The document discusses nitrogen management and utilization with cover crops. It promotes managing nitrogen as a system rather than individual applications to minimize environmental impact, optimize yield, and maximize nitrogen use. It introduces the Nitrogen Management System tool for inventorying, tracking, verifying, and applying the right source, rate, time, and place of nitrogen applications. The system involves periodic soil sampling and testing to monitor available nitrogen levels over the growing season.
Automating Management for a Vegetative Treatment System (VTS)LPE Learning Center
1) The document describes two automated vegetative treatment systems (VTS) built in Nebraska to treat livestock wastewater runoff.
2) The systems use soil moisture and water level sensors connected to a human-machine interface to monitor conditions in the VTS and alert producers when action is needed.
3) Preliminary findings show the more advanced monitoring system was effective but costly, while a lower-cost alternative provided less detailed real-time data for management decisions.
Jeremy Wilson - Return On Investment When Using Technology And DataJohn Blue
Return On Investment When Using Technology And Data - Jeremy Wilson, from the 2018 Conservation Tillage and Technology Conference, March 6 - 7, Ada, OH, USA.
More presentations at https://www.youtube.com/channel/UCZBwPfKdlk4SB63zZy16kyA
Simulating the sensitivity of maize crop propagation to seasonal weather chan...CTA
This study used the CROPWAT model to simulate the effects of temperature changes on maize crop yields in Ibadan, Nigeria. The results showed that rising temperatures had a negative effect on maize yields, though the reduction trends were not definite due to variability in temperatures. Yield reductions were low under definite interval irrigation and high without irrigation. Definite interval irrigation was determined to be the most effective strategy to minimize yield losses from temperature increases and weather variability.
1) The document is a summary of a webcast about using AgVeritas, a web-based yield analysis tool, to determine optimal input rates and test new products in different management zones within a field based on spatial analysis of yield data.
2) AgVeritas accounts for multiple factors that impact yield and identifies spatial effects not explained by known factors to provide more accurate analysis results.
3) An example analysis showed that seeding rates of 32K, 32K, and 35K were optimal in different yield zones within a field based on a seeding rate trial, and that compost provided benefits in some zones.
Increase Grower Profitability with More Accurate Yield Data Analysis - AgVeri...XSInc
This document summarizes an online presentation about the AgVeritas yield analysis tool. It was created by XSInc to help growers analyze multiple factors affecting yield variability and identify specific areas of fields where treatments would be most profitable. The tool uses advanced spatial statistics to examine all available data factors simultaneously for a single field, determining which factors best explain yield differences. This provides more confident conclusions than traditional approaches that look at only one or two factors at a time. The presentation provides an example analysis and invites growers to try a free data analysis using AgVeritas.
Improve insights by aggregating on farm trial dataXSInc
This webinar discussed how aggregating data from on-farm trials across multiple fields and farms can provide more robust conclusions about the performance of agricultural products and practices. It emphasized the importance of careful trial planning, standardization of data collection, and accounting for sources of noise to ensure quality data. Proper layout of trials and consideration of field characteristics was also highlighted. Tools like AgVeritas were presented as being able to analyze multiple factors simultaneously and determine their relative impacts on yield while controlling for spatial effects.
Maximizing the Value of On-Farm Research: An Industry Expert RoundtableXSInc
Precision Ag Insight Webcast featuring an expert panel answering questions on on-farm research best practices, common implementation pitfalls, and how to get the most out of the end of season analysis.
The document discusses nitrogen management and utilization with cover crops. It promotes managing nitrogen as a system rather than individual applications to minimize environmental impact, optimize yield, and maximize nitrogen use. It introduces the Nitrogen Management System tool for inventorying, tracking, verifying, and applying the right source, rate, time, and place of nitrogen applications. The system involves periodic soil sampling and testing to monitor available nitrogen levels over the growing season.
Automating Management for a Vegetative Treatment System (VTS)LPE Learning Center
1) The document describes two automated vegetative treatment systems (VTS) built in Nebraska to treat livestock wastewater runoff.
