Integrating Management Zones and Canopy Sensing to Improve Nitrogen Recommendation Algorithms PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Integrating Management Zones and Canopy Sensing to Improve Nitrogen Recommendation Algorithms PDF full book. Access full book title Integrating Management Zones and Canopy Sensing to Improve Nitrogen Recommendation Algorithms by Joel D. Crowther. Download full books in PDF and EPUB format.
Author: Joel D. Crowther
Publisher:
ISBN:
Category :
Languages : en
Pages : 202
Get Book Here
Book Description
Fertilizer nitrogen use efficiency (NUE) in maize (Zea mays L.) production is historically inefficient, presenting significant environmental and economic challenges. Low NUE can be attributed to poor synchrony between soil N supply and crop demand, applying uniform rates of N fertilizer to spatially variable landscapes, and failure to account for temporal variability in crop response to N. Innovative N management strategies, including crop canopy sensing and management zones (MZ), are tools that have proven useful in increasing NUE. Several researchers have proposed that the integration of these two approaches may result in further improvements in NUE and in profitability by synthesizing both crop- and soil-based information for more robust N management. The objectives of this research were to identify soil and topographic variables that could be used to delineate MZ that appropriately characterize areas with differential crop response to N fertilizer and then to test a sensor-based N application algorithm and evaluate the potential of an integrated MZ- and sensor-based approach compared to uniform N management and to sensor-based N management alone. Management zones delineated with a field-specific approach were able to appropriately characterize the spatial variability in in-season crop response to N in all eight fields and in yield response to N in three of six fields. Sensor-based application resulted in significantly increased NUE compared to uniform N management in six of eight fields, and marginal net return was significantly increased in four of eight fields. Delineated MZ appropriately classified areas of differing NUE in six of eight fields. Results from these studies indicate that integrating field-specific MZ and sensor-based N application has potential to increase NUE and profitability compared to sensor-based or MZ-based N management approaches alone. Additional research is needed to explore how to best incorporate static soil information into a sensor-based algorithm that can be generalized for a variety of soil, climatic, and managerial factors.
Author: Joel D. Crowther
Publisher:
ISBN:
Category :
Languages : en
Pages : 202
Get Book Here
Book Description
Fertilizer nitrogen use efficiency (NUE) in maize (Zea mays L.) production is historically inefficient, presenting significant environmental and economic challenges. Low NUE can be attributed to poor synchrony between soil N supply and crop demand, applying uniform rates of N fertilizer to spatially variable landscapes, and failure to account for temporal variability in crop response to N. Innovative N management strategies, including crop canopy sensing and management zones (MZ), are tools that have proven useful in increasing NUE. Several researchers have proposed that the integration of these two approaches may result in further improvements in NUE and in profitability by synthesizing both crop- and soil-based information for more robust N management. The objectives of this research were to identify soil and topographic variables that could be used to delineate MZ that appropriately characterize areas with differential crop response to N fertilizer and then to test a sensor-based N application algorithm and evaluate the potential of an integrated MZ- and sensor-based approach compared to uniform N management and to sensor-based N management alone. Management zones delineated with a field-specific approach were able to appropriately characterize the spatial variability in in-season crop response to N in all eight fields and in yield response to N in three of six fields. Sensor-based application resulted in significantly increased NUE compared to uniform N management in six of eight fields, and marginal net return was significantly increased in four of eight fields. Delineated MZ appropriately classified areas of differing NUE in six of eight fields. Results from these studies indicate that integrating field-specific MZ and sensor-based N application has potential to increase NUE and profitability compared to sensor-based or MZ-based N management approaches alone. Additional research is needed to explore how to best incorporate static soil information into a sensor-based algorithm that can be generalized for a variety of soil, climatic, and managerial factors.
