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### Prediction of qualitative characteristics of sunflower husked seed by near infrared spectroscopy

1. Oil Crops Research Institute of Chinese Academy of Agricultural Science/Key Laboratory of Biology and Genetic Im⁃ provement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China
• Online:2020-02-28 Published:2020-02-28
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Abstract:  For rapid and high throughput prediction of the quality of sunflower seeds, calibration equations were established on 154 materials of sunflower husked seeds. Combination methods included near-infrared spec⁃ troscopy (NIRS) scanning and chemical detecting with chemometrics method to determine the optimal calibration models. Results showed that the model of modified partial least-squares method was appropriate. The determination coefficient of NIRS model for crude fat, crude protein, oleic acid, linoleic acid, saturated fatty acid and unsaturated fatty acid were 0.975, 0.950, 0.973, 0.951 and 0.913 respectively. Their cross-validation correlation coefficients were 0.969, 0.939, 0.915, 0.927 and 0.711 correspondingly. Validation testing results showed that the external vali⁃ dation correlation coefficient for crude fat, crude protein, oleic acid, linoleic acid, saturated fatty acid and unsaturat⁃ ed fatty acid were 0.959, 0.950, 0.937, 0.906 and 0.930 respectively. The results indicated that the established NIRS model could be used as a tool for rapid prediction of qualitative characteristics in sunflower husked seed for large-scale screening of sunflower quality breeding.

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