关键词: 甜玉米, 葡萄糖含量, 果糖含量, 蔗糖含量, 近红外光谱定标模型

Abstract: Sweet corn is an important fruit and vegetable crop in the world. It is of great significance to establish a rapid and non-destructive method detecting sweet corn sugar content for the identification and screening of sweet corn materials for quality breeding. This experiment selected 104 sweet corn samples with high sugar content, and carried out near infrared spectroscopy analysis on them. Combined with the chemical value measured by enzymatic method, partial least square method and different spectral pretreatment and mathematical treatment were adopted to conduct stoichiometric analysis on the total spectral band and constructed the near infrared spectroscopy calibration model of glucose, fructose and sucrose content. External verification was carried out by sample set of external validation, and the actual prediction of the constructed model was tested. The results showed that the optimal spectral treatment of glucose was a weighted multicomponent scattering correction, fructose and sucrose were standard normalized plus descattering treatment. The optimal derivative treatment of glucose was a second derivative, fructose and sucrose were the 1st and 3rd derivatives. The correlation coefficients of glucose, fructose and sucrose were 0.646, 0.645 and 0.820, respectively. The standard deviation of interaction validation was 0.321, 0.275 and 1.508, respectively. The predicted correlation coefficients of glucose, fructose and sucrose were 0.593, 0.780 and 0.891, respectively. These results indicated that the established fructose and sucrose prediction models had better predictability and could be applied to select sweet corn germplasm resources, while the predictability of glucose model was poor and needed to be improved.

Key words: sweet corn, glucose content, fructose content, sucrose content, near infrared spectral calibration models