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Maimaitijiang, M
Ma, K
Christensen, A
Mommen, D
Mercatoris, B
Cooper, J
Mistele, B
Cullop, J
Chok, S.E
Colley, T
Muthamia, J
Castro, S.G
Mercante, E
McArthor , B
Mueller, T
Maidl, F.X
Cui, Z
McEntee, P
Mohd Soom, M
Maidl, F
Maggi, M.F
Marin-Barrero, C
McVeagh, P.J
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Authors
Mistele, B
Schmidhalter, U
Kipp, S
Gholizadeh , A
Mohd Soom , M
Saberioon, M
Gholizadeh, A
Saberioon, M
Mohd Soom, M
Mistele, B
Schmidhalter, U
Erdle, K
Mueller, T
Baresel, P
Mistele, B
Yuncai, H
Schmidhalter, U
Hackl, H
El-Sayed, S
Schmidhalter, U
Mistele, B
Mueller, T
Corá, J
Castrignanò, A
Rodrigues, M
Rienzi, E
Mueller, T
Gianello, E
Mijatovic, B
Rienzi, E
Rodrigues, M
Mueller, T
Matocha, C
Sikora, F
Mijatovic, B
Rienzi, E
Mueller, T
Miao, Y
Cao, Q
Cui, Z
Li, F
Dao, T.H
Khosla, R
Chen, X
de Solan, B
Lopez Lozano, R
Ma, K
Baret, F
Tisseyre, B
Strenner, M
Maidl, F
Mistele, B
Schmidhalter, U
Mueller, T
Neelakantan, S
Helmers, M
Dosskey, M
Castro, S.G
Kolln, O.T
Nakao, H.S
Franco, H.C
Braunbeck, O
Graziano Magalhães, P.S
Sanches, G.M
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Betzek, N.M
Souza, E.G
Bazzi, C.L
Schenatto, K
Gavioli, A
Maggi, M.F
McEntee, P
Bennett, S
Trotter, M
Belford, R
Harper, J
Yule, I.J
Chok, S.E
Grafton, M.C
White, M
Yule, I.J
Grafton, M.C
Willis, L.A
McVeagh, P.J
Yule, I.J
Pullanagari, R.R
Kereszturi, G
Irwin, M.E
McVeagh, P.J
Cushnahan, T
White, M
Sassenrath, G.F
Mueller, T
Alarcon, V.J
Kulesza, S.E
Shoup, D
Strenner, M
Maidl, F.X
Hülsbergen, K.J
Cullop, J
Griffin, T.W
Ibendahl, G
Barnes, E
Shockley, J
Devine, J
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
Rai, N
Zhang, Y
Quanbeck, J
Christensen, A
Sun, X
El-Mejjaouy, Y
Dumont, B
Oukarroum, A
Mercatoris , B
Vermeulen , P
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
McArthor , B
Prestholt, A
Kyveryga, P
Neils, W
Mommen, D
Virk, S
Colley, T
Kamerer, C
Harris, G
Beasley, D
Muthamia, J
Adolwa, I
Mutegi, J
Zingore, S
Phillips, S
Kovacs, P
Maimaitijiang, M
Millett, B
Dorissant, L
Acharya, I
Janjua, U.U
Dilmurat, K
Topics
Sensor Application in Managing In-season Crop Variability
Remote Sensing Applications in Precision Agriculture
Precision Conservation and Carbon Management
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Remote Sensing Applications in Precision Agriculture
Precision Conservation Management
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Robotics, Guidance and Automation
Big Data, Data Mining and Deep Learning
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Big Data, Data Mining and Deep Learning
Decision Support Systems
Site-Specific Nutrient, Lime and Seed Management
On Farm Experimentation with Site-Specific Technologies
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results39 paper(s) found.

1. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain

... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen

2. Interest Of 3D Modeling For Lai Retrieval From Canopy Transmittance Measurements: The Cases Of Wheat And Vineyard

Remote sensing techniques are now widely used in agriculture, for cultivar screening as well as for decision making tools. Empirical methods relate directly the remote sensing measured values to crop characteristics. These methods are limited by the important amount of ground data necessary for their calibration. Their validity domain is generally not very well defined as well as the associated uncertainties. Conversely, radiative transfer models allow simulating a wide range of conditions, and... B. De solan, R. Lopez lozano, K. Ma, F. Baret, B. Tisseyre

3. Comparison Of Different Vegetation Indices And Their Suitability To Describe N-uptake In Winter Wheat For Precision Farming

