Yi-nuo IU, Zheng-ting HUO, YANG Ren-jie, DONG Gui-mei, YU Ya-ping, LI Liu-an. Qualitative and Quantitative Analysis of Microplastics in Chicken Feed Based on Portable Near Infrared Spectrometer[J]. Journal of instrumental analysis, 2025, 44(6): 1123-1130.
Yi-nuo IU, Zheng-ting HUO, YANG Ren-jie, DONG Gui-mei, YU Ya-ping, LI Liu-an. Qualitative and Quantitative Analysis of Microplastics in Chicken Feed Based on Portable Near Infrared Spectrometer[J]. Journal of instrumental analysis, 2025, 44(6): 1123-1130. DOI: 10.12452/j.fxcsxb.25021691.
Qualitative and Quantitative Analysis of Microplastics in Chicken Feed Based on Portable Near Infrared Spectrometer
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 a
nd quantitative analysis of MPs-contaminated chicken feed samples. A total of 244 chicken 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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Vethaak A D , Legler J . Science , 2021 , 371 ( 6530 ): 672 - 674 .
He X J , Li J Y . J. Instrum. Anal. (何晓杰,李菊英. 分析测试学报), 2024 , 43 ( 8 ): 1135 - 1143 .
Habib R Z , Kindi R A , Salem F A , Kittaneh W F , Poulose V , Iftikhar S H , Thiemann T . Int. J. Environ. Res. Public Health , 2022 , 19 ( 20 ): 13442 .
Chen J , Chen G , Peng H , Qi L , Zhang D , Nie Q , Luo W . Sci. Total Environ. , 2023 , 882 : 163305 .
Chen L , Yang Z , Han L . Appl. Spectrosc. Rev. , 2023 , 48 ( 7 ): 509 - 522 .
Li Y P , Li H H , Zhu Q , Qiao J Y , Wang W J . China Feed(李玉鹏 , 李海花 , 朱琪 , 乔佳运 , 王文杰 . 中国饲料) , 2017 ,( 4 ): 22 - 26 .
Bin J R , Xing H B , Xiao X Y , Zheng Y J , Cai H C , Song M , Huang M Y . China Feed(宾金荣 , 邢宏博 , 肖小云 , 郑玉姣 , 蔡汉聪 , 宋敏 , 黄明媛 . 中国饲料) , 2024 ,( 23 ): 170 - 175 .
Xiccato G , Trocino A , De Boever J L , Maertens L , Carabaño R , Pascual J J , Falcao-E-Cunha L . Anim. Feed Sci. Technol. , 2003 , 104 ( 1/4 ): 153 - 168 .
Sun D D , Li J G , Qin Y C , Dong Y C . Chin. J. Anim. Nutr. (孙丹丹,李军国,秦玉昌,董颖超. 动物营养学报), 2015 , 27 ( 4 ): 1199 - 1206 .
Xu J P , Bi W J , Hua L T , Cheng Z P , Wang Y , Li D D , Liu W T , Wang L , Sun H W . Chemosphere , 2022 , 307 : 135847 .
Wang Q , Li J J , Zhu X P , Sun C , Teng J , Chen L M , Shan E C , Zhao J M . Sci. Total Environ. , 2021 , 807 : 151049 .
Maganti S S , Akkina R C . Online J. Anim. Feed Res. , 2023 , 13 ( 5 ): 348 - 356 .
Shenk J S , Workman Jr J J , Westerhaus M O . In Handbook of Near-infrared Analysis . Florida : CRC Press , 2007 : 365 - 404 .
Masoero G , Barbera S , Kaihara H , Mabrouki S , Patrucco S G , Abid K , Tassone S . Acta IMEKO , 2024 , 13 ( 2 ): 1 - 6 .
Liu Y N , Huo Z T , Huang M Y , Yang R J , Dong G M , Yu Y P , Wang B . Spectrochim. Acta A , 2025 , 329 : 125617 .
Chu X L , Shi Y Y , Chen P , Li J Y , Xu Y P . J. Instrum. Anal. (褚小立,史云颖,陈瀑,李敬岩,许育鹏. 分析测试学报), 2019 , 38 ( 5 ): 603 - 611 .
