Integration of Plant-based Canopy Sensors for Site-specific Nitrogen Management 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 Integration of Plant-based Canopy Sensors for Site-specific Nitrogen Management PDF full book. Access full book title Integration of Plant-based Canopy Sensors for Site-specific Nitrogen Management by Luciano Shozo Shiratsuchi. Download full books in PDF and EPUB format.
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: 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 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: 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: 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: Ciza Thomas
Publisher: BoD – Books on Demand
ISBN: 9533074469
Category : Computers
Languages : en
Pages : 242
Get Book Here
Book Description
Sensor Fusion - Foundation and Applications comprehensively covers the foundation and applications of sensor fusion. This book provides some novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. The book explores some of the latest practices and research works in the area of sensor fusion. The book contains chapters with different methods of sensor fusion for different engineering as well as non-engineering applications. Advanced applications of sensor fusion in the areas of mobile robots, automatic vehicles, airborne threats, agriculture, medical field and intrusion detection are covered in this book. Sufficient evidences and analyses have been provided in the chapter to show the effectiveness of sensor fusion in various applications. This book would serve as an invaluable reference for professionals involved in various applications of sensor fusion.
Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 0429775229
Category : Science
Languages : en
Pages : 348
Get Book Here
Book Description
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing stateof- the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Hyperspectral remote sensing or imaging spectroscopy data has been increasingly used in studying and assessing the biophysical and biochemical properties of agricultural crops and natural vegetation. Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume III through the editors’ perspective. Key Features of Volume III: Covers recent abilities to better quantify, model, and map plant biophysical, biochemical water, and structural properties. Demonstrates characteristic hyperspectral properties through plant diagnostics or throughput phenotyping of plant biophysical, biochemical, water, and structural properties. Establishes plant traits through hyperspectral imaging spectroscopy data as well as its integration with other data, such as LiDAR, using data from various platforms (ground-based, UAVs, and earth-observing satellites). Studies photosynthetic efficiency and plant health and stress through hyperspectral narrowband vegetation indices. Uses hyperspectral data to discriminate plant species and\or their types as well as their characteristics, such as growth stages. Compares studies of plant species of agriculture, forests, and other land use\land cover as established by hyperspectral narrowband data versus multispectral broadband data. Discusses complete solutions from methods to applications, inventory, and modeling considering various platform (e.g., earth-observing satellites, UAVs, handheld spectroradiometers) from where the data is gathered. Dwells on specific applications to detect and map invasive species by using hyperspectral data.
Author: Hermann J. Heege
Publisher: Springer Science & Business Media
ISBN: 9400767609
Category : Technology & Engineering
Languages : en
Pages : 361
Get Book Here
Book Description
High yields and environmental control in crop farming call for precise adaptations to local growing conditions. Treating large fields in a uniform way by high capacity machinery cannot be regarded as a sustainable method for many situations. Because differences existing within single fields must be considered. The transition from former field work carried out manually or by small implements to present-day high-capacity machinery caused that the farmers lost the immediate and close contact with soils and crops. However, modern sensing and controlling technology can make up for this deficit. High tech methods that include proximal sensing and signals from satellites can provide for controls that allow adjusting farming operations to small fractions of one ha and sometimes even down to some m2, hence in a site-specific mode. This applies to operations for soil cultivation, sowing, fertilizing and plant protection. This book deals with site-specific concepts, applications and results.
Author: John V. Stafford
Publisher: Brill Wageningen Academic
ISBN: 9789086863372
Category : Precision farming
Languages : en
Pages : 0
Get Book Here
Book Description
Precision agriculture is a reality in agriculture and is playing a key role as the industry comes to terms with the environment, market forces, quality requirements, traceability, vehicle guidance and crop management. These proceedings contain reviewed papers presented at the 12th European Conference on Precision Agriculture. The papers reflect the wide range of disciplines that impinge on precision agriculture - technology, crop science, soil science, agronomy, information technology, decision support, remote sensing and others.
Author: Liping Di
Publisher: Springer Nature
ISBN: 3030663876
Category : Science
Languages : en
Pages : 418
Get Book Here
Book Description
This volume collects and presents the fundamentals, tools, and processes of utilizing geospatial information technologies to process remotely sensed data for use in agricultural monitoring and management. The issues related to handling digital agro-geoinformation, such as collecting (including field visits and remote sensing), processing, storing, archiving, preservation, retrieving, transmitting, accessing, visualization, analyzing, synthesizing, presenting, and disseminating agro-geoinformation have never before been systematically documented in one volume. The book is edited by International Conference on Agro-Geoinformatics organizers Dr. Liping Di (George Mason University), who coined the term “Agro-Geoinformatics” in 2012, and Dr. Berk Üstündağ (Istanbul Technical University) and are uniquely positioned to curate and edit this foundational text. The book is composed of eighteen chapters that can each stand alone but also build on each other to give the reader a comprehensive understanding of agro-geoinformatics and what the tools and processes that compose the field can accomplish. Topics covered include land parcel identification, image processing in agricultural observation systems, databasing and managing agricultural data, crop status monitoring, moisture and evapotranspiration assessment, flood damage monitoring, agricultural decision support systems and more.
