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1. Application Of Precision Agriculture In Carbon Farming Practices Using The Real-time Soil Sensor... Y. Li |
2. An Overview of Soil Carbon, Management, and Agricultural SystemsTopics to be covered include a discussion of what soil carbon sequestration is, how and where in the soil it occurs, and its role in maintaining important soil properties. The author draws upon his experience and that of others about practices for various parts of the US to describe on-farm and experimental agricultural systems and their degree of success to sequester carbon and improve soil quality. Included is an overview of carbon sequestration strategies and pos... R. Follett, E. Short |
3. Soil Organic Carbon Maintenance Requiremnets And Mineralizatyion Rate Constants: Site Specific CalcuationsOver the past 100 years numerous studies have been conducted with the goal of quantifying the impact of management on carbon turnover. It is difficult to conduct a mechanistic evaluation of these studies because each study was conducted under unique soil, climatic, and management conditions. Techniques for directly comparing data from unique studies are needed. This study discusses techniques for comparing data collected... D.E. Clay, G. Carlson, J. Tatge |
4. On-combine Sensing Technique For Mapping Straw Yield Within Wheat FieldsStraw from production of wheat is available for conversion to bioenergy. However, not all of this straw is available for conversion because a certain amount must be returned to the soil for conservation. County and state-wide inventories do not account for variation within farm fields. In this study, a technique is described that applies information from on-combine crop sensors into estimation of straw yield across fields. Straw yiel... D.S. Long, , |
5. Modeling Soil Carbon Spatial Variation: Case Study In The Palouse RegionSoil organic carbon (Cs) levels in the soil profile reflect the transient state or equilibrium conditions determined by organic carbon inputs and outputs. In areas with strong topography, erosion, transport and deposition control de soil carbon balance and determine strong within-field differences in soil carbon. Carbon gains or losses are therefore difficult to predict for the average field. Total Cs ranged from 54 to 272 Mg C ha-1, with 42% (range 25 to 78%) of Cs in the top 0.3-m of the so... A.R. Kemanian, D.R. Huggins, D.P. Uberuaga |
6. Performance Of The Veris Nir Spectrophotometer For Mapping Soil C In The Palouse Soils Of Eastern WashingtonRecent advances in sensing technology have made measuring and mapping the dynamics of important soil properties that regulate carbon and nutrient budgets possible. The Veris Technologies (Salinas, KS) Near Infrared (NIR) Spectrometer is one of the first sensors available for collecting geo-referenced NIR soil spectra on-the-go. Field studies were conducted to evaluate the performance of the Veris NIR in wheat grown under both conventional and no-till management in the Palouse region of easter... F. Pierce, E.M. Perry, S.L. Young, H.P. Collins, P.G. Carter |
7. Landscape Position And Climatic Gradient Impacts On Carbon Turnover in Dryland Cropping Systems in ColoradoSoil organic carbon has decreased in cultivated wheat-fallow systems due to increased carbon oxidation, low carbon input and soil erosion. Implementation of more intensive cropping with no-till management has reversed the trend in soil carbon loss. Our objective in this presentation is to review the effects of landscape position on soil carbon status as related to intensification of cropping system. Our analysis wi... G. Peterson, D. Westfall, L.A. Sherrod |
8. C And N Coupling Through Time: Soil C, N, And Grain Yield In A Long-term Continuous Corn TrialGains and losses of both C and N are important in agricultural landscapes. Temporal changes in the pattern of crop yield response to tillage and fertilizer input are commonly observed; often weakly interpreted, in long-term research. A 38-year-long monoculture corn (Zea mays L.) tillage (moldboard plow, no-tillage) by N rate (0, 84, 168, 336 kg N per hectare) trial was sampled to a depth of 100 cm, as was the surround... J. Grove, E.M. Pena-yewtukhiw |
9. Estimating Soil Productivity And Energy Efficiency Using Websoil Survey, Soil Productivity Index Calculator, And Biofuel Energy Systems SimulatorSoils have varying production capacities for a specific plant or sequence of plants under defined management strategies. The production capacity or “productivity” can be quantified as a mathematical function of a soils ability to sufficiently sustain plant ... K.D. Reitsma, T.E. Schumacher |
10. Variability Of Carbon Sequestration In The Tidewater Region Of The Southeastern U.S.In the southeastern US climatic conditions favor long periods of plant growth. This combined with intense rainfall and poor drainage provides idea conditions for the conversion of plant biomass into organic matter. This study combines the results of field experiments designed to examine crop management practices that favor the development of soil organic carbon and organic matter with an examination of the causes for the extreme variability... R. Heiniger |
