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便攜式蔬菜葉片重金屬鎘含量無損檢測儀設(shè)計與試驗
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國家自然科學(xué)基金面上項目(31971788)、江蘇省農(nóng)業(yè)科技自主創(chuàng)新資金項目(CX(19)3089),、江蘇高校優(yōu)勢學(xué)科建設(shè)工程(三期)項目(PAPD-2018-87)和江蘇省現(xiàn)代農(nóng)業(yè)裝備與技術(shù)協(xié)同創(chuàng)新中心項目(4091600030)


Design and Experiment of Portable Non-destructive Tester for Heavy Metal Cadmium Content in Vegetable Leaves
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    摘要:

    針對蔬菜葉片重金屬鎘檢測傳統(tǒng)方法存在的檢測儀器體積大,、檢測成本高和具有破壞性等問題,提出一種基于可見光-近紅外波段光譜蔬菜葉片重金屬鎘檢測方法,并設(shè)計了一款無需預(yù)處理,、檢測速度快,、體積小且便于攜帶的重金屬鎘檢測儀,能夠適用于移動式的現(xiàn)場檢測,。配置4個重金屬鎘脅迫梯度(0,、1、3,、5mg/L)營養(yǎng)液,,培育各鎘脅迫的生菜樣本,通過高光譜成像系統(tǒng)采集葉片反射光譜數(shù)據(jù),,利用主成分分析法(Principal component analysis,,PCA)篩選出3個特征波長(550,、680,、800nm),采用偏最小二乘回歸法(Partial least squares regression,,PLSR)搭建重金屬鎘檢測模型,,該模型測試集相關(guān)系數(shù)Rp為0.9149,測試集均方根誤差為0.5271mg/kg,。使用自制的儀器做標(biāo)定試驗,,選擇A/D采集電壓做參考,用標(biāo)定數(shù)據(jù)進(jìn)行建模,,模型訓(xùn)練集相關(guān)系數(shù)Rc為0.8581,,訓(xùn)練集均方根誤差為0.4975mg/kg,測試集相關(guān)系數(shù)Rp為0.8432,,測試集均方根誤差為0.5526mg/kg,,模型預(yù)測效果較好。最后對便攜式重金屬鎘無損檢測儀檢測精度進(jìn)行驗證,,選取與建模無關(guān)的30組鎘脅迫生菜葉片實時檢測,,與標(biāo)準(zhǔn)理化值對比,均方根誤差為0.32mg/kg,,絕對測量誤差為-0.69~0.66mg/kg,,平均絕對誤差為0.26mg/kg,結(jié)果表明檢測儀能夠?qū)崿F(xiàn)生菜葉片鎘含量的實時無損檢測,。

    Abstract:

    Aiming at the problems of large size, high cost and destructive detection of the traditional method of heavy metal cadmium detection in vegetable leaves, a method for detecting heavy metal cadmium in vegetable leaves based on visible light-near-infrared spectroscopy was proposed, and a method was built without pretreatment. The heavy metal cadmium detection instrument with fast detection speed, small size and easy to carry can be suitable for mobile onsite detection. Nutrient solution of four heavy metal cadmium stress gradients (0mg/L, 1mg/L, 3mg/L and 5mg/L) was configured, lettuce samples were cultivated under each cadmium stress, and leaf reflectance data was collected through a hyperspectral imaging system. Three characteristic bands (550nm, 680nm and 800nm) were selected by using principal component analysis (PCA), and a heavy metal cadmium detection model was built by using partial least squares regression (PLSR). The correlation coefficient RP of test set was 0.9149, and the root mean square error of test set was 0.5271mg/kg. The designed detection instrument for heavy metal cadmium in vegetable leaves included: light source part, signal processing part, display part, power supply part and control part. The size of the instrument was 50mm×70mm×60mm. Using self-made instrument for calibration experiment, selecting A/D acquisition voltage as reference, calibration data were used for modeling, model training set correlation coefficient Rc was 0.8581, training set root mean square error was 0.4975 mg/kg, test set correlation coefficient Rp was 0.8432, root mean square error of the test set was 0.5526mg/kg, and the model prediction performance was better. Finally, the detection accuracy of the portable heavy metal cadmium nondestructive testing instrument was verified. Totally 30 groups of cadmiumstressed lettuce leaves were selected for real-time detection, which were not related to the modeling. Compared with the standard physical and chemical values, the root mean square error was 0.32 mg/kg, and the absolute measurement error was -0.69~0.66 mg/kg, the average absolute error was 0.26mg/kg. The results showed that the instrument can realize real-time nondestructive detection of cadmium content in lettuce leaves.

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孫俊,胡雙齊,周鑫,張林,武小紅,戴春霞.便攜式蔬菜葉片重金屬鎘含量無損檢測儀設(shè)計與試驗[J].農(nóng)業(yè)機(jī)械學(xué)報,2022,53(2):195-202,220. SUN Jun, HU Shuangqi, ZHOU Xin, ZHANG Lin, WU Xiaohong, DAI Chunxia. Design and Experiment of Portable Non-destructive Tester for Heavy Metal Cadmium Content in Vegetable Leaves[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(2):195-202,220.

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  • 收稿日期:2021-02-06
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  • 在線發(fā)布日期: 2021-03-06
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