The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increas...The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increasingly necessary due to increasing habitat degredation in deep waters(>200 m depth).At these depths,which are far beyond those accessible by divers,only established and emerging robotic platforms such as remotely operated vehicles(ROVs),autonomous underwater vehicles(AUVs),landers,and crawlers can operate through manipulators and multiparametric sensor arrays(e.g.,optoacoustic imaging,omics,and environmental probes).The use of advanced technologies for deep-sea ecosystem restoration can provide:①high-resolution three-dimensional(3D)imaging and acoustic mapping of substrates and key taxa,②physical manipulation of substrates and key taxa,③real-time supervision of remote operations and long-term ecological monitoring,and④the potential to work autonomously.Here,we describe how robotic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across large spatial scales.We expect that these devices will be particularly useful in deep-sea habitats,such as①reef-building cold-water corals,②soft-bottom bamboo corals,and③soft-bottom fishery resources that have already been damaged by offshore industries(i.e.,fishing and oil/gas).展开更多
A 2-year field experiment was conducted in 2015 and 2016 by using artificial root pruning to simulate mechanical root injury caused by agricultural machinery components and reveal its effects on maize growth and yield...A 2-year field experiment was conducted in 2015 and 2016 by using artificial root pruning to simulate mechanical root injury caused by agricultural machinery components and reveal its effects on maize growth and yield.Quasi-level orthogonal experimental design was employed to create orthogonal tables with four factors of interest,namely,pruning time(jointing stage,JS;big trumpet period,BTP),pruning method(unilateral pruning,UNP;bilateral pruning,BIP),pruning distance(5,10,and 15 cm)and pruning depth(5,10,and 15 cm).Results revealed that (1)maize growth was inhibited at the beginning of root pruning;(2)stem diameter(SD)and plant height(PHE)were smaller than those of the control check(CK)but exceeded the latter after 20 d of root pruning in JS;(3)SD and PHE were always smaller than those of the CK under root pruning in BTP;(4)T8(BTP,BIP,5 cm of pruning distance and 15 cm of pruning depth)can reach to a significant level(p<0.01).The vertical distribution and total dry weight(TDW)of maize roots in soil were affected by different root pruning treatments.When pruning in JS,the root ratio in 0-10 cm soil was 11.6%in T2(JS,UNP,a pruning distance of 10 cm and pruning depth of 10 cm).When pruning in BTP,the root ratio of 10-20 cm soil layer increased by 15%.However,the TDW of maize decreased,the largest of which occurred in T8 at 53%.With the exception of a 0.43%increase in T3(JS,UNP,15 cm of pruning distance and 15 cm of pruning depth),the maize yield of all other treatments decreased compared with that of CK,and the largest reduction was in T8 at up to 19.1%.This finding suggests that a small pruning distance and a large pruning depth greatly influence the growth and yield of maize before and during pruning in BTP.The influence of BIP is greater than that of UNP.These results provide evidence for the effects of mechanical root injury on maize growth and yield and serve as a reference for the selection of mechanical topdressing parameters.展开更多
Food consumption is constantly increasing at global scale.In this light,agricultural production also needs to increase in order to satisfy the relevant demand for agricultural products.However,due to by environmental ...Food consumption is constantly increasing at global scale.In this light,agricultural production also needs to increase in order to satisfy the relevant demand for agricultural products.However,due to by environmental and biological factors(e.g.soil compaction)the weight and size of the machinery cannot be further physically optimized.Thus,only marginal improvements are possible to increase equipment effectiveness.On the contrary,late technological advances in ICT provide the ground for significant improvements in agriproduction efficiency.In this work,the V-Agrifleet tool is presented and demonstrated.VAgrifleet is developed to provide a “hands-free”interface for information exchange and an “Olympic view”to all coordinated users,giving them the ability for decentralized decision-making.The proposed tool can be used by the end-users(e.g.farmers,contractors,farm associations,agri-products storage and processing facilities,etc.)order to optimize task and time management.The visualized documentation of the fleet performance provides valuable information for the evaluation management level giving the opportunity for improvements in the planning of next operations.Its vendorindependent architecture,voice-driven interaction,context awareness functionalities and operation planning support constitute V-Agrifleet application a highly innovative agricultural machinery operational aiding system.展开更多
基金conceived within the preparation of the Project Restoration of Deep-sea habitats to Rebuild European Seas (REDRESS):HORIZON CL6-2023-BIODIV-Restoration of deepsea habitats carried out within the framework of the activities of the Spanish Government through the"Severo Ochoa Centre Excellence"granted to ICM-CSIC (CEX2019-000928-S)and the Research Unit Tecnoterra (ICM-CSIC/UPC)supported the work were those of the Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 of the Spanish government:BITER-LANDER (PID2020-114732RB-C32),BITER-ECO (PID2020-114732RB-C31),BITER-AUV (PID2020-114732RB-C33),PLOME (PLEC2021-007525/AEI/10.13039/501100011033)+3 种基金the conceptual development,falls within the framework of EU LIFE Project ECOREST (LIFE20 NAT/ES/001270)funded by a Juan de la Cierva Formación Post-doctoral Fellowship (FJC2021-047734-Ifinanced by Ministerio de Cuyltura e Innovación/Agencia Española de Investigación and European Union NextGeneration EU/PRTR funds)funded by the Spanish Government (Agencia Española de Investigación-AEI)through the‘Severo Ochoa Centre of Excellence’accreditation (CEX2019-000928-S).