To avoid environment pollution and to minimize the costs of using mineral fertilizers an efficient fertilization system, tailored to the plant needs becomes more and more important. For that, the essential information can be determined by detecting certain crop parameters, like dry matter of the plant biomass above ground, N-content and N-uptake. By using fluorescence and reflectance measurements of the canopy and the mathematical analysis these parameters are appreciable. In three years,... M. Strenner, F. Maidl

4. A Comparison Of Spectral Reflectance And Laser-induced Cholorphyll Fluorescence Measurements To Detect Differences In Aerial Dry Weight And Nitrogen Update Of Wheat

       Chlorophyll fluorescence and spectral reflectance analysis are both powerful tools to study the spatial and temporal heterogeneity of plants` biomass and nitrogen status. Whereas reflectance techniques have intensively been tested for their use in precision fertilizer application, laser-induced chlorophyll fluorescence has been tested to a lesser degree, and there are hardly any... B. Mistele, U. Schmidhalter

5. Active Sensor Performance – Dependence to Measuring Height, Light Intensity and Device Temperature

For land use management, agriculture, and crop management spectral remote sensing is widely used. Ground-based sensing is particularly advantageous allowing to directly link on-site spectral information with agronomic algorithms. Sensors are nowadays most frequently used in site-specific oriented applications of fertilizers, but similarly site-specific applications of growth regulators, herbicides and pesticides become more often adopted. Generally little is known about the effects of... B. Mistele, U. Schmidhalter, S. Kipp

6. Estimation of Nitrogen of Rice in Different Growth Stages Using Tetracam Agriculture Digital Camera

Many methods are available to monitor nitrogen content of rice during various growth stages. However, this monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera (ADC) was used to acquire high spatial and temporal resolution in order to determine the status of nitrogen (N) and predict the grain yield of rice (Oriza sativa L.). In this study, 12 pots of rice with four different N treatments (0, 125,... A. Gholizadeh , M. Mohd soom , M. Saberioon

7. Potential of Visible and Near Infrared Spectroscopy for Prediction of Paddy Soil Physical Properties

A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of Visible (Vis) and Near-infrared Reflectance Spectroscopy (NIRS) to predict paddy soil physical properties in a typical Malaysian paddy field. To assess the utility of spectroscopy for soil physical characteristics prediction, we used 118 soil samples for laboratory analysis and optical measurement in the Vis-NIR region... A. Gholizadeh, M. Saberioon, M. Mohd soom

8. Comparison of Active and Passive Spectral Sensors in Discriminating Biomass Parameters and Nitrogen Status in Wheat Cultivars

Several sensor systems are available for ground-based remote sensing in crops. Vegetation indices of multiple active and passive sensors have seldom been compared in determining plant health. This study was aimed to compare active and passive sensing systems in terms of their ability to recognize agronomic parameters. One bi-directional passive radiometer (BDR) and three active sensors (Crop Circle, GreenSeeker, and an active flash sensor (AFS)) were tested for their ability to assess six destructively... B. Mistele, U. Schmidhalter, K. Erdle

9. Cloud Computing and Web 2.0 Mapping Technologies for Disseminating Land Use Planning Information

Open source software and cloud computing techniques could substantially improve the performance and reduce the cost of disseminating land-use planning information for the USDA-NRCS and other organizations. This is a major upgrade of our previously work (Hamilton,2009; Neelakantan et al., 2011). The purpose of this study is to develop a prototype cloud-based Web 2.0 mapping system for MLRA-121 which is primarily in Kentucky... T. Mueller

10. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

11. Assessing Water Status in Wheat under Field Conditions Using Laser-Induced Chlorophyll Fluorescence and Hyperspectral Measurements

Classical measurements for estimating water status in plants using oven drying or pressure chambers are tedious and time-consuming. In the field, changes in radiation conditions may further influence the measurements and thus require... S. El-sayed, U. Schmidhalter, B. Mistele

12. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate Factors

Effective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability.  The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measured... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi

13. On-The-Go pH Sensor: An Evaluation in a Kentucky Field

A commercially available on-the-go soil pH sensor measures and maps subsurface soil pH at high spatial intensities across managed landscapes.  The overall purpose of this project was to evaluate the potential for this sensor to be used in agricultural fields. The specific goals were to determine and evaluate 1) the accuracy with which this instrument can be calibrated, 2) the geospatial structure of soil pH measurements,... T. Mueller, E. Gianello, B. Mijatovic, E. Rienzi, M. Rodrigues

