Faced with a shortage of agricultural land and a changing climate,Asia urgently needs to focus on smart agriculture to meet the food demands of an increasing population.In recent years,advances in information technolo...Faced with a shortage of agricultural land and a changing climate,Asia urgently needs to focus on smart agriculture to meet the food demands of an increasing population.In recent years,advances in information technology and governmental support have promoted the rapid development of smart agriculture in Asia.This study provides a comprehensive review of the progress of smart agriculture in Asia.First,using bib-liometrics,we conduct a comprehensive analysis of Asian smart-agriculture research in terms of countries,institutions,and keywords.Second,we investigate innovative technologies used in smart agriculture and provide a systematic summary of agricultural production in Asia,from breeding to harvest.In addition,we conduct qualitative and quantitative assessments of smart-agriculture policies across Asia and present cutting-edge solutions to key challenges such as climate change,labor shortage,and water scarcity.Currently,Asian smart-agriculture policies are insufficient in areas such as risk prevention and control,in-ternational cooperation,and standardization.Accordingly,future efforts may focus on enhancing data se-curity and standardization to promote the global development and popularization of smart agriculture.Finally,we discuss trends and challenges that need to be considered and addressed in the future.This re-view aims to analyze the technical characteristics and application status of smart agriculture in Asia and to provide resources for researchers and policy makers.展开更多
At present,automatic broccoli harvest in field still faces some issues.It is difficult to segment broccoli in real time under complex field background,and hard to pick tilt-growing broccoli for the end-effector of rob...At present,automatic broccoli harvest in field still faces some issues.It is difficult to segment broccoli in real time under complex field background,and hard to pick tilt-growing broccoli for the end-effector of robot.In this research,an improved YOLOv8n-seg model,named YOLO-Broccoli-Seg was proposed for broccoli recognition.Through adding a triplet attention module to YOLOv8-Seg model,the feature fusion capability of the algorithm is improved significantly.The mean average precision mAP50(Mask),mAP95(Mask),mAP50(Bounding Box,Bbox)and mAP95(Bbox)of YOLO-Broccoli-Seg are 0.973,0.683,0.973 and 0.748 respectively.Precision P-value was improved the most,with an increment of 8.7%.In addition,an attitude estimation method based on three-dimensional point cloud is proposed.When the tilt angle of broccoli is between−30°and 30°,the R2 between the estimated value and the true value is 0.934.It indicated that this method can well represent the growth attitude of broccoli.This research can provide the rich broccoli information and technical basis for the automated broccoli picking.展开更多
基金funded by the Zhejiang Province Agricultural Machinery Research,Manufacturing and Application Integration Project(grant numbers 2023-YT-06,YF20220801)the National Innovation Park for Forestry and Grass Equipment(grant numbers 2023YG08)the Fundamental Research Funds for the Zhejiang Provincial Universities(grant numbers 226-2024-00191).
文摘Faced with a shortage of agricultural land and a changing climate,Asia urgently needs to focus on smart agriculture to meet the food demands of an increasing population.In recent years,advances in information technology and governmental support have promoted the rapid development of smart agriculture in Asia.This study provides a comprehensive review of the progress of smart agriculture in Asia.First,using bib-liometrics,we conduct a comprehensive analysis of Asian smart-agriculture research in terms of countries,institutions,and keywords.Second,we investigate innovative technologies used in smart agriculture and provide a systematic summary of agricultural production in Asia,from breeding to harvest.In addition,we conduct qualitative and quantitative assessments of smart-agriculture policies across Asia and present cutting-edge solutions to key challenges such as climate change,labor shortage,and water scarcity.Currently,Asian smart-agriculture policies are insufficient in areas such as risk prevention and control,in-ternational cooperation,and standardization.Accordingly,future efforts may focus on enhancing data se-curity and standardization to promote the global development and popularization of smart agriculture.Finally,we discuss trends and challenges that need to be considered and addressed in the future.This re-view aims to analyze the technical characteristics and application status of smart agriculture in Asia and to provide resources for researchers and policy makers.
基金supported by National Innovation Park for Forestry and Grass Equipments[grant numbers 2023YG08]Zhejiang Province Agricultural Machinery Research,Manufacturing and Application Integration Project[grant numbers 2023-YT-06]+1 种基金the Zhejiang University-Yongkang Intelligent Agricultural Machinery Equipment Joint Research Center[grant numbers Zdyk2303Y]the Jiangsu Province and Education Ministry Co-sponsored Synergistic Innovation Center of Modern Agricultural Equipment[grant number XTCX2009].
文摘At present,automatic broccoli harvest in field still faces some issues.It is difficult to segment broccoli in real time under complex field background,and hard to pick tilt-growing broccoli for the end-effector of robot.In this research,an improved YOLOv8n-seg model,named YOLO-Broccoli-Seg was proposed for broccoli recognition.Through adding a triplet attention module to YOLOv8-Seg model,the feature fusion capability of the algorithm is improved significantly.The mean average precision mAP50(Mask),mAP95(Mask),mAP50(Bounding Box,Bbox)and mAP95(Bbox)of YOLO-Broccoli-Seg are 0.973,0.683,0.973 and 0.748 respectively.Precision P-value was improved the most,with an increment of 8.7%.In addition,an attitude estimation method based on three-dimensional point cloud is proposed.When the tilt angle of broccoli is between−30°and 30°,the R2 between the estimated value and the true value is 0.934.It indicated that this method can well represent the growth attitude of broccoli.This research can provide the rich broccoli information and technical basis for the automated broccoli picking.
