This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a...This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration traits.Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes.When the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center.The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.展开更多
Thosea sinensis Walker(TSW)rapidly spreads and severely damages the tea plants.Therefore,finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research co...Thosea sinensis Walker(TSW)rapidly spreads and severely damages the tea plants.Therefore,finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community.Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests.In this work,based on the unmanned aerial vehicle(UAV)platform,five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations.By combining the minimum redundancy maximum relevance(mRMR)with the selected spectral features,a comprehensive spectral selection strategy was proposed.Then,based on the selected spectral features,three classic machine learning algorithms,including random forest(RF),support vector machine(SVM),and k-nearest neighbors(KNN)were used to construct the pest monitoring model and were evaluated and compared.The results showed that the strategy proposed in this work obtained ideal monitoring accuracy by only using the combination of a few optimized features(2 or 4).In order to differentiate the healthy and TSW-damaged areas(2-class model),the monitoring accuracies of all the three models were computed,which were above 96%.The RF model used the least number of features,including only SAVI and Bandred.In order to further discriminate the pest incidence levels(3-class model),the monitoring accuracies of all the three models were computed,which were above 80%,among which the RF algorithm based on SAVI,Band_(red),VARI__(green),and Band_(red_edge) features achieve the highest accuracy(OAA of 87%,and Kappa of 0.79).Considering the computational cost and model accuracy,this work recommends the RF model based on a few optimal feature combinations to monitor and distinguish the severity of TSW in tea plantations.According to the UAV remote sensing mapping results,the TSW infestation exhibited an aggregated distribution pattern.The spatial information of occurrence and severity can offer effective guidance for precise control of the pest.In addition,the relevant methods provide a reference for monitoring other leaf-eating pests,effectively improving the management level of plant protection in tea plantations,and guaranting the yield and quality of tea plantations.展开更多
[Objectives]This study was conducted to screen high-efficiency formula pesticides and precise and efficient application techniques for the prevention and control of Sesamia inferens Walker and Ceratovacuna lanigera Ze...[Objectives]This study was conducted to screen high-efficiency formula pesticides and precise and efficient application techniques for the prevention and control of Sesamia inferens Walker and Ceratovacuna lanigera Zehntner.[Methods]Field efficacy trials were conducted using different combinations of 70%directed enhanced thiamethoxam seed treatment dispersible powder and 46%monosultap·Bacillus thuringiensis wettable powder.[Results]70%directed enhanced thiamethoxam ZF 450 g/hm^(2)+46%monosultap·B.thuringiensis WP 2250 g/hm^(2)had good control effects on both S.inferens and C.lanigera,so it was an ideal high-efficiency formula pesticide for controlling sugarcane S.inferens and C.lanigera.From January to May,combining with new plant or perennial root cultivation management,70%directed enhanced thiamethoxam ZF 450 g/hm^(2)can be evenly spread on sugarcane ditches and sugarcane stumps after being well mixed with fertilizers applied per hectare,and covered with soil in a timely manner,and during the peak incubation period of the first and second generation of S.inferens eggs from March to May,46%monosultap·B.thuringiensis WP 2250 g/hm^(2)was sprayed to the leaf surface in the mixture with water 675 kg with an electric backpack or a motorized sprayer.In such a way,the control efficacy on dead heart seedlings could reach over 89.8%,and that on C.lanigera could reach 100%.Meanwhile,it could effectively and concurrently control thrips,and the increases in yield and sugar content could reach 29310 kg/hm^(2)and 5.9 percentage points,respectively.[Conclusions]The promotion and application of the formula pesticide could achieve precise application and control of sugarcane pests,and improvement of sugarcane quality and planting efficiency,and help promote green prevention and control of sugarcane diseases and pests and the sustained high-quality development of the sugar industry.展开更多
基金the National Key R&D Program of China(Grant No.2022YFC3003902)the National Natural Science Foundation of China(Grant No.42075146).
文摘This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration traits.Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes.When the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center.The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.
