Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desir...Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.展开更多
以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,...以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,导致以往评价偏差较大。本文针对无人驾驶小巴的表现构建综合评价体系,并在实测数据的基础上,采用博弈论组合赋权的优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)模型,对车辆在复杂场景下的表现进行综合评价。选取驾驶安全性、乘坐舒适性、车辆智能性及车辆高效性这4个评价维度,并细分为12个客观评价指标。首先,通过实地测试采集无人驾驶小巴在运行场景中的数据;其次,利用基于博弈论的组合赋权法,对层次分析法和熵权法获得的权重进行组合;最后,为验证模型的有效性,运用TOPSIS模型对3条具有不同复杂度的测试路线进行综合评价值的计算。结果显示,无人驾驶小巴表现评价中,准则层的重要程度排序为车辆智能性、驾驶安全性、乘坐舒适性、车辆高效性,指标层敏感指标则为自动驾驶状态、平均角速度。基于博弈论组合赋权的TOPSIS模型对不同场景复杂度路线进行的无人驾驶小巴表现评价结果与实际运行情况一致,展示了方法的有效性。展开更多
文摘Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.
文摘以无人驾驶小巴为代表的客运自动驾驶工具在公交微循环中发挥着重要作用,为实现无人驾驶技术的商业化规模运用,除了传统的车辆性能测试外,还需评估其在复杂场景下的表现。由于测试数据缺乏,评价模型适用场景单一和评价方法主观等问题,导致以往评价偏差较大。本文针对无人驾驶小巴的表现构建综合评价体系,并在实测数据的基础上,采用博弈论组合赋权的优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)模型,对车辆在复杂场景下的表现进行综合评价。选取驾驶安全性、乘坐舒适性、车辆智能性及车辆高效性这4个评价维度,并细分为12个客观评价指标。首先,通过实地测试采集无人驾驶小巴在运行场景中的数据;其次,利用基于博弈论的组合赋权法,对层次分析法和熵权法获得的权重进行组合;最后,为验证模型的有效性,运用TOPSIS模型对3条具有不同复杂度的测试路线进行综合评价值的计算。结果显示,无人驾驶小巴表现评价中,准则层的重要程度排序为车辆智能性、驾驶安全性、乘坐舒适性、车辆高效性,指标层敏感指标则为自动驾驶状态、平均角速度。基于博弈论组合赋权的TOPSIS模型对不同场景复杂度路线进行的无人驾驶小巴表现评价结果与实际运行情况一致,展示了方法的有效性。