文摘The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increasingly necessary due to increasing habitat degredation in deep waters(>200 m depth).At these depths,which are far beyond those accessible by divers,only established and emerging robotic platforms such as remotely operated vehicles(ROVs),autonomous underwater vehicles(AUVs),landers,and crawlers can operate through manipulators and multiparametric sensor arrays(e.g.,optoacoustic imaging,omics,and environmental probes).The use of advanced technologies for deep-sea ecosystem restoration can provide:①high-resolution three-dimensional(3D)imaging and acoustic mapping of substrates and key taxa,②physical manipulation of substrates and key taxa,③real-time supervision of remote operations and long-term ecological monitoring,and④the potential to work autonomously.Here,we describe how robotic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across large spatial scales.We expect that these devices will be particularly useful in deep-sea habitats,such as①reef-building cold-water corals,②soft-bottom bamboo corals,and③soft-bottom fishery resources that have already been damaged by offshore industries(i.e.,fishing and oil/gas).
基金supported by the Key Scientific Research Fund of Xihua University(Grant No.Z17121)Science and Technology Plan Project of Sichuan Provincial(Grant No.2021TDR0054).
文摘A 2-year field experiment was conducted in 2015 and 2016 by using artificial root pruning to simulate mechanical root injury caused by agricultural machinery components and reveal its effects on maize growth and yield.Quasi-level orthogonal experimental design was employed to create orthogonal tables with four factors of interest,namely,pruning time(jointing stage,JS;big trumpet period,BTP),pruning method(unilateral pruning,UNP;bilateral pruning,BIP),pruning distance(5,10,and 15 cm)and pruning depth(5,10,and 15 cm).Results revealed that (1)maize growth was inhibited at the beginning of root pruning;(2)stem diameter(SD)and plant height(PHE)were smaller than those of the control check(CK)but exceeded the latter after 20 d of root pruning in JS;(3)SD and PHE were always smaller than those of the CK under root pruning in BTP;(4)T8(BTP,BIP,5 cm of pruning distance and 15 cm of pruning depth)can reach to a significant level(p<0.01).The vertical distribution and total dry weight(TDW)of maize roots in soil were affected by different root pruning treatments.When pruning in JS,the root ratio in 0-10 cm soil was 11.6%in T2(JS,UNP,a pruning distance of 10 cm and pruning depth of 10 cm).When pruning in BTP,the root ratio of 10-20 cm soil layer increased by 15%.However,the TDW of maize decreased,the largest of which occurred in T8 at 53%.With the exception of a 0.43%increase in T3(JS,UNP,15 cm of pruning distance and 15 cm of pruning depth),the maize yield of all other treatments decreased compared with that of CK,and the largest reduction was in T8 at up to 19.1%.This finding suggests that a small pruning distance and a large pruning depth greatly influence the growth and yield of maize before and during pruning in BTP.The influence of BIP is greater than that of UNP.These results provide evidence for the effects of mechanical root injury on maize growth and yield and serve as a reference for the selection of mechanical topdressing parameters.
基金The authors wish to acknowledge financial support provided by the Special Account for Research Funds of the Technological Education Institute of Central Macedonia,Greece,under grant SMF/LG/060219–23/3/19.
文摘Food consumption is constantly increasing at global scale.In this light,agricultural production also needs to increase in order to satisfy the relevant demand for agricultural products.However,due to by environmental and biological factors(e.g.soil compaction)the weight and size of the machinery cannot be further physically optimized.Thus,only marginal improvements are possible to increase equipment effectiveness.On the contrary,late technological advances in ICT provide the ground for significant improvements in agriproduction efficiency.In this work,the V-Agrifleet tool is presented and demonstrated.VAgrifleet is developed to provide a “hands-free”interface for information exchange and an “Olympic view”to all coordinated users,giving them the ability for decentralized decision-making.The proposed tool can be used by the end-users(e.g.farmers,contractors,farm associations,agri-products storage and processing facilities,etc.)order to optimize task and time management.The visualized documentation of the fleet performance provides valuable information for the evaluation management level giving the opportunity for improvements in the planning of next operations.Its vendorindependent architecture,voice-driven interaction,context awareness functionalities and operation planning support constitute V-Agrifleet application a highly innovative agricultural machinery operational aiding system.