2) The systems use soil moisture and water level sensors connected to a human-machine interface to monitor conditions in the VTS and alert producers when action is needed.
3) Preliminary findings show the more advanced monitoring system was effective but costly, while a lower-cost alternative provided less detailed real-time data for management decisions.
Jeremy Wilson - Return On Investment When Using Technology And DataJohn Blue
Return On Investment When Using Technology And Data - Jeremy Wilson, from the 2018 Conservation Tillage and Technology Conference, March 6 - 7, Ada, OH, USA.
More presentations at https://www.youtube.com/channel/UCZBwPfKdlk4SB63zZy16kyA
Simulating the sensitivity of maize crop propagation to seasonal weather chan...CTA
This study used the CROPWAT model to simulate the effects of temperature changes on maize crop yields in Ibadan, Nigeria. The results showed that rising temperatures had a negative effect on maize yields, though the reduction trends were not definite due to variability in temperatures. Yield reductions were low under definite interval irrigation and high without irrigation. Definite interval irrigation was determined to be the most effective strategy to minimize yield losses from temperature increases and weather variability.
1) The document is a summary of a webcast about using AgVeritas, a web-based yield analysis tool, to determine optimal input rates and test new products in different management zones within a field based on spatial analysis of yield data.
2) AgVeritas accounts for multiple factors that impact yield and identifies spatial effects not explained by known factors to provide more accurate analysis results.
3) An example analysis showed that seeding rates of 32K, 32K, and 35K were optimal in different yield zones within a field based on a seeding rate trial, and that compost provided benefits in some zones.
Increase Grower Profitability with More Accurate Yield Data Analysis - AgVeri...XSInc
This document summarizes an online presentation about the AgVeritas yield analysis tool. It was created by XSInc to help growers analyze multiple factors affecting yield variability and identify specific areas of fields where treatments would be most profitable. The tool uses advanced spatial statistics to examine all available data factors simultaneously for a single field, determining which factors best explain yield differences. This provides more confident conclusions than traditional approaches that look at only one or two factors at a time. The presentation provides an example analysis and invites growers to try a free data analysis using AgVeritas.
Improve insights by aggregating on farm trial dataXSInc
This webinar discussed how aggregating data from on-farm trials across multiple fields and farms can provide more robust conclusions about the performance of agricultural products and practices. It emphasized the importance of careful trial planning, standardization of data collection, and accounting for sources of noise to ensure quality data. Proper layout of trials and consideration of field characteristics was also highlighted. Tools like AgVeritas were presented as being able to analyze multiple factors simultaneously and determine their relative impacts on yield while controlling for spatial effects.
Maximizing the Value of On-Farm Research: An Industry Expert RoundtableXSInc
Precision Ag Insight Webcast featuring an expert panel answering questions on on-farm research best practices, common implementation pitfalls, and how to get the most out of the end of season analysis.
Precision Ag Insight Webcast: Turn Your Yield Data into a Decision-Making ToolXSInc
In this Precision Ag Insight webcast, Dr. Chad Godsey presents best practices for turning your yield data into valuable insight for data-driven decision making.
The webcast covers tools and techniques for:
• Collecting high quality yield data
• Cleaning yield data
• Making management decisions with yield analysis
Este documento trata sobre la geometría del espacio. Explica que los elementos fundamentales son los puntos, las rectas y los planos. Define estos conceptos y describe cómo se determinan los planos a través de puntos y rectas. También cubre las posiciones relativas de rectas y planos, así como conceptos como ángulos entre rectas y planos, rectas perpendiculares a planos, y ángulos diedros y triedros.
This document summarizes Stephen Quandzie's MSc thesis on the potential to increase agricultural water productivity in Ghana's Black Volta Basin. The research questions whether agricultural water productivity can be increased, if increased dry season agriculture would help reduce poverty, and which agricultural water management intervention has the potential to improve livelihoods sustainably. The methodology involves using the CROPWAT and CLIMWAT models to analyze crop water consumption factors and physical, economic, and livestock water productivity. The results found that small reservoirs, shallow wells, and water pumps with reservoirs over-irrigated crops. Water pumps with reservoirs or river access were identified as having the best potential to enhance agricultural water management and promote off-farm skills development.
Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
Flood Prediction Model using Artificial Neural NetworkEditor IJCATR
This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN)
approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are
responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve
this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN’s Feed Forward (FF) and Back
Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our
simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts
the flood water level 24 hours ahead of time.
This document discusses using the CROPWAT and CLIMWAT models to evaluate and plan irrigation for cotton and rice crops in India. It summarizes that India currently produces lower rice yields than countries like China and Brazil from the same amount of land. Increasing yields through improved irrigation practices could increase production and reduce land usage. The document then outlines using the CROPWAT model to analyze reference evapotranspiration, crop water requirements, irrigation requirements, and develop irrigation schedules for cotton and rice in the Kurnool region of India based on climatic and soil data. It concludes that significantly increasing crop yields through using CROPWAT could boost the economy by improving farmer livelihoods and freeing up land.
There are 4 parks near the author's house that use different irrigation systems. DDA Park in Sector 11 uses sprinkler irrigation, which sprays water into the air to water the entire soil surface. DDA Park in Sector 6 uses drip irrigation, which applies water slowly at the base of plants. Rotary irrigation is used in DDA Park in Sector 10 and involves mechanically driven sprinklers that reach distances of up to 100 feet. The center-pivot system used in one park conserves water by using less than surface irrigation and reducing labor costs. Overextraction of groundwater has caused levels to drop by over 5 feet per year in some places.
This document discusses precision agriculture and provides an overview of key concepts:
1. Precision agriculture aims to optimize field management to match crop needs, protect the environment, and boost farm economics through efficient practices.
2. It involves characterizing field variability, making decisions based on soil maps and sensor data, and implementing variable-rate technology.
3. Current trends include high-accuracy GPS, input management like variable-rate fertilizer application, and information management tools to aid decision-making.
4. The document describes technologies like guidance systems, drones, wireless sensors, and yield mapping that are part of precision agriculture approaches.
This is the second presentation I was invited to give at the CAVI conference held in Galway, Ireland on October 12. it deals with precision dairy farming. A field that is coming up and growing in importance in modern dairy farming
Precision Agriculture; Past, present and futureNetNexusBrasil
This document provides an overview of the history and future of precision agriculture. It discusses early efforts using soil testing and yield monitors in the 1990s. Current technologies like crop canopy sensors that measure biomass and chlorophyll are highlighted. The document also reviews ongoing work optimizing in-season nitrogen management. International collaboration between USDA-ARS and Embrapa Brazil on precision agriculture research is summarized.
Applications of Artificial Neural Networks in Civil EngineeringPramey Zode
An artificial brain-like network based on certain mathematical algorithms developed using a numerical computing environment is called as an ‘Artificial Neural Network (ANN)’. Many civil engineering problems which need understanding of physical processes are found to be time consuming and inaccurate to evaluate using conventional approaches. In this regard, many ANNs have been seen as a reliable and practical alternative to solve such problems. Literature review reveals that ANNs have already being used in solving numerous civil engineering problems. This study explains some cases where ANNs have been used and its future scope is also discussed.
Precision agriculture is a farming system that uses information technology like GPS and GIS to increase farm production efficiency and profitability while minimizing environmental impacts. It involves tools like yield monitors, GPS, GIS software, and variable rate technology to collect and analyze field data to precisely vary inputs based on site-specific needs. Implementing precision agriculture can optimize production efficiency, quality, minimize risks and environmental impacts, and provide farmers with information to improve decision making.
This document summarizes four main irrigation methods: surface irrigation (flooding), sprinkler irrigation (applying water under pressure), drip or trickle irrigation (applying water slowly to the soil), and sub-surface irrigation (flooding water underground). Surface irrigation is the most widely used method, covering 90% of irrigated land. Sprinkler irrigation is ideal for scarce water areas. Drip irrigation conserves water, controls weeds, and applies water at a slow rate matching crop needs. Sub-surface irrigation is used where soil and topography allow watering underground.
