Proceedings
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1. Early Detection of Oil Palm Fungal Disease Infestation Using A Mid-Infrared Spectroscopy TechniqueBasal stem rot (BSR) caused by Ganoderma boninense is known as the most destructive disease of oil palm plantations in Southeast Asia. Ganoderma could potentially reduce the market share of palm oil for Malaysia. Currently Malaysia produces about 50% of the world’s supply of palm oil. Early, accurate, and non-destructive diagnosis of Ganoderma fungal infection is critical for management of this disease. Early disease management of Ganoderma could also prevent great losses in production and... S. Liaghat, S. Mansor, H. Shafri, S. Meon, R. Ehsani, S. Azam, N. Noh |
2. Bayesian Methods for Predicting LAI and Soil MoistureCrop models describe the growth and development of a crop interacting with soil, climate, and management... M. Majdi, D. Benjamin, D. Marie-france |
3. OptiThin - Precision Fruiticulture by Tree-Specific Mechanical ThinningApple cultivars show biennial fluctuations in yields (alternate bearing). The phenomenon is induced by reduced yields in one year due to freeze damage, low pollination rate or other reasons. Consequently, trees develop many flower buds that blossom in the following year. The many flowers lead to a high number of small fruits that won’t be accepted on the market. Endogenous factors (phytohormones and carbohydrate allocation) subsequently establish the biennial cycle. The alternate bearing... A. Betz, H. Benny, M. Jens, M. Özyurtlu, M. Pflanz, T. Rachow-autrum, A. Schischmanow, M. Scheele, J. Schrenk, L. Schrenk, M. Zude, R. Gebbers |
4. Estimating Soil Quality Indicators with Diffuse Reflectance SpectroscopyKnowledge of within-field spatial variability in soil quality indicators is important to assess the impact of site-specific management on the soil. Standard methods for measuring these properties require considerable time and expense, so sensor-based approaches would be... R.J. Kremer, N.R. Kitchen, K.A. Sudduth, D.B. Myers |
5. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological ConditionsThis study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. campoy, C. Wellington, W. Swen, J. Camergo neto |
6. Physiological Repsonses Of Corn To Variable Seeding Rates In Landscape-Scale Strip TrialsMany producers now have the capability to vary seeding rates on-the-go. Methods are needed to develop variable rate seeding approaches in corn but require an understanding of the physiological response of corn to soil-landscape and weather conditions. Interplant competition fundamentally differs at varied seeding rate and may affect corn leaf area, transpiration, plant morphology, and assimilate partitioning. Optimizing these physiological effects with optimal seeding rates in a site-specific... D.B. Myers, N.R. Kitchen, K.A. Sudduth, B.J. Leonard |
7. Development of a PWM Precision Spraying System for Unmanned HelicopterApplication of protection materials is a crucial component in the high productivity of agriculture. Motivated by the needs of aerial precision application, in this paper we present a pulse width modulation (PWM) based precision spraying system for unmanned helicopter. The system is composed of the tank, pipelines, pump, nozzles and the automatic control unit. The system can spray with a constant rate automatically when the speed of the UAV fluctuates between 1 m/s to 8 m/s. The application rate... R. Zhang, L. Chen, T. Yi, Y. Guo, H. Zhang |
8. Selection and Utility of Uncooled Thermal Cameras for Spatial Crop Temperature Measurement Within Precision AgricultureSince previous research used local, single-point measurements to indicate crop water stress, thermography is presented as a technique capable of measuring spatial temperatures supporting its use for monitoring crop water stress. This study investigated measurement accuracy of uncooled thermal cameras under strict environmental conditions, developed hardware and software to implement uncooled thermal cameras and quantified intrinsic properties that impact measurement accuracy and repeatability.... D.L. Mangus, A. Sharda |
9. Spectral Vegetation Indices to Quantify In-field Soil Moisture VariabilityAgriculture is the largest consumer of water globally. As pressure on available water resources increases, the need to exploit technology in order to produce more food with less water becomes crucial. The technological hardware requisite for precise water delivery methods such as variable rate irrigation is commercially available. Despite that, techniques to formulate a timely, accurate prescription for those systems are inadequate. Spectral vegetation indices, especially Normalized Difference... J. Siegfried, R. Khosla, L. Longchamps |