Huo X S , Chen P , Dai J W , Wang H P , Liu D , Li J Y , Xu Y P , Chu X L . J. Instrum. Anal. (霍学松,陈瀑,戴嘉伟,王海朋,刘丹,李敬岩,许育鹏,褚小立. 分析测试学报), 2022 , 41 ( 9 ): 1301 - 1313 .
Pierna J A F , Abbas O , Lecler B , Hogrel P , Dardenne P , Baeten V . Food Chem. , 2015 , 189 : 2 - 12 .
Zhou H J , Li X Y , Feng Y , Zhang D , Yin G P , Wang S , Zhen Y G , Wang T . Heilongjiang Anim. Sci. Vet. (周昊杰,李小宇,冯煜,张丹,尹国沛,王爽,甄玉国,王涛. 黑龙江畜牧兽医), 2020 , 3 : 106 - 109 .
Modroño S , Soldado A , Martínez-Fernández A , de la Roza-Delgado B . Talanta , 2017 , 162 : 597 - 603 .
Bec K B , Grabska J , Pfeifer F , Siesler H W , Huck C W . J. Hazard. Mater. , 2024 , 480 : 135967 .
Marchesi C , Rani M , Federici S , Alessandri I , Vassalini I , Ducoli S , Depero L E . Environ. Res. , 2023 , 216 : 114632 .
Xu P , Tu Z H , Mi Q , Qiu C G , Lu Y , Luo W X , Yu J X , Chen J , Zheng G W . J. Instrum. Anal. (徐萍,涂振华,米琪,邱昌桂,陆尤,罗文秀,余建新,陈佳,郑国伟. 分析测试学报), 2024 , 43 ( 11 ): 1813 - 1820 .
El Maouardi M , De Braekeleer K , Bouklouze A , Vander Heyden Y . Food Control , 2024 , 165 : 110671 .
Liang H , Shi Z L , Fan Y P , Ren Z X , Yuan T Y , Huang Y P , Han L J , Yang Z L . Trans. Chin. Soc. Agric. Eng. (梁浩,史卓林,范雅彭,任朝霞,袁天怡,黄圆萍,韩鲁佳,杨增玲. 农业工程学报), 2022 , 38 ( 10 ): 208 - 215 .
Zhang W T , Wang K J , Lu Y M , Yang W Y , Xiong Y R , Wu Q , Du Y P . J. Instrum. Anal. (张文婷,王凯君,路亚梅,杨吴烨,熊訚然,吴琼,杜一平. 分析测试学报), 2024 , 43 ( 5 ): 746 - 754 .
Wang J H , Zhang X W , Wang J , Han D H . Spectrosc. Spectral Anal. (王加华,张晓伟,王军,韩东海. 光谱学与光谱分析), 2014 , 34 ( 10 ): 2679 - 2684 .
Hu X Y , Bian X H , Xiang Y , Zhang H , Wei J F . Spectrosc. Spectral Anal. (胡晓云,卞希慧,项洋,张环,魏俊富. 光谱学与光谱分析), 2023 , 43 ( 1 ): 78 - 84 .
Zhai C , Gao M , Luan X X , Qian C J , Zhang W W , Shi X M , Luo Y J , Lü C Z . Feed Res. (翟晨 , 高曼 , 栾鑫鑫 , 钱承敬 , 张巍巍 , 史晓梅 , 罗云敬 , 吕朝政 . 饲料研究) , 2024 ,( 47 ): 126 - 131 .
Blanco M , Coello J , Iturriaga H , Maspoch S , Pezuela C D L . Appl. Spectrosc. , 1997 , 51 ( 2 ): 240 - 246 .
Fan C , Huang Y Z , Lin J N , Li J W . Environ. Technol. Innov. , 2021 , 23 : 101798 .
Koljonen J , Nordling T E , Alander J T . J. Near Infrared Spectrosc. , 2008 , 16 ( 3 ): 189 - 197 .
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