This document provides an overview of irrigation engineering. It discusses the necessity of irrigation due to factors like insufficient rainfall and uneven distribution. It describes different types of irrigation systems including flow irrigation, lift irrigation, and storage irrigation. It also defines important terms used in irrigation like duty, delta, command area. The document outlines the benefits of irrigation such as increased crop yields and prosperity of farmers. It also notes some ill effects like raising water tables and creating breeding grounds for mosquitoes. Overall, the document provides a broad introduction to key concepts in irrigation engineering.
Increase yields and reduce costs with variable rate plantingXSInc
This document summarizes a webinar about using variable rate planting to increase yields and reduce costs. It finds that most growers are just starting to use variable seeding technology. The webinar discusses developing management zones using soil data and yield maps, understanding hybrid performance data, and evaluating the effectiveness of variable rate planting recommendations. Growers' biggest challenges are evaluating variable rate planting results and establishing effective management zones.
Reducing rural poverty and improving household nutrition are common goals across all developing countries in the
Asia and Pacific region. To this end, the region has experienced a recent resurgence in large investments in irrigation
infrastructure. This surge in funding flows has created pressure from donors and central financing agencies, both of
which are increasingly demanding more robust justification for the investments. To date, providing this justification for
irrigation investments has been challenging due to a lack of reliable longitudinal data that measure the performance of
irrigated agriculture and associated water delivery services. Consequently, there is very little information on the real
returns on investments already made. Historic data has tended to be project based, point-in-time data constrained to a
defined area of infrastructure investment, not on-going and geographically broad-based.
Irrigation benchmarking is a process of comparative analysis of irrigation performance that enables scheme managers
to understand the performance of their irrigation services (International Water Management Institute, 2019). To better
understand the process of monitoring irrigation performance, this brief will use Cambodia as an illustrative example.
Irrigated rice production in Cambodia has significant potential, yet performance of the sector lags behind surrounding
countries, such as Viet Nam’s delta region (Mainuddin and Kirby, 2009). In addition, there are limited available and
published data in Cambodia, making it difficult to analyse the current and changing state of irrigation in the country,
the productivity levels, or irrigation’s contribution to poverty alleviation and economic growth (Tucker et al., 2020). For
these reasons, Cambodia was selected as a country to pilot the transfer of key learnings from the Australian experience
of irrigation performance benchmarking, and to develop a benchmarking methodology as a first step to undertake
ongoing performance assessment of irrigation schemes for strategic investments in increasing water productivity.
Precision Ag Insight Webcast: Turn Your Yield Data into a Decision-Making ToolXSInc
In this Precision Ag Insight webcast, Dr. Chad Godsey presents best practices for turning your yield data into valuable insight for data-driven decision making.
The webcast covers tools and techniques for:
• Collecting high quality yield data
• Cleaning yield data
• Making management decisions with yield analysis
Este documento trata sobre la geometría del espacio. Explica que los elementos fundamentales son los puntos, las rectas y los planos. Define estos conceptos y describe cómo se determinan los planos a través de puntos y rectas. También cubre las posiciones relativas de rectas y planos, así como conceptos como ángulos entre rectas y planos, rectas perpendiculares a planos, y ángulos diedros y triedros.
This document summarizes Stephen Quandzie's MSc thesis on the potential to increase agricultural water productivity in Ghana's Black Volta Basin. The research questions whether agricultural water productivity can be increased, if increased dry season agriculture would help reduce poverty, and which agricultural water management intervention has the potential to improve livelihoods sustainably. The methodology involves using the CROPWAT and CLIMWAT models to analyze crop water consumption factors and physical, economic, and livestock water productivity. The results found that small reservoirs, shallow wells, and water pumps with reservoirs over-irrigated crops. Water pumps with reservoirs or river access were identified as having the best potential to enhance agricultural water management and promote off-farm skills development.
Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
Flood Prediction Model using Artificial Neural NetworkEditor IJCATR
This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN)
approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are
responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve
this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN’s Feed Forward (FF) and Back
Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our
simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts
the flood water level 24 hours ahead of time.
This document discusses using the CROPWAT and CLIMWAT models to evaluate and plan irrigation for cotton and rice crops in India. It summarizes that India currently produces lower rice yields than countries like China and Brazil from the same amount of land. Increasing yields through improved irrigation practices could increase production and reduce land usage. The document then outlines using the CROPWAT model to analyze reference evapotranspiration, crop water requirements, irrigation requirements, and develop irrigation schedules for cotton and rice in the Kurnool region of India based on climatic and soil data. It concludes that significantly increasing crop yields through using CROPWAT could boost the economy by improving farmer livelihoods and freeing up land.
There are 4 parks near the author's house that use different irrigation systems. DDA Park in Sector 11 uses sprinkler irrigation, which sprays water into the air to water the entire soil surface. DDA Park in Sector 6 uses drip irrigation, which applies water slowly at the base of plants. Rotary irrigation is used in DDA Park in Sector 10 and involves mechanically driven sprinklers that reach distances of up to 100 feet. The center-pivot system used in one park conserves water by using less than surface irrigation and reducing labor costs. Overextraction of groundwater has caused levels to drop by over 5 feet per year in some places.
This document discusses precision agriculture and provides an overview of key concepts:
1. Precision agriculture aims to optimize field management to match crop needs, protect the environment, and boost farm economics through efficient practices.
2. It involves characterizing field variability, making decisions based on soil maps and sensor data, and implementing variable-rate technology.
3. Current trends include high-accuracy GPS, input management like variable-rate fertilizer application, and information management tools to aid decision-making.
4. The document describes technologies like guidance systems, drones, wireless sensors, and yield mapping that are part of precision agriculture approaches.
This is the second presentation I was invited to give at the CAVI conference held in Galway, Ireland on October 12. it deals with precision dairy farming. A field that is coming up and growing in importance in modern dairy farming
Precision Agriculture; Past, present and futureNetNexusBrasil
This document provides an overview of the history and future of precision agriculture. It discusses early efforts using soil testing and yield monitors in the 1990s. Current technologies like crop canopy sensors that measure biomass and chlorophyll are highlighted. The document also reviews ongoing work optimizing in-season nitrogen management. International collaboration between USDA-ARS and Embrapa Brazil on precision agriculture research is summarized.
Applications of Artificial Neural Networks in Civil EngineeringPramey Zode
An artificial brain-like network based on certain mathematical algorithms developed using a numerical computing environment is called as an ‘Artificial Neural Network (ANN)’. Many civil engineering problems which need understanding of physical processes are found to be time consuming and inaccurate to evaluate using conventional approaches. In this regard, many ANNs have been seen as a reliable and practical alternative to solve such problems. Literature review reveals that ANNs have already being used in solving numerous civil engineering problems. This study explains some cases where ANNs have been used and its future scope is also discussed.
Precision agriculture is a farming system that uses information technology like GPS and GIS to increase farm production efficiency and profitability while minimizing environmental impacts. It involves tools like yield monitors, GPS, GIS software, and variable rate technology to collect and analyze field data to precisely vary inputs based on site-specific needs. Implementing precision agriculture can optimize production efficiency, quality, minimize risks and environmental impacts, and provide farmers with information to improve decision making.
This document summarizes four main irrigation methods: surface irrigation (flooding), sprinkler irrigation (applying water under pressure), drip or trickle irrigation (applying water slowly to the soil), and sub-surface irrigation (flooding water underground). Surface irrigation is the most widely used method, covering 90% of irrigated land. Sprinkler irrigation is ideal for scarce water areas. Drip irrigation conserves water, controls weeds, and applies water at a slow rate matching crop needs. Sub-surface irrigation is used where soil and topography allow watering underground.
