This study aimed to screen out cold-tolerant sugarcane cultivars through acomprehensive cold tolerance evaluation. A total of 9 sugarcane cultivars with good agronomic traits, bred by the Yunnan Agricultural Universit...This study aimed to screen out cold-tolerant sugarcane cultivars through acomprehensive cold tolerance evaluation. A total of 9 sugarcane cultivars with good agronomic traits, bred by the Yunnan Agricultural University, were selected. They were treated by low temperaturestress （3 ℃）, and the changes of their cold-tolerant physiological and biochemical indices were monitored. The cold tolerance of the sugarcane cultivars was evaluated comprehensively by polar ordination. The results showed that the low temperature stress increased the averagemembrane conductivi- ty, soluble sugar content, MDA content, proline content, soluble protein content, chlorophyll content and peroxidase （POD） activity in sugarcane leaves by 21.21%, 134.1%, 83.60%, 35.47%, 47.72%, 9.07% and 565.2%, respectively, but decreased the superoxide dismutase （SOD） activity in sugarcane leaves by 19.67%. Among the 9 sugarcane cultivars, Dianzhe 03-91 showed the strongest cold tolerance, while Dianzhe 02-39 showed the poorest cold tolerance; the cold tolerance of Dianzhe 08-5, Dianzhe 05-103 and Dianzhe 01-58 was stronger than that of Dianzhe 04- 14, Dianzhe 04-429, Dianzhe 05-522 and Dianzhe 02-227.展开更多
Changes in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it...Changes in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it is important to investigate the ranking of hottest years. In this study, the Wilcoxon signed-ranktest and Monte Carlo simulation are used to estimate the ranking of the hottest years for theTibetan Plateau （TP） in recent decades, and the uncertainty in the ranking.The Wilcoxon signed-rank test shows that the top 10 hottest years on record over the TP mainly occur after 1998. The top three hottest years are ranked as 2006, 2009, and 2010, but there is almost no significant difference between them. When both sampling and observational errors are considered, only five years have a non-zero probability of being the hottest year, with the three highest probabilities being for the years 2006 （-47.231%）, 2009 （-40.390%）, and 2010 （-12.376%）. Similarly, with respect to a given year that is among the 10 hottest years, our results show that all the years among the ranks of 1-10 resulting from the Wilcoxon signed-rank test have probabilities above 10%, while the years 2001 and 2012 have probabilities of 3% and 4%.展开更多
Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-di...Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.展开更多
基金Supported by National Natural Science Foundation of China(31560417)Applied Basic Research Program of Science and Technology Commission Foundation of Yunnan Province(2015FA024)+2 种基金Program for Industry Technology System of Cane in Yunnan(YCJ[2015]90)Key New Product Development Plan of Yunnan Province(2012BB014)Program for Innovation Research Team in Yunnan Province(YKRF[2012]18)~~
文摘This study aimed to screen out cold-tolerant sugarcane cultivars through acomprehensive cold tolerance evaluation. A total of 9 sugarcane cultivars with good agronomic traits, bred by the Yunnan Agricultural University, were selected. They were treated by low temperaturestress （3 ℃）, and the changes of their cold-tolerant physiological and biochemical indices were monitored. The cold tolerance of the sugarcane cultivars was evaluated comprehensively by polar ordination. The results showed that the low temperature stress increased the averagemembrane conductivi- ty, soluble sugar content, MDA content, proline content, soluble protein content, chlorophyll content and peroxidase （POD） activity in sugarcane leaves by 21.21%, 134.1%, 83.60%, 35.47%, 47.72%, 9.07% and 565.2%, respectively, but decreased the superoxide dismutase （SOD） activity in sugarcane leaves by 19.67%. Among the 9 sugarcane cultivars, Dianzhe 03-91 showed the strongest cold tolerance, while Dianzhe 02-39 showed the poorest cold tolerance; the cold tolerance of Dianzhe 08-5, Dianzhe 05-103 and Dianzhe 01-58 was stronger than that of Dianzhe 04- 14, Dianzhe 04-429, Dianzhe 05-522 and Dianzhe 02-227.
基金supported by the National Natural Science Foundation of China[grant number 41405069],[grant number91537214],[grant number 41605063]the Key Foundation of the Education Department of Sichuan Province[grant number16ZA0203]the Scientific Research Foundation of Chengdu University of Information Technology[grant number KYTZ201517],[grant number J201516],[grant number J201518]
文摘Changes in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it is important to investigate the ranking of hottest years. In this study, the Wilcoxon signed-ranktest and Monte Carlo simulation are used to estimate the ranking of the hottest years for theTibetan Plateau （TP） in recent decades, and the uncertainty in the ranking.The Wilcoxon signed-rank test shows that the top 10 hottest years on record over the TP mainly occur after 1998. The top three hottest years are ranked as 2006, 2009, and 2010, but there is almost no significant difference between them. When both sampling and observational errors are considered, only five years have a non-zero probability of being the hottest year, with the three highest probabilities being for the years 2006 （-47.231%）, 2009 （-40.390%）, and 2010 （-12.376%）. Similarly, with respect to a given year that is among the 10 hottest years, our results show that all the years among the ranks of 1-10 resulting from the Wilcoxon signed-rank test have probabilities above 10%, while the years 2001 and 2012 have probabilities of 3% and 4%.
基金Supported by the National Natural Science Foundation of China(61333010,61134007and 21276078)“Shu Guang”project of Shanghai Municipal Education Commission,the Research Talents Startup Foundation of Jiangsu University(15JDG139)China Postdoctoral Science Foundation(2016M591783)
文摘Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.