14. Soil Organic Carbon Multivariate Predictions Based on Diffuse Spectral Reflectance: Impact of Soil Moisture

Spatial predictions of soil organic carbon (OC) developed with proximal and remotely sensed diffuse reflectance spectra are complicated by field soil moisture variation. Our objective was to determine how moisture impacted spectral reflectance and Walkley-Black OC predictions. Soil reflectance from the North American Proficiency Testing... T. Mueller, C. Matocha, F. Sikora, B. Mijatovic, E. Rienzi

15. Cloud Computing, Web-Based GIS, Terrain Analysis, Data Fusion, and Multivariate Statistics for Precision Conservation in the 21st Century

... T. Mueller

16. Precision Design Of Vegetative Buffers

Precision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, variable-width,... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey

17. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy Sensor

The use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be detected... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches

18. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine Vision

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen  concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

19. Rectification of Management Zones Considering Moda and Median As a Criterion for Reclassification of Pixels

Management zones (MZ) make economically viable the application of precision agriculture techniques by dividing the production areas according to the homogeneity of its productive characteristics. The divisions are conducted through empirical techniques or cluster analysis, and, in some cases, the MZ are difficult to be delimited due to isolated cells or patches within sub-regions. The objective of this study was to apply computational techniques that provide smoothing of MZ, so as to become viable... N.M. Betzek, E.G. Souza, C.L. Bazzi, K. Schenatto, A. Gavioli, M.F. Maggi

20. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.

Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index was... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper

21. Accuracy of Differential Rate Application Technology for Aerial Spreading of Granular Fertiliser Within New Zealand

Aerial topdressing of granular fertilizer is common practice on New Zealand hill country farms because of the challenging topography. Ravensdown Limited is a New Zealand fertilizer manufacturer, supplier and applicator, who are funding research and development of differential rate application from aircraft. The motivation for utilising this technology is to improve the accuracy of fertilizer application and fulfil the variable nutrient requirements of hill country farms.  The capability of... I.J. Yule, S.E. Chok, M.C. Grafton, M. White

22. Measuring Pasture Mass and Quality Indices Over Time Using Proximal and Remote Sensors

Traditionally pasture has been measured or evaluated in terms of a dry matter yield estimate, which has no reference to other important quality factors. The work in this paper measures pasture growth rates on different slopes and aspects and pasture quality through nitrogen N% and metabolizable energy and ME concentration. It is known that permanent pasture species vary greatly in terms of quality and nutritional value through different stages of maturity. Pasture quality decreases as grass tillers... I.J. Yule, M.C. Grafton, L.A. Willis, P.J. Mcveagh

23. Hyperspectral Imaging to Measure Pasture Nutrient Concentration and Other Quality Parameters

Managing pasture nutrient requirements on large hill country sheep and beef properties based on information from soil sampling is expensive because of the time and labor involved. High levels of error are also expected as these properties are often greatly variable and it is therefore extremely difficult to sample intensively enough to capture this variation. Extensive sampling was also not considered viable as there was no effective means of spreading fertilizer with a variable rate capability... I.J. Yule, R.R. Pullanagari, G. Kereszturi, M.E. Irwin, P.J. Mcveagh, T. Cushnahan, M. White

24. In-field Variability of Terrain and Soils in Southeast Kansas: Challenges for Effective Conservation

A particular challenge for crop production in southeast Kansas is the shallow topsoil, underlain with a dense, unproductive clay layer. Concerns for topsoil loss have shifted production systems to reduced tillage or conservation management practices. However, historical erosion events and continued nutrient and sediment loss still limit the productive capacity of fields. To improve crop production and further adoption of conservation practices, identification of vulnerable areas of fields was... G.F. Sassenrath, T. Mueller, V.J. Alarcon, S.E. Kulesza, D. Shoup

25. Nitrogen Sensing by Using Spectral Reflectance Measurements in Cereal Rye Canopy

Cereal rye (cereale secale L.) is a winter crop well suited for cultivation especially besides high yield areas because of its relatively low demands on the soil and on the climate as well. In 2016 about 4.9% of arable land in Germany was cultivated with cereal rye (Statistisches Bundesamt, 2017). Unlike other crops such as wheat, there is little research on cereal rye for site specific farming. Furthermore, also in a cereal rye cultivation it is necessary to minimize nitrogen loss.... M. Strenner, F.X. Maidl, K.J. Hülsbergen