10. Spatial and Temporal Variation of Soil Nitrogen Within Winter Wheat Growth SeasonThis study aims to explore the spatial and temporal variation characteristics of soil ammonium nitrogen and nitrate nitrogen within winter wheat growth season. A nitrogen-rich strip fertilizer experiment with eight different treatments was conducted in 2014. Soil nitrogen samples of 20-30cm depth near wheat root were collected by in-situ Macro Rhizon soil solution collector then soil ammonium nitrogen and nitrate nitrogen content determined by SEAL AutoAnalyzer3 instrument. Classical statistics... X. Song, G. Yang, Y. Ma, R. Wang, C. Yang |
11. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, BrazilIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphic... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto |
12. Utilizing Space-based Technology for Cotton Irrigation SchedulingAccurate soil moisture content measurements are vital to precision irrigation management. Electromagnetic sensors such as capacitance and time domain reflectometry have been widely used for measuring soil moisture content for decades. However, to estimate average soil moisture content over a large area, a number of ground-based in-situ sensors would need to be installed, which would be expensive and labor intensive. Remote sensing using the microwave spectrum (such as GPS signals) has been used... A. Khalilian, X. Qiao, J.O. Payero, J.M. Maja, C.V. Privette, Y.J. Han |
13. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy TemperatureDevelopment of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment included... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki |
14. Spatial Variability and Correlations Between Soil Attributes and Productivity of Green Corn CropIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphic... W.J. Souza, S.H. Benez, P.H. Nakazawa, A.J. Santana neto, L.C. Citon, V.S. Akune |
15. Translating Data into Knowledge - Precision Agriculture Database in a Sugarcane Production.The advent of Information Technology in agriculture, surveying and data collection became a simple task, starting the era of "Big Data" in agricultural production. Currently, a large volume of data and information associated with the plant, soil and climate are collected quick and easily. These factors influence productivity, operating costs, investments and environment impacts. However, a major challenge for this area is the transformation of data and information... G.M. Sanches, O.T. Kolln, H.C. Franco, P.S. Magalhaes, D.G. Duft |
16. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane FieldsOne important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco |
17. Sensor-based Nitrogen Applications Out-performed Producer-chosen Rates for Corn in On-farm DemonstrationsOptimal nitrogen fertilizer rate for corn can vary substantially within and among fields. Current N management practices do not address this variability. Crop reflectance sensors offer the potential to diagnose crop N need and control N application rates at a fine spatial scale. Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer. Fifty-five replicated on-farm demonstrations... P. Scharf, K. Shannon, K. Sudduth, N. Kitchen |
18. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in CornRemotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia |
19. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPTAgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy |
20. Precision Farming Basics Manual - a Comprehensive Updated Textbook for Teaching and Extension EffortsToday precision agricultural technologies are limited by the lack of a workforce that is technology literate, creative, innovative, fully trained in their discipline, able to utilize and interpret information gained from information-age technologies to make smart management decisions, and have the capacity to convert locally collected information into practical solutions. As part of a grant entitled Precision Farming Workforce Development: Standards, Working Groups, and Experimental Learning... K. Shannon |
21. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility StudyThe fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffuse... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki |
22. Rationale for and Benefits of a Community for On-Farm Data SharingMost data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger |
23. Precision Nitrogen Management Based on Nitrogen Removal in Rainfed WheatGrowers of hard red spring wheat may capture price premiums for maximizing the protein concentration of their grain. Nitrogen (N) nutrition adequacy is crucial to achieving high grain protein concentration. The objective of this study was to determine the usefulness of N removal maps by comparing grain protein, yields, and dollar returns obtained from this precision N management approach with that from conventional uniform N management. Strip plot experiments were designed to compare spatially... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long |
