Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Ag...Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAASS).展开更多
Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Ag...Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAASS).JIA is a peer-reviewed and multi-disciplinary international journal and published monthly in English.JIA Editorial Board consists of 289 well-respected scholars of agricultural scientific fields.展开更多
Ploughing and fertilization practices in rice-wheat system have deteriorated the soil carbon (C) pools. Conservation agriculture (CA) based management approaches have proven to enhance C sequestration and reverse the ...Ploughing and fertilization practices in rice-wheat system have deteriorated the soil carbon (C) pools. Conservation agriculture (CA) based management approaches have proven to enhance C sequestration and reverse the loss of soil-organic-carbon (SOC), which further enhances soil fertility. Different fractions of SOC pools react to the alterations in management practices and indicate changes in SOC dynamics as compared to total C in the soil. Higher SOC levels in soil have been observed in case of reduced/no-till (NT) practices than conventional tillage (CT). However, between CT and zero tillage/NT, total SOC stocks diminished with an increase in soil depth, which demonstrated that the benefits of SOC are more pronounced in the topsoil under NT. Soil aggregation provides physical protection to C associated with different-sized particles, thus, the improvement in soil aggregation through CA is an effective way to mitigate soil C loss. Along with less soil disturbance, residual management, suitable crop rotation, rational application of manures and fertilizers, and integrated nutrient management have been found to be effective in not only improving soil C stock but also enhancing the soil health and productivity. Thus, CA can be considered as a potential method in the build-up of SOC of soil in rice-wheat system.展开更多
Food security and sustainable development is making a mandatory move in the entire human race.The attainment of this goal requires man to strive for a highly advanced state in thefield of agriculture so that he can pro...Food security and sustainable development is making a mandatory move in the entire human race.The attainment of this goal requires man to strive for a highly advanced state in thefield of agriculture so that he can produce crops with a minimum amount of water and fertilizer.Even though our agricultural methodol-ogies have undergone a series of metamorphoses in the process of a present smart-agricultural system,a long way is ahead to attain a system that is precise and accurate for the optimum yield and profitability.Towards such a futuristic method of cultivation,this paper proposes a novel method for monitoring the efficientflow of a small quantity of water through the conventional irrigation system in cultiva-tion using Clustered Wireless Sensor Networks(CWSN).The performance measure is simulated the creation of edge-fixed geodetic clusters using Mat lab’s Cup-carbon tool in order to evaluate the suggested irrigation process model’s performance.Thefindings of blocks 1 and 2 are assessed.Each signal takes just a little amount of energy to communicate,according to the performance.It is feasible to save energy while maintaining uninterrupted communication between nodes and cluster chiefs.However,the need for proper placement of a dynamic control station in WSN still exists for maintaining connectivity and for improving the lifetime fault tolerance of WSN.Based on the minimum edgefixed geodetic sets of the connected graph,this paper offers an innovative method for optimizing the placement of control stations.The edge-fixed geodetic cluster makes the network fast,efficient and reliable.Moreover,it also solves routing and congestion problems.展开更多
The research objective of this review is to discuss the rationale that led to the development of Controlled Environment Agriculture (CEA) and investigate this agricultural approach as a potential solution to mitigate ...The research objective of this review is to discuss the rationale that led to the development of Controlled Environment Agriculture (CEA) and investigate this agricultural approach as a potential solution to mitigate the increased pressures on food security. It describes the need for urban cultivation systems using controlled environments and how they can be harnessed to address pressures facing food security. The factors that have contributed to the growth of CEAs, education, environmental justice, and the advantages and disadvantages of growing crops in CEAs in urban areas will be discussed. The article reviews global urban cultivation systems using controlled environments, by identifying the technologies needed to establish them. The practice of CEA is being increasingly adopted worldwide and we describe urban agriculture and compare it with traditional growing systems. Indoor farming systems that integrate into existing urban infrastructure such as vertical farming and plant factories using CEAs are discussed. Indoor farming gives urban areas enhanced access to food sources, but the cost is high, however decreasing due to recent technological advances. The current review extends the literature by incorporating recent research on the topic of agriculture in urban areas and food security. This review seeks to provide additional information regarding the viability of CEA in urban areas.展开更多