Author: Luciano Shozo Shiratsuchi
Publisher:
ISBN: 9781267054036
Category : Corn
Languages : en
Pages :
Get Book Here
Book Description
Abstract: The soil's nitrogen (N) supply can vary drastically in the field, spatially as well as temporally making any soil prediction difficult even with very detailed mapping. Consequently, a plant-based approach wherein the measured canopy can indicate the N needs in a reactive and spatially-variable way can be a better approach than mapping, because integrate the soil N supply and translate the crop need on-the-go. The first experiment evaluated the performance of various spectral indices for sensing N status of corn, where spectral variability might be confounded by water-induced variations in crop reflectance. We found that water and previous crops effects on vegetation indices (VI) must be considered, and also that some VIs are less susceptible to water with good ability for N differentiation. In the second experiment, the objective was to develop an approach that relies on local soil conditions as well as on active canopy sensor measurements for real-time adjustment of N application rate. We found that local variations in plant N availability must be considered to determine the optimal N rate on-the-go, and that the localized reference incorporated the spatial variability of the N-rich plot. Next, we determined the correlation between active canopy sensors assessments of N availability and ultrasonic sensor measurements of canopy height at several growth stages for corn. We found strong correlations between both sensors and that they had similar abilities to distinguish N-mediated differences in canopy development. The integrated use of both sensors improved the N estimation compared to the isolated use of either sensor. Based on these strong correlations, we developed an N recommendation algorithm based on ultrasonic plant height measurements to be used for on-the-go variable rate N application. Lastly, we evaluated the crop water status using infrared thermometry integrated with optical and ultrasonic sensors, we concluded that the integration of sensors was beneficial to detect water-stressed zones in the field, affecting yield and possibly promising to delineate zones for N and water management.
Author: Nicholas Clarke
Publisher: Springer Nature
ISBN: 9819928281
Category : Technology & Engineering
Languages : en
Pages : 264
Get Book Here
Book Description
The edited volume focuses on modern agro-technologies for achieving climate smart agriculture in China and meeting the UN sustainable development goals (especially SDGs 2, 13, and 15). It describes the technologies being adopted in China for meeting food security challenges, with the main focus being on soils. China is a large and diverse country, and what happens there has a global impact. In the past decades, China has achieved remarkable increases in food production, feeding nearly 20% of the world population with less than 10% of the arable land. This great achievement was mainly based on the intensive use of chemical inputs like fertilizers and pesticides, which in turn caused environmental pollution and food safety issues. China has fully realized this important issue and has adopted a “Zero Growth” policy to restrict the further increase in chemical fertilizers after 2020. Chinese scientists have developed regional optimum crop management practices and guidelines to increase crop yield and nutrient use efficiencies compared with current farming practices. Chinese agricultural soil is also currently in critical condition with severe environmental pollution. These agricultural practices need improvement to maintain sustainable food production with minimum environmental footprint. At present, the traditional mode of agricultural production in China is difficult to sustain. This book offers case studies and sustainable solutions for transforming agricultural sciences in China. The book is a useful reading material for stakeholders such as governments, policymakers, research institutions, and farmers.
Author: Samantha L. Teten
Publisher:
ISBN:
Category : Corn
Languages : en
Pages : 136
Get Book Here
Book Description
Optimizing nitrogen (N) fertilizer applications in corn to reduce environmental impacts while maintaining producer profitability remains a challenge due to spatial and temporal variability in crop yield potential and soil N dynamics. In response to these challenges, active crop canopy sensors and imagery systems have been studied to test the performance of vegetative index-based N management, but adoption has been low. There is also a lack of field-scale research evaluating this technology in water-limiting environments. The evaluation of two sensor-based N management techniques was completed at nine non-irrigated sites in Eastern Nebraska. The first sensor-based N management technique evaluated an active crop canopy sensor and Holland-Schepers model to direct real-time, in-season N applications on corn. Compared to growers' management, active sensor management improved N use efficiency (NUE) by 16.8±8.4 kg grain kg N-1 and reduced N fertilizer inputs by 38.7±20.8 kg N ha-1 . All sites resulted in less N applied than the growers' management. Two of the nine sites resulted in significant yield losses compared to the sensor-based management with an average yield loss across all sites of 0.49±0.69 Mg grain ha-1 . Average partial profitability was $2.40±15.48 US$ ha-1 less than the growers' practices. Early season base N rates and timing influenced the NUE of active sensor N management approach. The second sensor-based management technique utilized aerial imagery and the Holland-Schepers model to develop variable-rate N prescriptions for in-season applications. The approach incorporated sub-field yield potential by varying the estimated optimum N rate used in the algorithm based on management zones (MZ). The aerial imagery-based management improved NUE compared to the growers' current management by 23.6±15.3 kg grain kg N-1 and did not result in differences in partial profit. The integration of MZs influenced the total N applied and demonstrated the potential to improve imagery-based recommendations using spatial field data. Overall, compared to grower management, active sensors improved NUE in nonirrigated sites where rainfall is a yield limiting factor. Aerial imagery-based prescriptions also improved NUE compared to grower management and provided an opportunity to further refine sensor-based management to account for sub-field variability by incorporating yield potential and soil attributes.