24. On-combine Near Infrared Spectroscopy Applied to Prediction of Grain Test WeightWhole grain near infrared (NIR) spectroscopy is a widely accepted method for analysis of the protein and moisture contents of grain, but is seldom applied to predict test weight. Test weight is a widely used specification for grading of wheat and predictor of flour yield. The objective of this study was to determine whether NIR spectroscopy could be used for measuring the test weight of grain. Reference grain samples of hard red spring wheat were obtained from dryland fields in the semiarid Negev... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long |
25. Using Pricise Gps/gis Based Barley Yield Maps to Predict Site-specific Phosphorus RequirementsThree fundamental stages and technologies as main parts of a precision farming project should be considered precisely. These are access to actual multi- dimensional variability detail or variable description on farms, creating a suitable variable-rate technology, and finally providing a decision support system. Some results of a long term practical research conducted by the author in Upon-Tyne Newcastle University of UK for reliable yield monitoring and mapping were utilised to prepare this paper. The... A. Sanaei |
26. Seasonal Patterns of Vegetative Indices Over Cropping SystemsRemote sensing of reflectance in the visible and near-infrared portions of the spectrum has been used for agronomic applications for a number of years. The combination of different wavelengths into vegetative indices have proven useful for a variety of applications that range from biomass, leaf area, leaf chlorophyll, yield, crop residue, and crop damage. To help refine our understanding of vegetative indices studies were conducted on corn (Zea mays L.), soybean (Glycine max (L.) Merr.), wheat... J.L. Hatfield, J.H. Prueger |
27. Spatial Patterns of Nitrogen Response Within Corn Production FieldsCorn (Zea mays L.) yield response to nitrogen (N) application is critical to being able to develop management practices that reduce N application or improve N use efficiency. Nitrogen rate studies have been conducted within small plots; however, there have been few field scale evaluations. This study was designed to evaluate N response across 14 corn fields in central Iowa using different rates of N applied in strips across fields. These fields ranged in size from 15 to 130 ha with N... J.L. Hatfield |
28. Practical and Affordable Technologies for Precision Agriculture in Small Fields: Present Status and Scope in IndiaThe objective of this review paper is to find out practical and affordable precision agriculture(PA) technologies present status and scope in India that are suitable for small fields. The judicious use of inputs like water, fertilizers, herbicides, pesticides and better management of farm equipments will increase the net profit for farmers. The important components of PA in India which are being used for small lands are Geographic Information System(GIS), laser land leveler, leaf color chart,... S. Kumar, M. Singh, H. Mirzakhaninafchi, R.U. Modi, M. Ali, M. Bhardwaj, R. Soni |
29. Realising the Full Potential of Precision Agriculture: Encouraging Farmer 'Buy-in' by Building Trust in Data SharingUncertainty around the ownership, privacy and security of farm data are most commonly the reasons cited for farmer’s reluctance to “buy-in” to big data in agriculture. Evidence provided to the recent US Committee on Commerce, Science, and Transportation Subcommittee on Consumer Protections, Product Safety, Insurance, and Data Security, United States Senate Technology in Agriculture: Data Driven Farming (Nov 2017) highlighted that “data ownership, and related... L. Wiseman, J. Sanderson |
30. Delineation of Site-Specific Nutrient Management Zones to Optimize Rice Production Using Proximal Soil Sensing and Multispectral ImagingEvaluating nutrient uptake and site-specific nutrient management zones in rice in Costa Rica from plant tissue and soil sampling is expensive because of the time and labor involved. In this project, a range of measurement techniques were implemented at different vintage points (soil, plant and UAVs) in order to generate and compare nutrient management information. More precisely, delineation of site-specific nutrient management zones were determined using 1) georeferenced soil/tissue... J.E. Villalobos, J.S. Perret, K. Abdalla, C.L. Fuentes, J.C. Rodriguez, W. Novais |
31. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial VehicleAbove-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas |
32. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm ProfitabilityIntra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White |
33. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide EmissionsTo minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions. Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller |
34. 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 |
35. 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 |
36. 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 resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal |
37. 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 acquire... R. Karn, H. Gu, O. Adedeji, W. Guo |