Precision Agriculture(PA)has been used in many countries and serving the agricultural sectors.The use of PA solutions intervened with many agricultural businesses and supported decision making using data analytics.Pre...Precision Agriculture(PA)has been used in many countries and serving the agricultural sectors.The use of PA solutions intervened with many agricultural businesses and supported decision making using data analytics.Precision Agriculture depends on weather,soil,plants,and water information that are essential for farming.Precision Agriculture depends on the use of several technologies such as image sensors,vision machines,drones,robots,machine learning,and artificial intelligence.The use of Precision Agriculture Technologies(PAT)depends on integration between devices,sensors,and systems to ensure the proper implementation of activities.This paper is generated from research on the applicability of PA in in Egypt that ended with a proposed framework for proper implementation of it.The conducted research depended on a survey,focus group discussions,and an online questionnaire that reached 271 respondents from 19 Egyptian governorates.The framework has been developed to enhance the role of an initiative leader to promote PAT through collaboration with other stakeholders in the agricultural sector.The proposed framework can be used by governmental,non-governmental entities,universities and private sector institutions and could be used at countries facing issues with land fragmentation,limited access to information,limited access to agricultural extension services,and increase in agricultural input’s prices.展开更多
Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)approaches.Weed plays a vital ...Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)approaches.Weed plays a vital role in influencing crop productivity.The wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are increased.Since the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity,this study presents a novel computer vision and deep learning based weed detection and classification(CVDL-WDC)model for precision agriculture.The proposed CVDL-WDC technique intends to prop-erly discriminate the plants as well as weeds.The proposed CVDL-WDC technique involves two processes namely multiscale Faster RCNN based object detection and optimal extreme learning machine(ELM)based weed classification.The parameters of the ELM model are optimally adjusted by the use of farmland fertility optimization(FFO)algorithm.A comprehensive simulation analysis of the CVDL-WDC technique against benchmark dataset reported the enhanced out-comes over its recent approaches interms of several measures.展开更多
The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the mo...The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.DEMETER(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food chain.This paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER lifecycle.This paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.展开更多
Instruction to Authors Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by...Instruction to Authors Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.展开更多
Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASc),founded in 2002,is sponsoredby Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of...Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASc),founded in 2002,is sponsoredby Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JiA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.JIA publishes manuscripts in the categories of Commentary,Review,Research Article,Letter and'Short Communication,focusing on the core subjects:Crop Science Horticulture·Plant Protection·Animal Science·Veterinary Medicine·Agro-ecosystem&Environment:Food Science·Agricultural Economics and Management·Agricultural Information Science.展开更多
Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association o...Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.JIA publishes manuscripts in the categories of Commentary,Review,Research Article,Letter and Short Communication,focusing on the core subjects:Crop Science.Horticulture·Plant Protection·Animal Science·Veterinary Medicine·Agro-ecosystem&Environment·Food Science·Agriculturai Economics and Management·Agricultural Information Science.展开更多
Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(As),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agr...Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(As),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAAsS).展开更多
The overgrowth of weeds growing along with the primary crop in the fields reduces crop production.Conventional solutions like hand weeding are labor-intensive,costly,and time-consuming;farmers have used herbicides.The...The overgrowth of weeds growing along with the primary crop in the fields reduces crop production.Conventional solutions like hand weeding are labor-intensive,costly,and time-consuming;farmers have used herbicides.The application of herbicide is effective but causes environmental and health concerns.Hence,Precision Agriculture(PA)suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary plants.Motivated by the gap above,we proposed a Deep Learning(DL)based model for detecting Eggplant(Brinjal)weed in this paper.The key objective of this study is to detect plant and non-plant(weed)parts from crop images.With the help of object detection,the precise location of weeds from images can be achieved.The dataset is collected manually from a private farm in Gandhinagar,Gujarat,India.The combined approach of classification and object detection is applied in the proposed model.The Convolutional Neural Network(CNN)model is used to classify weed and non-weed images;further DL models are applied for object detection.We have compared DL models based on accuracy,memory usage,and Intersection over Union(IoU).ResNet-18,YOLOv3,CenterNet,and Faster RCNN are used in the proposed work.CenterNet outperforms all other models in terms of accuracy,i.e.,88%.Compared to other models,YOLOv3 is the least memory-intensive,utilizing 4.78 GB to evaluate the data.展开更多