26. Economics of Swarm Bot Profitability for Cotton Harvest

Improved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine

27. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

28. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

29. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

30. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

31. Sun Effect on the Estimation of Wheat Ear Density by Deep Learning

Ear density is one of the yield components of wheat and therefore a variable of high agronomic interest. Its traditional measurement necessitates laborious human observations in the field or destructive sampling. In the recent years, deep learning based on RGB images has been identified as a low-cost, robust and high-throughput alternative to measure this variable. However, most of the studies were limited to the computer challenge of counting the ears in the images, without aiming to convert... S. Dandrifosse, E. Ennadifi, A. Carlier, B. Gosselin, B. Dumont, B. Mercatoris

32. Spotweeds: a Multiclass UASs Acquired Weed Image Dataset to Facilitate Site-specific Aerial Spraying Application Using Deep Learning

Unmanned aerial systems (UASs)-based spot spraying application is considered a boon in Precision Agriculture (PA). Because of spot spraying, the amount of herbicide usage has reduced significantly resulting in less water contamination or crop plant injury. In the last demi-decade, Deep Learning (DL) has displayed tremendous potential to accomplish the task of identifying weeds for spot spraying application. Also, most of the ground-based weed management technologies have relied on DL techniques... N. Rai, Y. Zhang, J. Quanbeck, A. Christensen, X. Sun

33. Investigating the Potential of Visible and Near-infrared Spectroscopy (VNIR) for Detecting Phosphorus Status of Winter Wheat Leaves Grown in Long-term Trial

The determination of plant nutrient content is crucial for evaluating crop nutrient removal, enhancing nutrient use efficiency, and optimizing yields. Nutrient conventional monitoring involves colorimetric analyses in the laboratory; however, this approach is labor-intensive, costly, and time-consuming. The visible and near-infrared spectroscopy (VNIR) or hyperspectral non-imaging sensors have been an emerging technology that has been proved its potential for rapid detection of plant nutrient... Y. El-mejjaouy, B. Dumont, A. Oukarroum, B. Mercatoris , P. Vermeulen

34. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

35. Soybean Variable Rate Planting Simulator Using Economic Scenarios

Soybean seed costs have increased considerably over the past 15 years, causing a growing interest in variable rate planting (VRP) to optimize seeding rates within soybean fields. We developed a publicly available online Soybean Variable Rate Planting Simulator (http://analytics.iasoybeans.com/cool-apps/SoybeanVRPsimulator/) tool to help farmers, agronomists, and other agriculturalists to understand the essential prerequisite agronomic or economic conditions necessary for profitable VRP implementation.... B. Mcarthor , A. Prestholt, P. Kyveryga

36. A Flexible Software Architecture for General Precision Agriculture Decision Support Systems

Agricultural data management is a complex problem. Both the data and the needs of the users are diverse. Given the complexity of the problem, it's easy to ascertain that a single solution will not be able to meet the needs of all users. This paper presents a software architecture designed to be extensible as well as flexible enough to provide agricultural management tools for a wide variety of users. The solution is based on a microservice architecture, which allows for the creation of new... W. Neils, D. Mommen

37. Improving Site-specific Nutrient Management in the Southeastern US: Variable-rate Fertilization Based on Yield Goal by Management Zone

Site-specific nutrient management is a critical aspect of row crop production, especially when aiming to achieve improved yields in the highly variable fields in the Southeastern United States. Variable-rate (VR) fertilizer application is a common practice to implement site-specific nutrient management and relies heavily on the use of precision soil sampling methods (grid or zone) to obtain accurate information on spatial nutrient variability within the fields. Most fields in the southeastern... S. Virk, T. Colley, C. Kamerer, G. Harris, D. Beasley

38. Harnessing Farmers’, Researchers’ and Other Stakeholders’ Knowledge and Experiences to Create Shared Value from On-farm Experimentation: Lessons from Kenya

Achieving greater sustainability in farm productivity is a major challenge facing smallholder farmers in Kenya. Existing technologies have not solved the challenges around declining productivity because they are one-size-fits-all that doesn’t account for the diverse smallholder contexts. A study was carried out in Kenya by a multi-disciplinary team to assess the value of On-Farm Experimentation (OFE) to tailor technologies to local conditions. The OFE process begun with identification of... J. Muthamia, I. Adolwa, J. Mutegi, S. Zingore, S. Phillips

39. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask Learning

Rapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat