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1.天津农学院 工程技术学院,天津 300384
2.天津农学院 动物科学与动物医学学院,天津 300384
杨仁杰,博士,教授,研究方向:光谱检测技术与应用,E-mail:rjyang1978@163.com
收稿日期:2025-02-16,
修回日期:2025-03-18,
录用日期:2025-03-20,
网络出版日期:2025-05-21,
纸质出版日期:2025-06-15
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刘一诺,霍正婷,杨仁杰,董桂梅,于亚萍,李留安.基于便携式近红外光谱仪的鸡饲料中微塑料定性定量分析[J].分析测试学报,2025,44(06):1-8.
LIU Yi-nuo, Zheng-ting HUO, YANG Ren-jie, DONG Gui-mei, YU Ya-ping, LI Liu-an. Quantitative Analysis of Microplastics in Chicken Feed Based on Portable Near Infrared Spectrometer[J/OL]. Journal of instrumental analysis, 2025, 441-8.
刘一诺,霍正婷,杨仁杰,董桂梅,于亚萍,李留安.基于便携式近红外光谱仪的鸡饲料中微塑料定性定量分析[J].分析测试学报,2025,44(06):1-8. DOI: 10.12452/j.fxcsxb.25021691.
LIU Yi-nuo, Zheng-ting HUO, YANG Ren-jie, DONG Gui-mei, YU Ya-ping, LI Liu-an. Quantitative Analysis of Microplastics in Chicken Feed Based on Portable Near Infrared Spectrometer[J/OL]. Journal of instrumental analysis, 2025, 441-8. DOI: 10.12452/j.fxcsxb.25021691.
采用便携式近红外(NIR)光谱仪对被微塑料(MPs)污染的鸡饲料样品进行定性和定量分析。共制备了鸡饲料样品244份,包括未被MPs污染的鸡饲料样品61份和分别被聚丙烯(PP)、聚氯乙烯(PVC)和聚对苯二甲酸乙二酯(PET)污染的鸡饲料样品(质量分数均为0.01%~0.8%)183份。基于便携式近红外光谱仪(波长范围900~1 700 nm)采集所有样品的近红外光谱,随机选择1/3样品作为预测集,剩余2/3样品作为校正集,并采用偏最小二乘法建立定性定量分析鸡饲料中MPs的数学模型。对于定性模型:多元散射处理所建模型的性能最佳,对校正集和预测集样品的判别正确率分别为99.38%和100%;对于定量偏最小二乘回归(PLSR)模型:遗传算法(GA)在波长选择方面对提高鸡饲料中MPs定量模型的预测性能展现出显著优势,GA-PLSR模型对3种MPs的预测相关系数(
R
p
)均超过0.873 7,残余预测偏差比(RPD)均超过2.709 0。结果表明:基于便携式近红外光谱仪定性定量分析鸡饲料中MPs是可行的。该研究为饲料中MPs检测提供了一种低成本的快速检测方法。
Rapid and low-cost detection tools provide new methods for the qualitative and quantitative analysis of microplastics(MPs)in chicken feed. In this study,a portable near infrared(NIR)spectrometer was used for qualitative and quantitative analysis of MPs-contaminated chicken feed samples. A total of 244 chick
en feed samples were prepared,including 61 non-contaminated chicken feed samples and 183 MPs-contaminated chicken feed samples(mass fraction range of 0.01%-0.8%)namely polypropylene(PP),polyvinyl chloride(PVC) and polyethylene terephthalate(PET),respectively. The NIR spectra of all samples were collected based on the portable NIR spectrometer(wavelength range,900-1 700 nm). 1/3 of the samples were randomly selected as the prediction set,and the remaining 2/3 of the samples were used as the calibration set. The mathematical model for qualitative and quantitative analysis of MPs in chicken feed was developed using the partial least squares method. For the qualitative models:the model built by the multiple scattering treatment showed the best performance. The discrimination accuracies were 99.38% and 100% for the samples in the calibration and prediction sets,respectively. For quantitative partial least squares regression(PLSR)models:genetic algorithms(GA)showed significant advantages in wavelength selection for improving the prediction performance of the PLSR models for MPs in chicken feed. The GA-PLSR model predicted correlation coefficients(
R
p
) more than 0.873 7 and residual prediction deviation ratios(RPD) more than 2.709 0 for the three MPs. The results showed that it was feasible to analyze MPs in chicken feed by qualitative and quantitative analysis based on portable NIR spectroscopy. This study provides a low-cost and rapid method for the detection of MPs in feed.
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