11. Investigating Profile And Landscape Scale Variability In Soil Organic Carbon: Implications For Process-oriented Precision ManagementMitigation of rising greenhouse gases concentrations in the atmosphere has focused attention on agricultural soil organic C (SOC) sequestration. However, field scale knowledge of the processes and factors regulating SOC dynamics, distribution and variability is lacking. The objectives of this study are to characterize the pr... D.R. Huggins, |
12. The Daily Erosion Project - High Resolution, Daily Estimates of Runoff, Detachment, Erosion, and Soil MoistureRunoff and sediment transport from agricultural uplands are substantial threats to water quality and sustained crop production. Farmers, conservationists, and policy makers must understand how landforms, soil types, farming practices, and rainfall affect soil erosion and runoff in order to improve management of soil and water resources. A system was designed and implemented a decade ago to inventory precipitation, runoff, and soil erosion across the state of Iowa, United States. That system u... B.K. Gelder, R. Cruse, D. James, D. Herzmann, C. Sandoval-green, T. Sklenar |
13. A Decade of Precision Agriculture Impacts on Grain Yield and Yield VariationTargeting management practices and inputs with precision agriculture has high potential to meet some of the grand challenges of sustainability in the coming century, including simultaneously improving crop yields and reducing environmental impacts. Although the potential is high, few studies have documented long-term effects of precision agriculture on crop production and environmental quality. More specifically, long-term impacts of precision conservation practices such as cover crops, no-ti... M.A. Yost, N. Kitchen, K. Sudduth, S. Drummond, J. Sadler |
14. Economics of Gps-enabled Navigation TechnologiesTo address the economic feasibility of global positioning system (GPS) enabled navigation technologies including automated guidance and lightbar, a linear programming model was formulated using data from Midwestern U.S. Corn Belt farms. Five scenarios were compared: (i) a baseline scenario with foam, disk or other visual marker reference, (ii) lightbar navigation with basic GPS availability (+/-3 dm accuracy), (iii) lightbar with satellite subscription correction GPS (+/-1 dm), (iv) automated... T.W. Griffin, D.M. Lambert, J. Lowenberg-deboer |
15. Synchronized Windrow Intelligent Perception System (SWIPE)The practice of bale production, in forage agriculture, involves various machines that include tractors, tedders, rakers, and balers. As part of the baling process, silage material is placed in windrows, linearly raked mounds, to drive over with a baler for easy collection into bales. Traditionally, a baler is an implement that is attached on the back of a tractor to generate bales of a specific shape. Forage agricultural equipment manufacturers have recently released an operator driven, self... E.M. Dupont, P.R. Kolar |
16. Application of Drone Data to Assess Damage Intensity of Bacterial Leaf Blight Disease on Rice Crop in IndonesiaThe Government of Indonesia has launched agricultural insurance program since 2016. A key in agricultural insurance is damage assessment which is required to be as precise, quick, quantitative and inexpensive as possible. Current method is to inspect the damage by human eyes of specialist having experiences. This method, however, costs much and is difficult to estimate disease infected fields precisely in wide area. So, there is increasing need to develop effective, simplified and low cost me... C. Hongo, S. Isono, G. Sigit, B. Utoyo, E. Tamura |
17. Economics of Field Size for Autonomous Crop MachinesField size constrains spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectar... A. Al amin, J. Lowenberg‑deboer, K. Franklin, K. Behrendt |
18. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS ImageryAerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimati... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster |
19. Knowledge-based Approach for Weed Detection Using RGB ImageryA workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, ... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu |
20. UAV-based Hyperspectral Monitoring of Peach Trees As Affected by Silicon Applications and Water Stress StatusPrevious research has shown that the application of reduced doses of Silicon (Si) improves crop tolerance to water stress, which is common in commercial young peach trees because irrigation is not usually applied during their first two years. In this study, aerial images were used to monitor the impact of different Si and water treatments on the hyperspectral response of peach trees. An experiment with 60 young (under 1 year old) peach trees located at the Musser Fruit Research Center (Seneca... J. Peña, J. Melgar, A. De castro, J. Maja, K. Nascimento-silva |
