruption (S3). The BP neural network was optimized by genetic algorithm (GA), and the coupling model of impedancevolatile base nitrogen, gasvolatile base nitrogen and impedancegasvolatile base nitrogen was established. The results showed that the prediction accuracy of the model at 4℃ was 96.93%, 86.32% and 98.77%, respectively. The prediction accuracy of S1 at 15℃ was 8632%, 86.32% and 87.04%; S2 was 87.04%, 88.86% and 89.81%; S3 was at least 92.28%, 96.20% and 93.79%. The prediction accuracy of S1 at 25℃ was 88.86%, 87.04% and 91.23%; S2 was 86.32%, 87.72% and 93.79%; S3 was at least 89.81%, 89.35% and 86.32%, respectively. The coupling model basically met the needs of quality prediction of river crab. The quality of river crab can be predicted through the biological signals which was done by building the link between volatile compounds, biological impedance and chemical indexes.

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王想,高乾鐘,肖新清,傅澤田,張小栓.?;钸\(yùn)輸河蟹品質(zhì)感知生物信號(hào)檢測(cè)與建模[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(10):268-277. WANG Xiang, GAO Qianzhong, XIAO Xinqing, FU Zetian, ZHANG Xiaoshuan. Quality Inspection and Modeling for Crab Transportation[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(10):268-277.

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  • 收稿日期:2020-01-11
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  • 在線發(fā)布日期: 2020-10-10
  • 出版日期: 2020-10-10
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