[Objectives]This study was conducted to investigate the effects of boron fertilizer on the root system and nutrient contents of yacon.[Methods]By the field test method,high-and low-dose of boron fertilizer(Na2B8O13,90...[Objectives]This study was conducted to investigate the effects of boron fertilizer on the root system and nutrient contents of yacon.[Methods]By the field test method,high-and low-dose of boron fertilizer(Na2B8O13,9000 and 3000 g/hm2)and equal amount of clean water(CK)were sprayed 3 times in the soil area where plants were grown in the early,middle and late stages of yacon growth,and the effects of applying boron fertilizer on the growth and fruit quality of yacon were analyzed.[Results]The indexes of the root system of yacon treated with boron fertilizer were significantly higher than those of the CK.The yield and total sugar,vitamin C,ash,Ca,Fe,Zn and other nutrients of the boron fertilizer treatments increased significantly compared with the CK.The yields of the low-and high-dose treatments increased by 77.2%and 211.2%,respectively,compared with the CK;and the contents of total sugar,vitamin C,ash,Ca,Fe and Zn in the high-dose treatment increased by 28.4%,163.6%,33.2%,73.3%,41.2%and 56.2%,respectively,compared with the CK.The nutrients in yacon treated with the low dose of boron fertilizer were lower than those with the high dose.The application of boron fertilizer could increase the yield of yacon,improve its quality and increase the contents of nutrients such as Ca,Fe,Zn and total sugar.[Conclusions]This study provides a reference for the reasonable application of boron fertilizer in the production of yacon and the improvement of the quality of yacon.展开更多
As the number of electric vehicles(EVs)increases,massive numbers of EVs have started to gather in commercial parking lots to charge and discharge,which may significantly impact the operation of the grid.There may also...As the number of electric vehicles(EVs)increases,massive numbers of EVs have started to gather in commercial parking lots to charge and discharge,which may significantly impact the operation of the grid.There may also be a deviation in the departure time of charged and discharged EVs in commercial parking lots.This deviation can lead to insufficient battery energy when the EVs leave the parking lot.This study uses the simulation software AnyLogic to build a commercial parking lot multi-agent simulation model,and the agent-based model can fully reflect the autonomy of individual EVs.Based on this simulation model,we propose an EV scheduling algorithm.The algorithm contains two main agents.The first is the power distribution center agent(PDCA),which is used to coordinate the energy output of photovoltaic(PV),energy storage system(ESS),and distribution station(DS)to solve the problem of grid overload.The second is the scheduling center agent(SCA),which is used to solve the insufficient battery energy problem due to EVs’random departures.The SCA includes two stages.In the first stage,a priority scheduling algorithm is proposed to emphasize the fairness of EV charging.In the second stage,a genetic algorithm is used to accurately determine the time interval between charging and discharging to ensure the maximum benefit of EV owner.Finally,simulation experiments are conducted in AnyLogic,and the results demonstrate the superiority of the algorithm over the classical algorithm.展开更多
基金School-level Scientific Research Fund Project of Guizhou Normal University(2017BS007)。
文摘[Objectives]This study was conducted to investigate the effects of boron fertilizer on the root system and nutrient contents of yacon.[Methods]By the field test method,high-and low-dose of boron fertilizer(Na2B8O13,9000 and 3000 g/hm2)and equal amount of clean water(CK)were sprayed 3 times in the soil area where plants were grown in the early,middle and late stages of yacon growth,and the effects of applying boron fertilizer on the growth and fruit quality of yacon were analyzed.[Results]The indexes of the root system of yacon treated with boron fertilizer were significantly higher than those of the CK.The yield and total sugar,vitamin C,ash,Ca,Fe,Zn and other nutrients of the boron fertilizer treatments increased significantly compared with the CK.The yields of the low-and high-dose treatments increased by 77.2%and 211.2%,respectively,compared with the CK;and the contents of total sugar,vitamin C,ash,Ca,Fe and Zn in the high-dose treatment increased by 28.4%,163.6%,33.2%,73.3%,41.2%and 56.2%,respectively,compared with the CK.The nutrients in yacon treated with the low dose of boron fertilizer were lower than those with the high dose.The application of boron fertilizer could increase the yield of yacon,improve its quality and increase the contents of nutrients such as Ca,Fe,Zn and total sugar.[Conclusions]This study provides a reference for the reasonable application of boron fertilizer in the production of yacon and the improvement of the quality of yacon.
基金supported by the National Natural Science Foundation of China(No.61873222)the Hunan Provincial Key Research and Development Program(No.2021GK2019)the Project of Hunan National Center for Applied Mathematics,China(No.2020ZYT003).
文摘As the number of electric vehicles(EVs)increases,massive numbers of EVs have started to gather in commercial parking lots to charge and discharge,which may significantly impact the operation of the grid.There may also be a deviation in the departure time of charged and discharged EVs in commercial parking lots.This deviation can lead to insufficient battery energy when the EVs leave the parking lot.This study uses the simulation software AnyLogic to build a commercial parking lot multi-agent simulation model,and the agent-based model can fully reflect the autonomy of individual EVs.Based on this simulation model,we propose an EV scheduling algorithm.The algorithm contains two main agents.The first is the power distribution center agent(PDCA),which is used to coordinate the energy output of photovoltaic(PV),energy storage system(ESS),and distribution station(DS)to solve the problem of grid overload.The second is the scheduling center agent(SCA),which is used to solve the insufficient battery energy problem due to EVs’random departures.The SCA includes two stages.In the first stage,a priority scheduling algorithm is proposed to emphasize the fairness of EV charging.In the second stage,a genetic algorithm is used to accurately determine the time interval between charging and discharging to ensure the maximum benefit of EV owner.Finally,simulation experiments are conducted in AnyLogic,and the results demonstrate the superiority of the algorithm over the classical algorithm.
