The amount of time and effort required to access and integrate Subsurface data from multiple sources is significant. Using Advanced Data Analytics, mainly python, an integrated subsurface dashboard titled Hybrid Integrated Visualization Environment (HIVE) was created using Spotfire to empower the integrated Exploration, Development and Well Reservoir and Facilities Management (WRFM) subsurface teams in: Professionalizing data and knowledge management to have "one" version of the truth. Data consolidation and preparation to avoid repetitive manual work & Enhancing opportunity identification to optimize production and value The approach of subsurface data integration can be broken down into 4 major steps, namely: Step 1: Python programming was used to pre-process, restructure and create unified data frames. Use of python significantly reduces the time required to pre-process a diverse number of subsurface data sources consisting of static, dynamic reservoir models, log data, historical production & pressure data and wells & completion data to name a few. Step 2: - Standard diagnostic industry recognized diagnostic plots were automated using advanced analytic techniques in HIVE with the help of unified data frames. Step 3: HIVE was created to link various internal corporate data stores like pressure, temperature, rate data from PI System (stores real time measured data), Energy Components (EC) and Oil Field Manager (OFM) in real time. This was done to ensure that data from various petroleum engineering disciplines could now be visualized and analyzed in a structured manner to make integrated business decisions. Step 4: One of the key objectives of pursuing this initiative was to ensure that subsurface professionals in Shell Trinidad and Tobago were trained and upskilled in the use of python as well visualization tools like Spotfire and Power BI to ensure the maintenance and improvement of HIVE going forward. The development of HIVE has made it easier and more efficient to access and visualize subsurface data, which was extremely time consuming earlier while using older conventional techniques. Standard diagnostic plots and visuals were developed and are now used to drive integrated decision making, with key focus being water and sand production management from a production management perspective. Consequently, HIVE also drives enhanced integration between disciplines (Petrophysics, Petroleum Geology, Production Technology, Reservoir Engineering and Production operations) and departments (Developments, Upstream and Exploration). The petroleum industry has started to embrace the application of advanced data analytics in our day-to-day work. A successful application of these techniques results in transforming the ways of working by increasing efficiency, transparency and integration among teams.
{"title":"Application of Advanced Data Analytics for Gas Reservoirs and Wells Management","authors":"A. Srinivasan, Gaurav Modi, R. Agrawal, V. Kumar","doi":"10.2118/200927-ms","DOIUrl":"https://doi.org/10.2118/200927-ms","url":null,"abstract":"\u0000 \u0000 \u0000 The amount of time and effort required to access and integrate Subsurface data from multiple sources is significant. Using Advanced Data Analytics, mainly python, an integrated subsurface dashboard titled Hybrid Integrated Visualization Environment (HIVE) was created using Spotfire to empower the integrated Exploration, Development and Well Reservoir and Facilities Management (WRFM) subsurface teams in:\u0000 Professionalizing data and knowledge management to have \"one\" version of the truth. Data consolidation and preparation to avoid repetitive manual work & Enhancing opportunity identification to optimize production and value\u0000 \u0000 \u0000 \u0000 The approach of subsurface data integration can be broken down into 4 major steps, namely:\u0000 Step 1: Python programming was used to pre-process, restructure and create unified data frames. Use of python significantly reduces the time required to pre-process a diverse number of subsurface data sources consisting of static, dynamic reservoir models, log data, historical production & pressure data and wells & completion data to name a few. Step 2: - Standard diagnostic industry recognized diagnostic plots were automated using advanced analytic techniques in HIVE with the help of unified data frames. Step 3: HIVE was created to link various internal corporate data stores like pressure, temperature, rate data from PI System (stores real time measured data), Energy Components (EC) and Oil Field Manager (OFM) in real time. This was done to ensure that data from various petroleum engineering disciplines could now be visualized and analyzed in a structured manner to make integrated business decisions. Step 4: One of the key objectives of pursuing this initiative was to ensure that subsurface professionals in Shell Trinidad and Tobago were trained and upskilled in the use of python as well visualization tools like Spotfire and Power BI to ensure the maintenance and improvement of HIVE going forward.\u0000 \u0000 \u0000 \u0000 The development of HIVE has made it easier and more efficient to access and visualize subsurface data, which was extremely time consuming earlier while using older conventional techniques. Standard diagnostic plots and visuals were developed and are now used to drive integrated decision making, with key focus being water and sand production management from a production management perspective. Consequently, HIVE also drives enhanced integration between disciplines (Petrophysics, Petroleum Geology, Production Technology, Reservoir Engineering and Production operations) and departments (Developments, Upstream and Exploration).\u0000 \u0000 \u0000 \u0000 The petroleum industry has started to embrace the application of advanced data analytics in our day-to-day work. A successful application of these techniques results in transforming the ways of working by increasing efficiency, transparency and integration among teams.\u0000","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79652793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mukhtar Elturki, P. McElroy, Dianfeng Li, Ahmed Kablan, Hasan Shaglouf