基金funded by the Zhejiang Agricultural Cooperative and Extensive Project of Key Technology(2020XTTGCY04-02,2020XTTGCY01-05)the Major Special Project for 2025 Scientific and Technological Innovation(Major Scientific and Technological Task Project in Ningbo City)(2021Z048).
文摘Thosea sinensis Walker(TSW)rapidly spreads and severely damages the tea plants.Therefore,finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community.Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests.In this work,based on the unmanned aerial vehicle(UAV)platform,five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations.By combining the minimum redundancy maximum relevance(mRMR)with the selected spectral features,a comprehensive spectral selection strategy was proposed.Then,based on the selected spectral features,three classic machine learning algorithms,including random forest(RF),support vector machine(SVM),and k-nearest neighbors(KNN)were used to construct the pest monitoring model and were evaluated and compared.The results showed that the strategy proposed in this work obtained ideal monitoring accuracy by only using the combination of a few optimized features(2 or 4).In order to differentiate the healthy and TSW-damaged areas(2-class model),the monitoring accuracies of all the three models were computed,which were above 96%.The RF model used the least number of features,including only SAVI and Bandred.In order to further discriminate the pest incidence levels(3-class model),the monitoring accuracies of all the three models were computed,which were above 80%,among which the RF algorithm based on SAVI,Band_(red),VARI__(green),and Band_(red_edge) features achieve the highest accuracy(OAA of 87%,and Kappa of 0.79).Considering the computational cost and model accuracy,this work recommends the RF model based on a few optimal feature combinations to monitor and distinguish the severity of TSW in tea plantations.According to the UAV remote sensing mapping results,the TSW infestation exhibited an aggregated distribution pattern.The spatial information of occurrence and severity can offer effective guidance for precise control of the pest.In addition,the relevant methods provide a reference for monitoring other leaf-eating pests,effectively improving the management level of plant protection in tea plantations,and guaranting the yield and quality of tea plantations.
基金Supported by China Agriculture Research System of MOF and MARA(CARS-170303)Yunling Industrial Technology Leading Talent Training Project(2018LJRC56)Special Fund for the Construction of Modern Agricultural Industry Technology System in Yunnan Province。
文摘[Objectives]This study was conducted to screen high-efficiency formula pesticides and precise and efficient application techniques for the prevention and control of Sesamia inferens Walker and Ceratovacuna lanigera Zehntner.[Methods]Field efficacy trials were conducted using different combinations of 70%directed enhanced thiamethoxam seed treatment dispersible powder and 46%monosultap·Bacillus thuringiensis wettable powder.[Results]70%directed enhanced thiamethoxam ZF 450 g/hm^(2)+46%monosultap·B.thuringiensis WP 2250 g/hm^(2)had good control effects on both S.inferens and C.lanigera,so it was an ideal high-efficiency formula pesticide for controlling sugarcane S.inferens and C.lanigera.From January to May,combining with new plant or perennial root cultivation management,70%directed enhanced thiamethoxam ZF 450 g/hm^(2)can be evenly spread on sugarcane ditches and sugarcane stumps after being well mixed with fertilizers applied per hectare,and covered with soil in a timely manner,and during the peak incubation period of the first and second generation of S.inferens eggs from March to May,46%monosultap·B.thuringiensis WP 2250 g/hm^(2)was sprayed to the leaf surface in the mixture with water 675 kg with an electric backpack or a motorized sprayer.In such a way,the control efficacy on dead heart seedlings could reach over 89.8%,and that on C.lanigera could reach 100%.Meanwhile,it could effectively and concurrently control thrips,and the increases in yield and sugar content could reach 29310 kg/hm^(2)and 5.9 percentage points,respectively.[Conclusions]The promotion and application of the formula pesticide could achieve precise application and control of sugarcane pests,and improvement of sugarcane quality and planting efficiency,and help promote green prevention and control of sugarcane diseases and pests and the sustained high-quality development of the sugar industry.