This document provides an overview of irrigation engineering. It discusses the necessity of irrigation due to factors like insufficient rainfall and uneven distribution. It describes different types of irrigation systems including flow irrigation, lift irrigation, and storage irrigation. It also defines important terms used in irrigation like duty, delta, command area. The document outlines the benefits of irrigation such as increased crop yields and prosperity of farmers. It also notes some ill effects like raising water tables and creating breeding grounds for mosquitoes. Overall, the document provides a broad introduction to key concepts in irrigation engineering.
Increase yields and reduce costs with variable rate plantingXSInc
This document summarizes a webinar about using variable rate planting to increase yields and reduce costs. It finds that most growers are just starting to use variable seeding technology. The webinar discusses developing management zones using soil data and yield maps, understanding hybrid performance data, and evaluating the effectiveness of variable rate planting recommendations. Growers' biggest challenges are evaluating variable rate planting results and establishing effective management zones.
Reducing rural poverty and improving household nutrition are common goals across all developing countries in the
Asia and Pacific region. To this end, the region has experienced a recent resurgence in large investments in irrigation
infrastructure. This surge in funding flows has created pressure from donors and central financing agencies, both of
which are increasingly demanding more robust justification for the investments. To date, providing this justification for
irrigation investments has been challenging due to a lack of reliable longitudinal data that measure the performance of
irrigated agriculture and associated water delivery services. Consequently, there is very little information on the real
returns on investments already made. Historic data has tended to be project based, point-in-time data constrained to a
defined area of infrastructure investment, not on-going and geographically broad-based.
Irrigation benchmarking is a process of comparative analysis of irrigation performance that enables scheme managers
to understand the performance of their irrigation services (International Water Management Institute, 2019). To better
understand the process of monitoring irrigation performance, this brief will use Cambodia as an illustrative example.
Irrigated rice production in Cambodia has significant potential, yet performance of the sector lags behind surrounding
countries, such as Viet Nam’s delta region (Mainuddin and Kirby, 2009). In addition, there are limited available and
published data in Cambodia, making it difficult to analyse the current and changing state of irrigation in the country,
the productivity levels, or irrigation’s contribution to poverty alleviation and economic growth (Tucker et al., 2020). For
these reasons, Cambodia was selected as a country to pilot the transfer of key learnings from the Australian experience
of irrigation performance benchmarking, and to develop a benchmarking methodology as a first step to undertake
ongoing performance assessment of irrigation schemes for strategic investments in increasing water productivity.
The Brussels Development Briefing n.45 on the subject of “Smart and Affordable farming solutions for Africa: the next driver for agricultural transformation” was held in Brussels at 09:00-13:00 on 13th July 2016 at the Albert Borschette Congress Center, Room 1.A (Rue Froissart 36, 1040 Brussels). This Briefing was organised by the ACP-EU Technical Centre for Agricultural and Rural Cooperation (CTA), in collaboration with the European Commission, the the European Commission / DEVCO, the ACP Secretariat, CONCORD, CEMA, Agricord and the PanAfrican Farmer’s Organisation (PAFO).
“Connecting data streams to make irrigation science easier to implement” by Justin Gibson at the 2023 Water for Food Global Conference. A recording of the presentation can be found on the conference playlist: https://youtube.com/playlist?list=PLSBeKOIXsg3JNyPowwJj6NDSpx4vlnCYj.
This document provides guidance on selecting sprinklers and discusses key factors to consider. It defines relevant terms like precipitation rate, distribution uniformity, and infiltration rate. Distribution uniformity is important for high yields and is calculated using the Christiansen Coefficient (%CU), Distribution Uniformity (%DU), or Scheduling Coefficient (SC) methods. The %DU and SC methods account for dry areas better than %CU. Together these metrics help ensure water is distributed evenly across fields.