Author: Nicholas C. Ward
Publisher:
ISBN: 9781321978445
Category :
Languages : en
Pages : 146
Get Book Here
Book Description
Water and nitrogen (N) are undoubtedly the two largest agricultural inputs globally. Coupled with advances in site-specific management technology their integration into production agriculture will allow for the most efficient use these crop input resources. Active canopy sensors offer the ability to measure biophysical plant traits rapidly and make assessments about plant status. Specifically, optical sensor measurements of light reflectance assess plant N status allowing for in-season and on-the-go N recommendations and applications; while infrared thermometers (IRT) measurement of canopy temperature can be used a tool for irrigation management. To evaluate how these technologies work among different plant stress environments a series of experiments were formulated. The first experiment compared reference strategies for normalizing reflectance data across multiple vegetation indices (VI). We found the virtual reference concept helped reduce variation of the calculated reference and placed sufficiency index values in a range that corresponded to plant N status. Additionally, VI varied in their ability to show significant responses to applied N fertilizer. In the second experiment, we sought to understand the influence of VI on how an in-season N application algorithm performs as well as the confounding effects of irrigation might have. We found N application rates would change based on algorithm and VI. Also, N rate can be affected by apparent water stress. In this case, reduced reflectance in the NIR spectrum reduced leaf area from leaf rolling. The final objective was to quantify the effect of N fertility on plant canopy temperature and determine if functions of canopy temperature could be useful for detecting apparent N stress. We concluded that plant canopy temperature can be affected by N stresses and that canopy temperature and canopy/air temperature difference provided equal sensitivity to plant stress. Therefore, these technologies will be vital to help conserve resources and maximize efficiency in production agriculture.
Author: Salim Lamine
Publisher: Elsevier
ISBN: 0323914640
Category : Technology & Engineering
Languages : en
Pages : 555
Get Book Here
Book Description
Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones' geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information. - Presents a well-integrated collection of chapters, with quality, consistency and continuity - Provides the latest RS techniques in Precision Agriculture that are addressed by leading experts - Includes detailed, yet geographically global case studies that can be easily understood, reproduced or implemented - Covers geospatial data, with codes available through shared links
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668453533
Category : Technology & Engineering
Languages : en
Pages : 1364
Get Book Here
Book Description
Agriculture has been an enduring human tradition key to survival and civilization. However, after the advent of industrialization and agricultural growth, the industry has been met with several challenges including pollution, land use, and food insecurity. With the agricultural industry contributing to pollution and emissions, many have found it imperative to investigate the causes and seek out solutions. The Research Anthology on Strategies for Achieving Agricultural Sustainability discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes. It analyzes the impact of agricultural pollution and food insecurity on a global scale, but also proposes solutions to promote agricultural sustainability. Covering topics such as bio-farming, smart farming, and population growth, this book is an indispensable resource for government officials, agricultural scientists, farmers, students and professors of higher education, activist groups, researchers, and academicians.
Author: Yuxin Miao
Publisher:
ISBN: 9783036557106
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This book focuses on the fundamental and applied research of the non-destructive estimation and diagnosis of crop leaf and plant nitrogen status and in-season nitrogen management strategies based on leaf sensors, proximal canopy sensors, unmanned aerial vehicle remote sensing, manned aerial remote sensing and satellite remote sensing technologies. Statistical and machine learning methods are used to predict plant-nitrogen-related parameters with sensor data or sensor data together with soil, landscape, weather and/or management information. Different sensing technologies or different modelling approaches are compared and evaluated. Strategies are developed to use crop sensing data for in-season nitrogen recommendations to improve nitrogen use efficiency and protect the environment.
Author:
Publisher:
ISBN:
Category : Soil conservation
Languages : en
Pages : 818
Get Book Here
Book Description
Vol. 25, no. 1 contains the society's Lincoln Chapter's Resource conservation glossary.
Author: D. Kent Shannon
Publisher: John Wiley & Sons
ISBN: 0891183663
Category : Technology & Engineering
Languages : en
Pages : 272
Get Book Here
Book Description
With the growing popularity and availability of precision equipment, farmers and producers have access to more data than ever before. With proper implementation, precision agriculture management can improve profitability and sustainability of production. Precision Agriculture Basics is geared at students, crop consultants, farmers, extension workers, and practitioners that are interested in practical applications of site-specific agricultural management. Using a multidisciplinary approach, readers are taught to make data-driven on-farm decisions using the most current knowledge and tools in crop science, agricultural engineering, and geostatistics. Precision Agriculture Basics also features a stunning video glossary including interviews with agronomists on the job and in the field.
