Rapid detection and spectroscopic feature analysis of mineral content in camel milk using fourier-transform mid-infrared spectroscopy and traditional machine learning algorithms

被引:0
|
作者
Li, Yongqing [1 ,2 ]
Fan, Yikai [1 ]
Gao, Jingyi [1 ]
Liu, Li [1 ,2 ]
Cao, Lijun [2 ]
Hu, Bo [2 ]
Abula, Zunongjiang [2 ]
Xieermaola, Yeerlan [2 ]
Wang, Haitong [1 ]
Chu, Chu [1 ]
Yang, Zhuo [1 ]
Yang, Guochang [1 ]
Wen, Peipei [1 ]
Wang, Dongwei [1 ]
Zheng, Wenxin [3 ]
Zhang, Shujun [1 ]
机构
[1] Huazhong Agr Univ, Key Lab Agr Anim Genet Breeding & Reprod, Minist Educ, Wuhan 430070, Peoples R China
[2] Xinjiang Acad Anim Sci, Inst Anim Husb Qual Stand, Urumqi 830011, Peoples R China
[3] Xinjiang Agr Univ, Urumqi 830052, Peoples R China
关键词
Camel milk; Minerals; FT-MIRS; Machine learning; Detection method; BOVINE-MILK; PREDICTION; DIFFERENTIATION; QUALITY;
D O I
10.1016/j.foodcont.2024.110983
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Camel milk is rich in nutrients and bioactive factors, with mineral content generally higher than that of cow milk, but there is currently no internationally established, rapid, batch-testing method for the mineral content. This study collected samples of camel milk from 113 locations in Xinjiang, China. For the first time internationally, based on the true mineral values determined by ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) and the extracted mid-infrared spectra data, a quantitative prediction model for 10 key minerals (Ca, Fe, K, Mg, Mn, Na, P, Sr, Zn, and Se) was established using Fourier-Transform Mid-Infrared Spectroscopy (FTMIRS) and the traditional machine learning algorithm Partial Least Squares Regression. The Rt2 of the test set ranged from 0.61 to 0.91, RMSEt ranged from 2.21ug/kg(Se) to 197.08 mg/kg(K) and the RPDt from 1.59 to 3.28. In addition, the distribution, patterns, and correlations of mineral-related characteristic wavenumbers in camel milk were summarized. This study opens a new avenue for the rapid detection of minerals in camel milk and fills the research gap in in using FT-MIRS to detect mineral content in camel milk.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Detection of adulterants in grape nectars by attenuated total reflectance Fourier-transform mid-infrared spectroscopy and multivariate classification strategies
    Whei Miaw, Carolina Sheng
    Sena, Marcelo Martins
    Carvalho de Souza, Scheilla Vitorino
    Callao, Maria Pilar
    Ruisanchez, Itziar
    FOOD CHEMISTRY, 2018, 266 : 254 - 261
  • [42] Predicting methane emissions of lactating Danish Holstein cows using Fourier transform mid-infrared spectroscopy of milk
    Shetty, N.
    Difford, G.
    Lassen, J.
    Lovendahl, P.
    Buitenhuis, A. J.
    JOURNAL OF DAIRY SCIENCE, 2017, 100 (11) : 9052 - 9060
  • [43] Rapid and quantitative detection of the microbial spoilage in milk using Fourier transform infrared spectroscopy and chemometrics
    Nicolaou, Nicoletta
    Goodacre, Royston
    ANALYST, 2008, 133 (10) : 1424 - 1431
  • [44] Rapid screening for autoimmune diseases using Fourier transform infrared spectroscopy and deep learning algorithms
    Wu, Xue
    Shuai, Wei
    Chen, Chen
    Chen, Xiaomei
    Luo, Cainan
    Chen, Yi
    Shi, Yamei
    Li, Zhengfang
    Lv, Xiaoyi
    Chen, Cheng
    Meng, Xinyan
    Lei, Xin
    Wu, Lijun
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [45] Breast cancer early detection by using Fourier-transform infrared spectroscopy combined with different classification algorithms
    Du, Yu
    Xie, Fei
    Yin, Longfei
    Yang, Yang
    Yang, Houpu
    Wu, Guohua
    Wang, Shu
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2022, 283
  • [46] Rapid estimation of the biochemical methane potential of plant biomasses using Fourier transform mid-infrared photoacoustic spectroscopy
    Bekiaris, Georgios
    Triolo, Jin M.
    Peltre, Clement
    Pedersen, Lene
    Jensen, Lars S.
    Bruun, Sander
    BIORESOURCE TECHNOLOGY, 2015, 197 : 475 - 481
  • [47] Rapid Measurement of Human Milk Macronutrients in the Neonatal Intensive Care Unit: Accuracy and Precision of Fourier Transform Mid-Infrared Spectroscopy
    Smilowitz, Jennifer T.
    Gho, Deborah S.
    Mirmiran, Majid
    German, J. Bruce
    Underwood, Mark A.
    JOURNAL OF HUMAN LACTATION, 2014, 30 (02) : 180 - 189
  • [48] The Characteristics of Milk Fatty Acid Profile Predicted by Fourier-Transform Mid-Infrared Spectroscopy (FT-MIRS) in Chinese Holstein Cows
    Li, Chunfang
    Wang, Haitong
    Fan, Yikai
    Zhou, Zengpo
    Li, Yuanbao
    Liang, Shengchao
    Ma, Yabin
    Zhang, Shujun
    ANIMALS, 2024, 14 (19):
  • [49] The use of milk Fourier-transform mid-infrared spectroscopy to diagnose pregnancy and determine spectral regional associations with pregnancy in US dairy cows
    Khanal, Piush
    Tempelman, Robert J.
    JOURNAL OF DAIRY SCIENCE, 2022, 105 (04) : 3209 - 3221
  • [50] Short communication: Predictive ability of Fourier-transform mid-infrared spectroscopy to assess CSN genotypes and detailed protein composition of buffalo milk
    Bonfatti, V.
    Cecchinato, A.
    Carnier, P.
    JOURNAL OF DAIRY SCIENCE, 2015, 98 (09) : 6583 - 6587