Cleaning yield monitor data for improved accuracy and insightsXSInc
The document discusses the importance of cleaning yield monitor data for accurate insights. It recommends using FOViewer and the Yield Editor tool to do basic cleaning by setting standard filter settings. More advanced cleaning may be needed for important analyses like on-farm trials. Cleaning yield data reduces variability and changes rankings and results. Clean data showed greater differences between management zones, UAN rates, and compost applications compared to uncleaned data. Advanced software like AgVeritas can further analyze cleaned yield data spatially and determine impact of various factors.
Dr. B. L. Sinha discusses the history and definition of precision agriculture. Precision agriculture has been practiced for hundreds of years through adaptations like the transition from horse-drawn plows to tractors. In recent decades, technology like GPS, GIS systems, and remote sensing has allowed for more precise data collection and analysis at subfield levels. This enables variable applications tailored to spatial and temporal variability in fields. By improving efficiency and reducing waste, precision agriculture benefits farmers through increased profits and more sustainable practices.
The document proposes a solution to improve service levels for single-source SKUs while maintaining supply chain losses. It involves implementing a national two-bin replenishment pull system with a multi-echelon inventory optimization model. Simulation results show the approach improves customer delivery performance and reduces inventory levels for non-innovation and innovation SKUs. Further refinement and testing of the model is recommended before full implementation.
The document discusses the implementation of the Water Erosion Prediction Project (WEPP) model through web-based applications and database services. WEPP is a process-based, daily time step model that simulates crop growth and soil erosion on a field scale over multiple years. It includes sub-models for soil, climate, management, hydrology, plant growth, decomposition, and erosion. The implementation provides conservation planners tools to model both wind and water erosion and evaluate management practices. It allows for risk-based planning by running simulations over 100 years of climate data. WEPP results and reports are accessible online without software installation.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions in smaller subfield areas. It utilizes technologies like GPS, GIS, yield monitors, and remote sensing to gather and analyze spatial and temporal data on factors like soil composition, crop yields, and pest populations. This allows for more efficient and environmentally friendly practices like variable rate application of inputs tailored to each subfield's specific needs, reducing costs and increasing yields. While the concept has existed for hundreds of years, recent technological advances have enabled much finer-scale data collection and analysis, driving improved management precision.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions on a sub-field level. This allows for more efficient use of inputs like fertilizer and chemicals by varying application rates within a single field based on differences in soil type, crop growth, and other factors. While the concept has existed for hundreds of years, recent technologies like GPS, GIS, sensors, and data analysis software have enabled much more precise data collection and implementation at scale. Potential benefits include cost savings from reduced input usage, improved environmental stewardship, and increased economic returns through optimized field management.
This document discusses sustainable agriculture and data management tools. It introduces the Agri-Data Solution, a secure online platform that allows farmers to track sustainability metrics and food security data for over 65 million acres. The platform can monitor metrics like soil conservation practices, nitrogen use efficiency, water and energy use, and integrate additional data like soil tests, yields, pesticides, and irrigation. It provides tools to help farmers and landowners improve sustainability and food production.
Artificial intelligence is being used in several agricultural applications with benefits such as increased yields, reduced costs, and improved sustainability. Some examples described are automated irrigation systems that precisely apply water to save resources; robotic strawberry harvesters that increase productivity and address labor shortages; and driverless tractors that allow more efficient use of equipment. Overall, AI and automation in agriculture are helping to boost outputs while minimizing environmental impacts through optimized resource use.
Crop metrics opportunity_ pa and probe presentation - v2Nick Lammers
$1,400.00
CropMetrics
Precision Data Specialist
CropMetrics Precision Water Management
Program - A Profitable Partnership
Opportunity for Growers and Dealers!
CropMetrics
Precision Data Specialist
Yield monitoring uses sensors and GPS data to collect georeferenced crop yield and characteristic data while harvesting. This allows farmers to create detailed yield maps of their fields to identify variable areas and optimize management practices. While yield monitors can provide accurate yield estimates if well-calibrated, challenges include sensor errors, moisture variations, and calibration biases. Yield monitoring is an important part of precision agriculture, enabling site-specific planting and variable input applications to improve efficiency and profitability.