The Honghe Hani Rice Terraces of Yunnan Province have become a national emblem for China and a UNESCO World Heritage Site,but some are beginning to crumble.This research attempts to address why this is happening and w...The Honghe Hani Rice Terraces of Yunnan Province have become a national emblem for China and a UNESCO World Heritage Site,but some are beginning to crumble.This research attempts to address why this is happening and what can be done about it.Previous work has failed to adequately address the possible shortcomings of recently introduced seed and water management technologies,their particular effect on rice terraces and the people who depend upon them.In an effort to better understand the issue,field observation was triangulated with in-depth interviews with local people,and the examination of scientific literature.To do this,the authors spent time in China with a translator in a key village known to be first in the area to truly succeed in carving the rice terraces and in making the mountain slope irrigation system required actually working.Results validated by experts in each field indicate that while the new seed and technologies do save water and improve lives,paired with migration,they may also be threatening the long-term viability of rice terracing in the region.The authors conclude that an integrated approach is needed and put forward a strategic blueprint to reinforce ecological,social and economic longevity.They also call for more research into the applicability of these resilience measures in other hybrid rice terracing regions,such as in the Philippines and Vietnam.展开更多
The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strate...The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strategies and prevent crop losses.Recent technological advancements highlight the opportunity to revolutionize monitoring of pests and diseases.Biosensing methodologies offer potential solutions for real-time and automated monitoring,which allow advancements in early and accurate detection and thus support sustainable crop protection.Herein,advanced biosensing technologies for pests and diseases monitoring,including image-based technologies,electronic noses,and wearable sensing methods are presented.Besides,challenges and future perspectives for widespread adoption of these technologies are discussed.Moreover,we believe it is necessary to integrate technologies through interdisciplinary cooperation for further exploration,which may provide unlimited possibilities for innovations and applications of agriculture monitoring.展开更多
This research paper assesses the reality of Climate-Smart Agriculture(CSA)practices’potential to promote the outcomes of sustainable food systems(SFS)within Ghana’s smallholding agriculture context.The study demon-s...This research paper assesses the reality of Climate-Smart Agriculture(CSA)practices’potential to promote the outcomes of sustainable food systems(SFS)within Ghana’s smallholding agriculture context.The study demon-strates that rural farmers generally perceive CSA’s contribution to‘food and nutrition security’and‘economic performance’as more important than CSA’s contribution to‘social equity’and‘environmental stewardship’.From a narrow perspective,the study demonstrates that farmers perceive CSA’s potential to‘prevent pest and disease outbreaks’and‘increase human capital information’as the most important contribution of CSA to SFS outcomes.In contrast,CSA’s potential to promote environmental stewardship is perceived as the least important among Ghana’s rural farmers.This enormity of displacement of smallholders’perceptions at large is motivated by de-mographic,socioeconomic and ecological factors.Moreso,the CSA for SFS outcomes narratives is driven by farmers’self-apprise,social networks and other local information dissemination agents.Furthermore,research findings suggest farmers’awareness of CSA practices and interventions is deficient owing to unmet training and information needs for approximately 82%of the CSA practices and interventions.This situation elucidates the dichotomy of CSA practices’narratives as tools for attaining food,nutrition security and economic performance to the detriment of critical issues such as increasing awareness and building farmers’capacity to engage with CSA practices while also managing socio-ecological trade-offs that emerge over time due to engagement with CSA.Critical(re)orientation is needed across the scale to drive CSA practices and interventions that confine cli-mate adaptation and food production practices within safe planetary boundaries without undermining social,economic,food and nutrition security needs.展开更多
