【摘要】 【目的】筛选不同选择目标下最适宜的谷子品种，综合评价适宜不同选择目标的最佳谷子品种。【方法】2021～2022年分析对比20份谷子新品种的25个农艺性状、产量和品质指标，利用熵权法对各指标赋权，采用DTOPSIS法、灰色关联度分析法评价对不同品种的农艺性状及产量与品质。【结果】除千粒重外，其余24个指标的谷子品种间差异均达极显著水平。2种分析方法的排序结果与产量排序结果的吻合程度更高，即灰色关联度分析较DTOPSIS法更注重评价产量。C_i最大差异值为30.01%,r_i最大差异值为7.71%,γ最大差异值为11.85%,DTOPSIS法更能体现出各谷子品种的差异性。【结论】DTOPSIS法和熵权法赋权的加权灰色关联度分析法适用于综合评价谷子品种。半干旱生产区应选择张杂谷16号；各性状更平衡的品种应选择金苗K₂;兼顾产量和各性状平衡的品种应选择济谷22号。更多还原

【Abstract】 【Objective】 It is necessary to determine the most suitable variety under different selection goals and the best comprehensive evaluation method for different selection goals of millet varieties.【Methods】 In this study from 2021 to 2022, 25 agronomic traits, yield, and quality indicators of 20 new millet varieties were analyzed and compared.Meanwhile, the entropy weight method was used to assign weights to each indicator, and DTOPSIS method and grey relational degree analysis method were used to evaluate different varieties.【Results】 Except for thousand-grain weight, the differences between varieties in the other 24 indicators reached a highly significant level.The ranking results of the two analytical methods, DTOPSIS and grey relational analysis, showed a higher degree of agreement with the yield ranking results.This indicated that grey relational analysis payed more attention to the evaluation of yield than the DTOPSIS method.The maximum difference value of Ci was 30.01%, the maximum difference value of ri was 7.71%, and the maximum difference value of γ was 11.85%, indicating that the DTOPSIS method could better demonstrate the differences between varieties.【Conclusion】 The DTOPSIS method and the weighted grey relational analysis method based on entropy weight are suitable for the comprehensive evaluation of millet varieties.In semi-arid production areas, if higher yield varieties are needed, Zhangzagu 16 should be selected; if varieties with more balanced traits are needed, Jinmiao K₂ should be chosen; if varieties with a balance between yield and various traits are needed, Jigu 22 should be selected.更多还原