[3] [3] Ozaki Y. Infrared spectroscopy—Mid-infrared, near-infrared, and far-infrared/terahertz spectroscopy[J]. Analytical Sciences, 2021, 37(9): 1193-1212.

[4] [4] Liu J, Munnaf MA, Mouazen AM. Micro-Near-Infrared (Micro-NIR) sensor for predicting organic carbon and clay contents in agricultural soil[J]. Soil and Tillage Research, 2024, 242: 106155.

[5] [5] Zeng M, Huang H H, Fang Z L, et al. Research on the wavelength intersection union fusion selection method for near-infrared spectroscopy analysis of apple sugar degree[C]. International Conference on Optoelectronic Information and Optical Engineering (OIOE), 2024, 13182: 177-186.

[13] [13] Li X, Wu J, Bai T, et al. Variety classification and identification of jujube based on near-infrared spectroscopy and 1D-CNN[J]. Computers and Electronics in Agriculture, 2024, 223: 109122.

[14] [14] Wu C, Fu J, Huang X, et al. Lithium-Ion Battery Health State Prediction Based on VMD and DBO-SVR[J]. Energies, 2023, 16(10): 3993.

[15] [15] Xue J K, Shen B. Dung beetle optimizer: a new meta-heuristic algorithm for global optimization[J]. The Journal of Supercomputing, 2022, 79(7): 7305-7336.

[16] [16] Xue J K, Shen B. A novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1): 22-34.

[18] [18] Qiao T, Ren J, Craigie C, et al. Quantitative Prediction of Beef Quality Using Visible and NIR Spectroscopy with Large Data Samples Under Industry Conditions[J]. Journal of Applied Spectroscopy, 2015, 82(1): 137-144.

[19] [19] Bian X H, Zhang C X, Tan X Y, et al. A boosting extreme learning machine for near-infrared spectral quantitative analysis of diesel fuel and edible blend oil samples[J]. Analytical Methods, 2017, 9(20): 2983-2989.