Production from unconventional reservoirs using hydraulic fractured wells has recently gained much attention due to its ability to increase recovery to high percentages. The placement of proppant in fractures plays a significant role in conductivity of fractures and well productivity. Here, we aimed to elucidate some basic concepts of the technique using FracPro simulator. FracPro and hydraulic fracturing consist of many design parameters that effect the results of the stimulation process. Of the many parameters that exist, three were focused on in this paper: proppant transport, the use of carbon dioxide (CO2) foam fracturing fluid, and the use of low specific weight versus higher specific weight. FracPro was also used to simulate the results of using a low specific gravity value of 1.9, a medium value of 2.7, and a high value of 3.5. The concentration of CO2 was also varied in each condition; concentrations of 30, 50, and 70% were used. After running investigating these scenarios, some unexpected results were obtained. Notably, a lower specific gravity should produce a longer effective proppant length; however, our data indicates shows the opposite.
{"title":"Simulation Study Investigating the Impact of Carbon Dioxide Foam Fracturing Fluids on Proppant Transport","authors":"Mukhtar Elturki, P. McElroy, Dianfeng Li, Ahmed Kablan, Hasan Shaglouf","doi":"10.2118/200950-ms","DOIUrl":"https://doi.org/10.2118/200950-ms","url":null,"abstract":"\u0000 Production from unconventional reservoirs using hydraulic fractured wells has recently gained much attention due to its ability to increase recovery to high percentages. The placement of proppant in fractures plays a significant role in conductivity of fractures and well productivity. Here, we aimed to elucidate some basic concepts of the technique using FracPro simulator. FracPro and hydraulic fracturing consist of many design parameters that effect the results of the stimulation process. Of the many parameters that exist, three were focused on in this paper: proppant transport, the use of carbon dioxide (CO2) foam fracturing fluid, and the use of low specific weight versus higher specific weight. FracPro was also used to simulate the results of using a low specific gravity value of 1.9, a medium value of 2.7, and a high value of 3.5. The concentration of CO2 was also varied in each condition; concentrations of 30, 50, and 70% were used. After running investigating these scenarios, some unexpected results were obtained. Notably, a lower specific gravity should produce a longer effective proppant length; however, our data indicates shows the opposite.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86902234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
U. Aslam, Luis Hernando Perez Cardenas, Andrey Klimushin
The Internet of Things has popularized the notion of a digital twin - a virtual representation of a physical system. There are substantial risks associated with designing a development plan for an oilfield and the industry has been making use of reservoir models - digital twins - to improve the decision-making process for many years. With an increase in the availability of computational resources, the industry is moving towards ensemble-based workflows to estimate risk in field development plans. In this paper, we demonstrate the use of an integrated ensemble-based approach to assess uncertainties in the reservoir models and quantify their impact on the decision-making process. An important feature of a digital twin is its ability to use sensor data to update the virtual model, more commonly known as history matching or data assimilation. We demonstrate how production data can be used to identify and constrain the uncertainties in the reservoir model. Production data is incorporated using Bayesian statistics and state-of-the-art supervised machine learning techniques to create an ensemble of models that capture the range of uncertainties in the reservoir model. This ensemble of calibrated models with an improved predictive ability provides a realistic assessment of the uncertainty associated with production forecasts. The ensemble-based approach is demonstrated through its application on an offshore oilfield located in the North Sea. The field is highly compartmentalized and has high structural uncertainty following the interpretation and depth conversion. An integrated cross-domain model is set up to incorporate typically ignored structural uncertainty in addition to the uncertainties and their dependencies in the dynamic parameters, including fault transmissibility, pore-volume, fluid contacts, saturation, and relative permeability endpoints, etc. Results from the history matched ensemble of models show a significa nt reduction in uncertainty in these parameters and the predicted production. An advantage of the proposed technique is that the automated, repeatable, and auditable ensemble-based workflow can assimilate the newly acquired measured data into the reservoir model at any time, keeping the model up-to-date and evergreen.