21. N-management Using Structural Data: UAV-derived Crop Height As an Estimator for Biomass, N Concentration, and N Uptake in Winter WheatIn the last 15 years, sensors mounted on Unmanned Aerial Vehicles (UAVs) have been intensively investigated for crop monitoring. Besides known remote sensing approaches based on multispectral and hyperspectral sensors, photogrammetric methods became very important. Structure for Motion (SfM) and Multiview Stereopsis (MVS) analysis approaches enable the quantitative determination of absolute crop height and crop growth. Since the first paper on UAV-derived crop height was published by Bendig e... G. Bareth, A. Jenal, H. Hüging |
22. Cotton Boll Detection and Yield Estimation Using UAS Lidar Data and RGB ImageCotton boll distribution is a critical phenotypic trait that represents the plant's response to its environment. Accurate quantification of boll distribution provides valuable information for breeding cultivars with high yield and fiber quality. Manual methods for boll mapping are time-consuming and labor-intensive. We evaluated the application of Lidar point cloud and RGB image data in boll detection and distribution and yield estimation. Lidar data was acquired at 15 m using a DJI Matri... Z. Lin, W. Guo, N. Gill |
23. Integration of Unmanned Aerial Systems Images and Yield Monitor in Improving Cotton Yield EstimationThe yield monitor is one of the most adopted precision agriculture technologies because it generates dense yield data to quantify the spatial variability of crop yield as a basis for site-specific management. However, yield monitor data has various errors that prevent proper interpretation and precise field management. The objective of this study was to evaluate the application of unmanned aerial systems (UAS) images in improving cotton yield monitor data. The study was conducted in a dryland... H. Gu, W. Guo |
24. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS ImageryDeep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high re... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal |
25. Evaluation of Unmanned Aerial Vehicle Images in Estimating Cotton Nitrogen ContentEstimating crop nitrogen content is a critical step for optimizing nitrogen fertilizer application. The objective of this study was to evaluate the application of UAV images in estimating cotton (Gossypium hirsutum L.) N content. This study was conducted in a dryland cotton field in Garza County, Texas, in 2020. The experiment was implemented as a randomized complete block design with three N rates of 0, 34, and 67 kg N ha-1. A RedEdge multispectral sensor was used to acqu... R. Karn, H. Gu, O. Adedeji, W. Guo |
26. Establishment of a Canola Emergence Assessment Methodology Using Image-based Plant Count and Ground Cover AnalysisManual assessment of emergence is a time-consuming practice that must occur within a short time-frame of the emergence stage in canola (Brassica napus). Unmanned aerial vehicles (UAV) may allow for a more thorough assessment of canola emergence by covering a wider scope of the field and in a more timely manner than in-person evaluations. This research aims to calibrate the relationship between emerging plant population count and the ground cover. The field trial took place at the Uni... K. Krys, S. Shirtliffe, H. Duddu, T. Ha, A. Attanayake, E. Johnson, E. Andvaag, I. Stavness |
27. Utilization of UASs to Predict Sugarcane Yields in Louisiana Prior to HarvestOne of the most difficult tasks that both sugarcane producers and processors face every year is estimating the yields of sugarcane fields prior to the start of harvest. This information is needed by processors to determine when the harvest season is to be initiated each year and by producers to decide when each field should be harvested. This is particularly important in Louisiana because the end of the harvest season is often affected by freeze events. These events can severely damage the cr... R.M. Johnson, B. Ramachandran |
28. Increasing the Accuracy of UAV-Based Remote Sensing Data for Strawberry Nitrogen and Water Stress DetectionThis paper presents the methods to increase the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data for the determination of plant nitrogen and water stresses with increased accuracy. As the demand for agricultural products is significantly increasing to keep up with the growing population, it is important to investigate methods to reduce the use of water and chemicals for water conservation, reduction in the production cost, and reduction in environmental impact. UAV-based r... S. Bhandari, A. Raheja |