Studies on mainstreaming climate-smart agriculture(CSA)practices can increase smallholder farmers’capacity and awareness to improve food security and establish sustainable livelihoods through resilient agricultural s...Studies on mainstreaming climate-smart agriculture(CSA)practices can increase smallholder farmers’capacity and awareness to improve food security and establish sustainable livelihoods through resilient agricultural systems,while achieving adaptation and mitigation benefits.Hence,valuable insights can be obtained from smallholder farmers in responding to present and forthcoming challenges of climate change impacts.However,there is little research work on trade-off and synergy assessments.Taking Geshy watershed in Southwest Ethiopia as a case study area,both quantitative and qualitative data analysis were undertaken in this study.The data were collected from 15 key informant interviews,6 focus group discussions,and 384 households to answer the following questions:(1)what are the top 5 preferred CSA practices for smallholder farmers in Geshy watershed when coping with the impacts of climate change?(2)What is the performance of the preferred CSA practices?And(3)which trade-offs and synergies are experienced upon the implementation of CSA practices?The study came up with the most preferred CSA practices such as the use of improved crop varieties,small-scale irrigation,improved animal husbandry,the use of efficient inorganic fertilizers,and crop rotation with legumes.The selected CSA practices showed that the productivity goal exhibit the best synergy,while the mitigation goal has trade-offs.The study also indicated that the use of improved crop varieties causes high synergies in all 3 goals of CSA practices;small-scale irrigation provides a medium synergy on productivity goal but high synergy for adaptation and mitigation goals;improved animal husbandry shows a high synergy with the adaptation goal,a relatively lower synergy with the productivity goal,and a trade-off with the mitigation goal;the use of efficient inorganic fertilizers shows maximum synergy for the productivity and adaptation goals;and crop rotation with legumes exhibits high synergy with the productivity and mitigation goals but a relatively lower synergy with the adaptation goal.These results can provide evidence to various stakeholder farmers in the value chain that the impacts of climate change can be addressed by the adoption of CSA practices.In general,CSA practices are considered indispensable.Smallholder farmers prefer CSA practices that help to increase crop productivity and household resilience to climate change impacts.The results generate a vital foundation for recommendations to smallholder farming decision-makers.It also sensitizes actions for innovative and sustainable methods that are able to upscale the preferred CSA practices in the agricultural system in Geshy watershed of Southwest Ethiopia and other regions.展开更多
Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agric...Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.展开更多
Food and Agriculture Organization(FAO)is appealing for a global implementation of urban agricultural strate-gies to increase food availability.Bandung,a city in Indonesia,is already participating in this initiative.Th...Food and Agriculture Organization(FAO)is appealing for a global implementation of urban agricultural strate-gies to increase food availability.Bandung,a city in Indonesia,is already participating in this initiative.This research aimed to assess the contribution of urban agriculture toward household food fulfillment and income.Furthermore,the impacts on urban,subsistence,semi-commercial,and commercial agriculture were considered.In-depth interviews to obtain qualitative data and observations were also utilized.A survey of 321 households,consisting of 107 for each urban agricultural type,used questionnaires to obtain quantitative data.These inputs were further analyzed to determine the contribution of household food fulfillment and income.The results showed that average urban agriculture has an insignificant and significant contribution of 9%and 41.5%to household food fulfillment and income.This was due to the vast complexities of metropolitan problems,including limited access to land,lack of participation,dependence on on-market products,and increasing commercialization which opposed urban agricultural policies。展开更多
Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield.Precision agriculture offers a novel solution utilizing a systematic technique for current...Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield.Precision agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental concerns.Weed control has become one of the significant problems in the agricultural sector.In traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same way.For more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed type.This may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable agriculture.This study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision Agriculture.The HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision agriculture.For image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise removal.In addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature vectors.To detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection performance.The experimental results of the HHOGCN-WD technique are investigated under the benchmark dataset.The results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.展开更多
文摘Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAASS).