{"title":"Application of an Integrated Ensemble-Based History Matching Approach - An Offshore Field Case Study","authors":"U. Aslam, Luis Hernando Perez Cardenas, Andrey Klimushin","doi":"10.2118/200908-ms","DOIUrl":"https://doi.org/10.2118/200908-ms","url":null,"abstract":"\u0000 The Internet of Things has popularized the notion of a digital twin - a virtual representation of a physical system. There are substantial risks associated with designing a development plan for an oilfield and the industry has been making use of reservoir models - digital twins - to improve the decision-making process for many years. With an increase in the availability of computational resources, the industry is moving towards ensemble-based workflows to estimate risk in field development plans. In this paper, we demonstrate the use of an integrated ensemble-based approach to assess uncertainties in the reservoir models and quantify their impact on the decision-making process.\u0000 An important feature of a digital twin is its ability to use sensor data to update the virtual model, more commonly known as history matching or data assimilation. We demonstrate how production data can be used to identify and constrain the uncertainties in the reservoir model. Production data is incorporated using Bayesian statistics and state-of-the-art supervised machine learning techniques to create an ensemble of models that capture the range of uncertainties in the reservoir model. This ensemble of calibrated models with an improved predictive ability provides a realistic assessment of the uncertainty associated with production forecasts.\u0000 The ensemble-based approach is demonstrated through its application on an offshore oilfield located in the North Sea. The field is highly compartmentalized and has high structural uncertainty following the interpretation and depth conversion. An integrated cross-domain model is set up to incorporate typically ignored structural uncertainty in addition to the uncertainties and their dependencies in the dynamic parameters, including fault transmissibility, pore-volume, fluid contacts, saturation, and relative permeability endpoints, etc. Results from the history matched ensemble of models show a significa nt reduction in uncertainty in these parameters and the predicted production.\u0000 An advantage of the proposed technique is that the automated, repeatable, and auditable ensemble-based workflow can assimilate the newly acquired measured data into the reservoir model at any time, keeping the model up-to-date and evergreen.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88356177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-22DOI: 10.36548/jaicn.2021.2.005
J SamuelManoharan
Herbal plants are crucial to human existence for medical reasons, and they can also provide free oxygen to the environment. Many herbal plants are rich in therapeutic goods and also it includes the active elements that will benefit future generations. Many valuable plant species are being extinguished and destroyed as a result of factors such as global warming, population growth, occupational secrecy, a lack of government support for research, and a lack of knowledge about therapeutic plants. Due to the lag of dimensional factors such as length and width, many existing algorithms fail to recognize herbal leaf in all seasons with the maximum accuracy. Henceforth, the proposed algorithm focuses on the incomplete problems in the datasets in order to improve the detection rate for herbal leaf identification. The inclusions of dimension factors in the datasets are performing good results in the image segmentation process. The obtained result has been validated with a machine learning classifier when combined with ex-or gate operation is called deep knowledge-based identification. This two-stage authentication (TSA) procedure is improving the recognition rate required for the detection of herbal leaf. This fusion of image segmentation with machine learning is providing good robustness for the proposed architecture. Besides, intelligent selection of image segmentation techniques to segment the leaf from the image is improving the detection accuracy. This procedure is addressing and answering the drawbacks associated with the detection of the herbal leaf by using many Machine Learning (ML) approaches. Also, it improves the rate of detection and minimizes the classification error. From the results, it is evident that the proposed method has obtained better accuracy and other performance measures.