29. Estimation of Cotton Biomass Using Unmanned Aerial Systems and Satellite-based Remote SensingSatellite and unmanned aerial system (UAS) images are effective in monitoring crop growth at various spatial, temporal, and spectral scales. The objective of the study was to estimate cotton biomass at different growth stages using vegetation indices (VIs) derived from UAS and satellite images. This research was conducted in a cotton field in Hale County, Texas, in 2021. Data collected include 54 plant samples at different locations for three dates of the growing season. Multispectral images ... O.I. Adedeji, B.P. Ghimire, H. Gu, R. Karn, Z. Lin, W. Guo |
30. Enhancing Spatial Resolution of Maize Grain Yield DataGrain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops. Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used t... J. Siegfried, R. Khosla, D. Mandal, W. Yilma |
31. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of un... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
32. Seed Localization System Suite with CNNs for Seed Spacing Estimation, Population Estimation and DoublesProper seed placement during planting is critical to achieve uniform emergence which optimizes the crop for maximum yield potential. Currently, the ideal way to determine planter performance is to manually measure plant spacing and seeding depth. However, this process is both cost- and labor-intensive and prone to human errors. Therefore, this study aimed to develop seed localization system (SLS) system to measure seed spacing and seeding depth and providing the geo-location of each planted s... A. Sharda, R. Harsha chepally |
33. Precision Nitrogen and Water Management for Optimized Sugar Beet Yield and Sugar ContentSugar beet (SB) production profitability is based on maximizing three parameters: beet yield, sucrose content, and sucrose recovery efficiency. Efficient nitrogen (N) and water management are key for successful SB production. Nitrogen deficits in the soil can reduce root and sugar yield. Overapplication of N can reduce sucrose content and increase nitrate impurities which lowers sucrose recovery. Application of N in excess of SB crop need leads to vigorous canopy growth, while compromising ro... O.S. Walsh, S. Shafian |
34. Agricultural Robots Classification Based on Clustering by Features and FunctionRobotic systems in agriculture (hereafter referred to as agrobots) have become popular in the last few years. They represent an opportunity to make food production more efficient, especially when coupled with technologies such as the Internet of Things and Big Data. Agrobots bring many advantages in farm operations: they can reduce humane fatigue and work-related accidents. In contrast, their large-scale diffusion is today limited by a lack of clarity and exhaustiveness in the regulatory fram... M. Canavari, M. Medici, G. Rossetti |
35. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of CottonThe use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationship... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash |
36. Agronomic Opportunities Highlighted by the Hands Free Hectare and Hands Free Farm Autonomous Farming ProjectsWith agriculture facing various challenges including population increase, urbanisation and both mitigating and managing climate change, agricultural automation and robotics have long been seen as potential solutions beyond precision farming. The Hands Free Hectare (HFH) and Hands Free Farm (HFF) collaborative projects based at Harper Adams University (HAU) have been developing autonomous farming systems since 2016 and have conducted multiple autonomous field crop production cycles since a wor... K.F. Franklin |
37. Possibilities for Improved Decision Making and Operating Efficiency Derived from the Predictability of Autonomous Farming OperationsFor the last 6 years, small autonomous agricultural vehicles have been operating on Harper Adams University’s fields in Shropshire. Starting with a single tractor on a single rectangular hectare (2.5 acres) and moving on to three tractors on 5 irregularly shaped fields covering over 30 hectares (75 acres). Multiple crops have been grown; planting, tending, and harvesting with autonomous tractors and harvesters. The fields are worked using a Controlled Traffic Farming s... M. Gutteridge |
38. Multispectral Assessment of Chickpea in the Northern Great PlainsChickpea is an increasingly important crop in the Montana agricultural system. From 2017 to 2021 the U.S. has planted an average of about 492,000 acres per year with Montana chickpea production accounting for around 44% of the U.S. total (USDA/NASS QuickStats accessed on 2/11/2021). This has led to an increase in breeding efforts for elite varieties adapted to the unique conditions in the Northern Great Plains. Breeding of chickpea often relies on traditional phenotyping techniques that are l... J.M. Vetch |
