Low temperature significantly restricts crop yield and quality.Medicago falcata(M.falcata)is a typical legume species that exhibits great capacity of tolerance to low temperature.To understand the low-temperature resp...Low temperature significantly restricts crop yield and quality.Medicago falcata(M.falcata)is a typical legume species that exhibits great capacity of tolerance to low temperature.To understand the low-temperature responses in M.falcata,the electrolyte leakage and lipid peroxidation level,and activities of superoxide dismutase(SOD),catalase(CAT)and peroxidase(POD),and contents of reduced glutathione(GSH),soluble protein,soluble sugar and proline were investigated in low-temperature-stressed M.falcata leaves.The electrolyte leakage and malondialdehyde(MDA)content increased,and could be used to quantify low-temperature damage at cellular level.And then,the significant change of SOD,POD and CAT activities,and GSH content reflected the higher reactive oxygen species(ROS)scavenging capacity in M.falcata.In addition,the significant change of soluble protein,soluble sugar and proline contents helped to maintain osmotic equilibrium,energy supply and protein functions.These nine physiological traits were analyzed by gray relational grade analysis and ranked from the highest to the lowest as follows:electrolyte leakage,GSH,proline,soluble protein,MDA,soluble sugar,SOD,CAT and POD,and illustrated that the electrolyte leakage level,GSH and proline contents should be selected and measured priority in M.falcata low-temperature tolerance to improve measurement efficiency.展开更多
A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accur...A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accuracy for the assessment and the optimal selection of the water consumption forecasting models. The results show that the forecasting model built on this comprehensive assessing method presents better self-adaptability and accuracy in forecasting.展开更多
基金Supported by Heilongjiang Provincial Natural Science Foundation of China(YQ2021C019)。
文摘Low temperature significantly restricts crop yield and quality.Medicago falcata(M.falcata)is a typical legume species that exhibits great capacity of tolerance to low temperature.To understand the low-temperature responses in M.falcata,the electrolyte leakage and lipid peroxidation level,and activities of superoxide dismutase(SOD),catalase(CAT)and peroxidase(POD),and contents of reduced glutathione(GSH),soluble protein,soluble sugar and proline were investigated in low-temperature-stressed M.falcata leaves.The electrolyte leakage and malondialdehyde(MDA)content increased,and could be used to quantify low-temperature damage at cellular level.And then,the significant change of SOD,POD and CAT activities,and GSH content reflected the higher reactive oxygen species(ROS)scavenging capacity in M.falcata.In addition,the significant change of soluble protein,soluble sugar and proline contents helped to maintain osmotic equilibrium,energy supply and protein functions.These nine physiological traits were analyzed by gray relational grade analysis and ranked from the highest to the lowest as follows:electrolyte leakage,GSH,proline,soluble protein,MDA,soluble sugar,SOD,CAT and POD,and illustrated that the electrolyte leakage level,GSH and proline contents should be selected and measured priority in M.falcata low-temperature tolerance to improve measurement efficiency.
基金Project(2003BA808A15-2-4) supported by the National Scientific and Technologies Key Task Program
文摘A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accuracy for the assessment and the optimal selection of the water consumption forecasting models. The results show that the forecasting model built on this comprehensive assessing method presents better self-adaptability and accuracy in forecasting.