{"title":"Flawless Detection of Herbal Plant Leaf by Machine Learning Classifier Through Two Stage Authentication Procedure","authors":"J SamuelManoharan","doi":"10.36548/jaicn.2021.2.005","DOIUrl":"https://doi.org/10.36548/jaicn.2021.2.005","url":null,"abstract":"Herbal plants are crucial to human existence for medical reasons, and they can also provide free oxygen to the environment. Many herbal plants are rich in therapeutic goods and also it includes the active elements that will benefit future generations. Many valuable plant species are being extinguished and destroyed as a result of factors such as global warming, population growth, occupational secrecy, a lack of government support for research, and a lack of knowledge about therapeutic plants. Due to the lag of dimensional factors such as length and width, many existing algorithms fail to recognize herbal leaf in all seasons with the maximum accuracy. Henceforth, the proposed algorithm focuses on the incomplete problems in the datasets in order to improve the detection rate for herbal leaf identification. The inclusions of dimension factors in the datasets are performing good results in the image segmentation process. The obtained result has been validated with a machine learning classifier when combined with ex-or gate operation is called deep knowledge-based identification. This two-stage authentication (TSA) procedure is improving the recognition rate required for the detection of herbal leaf. This fusion of image segmentation with machine learning is providing good robustness for the proposed architecture. Besides, intelligent selection of image segmentation techniques to segment the leaf from the image is improving the detection accuracy. This procedure is addressing and answering the drawbacks associated with the detection of the herbal leaf by using many Machine Learning (ML) approaches. Also, it improves the rate of detection and minimizes the classification error. From the results, it is evident that the proposed method has obtained better accuracy and other performance measures.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91540325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-21DOI: 10.36548/jaicn.2021.2.002
S. S, Haoxiang Wang
The concept of interconnecting smart vehicles and advancements in automotive automation leads to beneficial outcomes, such as a reduction in road fatalities and congestion. However, including a chain of automation in the attack surface will expand the attack surface and expose the security of automobiles to malicious infiltration. The proposed methodology provides access to specific users while restricting the third party requests. Moreover, it also makes use of data exchange that takes place between the roadside units and vehicle to track the vehicle status without compromising the in-vehicle network. To ensure a valid and authentic communication, vehicles with a proper and verifiable record will only be allowed to exchange messages in the blockchain network. Using qualitative arguments, we have identified that the proposed work is resilient to identified attacks. Similarly, quantitative experimentation indicates that this methodology shows a storage size compatibility and suitable response time in realistic scenarios. Simulation results indicate that, the proposed work shows positive results to secure vehicular networks, vehicular forensics and trust management.
{"title":"Security Enhancement in Smart Vehicle Using Blockchain-based Architectural Framework","authors":"S. S, Haoxiang Wang","doi":"10.36548/jaicn.2021.2.002","DOIUrl":"https://doi.org/10.36548/jaicn.2021.2.002","url":null,"abstract":"The concept of interconnecting smart vehicles and advancements in automotive automation leads to beneficial outcomes, such as a reduction in road fatalities and congestion. However, including a chain of automation in the attack surface will expand the attack surface and expose the security of automobiles to malicious infiltration. The proposed methodology provides access to specific users while restricting the third party requests. Moreover, it also makes use of data exchange that takes place between the roadside units and vehicle to track the vehicle status without compromising the in-vehicle network. To ensure a valid and authentic communication, vehicles with a proper and verifiable record will only be allowed to exchange messages in the blockchain network. Using qualitative arguments, we have identified that the proposed work is resilient to identified attacks. Similarly, quantitative experimentation indicates that this methodology shows a storage size compatibility and suitable response time in realistic scenarios. Simulation results indicate that, the proposed work shows positive results to secure vehicular networks, vehicular forensics and trust management.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80188008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the years progress, our world is becoming more technologically advanced, and humanity will soon be technologically focused. Henceforth, some fundamental measures should be made by individuals in order to develop the advanced next generation technologies. In this perspective, the proposed research work has developed an Android application with a unit comprising of ESP8266 Wi-Fi module, relay, logic level converter module, capacitive touch sensor module and also a Wi-Fi technology has been used to control the switches.
{"title":"Internet of Things (IOT) Based Smart Switch","authors":"Sejal Bagde, Pratiksha Ambade, Manasvi Batho, Piyush Duragkar, Prathmesh Dahikar, Avinash Ikhar","doi":"10.36548/jismac.2021.2.007","DOIUrl":"https://doi.org/10.36548/jismac.2021.2.007","url":null,"abstract":"As the years progress, our world is becoming more technologically advanced, and humanity will soon be technologically focused. Henceforth, some fundamental measures should be made by individuals in order to develop the advanced next generation technologies. In this perspective, the proposed research work has developed an Android application with a unit comprising of ESP8266 Wi-Fi module, relay, logic level converter module, capacitive touch sensor module and also a Wi-Fi technology has been used to control the switches.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75304056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-14DOI: 10.36548/JITDW.2021.2.004
Gaurav V. Barmase, Gaurav V. Khopade, Shital P. Thawkar, Sahil P. Bawankule, Nikhil D. Gajbhiye, Shailesh Sakhare
The main aim of this project is to develop a Graphical User Interface (GUI) based system to monitor and control the industrial process. The proposed protocol os user-friendly and it is more efficient due to the incorporation of a simple GUI. Moreover, the proposed system is installed to collect the valuable information.
{"title":"GUI based Industrial Monitoring and Control System","authors":"Gaurav V. Barmase, Gaurav V. Khopade, Shital P. Thawkar, Sahil P. Bawankule, Nikhil D. Gajbhiye, Shailesh Sakhare","doi":"10.36548/JITDW.2021.2.004","DOIUrl":"https://doi.org/10.36548/JITDW.2021.2.004","url":null,"abstract":"The main aim of this project is to develop a Graphical User Interface (GUI) based system to monitor and control the industrial process. The proposed protocol os user-friendly and it is more efficient due to the incorporation of a simple GUI. Moreover, the proposed system is installed to collect the valuable information.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74194942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-10DOI: 10.21475/ajcs.21.15.06.p3017
L. Link, L. S. Pereira, V. V. Batista, K. F. Oligini, E. Pellizari, P. F. Adami, L. Sartor
This research studied a suitable cover crop considering biomass accumulation and nutrient cycling and its herbicide management to be adopted in the maize-wheat offseason as well as its influence on wheat yield. Experiment was laid out as a randomized block design in a factorial scheme with five cover crops (Fagopyrum esculentum, Crotalaria juncea, Pennisetum glaucum, Urochloa brizantha and Crotalaria spectabilis at 2017/18 growing season and at 2018/19, Fagopyrum esculentum and Crotalaria spectabilis were switched for Dolichos lablab) and two herbicide management (Desiccation 17 days before and at the wheat Sowing day) with four replications. Fallow was used as a control. Fagopyrum esculentum showed the fastest cycle and can be recommended for shorter offseason periods (50 days). Pennisetum glaucum showed the highest biomass yield at both years, standing out as the best option for offseason periods of 70 to 80 days. Tradeoff between the additional biomass produced by millet and brachiaria between herbicide desiccation periods does not cover the wheat grain yield reduction, suggesting that its herbicide management should be anticipated. On the other hand, Crotalarias showed a linear increase in biomass along the periods without wheat yield effects and its herbicide dissection at the wheat sowing day is recommended
{"title":"Cover crop management in the maize-wheat offseason","authors":"L. Link, L. S. Pereira, V. V. Batista, K. F. Oligini, E. Pellizari, P. F. Adami, L. Sartor","doi":"10.21475/ajcs.21.15.06.p3017","DOIUrl":"https://doi.org/10.21475/ajcs.21.15.06.p3017","url":null,"abstract":"This research studied a suitable cover crop considering biomass accumulation and nutrient cycling and its herbicide management to be adopted in the maize-wheat offseason as well as its influence on wheat yield. Experiment was laid out as a randomized block design in a factorial scheme with five cover crops (Fagopyrum esculentum, Crotalaria juncea, Pennisetum glaucum, Urochloa brizantha and Crotalaria spectabilis at 2017/18 growing season and at 2018/19, Fagopyrum esculentum and Crotalaria spectabilis were switched for Dolichos lablab) and two herbicide management (Desiccation 17 days before and at the wheat Sowing day) with four replications. Fallow was used as a control. Fagopyrum esculentum showed the fastest cycle and can be recommended for shorter offseason periods (50 days). Pennisetum glaucum showed the highest biomass yield at both years, standing out as the best option for offseason periods of 70 to 80 days. Tradeoff between the additional biomass produced by millet and brachiaria between herbicide desiccation periods does not cover the wheat grain yield reduction, suggesting that its herbicide management should be anticipated. On the other hand, Crotalarias showed a linear increase in biomass along the periods without wheat yield effects and its herbicide dissection at the wheat sowing day is recommended","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73006462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-10DOI: 10.21475/ajcs.21.15.06.p3177