38. 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 from... O.I. Adedeji, B.P. Ghimire, H. Gu, R. Karn, Z. Lin, W. Guo |
39. 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 to... J. Siegfried, R. Khosla, D. Mandal, W. Yilma |
40. Automated Southern Leaf Blight Severity Grading of Corn Leaves in RGB Field ImageryPlant stress phenotyping research has progressively addressed approaches for stress quantification. Deep learning techniques provide a means to develop objective and automated methods for identifying abiotic and biotic stress experienced in an uncontrolled environment by plants comparable to the traditional visual assessment conducted by an expert rater. This work demonstrates a computational pipeline capable of estimating the disease severity caused by southern corn leaf blight in images of field-grown... C. Ottley, M. Kudenov, P. Balint-kurti, R. Dean, C. Williams |
41. Utilizing Hyperspectral Field Imagery for Accurate Southern Leaf Blight Severity Grading in CornCrop disease detection using traditional scouting and visual inspection approaches can be laborious and time-consuming. Timely detection of disease and its severity over large spatial regions is critical for minimizing significant yield losses. Hyperspectral imagery has been demonstrated as a useful tool for a broad assessment of crop health. The use of spectral bands from hyperspectral data to predict disease severity and progression has been shown to have the capability of enhancing early... G. Vincent, M. Kudenov, P. Balint-kurti, R. Dean, C.M. Williams |
42. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop ProtectionIn the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen |
43. Delineation of Site-Specific Management Zones using Sensor-based Data for Precision N managementNitrogen is a critical nutrient influencing crop yield, but the common practice of uniform application of nitrogen fertilizer across a field often results in spatially variable nitrogen availability for the crop, leading to over-application in some areas and under-application in others. This imbalance can cause economic losses and significant environmental issues. Precision nitrogen application involves application of N fertilizers based on soil conditions and crop requirements. One approach for... R. Joshi, R. Khosla, D. Mandal, R. Unruh, W.A. Admasu |
44. Delineating Dynamic Variable Rate Irrigation Management ZonesAgriculture irrigation strategies have traditionally been made without accounting for the natural small-scale variability in the field, leading to uniform applications that often over-irrigate parts of the field that do not need as much water. The future success of irrigated agriculture depends on advancements in the capability to account for and leverage the natural variability in croplands for optimum irrigation management both in space and time. Variable Rate Irrigation (VRI) management offers... R. Unruh, W.A. Yilma, D. Mandal, R. Joshi, R. Khosla |
45. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep LearningCrop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo |
46. The Evaluation of Spatial Response to Potassium in SoybeansIn agriculture, the nutrients that are in the largest demand are nitrogen (N), phosphorus (P), and potassium (K), as product demand increases so does demand for fertilizers. In the case of potassium, most soils can provide potassium in amounts that exceed crop demand; however the potassium within the soil is not always readily available to the crop, this leads to producers apply potassium to their crops even though soil tests suggests otherwise. One such crop where potassium is in demand... S. Akin, B. Arnall |
47. Influence of Potassium Variability on Soybean YieldDue to its role as a plant essential nutrient, Potassium (K) serves as a fundamental component for plant growth. Soybeans are heavily reliant upon this nutrient for root growth and the production of pods, so much so that after nitrogen, potassium is the second most in-demand nutrient. Much of the overall soybean crop grown in Oklahoma is not managed with the fertility of K directly in mind. However, as the potential and expectation for greater yield increases, so does interest from producers... J. Derrick, S. Akin, R. Sharry, B. Arnall |
48. Implementation of Autonomous Material Re-filling Using Customized UAV for Autonomous Planting OperationsThis project introduces a groundbreaking use case for customized Unmanned Aerial Vehicles (UAVs) in precision agriculture, focused on achieving holistic autonomy in agricultural operations through multi-robot collaboration. Currently, commercially available drones for agriculture are restrictive in achieving collaborative autonomy with the growing number of unmanned ground robots, limiting their use to narrow and specific tasks. The advanced payload capacities of multi-rotor UAVs,... V. Muvva, H. Mwunguzi, S. Pitla, K. Joseph |
49. Predicting Soybean Yield Using Remote Sensing and a Machine Learning ModelSoybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore |