[Application study of ant colony algorithm in near infrared spectroscopy quantitative analysis].
Ant colony algorithm is a novel bio-inspired optimization algorithm, which simulates the foraging behavior of ants for solving various complex combinatorial optimization problems. The advantages of ant colony algorithm are intelligent search, global optimization, robustness, distributed computation and easy combination with other heuristic method. Near infrared spectroscopy quantitative analysis has been applied in many fields, whereas the key step is building the calibration model of measured data. In the present paper, ant colony algorithm was used to build the quantitative analysis model of Fourier transform near infrared diffuse spectroscopy for protein in cereal. Satisfied results were obtained. For calibration set, the correlation coefficient and relative standard deviation were 0.943 and 3.41%, respectively, while for prediction set, the correlation coefficient and relative standard deviation were 0.913 and 4.67%, respectively.
Guo
Liang
L
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.
Ji
Hai-Yan
HY
D000465:Algorithms; D002523:Edible Grain / Q000737:chemistry*; D010940:Plant Proteins / Q000032:analysis*; D017550:Spectroscopy, Fourier Transform Infrared; D019265:Spectroscopy, Near-Infrared
D010940:Plant Proteins