Leonel Domingos Moiana, Pedro Soares Vidigal Filho, M. P. Maleia, Sudanailly Mufambira, J. João, Jaime Omar Teca, C. Domingos, C. Artur
The genetic diversity of species is an important way to maintain the natural capacity to respond to climate change and all stresses. This study aimed to estimate the general combining ability (GCA) and the specific combining ability (SCA) of the characteristics among 41 cotton cultivars and 9 inbred lines using circulant diallel. In 2016, 41 cultivars and 9 inbred lines and 75 hybrid combinations were evaluated at the Namialo Cotton Research and Seed and Multiplication Centre in the Meconta District, Nampula province. The experimental design was Federer's augmented blocks with four repetitions. The evaluated characteristics were: days for 50% of flowering (DAFlw), days for 50% of fruiting (DAFrut), plant height, average number of bolls (AnB), seed cotton yield in kilograms per hectare (Yield) and the mass of one hundred seeds (M100). The algorithm for establishing diallel crosses was based on Kempthorne and Curnow, where S was equal to 3. There was a predominance of non-additive effects for all characteristics analysed. The genotypes ALBAR FQ 902, IRMA 12-43 and MARICO showed greater additive effects for DAFlw, DAFrut, AnB, Yield and, M100
{"title":"General and specific combining ability of cotton germplasm in Mozambique using circulant dialells","authors":"Leonel Domingos Moiana, Pedro Soares Vidigal Filho, M. P. Maleia, Sudanailly Mufambira, J. João, Jaime Omar Teca, C. Domingos, C. Artur","doi":"10.21475/ajcs.21.15.06.p3177","DOIUrl":"https://doi.org/10.21475/ajcs.21.15.06.p3177","url":null,"abstract":"The genetic diversity of species is an important way to maintain the natural capacity to respond to climate change and all stresses. This study aimed to estimate the general combining ability (GCA) and the specific combining ability (SCA) of the characteristics among 41 cotton cultivars and 9 inbred lines using circulant diallel. In 2016, 41 cultivars and 9 inbred lines and 75 hybrid combinations were evaluated at the Namialo Cotton Research and Seed and Multiplication Centre in the Meconta District, Nampula province. The experimental design was Federer's augmented blocks with four repetitions. The evaluated characteristics were: days for 50% of flowering (DAFlw), days for 50% of fruiting (DAFrut), plant height, average number of bolls (AnB), seed cotton yield in kilograms per hectare (Yield) and the mass of one hundred seeds (M100). The algorithm for establishing diallel crosses was based on Kempthorne and Curnow, where S was equal to 3. There was a predominance of non-additive effects for all characteristics analysed. The genotypes ALBAR FQ 902, IRMA 12-43 and MARICO showed greater additive effects for DAFlw, DAFrut, AnB, Yield and, M100","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76799713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-10DOI: 10.21475/ajcs.21.15.06.p2857
CezÁrio F S JÚnior, Claudio T C Correoso, Marcos Copacheski, P. Boff, M. Boff
The substitution of landrace populations of beans (Phaseolus vulgaris L.) by commercial cultivars provided genetic uniformity and loss of rusticity. It makes the bean plants more vulnerable to pests, increasing the use of pesticides. The objective of this work was to evaluate the productivity and health of beans landraces compared to commercial cultivars, reducing the effect of high dynamic dilutions. The evaluated traits were grain yield (kg ha-1), thousand grain weight (g), and occurrence of anthracnose (Colletotrichum lindemuthianum) and bacteriosis (Xanthomonas sp.). Evaluation of high dynamic dilutions was also done in addition to the previous variables, was evaluated number of pods per plant and pods with the presence of anthracnose. The analysis of the data did not show any differences in the productivity and disease rate between the landraces and the commercial cultivars of beans. The high dynamic dilutions do not show any conclusive results in terms of productivity. However, all treatments were superior in phytosanitary management compared to control
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