Dr. Ken Sayre: Conservation Agriculture based hub strategy in Mexico sept 2...CIMMYT
This document describes the Conservation Agriculture-Based Applied Research and Delivery Hub (HUB) approach used by CIMMYT to develop and disseminate conservation agriculture technologies to farmers. The HUB approach involves multi-stakeholder collaboration through adaptive research platform trials and farmer module trials. The platform trials allow for testing and refinement of technologies through research on various components. Farmer module trials then test and demonstrate technologies in farmers' fields. Long-term strategic research trials also provide data on technology impacts. The HUB model facilitates participatory development and adoption of comprehensive conservation agriculture systems tailored to local conditions.
CANEFIT solution is a unique toolbox driven by
agronomic insights and developed by GAMAYA to address
the specific needs of sugarcane cultivation in Brazil.
Similar to Achieve the Potential of Variable Rate Irrigation (20)
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
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The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
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Achieve the Potential of Variable Rate Irrigation
1. Sponsored by XSInc
Achieve the Potential of
Variable Rate Irrigation
Chad Godsey, PhD
Precision Ag Insight Webinar
March 9, 2016
2. Sponsored by XSInc
Webcast Format
• You are muted.
• Please ask questions using the
“Questions” box.
• Click the red arrow to close/open
controls.
• Click the “plus” next to “Questions” if
you don’t see the questions box.
• A recording of today’s webcast
will be emailed to you.
Minimized
Controls
7. Sponsored by XSInc
VRI
• Effectively evaluating variable rate irrigation (VRI) is much
more difficult to do when compared to variable rate seeding
or fertilizer applications. The complexity comes from trying to
include an adequate “check” or reference strip to be able to
compare your variable rate irrigation treatments against.
8. Sponsored by XSInc
VRI Systems
• Sector based VRI - Sector VRI is accomplished by segmenting
the pivot path into 2 or more pie-like slices. Each unique
irrigation amount is usually accomplished by altering the pivot
speed at each slice.
9. Sponsored by XSInc
VRI Systems
• Zone VRI - Zone VRI divides the pivot area into 2 or more
zones (rings) around the pivot point. When combined with the
segmenting sectors, an even higher level of precision is made
possible with the use of several thousand individually
managed zones.
10. Sponsored by XSInc
VRI Systems
• Nozzle by Nozzle VRI – This approach each nozzle is controlled
individually, so irrigation amounts can be varied by nozzle.
11. Sponsored by XSInc
Delineating Zones
• Similar approaches to seeding of N zones
• EC
• EM
• Slope
• Soil Texture
• Multi-year Yield History
12. Sponsored by XSInc
Evaluating Sector based VRI
• To effectively evaluate VRI with sector based control it is best
to alternate every 30 degrees. A minimum of 30 percent of
the area should be flat-rated to serve as a check.
13. Sponsored by XSInc
Evaluating Zone or Nozzle by Nozzle
• Determine type of file format
• Some systems will accept a shapefile while others will only accept
.xml file types.
• Maintain at least 20-30 percent of the area in the field as a
check.
• This 20-30 percent should not be contiguous, instead it should be
spread out throughout the field.
• Keep in mind that with VRI the application is not as precise as
with fertilizer application equipment. The edges of the zones
may receive overthrow from neighboring nozzles or runoff so
check zones have to relatively large (>2 ac).
15. Sponsored by XSInc
Other data to collect
• Soil moisture data from as many zones as possible if soil
moisture probes are being used to help schedule irrigation.
• Collect irrigation amounts and rainfall from rain gauges if
possible.
• Any other observations that may have impacted yield.
19. Sponsored by XSInc
Results – Using soil moisture data
16%
42%
42%
Do not use Occasionally use it throughout the season Rely on it for weekly irrigation
29. Sponsored by XSInc
Thank You
Chad Godsey, PhD
Owner, Godsey Precision Ag
Phone: 970-630-7732
Email:
chad.godsey@godseyag.com
Web: godseyag.com
Twitter: @godseyag
Post event survey: Your feedback is greatly appreciated!