文摘Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAASS).JIA is a peer-reviewed and multi-disciplinary international journal and published monthly in English.JIA Editorial Board consists of 289 well-respected scholars of agricultural scientific fields.
文摘Ploughing and fertilization practices in rice-wheat system have deteriorated the soil carbon (C) pools. Conservation agriculture (CA) based management approaches have proven to enhance C sequestration and reverse the loss of soil-organic-carbon (SOC), which further enhances soil fertility. Different fractions of SOC pools react to the alterations in management practices and indicate changes in SOC dynamics as compared to total C in the soil. Higher SOC levels in soil have been observed in case of reduced/no-till (NT) practices than conventional tillage (CT). However, between CT and zero tillage/NT, total SOC stocks diminished with an increase in soil depth, which demonstrated that the benefits of SOC are more pronounced in the topsoil under NT. Soil aggregation provides physical protection to C associated with different-sized particles, thus, the improvement in soil aggregation through CA is an effective way to mitigate soil C loss. Along with less soil disturbance, residual management, suitable crop rotation, rational application of manures and fertilizers, and integrated nutrient management have been found to be effective in not only improving soil C stock but also enhancing the soil health and productivity. Thus, CA can be considered as a potential method in the build-up of SOC of soil in rice-wheat system.
文摘Food security and sustainable development is making a mandatory move in the entire human race.The attainment of this goal requires man to strive for a highly advanced state in thefield of agriculture so that he can produce crops with a minimum amount of water and fertilizer.Even though our agricultural methodol-ogies have undergone a series of metamorphoses in the process of a present smart-agricultural system,a long way is ahead to attain a system that is precise and accurate for the optimum yield and profitability.Towards such a futuristic method of cultivation,this paper proposes a novel method for monitoring the efficientflow of a small quantity of water through the conventional irrigation system in cultiva-tion using Clustered Wireless Sensor Networks(CWSN).The performance measure is simulated the creation of edge-fixed geodetic clusters using Mat lab’s Cup-carbon tool in order to evaluate the suggested irrigation process model’s performance.Thefindings of blocks 1 and 2 are assessed.Each signal takes just a little amount of energy to communicate,according to the performance.It is feasible to save energy while maintaining uninterrupted communication between nodes and cluster chiefs.However,the need for proper placement of a dynamic control station in WSN still exists for maintaining connectivity and for improving the lifetime fault tolerance of WSN.Based on the minimum edgefixed geodetic sets of the connected graph,this paper offers an innovative method for optimizing the placement of control stations.The edge-fixed geodetic cluster makes the network fast,efficient and reliable.Moreover,it also solves routing and congestion problems.
文摘The research objective of this review is to discuss the rationale that led to the development of Controlled Environment Agriculture (CEA) and investigate this agricultural approach as a potential solution to mitigate the increased pressures on food security. It describes the need for urban cultivation systems using controlled environments and how they can be harnessed to address pressures facing food security. The factors that have contributed to the growth of CEAs, education, environmental justice, and the advantages and disadvantages of growing crops in CEAs in urban areas will be discussed. The article reviews global urban cultivation systems using controlled environments, by identifying the technologies needed to establish them. The practice of CEA is being increasingly adopted worldwide and we describe urban agriculture and compare it with traditional growing systems. Indoor farming systems that integrate into existing urban infrastructure such as vertical farming and plant factories using CEAs are discussed. Indoor farming gives urban areas enhanced access to food sources, but the cost is high, however decreasing due to recent technological advances. The current review extends the literature by incorporating recent research on the topic of agriculture in urban areas and food security. This review seeks to provide additional information regarding the viability of CEA in urban areas.
文摘Precision Agriculture(PA)has been used in many countries and serving the agricultural sectors.The use of PA solutions intervened with many agricultural businesses and supported decision making using data analytics.Precision Agriculture depends on weather,soil,plants,and water information that are essential for farming.Precision Agriculture depends on the use of several technologies such as image sensors,vision machines,drones,robots,machine learning,and artificial intelligence.The use of Precision Agriculture Technologies(PAT)depends on integration between devices,sensors,and systems to ensure the proper implementation of activities.This paper is generated from research on the applicability of PA in in Egypt that ended with a proposed framework for proper implementation of it.The conducted research depended on a survey,focus group discussions,and an online questionnaire that reached 271 respondents from 19 Egyptian governorates.The framework has been developed to enhance the role of an initiative leader to promote PAT through collaboration with other stakeholders in the agricultural sector.The proposed framework can be used by governmental,non-governmental entities,universities and private sector institutions and could be used at countries facing issues with land fragmentation,limited access to information,limited access to agricultural extension services,and increase in agricultural input’s prices.
文摘Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)approaches.Weed plays a vital role in influencing crop productivity.The wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are increased.Since the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity,this study presents a novel computer vision and deep learning based weed detection and classification(CVDL-WDC)model for precision agriculture.The proposed CVDL-WDC technique intends to prop-erly discriminate the plants as well as weeds.The proposed CVDL-WDC technique involves two processes namely multiscale Faster RCNN based object detection and optimal extreme learning machine(ELM)based weed classification.The parameters of the ELM model are optimally adjusted by the use of farmland fertility optimization(FFO)algorithm.A comprehensive simulation analysis of the CVDL-WDC technique against benchmark dataset reported the enhanced out-comes over its recent approaches interms of several measures.
基金based on work carried out under the H2020 DEMETER project (Grant Agreement No 857202)that is funded by the European Commission under H2020-EU.2.1.1 (DT-ICT-08-2019).
文摘The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.DEMETER(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food chain.This paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER lifecycle.This paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.
文摘Instruction to Authors Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.
文摘Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASc),founded in 2002,is sponsoredby Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JiA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.JIA publishes manuscripts in the categories of Commentary,Review,Research Article,Letter and'Short Communication,focusing on the core subjects:Crop Science Horticulture·Plant Protection·Animal Science·Veterinary Medicine·Agro-ecosystem&Environment:Food Science·Agricultural Economics and Management·Agricultural Information Science.
文摘Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAAsS).The latest IF is 4.8.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.JIA publishes manuscripts in the categories of Commentary,Review,Research Article,Letter and Short Communication,focusing on the core subjects:Crop Science.Horticulture·Plant Protection·Animal Science·Veterinary Medicine·Agro-ecosystem&Environment·Food Science·Agriculturai Economics and Management·Agricultural Information Science.
文摘Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(As),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAAsS).
基金funded by the Researchers Supporting Project Number(RSP2023R 509),King Saud University,Riyadh,Saudi Arabia.
文摘The overgrowth of weeds growing along with the primary crop in the fields reduces crop production.Conventional solutions like hand weeding are labor-intensive,costly,and time-consuming;farmers have used herbicides.The application of herbicide is effective but causes environmental and health concerns.Hence,Precision Agriculture(PA)suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary plants.Motivated by the gap above,we proposed a Deep Learning(DL)based model for detecting Eggplant(Brinjal)weed in this paper.The key objective of this study is to detect plant and non-plant(weed)parts from crop images.With the help of object detection,the precise location of weeds from images can be achieved.The dataset is collected manually from a private farm in Gandhinagar,Gujarat,India.The combined approach of classification and object detection is applied in the proposed model.The Convolutional Neural Network(CNN)model is used to classify weed and non-weed images;further DL models are applied for object detection.We have compared DL models based on accuracy,memory usage,and Intersection over Union(IoU).ResNet-18,YOLOv3,CenterNet,and Faster RCNN are used in the proposed work.CenterNet outperforms all other models in terms of accuracy,i.e.,88%.Compared to other models,YOLOv3 is the least memory-intensive,utilizing 4.78 GB to evaluate the data.
文摘The Honghe Hani Rice Terraces of Yunnan Province have become a national emblem for China and a UNESCO World Heritage Site,but some are beginning to crumble.This research attempts to address why this is happening and what can be done about it.Previous work has failed to adequately address the possible shortcomings of recently introduced seed and water management technologies,their particular effect on rice terraces and the people who depend upon them.In an effort to better understand the issue,field observation was triangulated with in-depth interviews with local people,and the examination of scientific literature.To do this,the authors spent time in China with a translator in a key village known to be first in the area to truly succeed in carving the rice terraces and in making the mountain slope irrigation system required actually working.Results validated by experts in each field indicate that while the new seed and technologies do save water and improve lives,paired with migration,they may also be threatening the long-term viability of rice terracing in the region.The authors conclude that an integrated approach is needed and put forward a strategic blueprint to reinforce ecological,social and economic longevity.They also call for more research into the applicability of these resilience measures in other hybrid rice terracing regions,such as in the Philippines and Vietnam.
基金supported by National Key Research and Development Program of China(Grant No.2022YFC2602100)Chinese Academy of Inspection and Quarantine(2022JK38).
文摘The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strategies and prevent crop losses.Recent technological advancements highlight the opportunity to revolutionize monitoring of pests and diseases.Biosensing methodologies offer potential solutions for real-time and automated monitoring,which allow advancements in early and accurate detection and thus support sustainable crop protection.Herein,advanced biosensing technologies for pests and diseases monitoring,including image-based technologies,electronic noses,and wearable sensing methods are presented.Besides,challenges and future perspectives for widespread adoption of these technologies are discussed.Moreover,we believe it is necessary to integrate technologies through interdisciplinary cooperation for further exploration,which may provide unlimited possibilities for innovations and applications of agriculture monitoring.
基金PTQ receives funding from the Canada First Research Excellence Fund(Grant No.499077)and the Canada Research Chairs Program.
文摘This research paper assesses the reality of Climate-Smart Agriculture(CSA)practices’potential to promote the outcomes of sustainable food systems(SFS)within Ghana’s smallholding agriculture context.The study demon-strates that rural farmers generally perceive CSA’s contribution to‘food and nutrition security’and‘economic performance’as more important than CSA’s contribution to‘social equity’and‘environmental stewardship’.From a narrow perspective,the study demonstrates that farmers perceive CSA’s potential to‘prevent pest and disease outbreaks’and‘increase human capital information’as the most important contribution of CSA to SFS outcomes.In contrast,CSA’s potential to promote environmental stewardship is perceived as the least important among Ghana’s rural farmers.This enormity of displacement of smallholders’perceptions at large is motivated by de-mographic,socioeconomic and ecological factors.Moreso,the CSA for SFS outcomes narratives is driven by farmers’self-apprise,social networks and other local information dissemination agents.Furthermore,research findings suggest farmers’awareness of CSA practices and interventions is deficient owing to unmet training and information needs for approximately 82%of the CSA practices and interventions.This situation elucidates the dichotomy of CSA practices’narratives as tools for attaining food,nutrition security and economic performance to the detriment of critical issues such as increasing awareness and building farmers’capacity to engage with CSA practices while also managing socio-ecological trade-offs that emerge over time due to engagement with CSA.Critical(re)orientation is needed across the scale to drive CSA practices and interventions that confine cli-mate adaptation and food production practices within safe planetary boundaries without undermining social,economic,food and nutrition security needs.