39. Crop Modeling-based Framework to Explore Region-specific Impact of Nitrogen Fertilizer Management on Productivity and Environmental FootprintTo maintain current crop production while reducing negative environmental impacts, improved understanding of the relative impact of the 4Rs for nitrogen (N) management (rate, time, place, and source) for a given geo-agroecosystem are needed and can play a critical role in driving policy, recommendations, and local practices. However, the timeframe and cost required to assess and characterize the impact of N rate and timing over years and weather conditions through field experiments is prohibi... L. Thompson, S. Archontoulis, P. Grassini, L. Puntel, T. Mieno |
40. Development of Standard Protocols for Soil Tilth Assessment As an Essential Component of Tillage Tool Automation to Improve Soil HealthThe accurate assessment of soil tilth may be pivotal when assessing soil health as part of a holistic process to ensure sustainable and profitable crop production practices. In this study, we focus on demonstrating methodologies for the spatial assessment of soil tilth as ground truth for assessing real-time soil tilth quality sensing technologies. The proposed methodologies for evaluating tillage effects involve the integration of the line transect method for residue distribution analysis. S... C. Dean, A. Klopfenstein, A. Klopfenstein, S.A. Shearer |
41. Optimizing Corn Irrigation Strategies: Insights from NDVI Trends, Soil Moisture Dynamics, and Remote SensingThis comprehensive field experiment systematically examines the impact of varied irrigation rates on corn growth and yield across three treatments: 33%, 67%, and 100% irrigation rates. Utilizing the normalized difference vegetation index (NDVI) as a parameter for vegetation health, distinct patterns emerge throughout key growth stages. The 100% irrigation treatment consistently exhibits superior vegetation health, sustaining higher NDVI values across all stages, while the 33% treatment reveal... J.O. Abon, A. Sharda |
42. Hyperspectral Sensing to Estimate Soil Nitrogen and Reduce Soil Sampling IntensityRecognizing soil's critical role in agriculture, swift and accurate quantification of soil components, specifically nitrogen, becomes paramount for effective field management. Traditional laboratory methods are time-consuming, prone to errors, and require hazardous chemicals. Consequently, this research advocates the use of non-imaging hyperspectral data and VIS-NIR spectroscopy as a safer, quicker, and more efficient alternative. These methods take into account various soil components, i... W.A. Admasu, D. Mandal, R. Khosla |
43. Changes in Soil Chemical and Physical Properties After a Flooding Event in ChileDuring the winter of 2023, ridges were made to plant French prunes (Prunus domestica). After building the ridges, the soil was surveyed using gamma radiation technology (SoilOptix technologies, Ontario, CA). Due to the intense rains that occurred at the end of august 2023, the Cachapoal River, the main water supply of the O’Higgins region, left its course and flooded several fields, including the one where the ridges had been built, destroying them. Ridges were washed out... R.A. Ortega, H.P. Poblete |
44. Extension Program Prioritization Guides Web-mapping Application Delivery to RanchersCooperative Extension has a long history of helping agricultural producers address their current needs and emerging public issues; often through training in the use of technologies that are not yet widely adopted. The quality of geospatial data and tools to visualize and analyze that data continues to improve. However, barriers exist to rancher adoption of geospatial decision support tools. These barriers can include costs, ease of use, and privacy concerns. The sustainability of beef ca... W. Boyer |
45. Fertigation Management Strategies Effect on Residual Nitrates in the Soil Profile and Ground WaterNitrogen is an input that is vital for growth and productivity within the corn belt states of the U.S. However, when nitrogen as an input into agricultural cropping systems is often over-applied and thus not optimally utilized by the cropping system. Therefore, it is at risk of loss within the environment through processes of leaching, denitrification, and volatilization. This is a major concern in Nebraska, as the reality is that much of the state’s groundwater has been contaminated wi... K.J. Bathke, T. Cross, J.D. Luck |
46. Integrating Collected Field Machine Vibration Data with Machine Learning for Enhanced Precision in Agricultural OperationsIn this research, we provide an innovative combination of the Agricultural Vibration Data Acquisition Platform (avDAQ) with cutting-edge machine learning methods for data collecting from agricultural machinery. The avDAQ system, which has a strong connection to a GPS sensor, provides precise spatial information to the vibration data that has been collected, providing an in-depth explanation of the locations of the vibrations. The objective is to fully utilize avDAQ's potential to extract ... S. Janbazialamdari, E. Brokesh |