[1] Wang Y, Tong J J, Li X X et al. Attenuated total reflection Fourier transform infrared spectral identification of bioaerosol based on 1D-CNN[J]. Acta Optica Sinica, 44, 2430003(2024).

[2] Kovalev E P, Prikhod’ko S A, Shalygin A S et al. Spectral characteristics of ethylene sorbed by silver-containing ionic liquids studied by in situ ATR-FTIR spectroscopy[J]. Mendeleev Communications, 33, 425-427(2023).

[3] Xu Q L, Guo L Y, Du K et al. A hybrid shrinkage strategy based on variable stable weighted for solution concentration measurement in crystallization via ATR-FTIR spectroscopy[J]. Spectroscopy and Spectral Analysis, 43, 1413-1418(2023).

[4] Martins M S, Nascimento M H, Barbosa L L et al. Detection and quantification using ATR-FTIR spectroscopy of whey protein concentrate adulteration with wheat flour[J]. LWT, 172, 114161(2022).

[5] Naim N, Ennahli N, Hanine H et al. ATR-FTIR spectroscopy combined with DNA barcoding and GC-MS to assess the quality and purity of saffron (Crocus sativus L.)[J]. Vibrational Spectroscopy, 123, 103446(2022).

[6] Eilers P, Boelens H. Baseline correction with asymmetric least squares smoothing[EB/OL]. https:∥www.researchgate.net/publication/228961729_Baseline_Correction_with_Asymmetric_Least_Squares_Smoothing

[7] Zhang Z M, Chen S, Liang Y Z. Baseline correction using adaptive iteratively reweighted penalized least squares[J]. The Analyst, 135, 1138-1146(2010).

[8] Li Z, Zhan D J, Wang J J et al. Morphological weighted penalized least squares for background correction[J]. The Analyst, 138, 4483-4492(2013).

[9] Baek S J, Park A, Ahn Y J et al. Baseline correction using asymmetrically reweighted penalized least squares smoothing[J]. The Analyst, 140, 250-257(2015).

[10] Yang G F, Dai J C, Liu X J et al. Multiple constrained reweighted penalized least squares for spectral baseline correction[J]. Applied Spectroscopy, 74, 1443-1451(2020).

[11] Jiang X Y, Li F S, Wang Q Y et al. Baseline correction method based on improved adaptive iteratively reweighted penalized least squares for the X-ray fluorescence spectrum[J]. Applied Optics, 60, 5707-5715(2021).

[12] Zhang F, Tang X J, Tong A X et al. Baseline correction for infrared spectra using adaptive smoothness parameter penalized least squares method[J]. Spectroscopy Letters, 53, 222-233(2020).

[13] Li X S, Tang X J, Wang B et al. An adaptive extended Gaussian peak derivative reweighted penalised least squares method for baseline correction[J]. Analytical Methods, 15, 6048-6060(2023).

[14] Guo Y X, Jin W Q, Wang W L et al. Baseline correction for Raman spectra using a spectral estimation-based asymmetrically reweighted penalized least squares method[J]. Applied Optics, 62, 4766-4776(2023).

[15] Dong Z Y, Xu J L. Baseline estimation using optimized asymmetric least squares (O-ALS)[J]. Measurement, 233, 114731(2024).

[16] He N, Shan P, He Z H et al. Study on the fractional baseline correction method of ATR-FTIR spectral signal in the fermentation process of sodium glutamate[J]. Spectroscopy and Spectral Analysis, 42, 1848-1854(2022).

[17] Han Q J, Xie Q, Peng S L et al. Simultaneous spectrum fitting and baseline correction using sparse representation[J]. The Analyst, 142, 2460-2468(2017).

[18] Li H R, Dai J S, Pan T H et al. Sparse Bayesian learning approach for baseline correction[J]. Chemometrics and Intelligent Laboratory Systems, 204, 104088(2020).

[19] Qin Z J, Tao Z H, Liu J X et al. Baseline correction of Raman spectrum based on piecewise linear fitting[J]. Spectroscopy and Spectral Analysis, 33, 383-386(2013).

[20] Zhao M, Guo Y X, He Y Q et al. Baseline correction of UV Raman spectrum based on improved piecewise linear fitting[J]. Spectroscopy and Spectral Analysis, 40, 1862-1868(2020).

[21] Loverro A[M]. Fractional calculus: history, definitions and applications for the engineer(2004).

[22] Zhang S Y, Fei T, Chen Y Y et al. Estimating cadmium-lead concentrations in rice blades through fractional order derivatives of foliar spectra[J]. Biosystems Engineering, 219, 177-188(2022).

[23] Xia Z Z, Yang J, Wang J et al. Optimizing rice near-infrared models using fractional order Savitzky‒Golay derivation (FOSGD) combined with competitive adaptive reweighted sampling (CARS)[J]. Applied Spectroscopy, 74, 417-426(2020).

[24] Jiang Y H, Yan B, Zhuang Q Y et al. Quantitative inversion model of soil heavy metals Zn and Ni based on fractional order derivative[J]. Spectroscopy and Spectral Analysis, 44, 2850-2857(2024).