文摘Studies on mainstreaming climate-smart agriculture(CSA)practices can increase smallholder farmers’capacity and awareness to improve food security and establish sustainable livelihoods through resilient agricultural systems,while achieving adaptation and mitigation benefits.Hence,valuable insights can be obtained from smallholder farmers in responding to present and forthcoming challenges of climate change impacts.However,there is little research work on trade-off and synergy assessments.Taking Geshy watershed in Southwest Ethiopia as a case study area,both quantitative and qualitative data analysis were undertaken in this study.The data were collected from 15 key informant interviews,6 focus group discussions,and 384 households to answer the following questions:(1)what are the top 5 preferred CSA practices for smallholder farmers in Geshy watershed when coping with the impacts of climate change?(2)What is the performance of the preferred CSA practices?And(3)which trade-offs and synergies are experienced upon the implementation of CSA practices?The study came up with the most preferred CSA practices such as the use of improved crop varieties,small-scale irrigation,improved animal husbandry,the use of efficient inorganic fertilizers,and crop rotation with legumes.The selected CSA practices showed that the productivity goal exhibit the best synergy,while the mitigation goal has trade-offs.The study also indicated that the use of improved crop varieties causes high synergies in all 3 goals of CSA practices;small-scale irrigation provides a medium synergy on productivity goal but high synergy for adaptation and mitigation goals;improved animal husbandry shows a high synergy with the adaptation goal,a relatively lower synergy with the productivity goal,and a trade-off with the mitigation goal;the use of efficient inorganic fertilizers shows maximum synergy for the productivity and adaptation goals;and crop rotation with legumes exhibits high synergy with the productivity and mitigation goals but a relatively lower synergy with the adaptation goal.These results can provide evidence to various stakeholder farmers in the value chain that the impacts of climate change can be addressed by the adoption of CSA practices.In general,CSA practices are considered indispensable.Smallholder farmers prefer CSA practices that help to increase crop productivity and household resilience to climate change impacts.The results generate a vital foundation for recommendations to smallholder farming decision-makers.It also sensitizes actions for innovative and sustainable methods that are able to upscale the preferred CSA practices in the agricultural system in Geshy watershed of Southwest Ethiopia and other regions.
基金The APC was funded by Universidad Tecnológica Indoamérica with funding code INV-0012-002.
文摘Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.
基金This study was funded by an internal grant for the Aca-demic Leadership Grant of Universitas Padjadjaran awards numbers 1427/UN6.3.1/LT/2020 and 1959/UN6.3.1/PT.00/2021.
文摘Food and Agriculture Organization(FAO)is appealing for a global implementation of urban agricultural strate-gies to increase food availability.Bandung,a city in Indonesia,is already participating in this initiative.This research aimed to assess the contribution of urban agriculture toward household food fulfillment and income.Furthermore,the impacts on urban,subsistence,semi-commercial,and commercial agriculture were considered.In-depth interviews to obtain qualitative data and observations were also utilized.A survey of 321 households,consisting of 107 for each urban agricultural type,used questionnaires to obtain quantitative data.These inputs were further analyzed to determine the contribution of household food fulfillment and income.The results showed that average urban agriculture has an insignificant and significant contribution of 9%and 41.5%to household food fulfillment and income.This was due to the vast complexities of metropolitan problems,including limited access to land,lack of participation,dependence on on-market products,and increasing commercialization which opposed urban agricultural policies。
基金This research was partly supported by the Technology Development Program of MSS[No.S3033853]by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2020R1I1A3069700).
文摘Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield.Precision agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental concerns.Weed control has become one of the significant problems in the agricultural sector.In traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same way.For more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed type.This may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable agriculture.This study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision Agriculture.The HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision agriculture.For image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise removal.In addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature vectors.To detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection performance.The experimental results of the HHOGCN-WD technique are investigated under the benchmark dataset.The results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.
