Proceedings
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| Filter results54 paper(s) found. |
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1. Designing Variable-width Filter Strips Using GIS And Terrain AnalysisFilter strips are a widely-used practice for reducing the load of pollutants that leave agricultural fields in overland runoff. They are typically designed to intercept uniformly-distributed runoff with a constant width strip along a field margin. Non-uniform runoff flow, however, can reduce the effectiveness of a constant-width filter strip. Non-uniform flow is created by topographic undulations and swales in fields that concentrate runoff into certain locations... M.G. Dosskey, T.G. Mueller |
2. Multi, Super Or Hyper Spectral Data, The Right Way From Research Toward Application In AgricultureRemote sensing provides opportunities for diverse applications in agriculture. One consideration of maximizing the utility of these applications, is the need to choose the most efficient spectral resolution. Picking the optimal spectral resolutions (multi, super or hyper) for a specific application is also influenced by other factors (e.g., spatial and temporal resolutions) of the utilized device. This work focuses mainly on... D.J. Bonfil, I. Herrmann, A. Pimstein, A. Karnieli |
3. Weeds Detection By Ground-level Hyperspectral ImagingWeeds are a severe pest in agriculture, causing extensive yield loss. Weed control of grass and broadleaf weeds is commonly performed by applying selective herbicides homogeneously all over the field. As presented in several studies, applying the herbicide only where needed has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically... U. Shapira , I. Herrmann, A. Karnieli, D.J. Bonfil |
4. Assessment Of Field Crops Leaf Area Index By The Red-edge Inflection Point Derived From Venus BandsThe red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional status.... I. Herrmann, A. Pimstein, A. Karnieli, Y. Cohen, V. Alchanatis , D.J. Bonfil |
5. The Use Of A Ground Based Remote Sensor For Winter Wheat Grain Yield Prediction In Northern PolandThe aim of the research was to investigate if algorithms developed for winter wheat, cv. Trend, yield predictions, based on ground measured GNDVI, differ significantly between 2 sequent years. The research was conducted in Pomerania, northern Poland (54° 31' N 17° 18' E) on sandy loam soils. The strip-trial design was used to compare the effect of 6 N treatments: 0, 50, 100, 150, 200 and 250 kg ha-1, applied as one dose at the beginning... S.M. Samborski, D. Gozdowski, S.E. Dobers |
6. Changes Of Data Sampling Procedure To Avoid Energy And Data Losses During Microclimates Monitoring With Wireless Sensor Networks... J.C. Benavente, C.E. Cugnasca, M.F. Barros, H.P. Santos, G. Http://icons.paqinteractive.com/16x16/ac |
7. A Comparison Of Alternative Methods For Prioritizing Buffer Placement In Agricultural Watersheds For Water Quality ImprovementConservation buffers are a widely used best management practice for reducing agricultural nonpoint source pollution. Various governmental programs and community initiatives have been implemented to adopt conservation buffers for water quality improvement. Since there is substantial cost for installing conservation buffers in watersheds, cost-effectiveness would be improved by targeting buffers to locations where they would produce greater benefit and to avoid locations... Z. Qiu, M.G. Dosskey, D. Frieberg |
8. Spatial And Vertical Distribution Of Soil P, K, And Mg Content In A Vineyard Of The Do Ca Rioja Using Grid And Target Sampling MethodsKnowledge of spatial variability of soil nutrient contents is very important to design a fertilization strategy based on the needs of the vine. Matching fertilization and nutritional plant needs is very important due to the influence of nutritional status of vineyards on productive and qualitative factors. The aim of this work was to study the spatial and vertical variability of P, K and Mg in a vineyard soil by two methods: (i) the grid sampling at three depth ranges (0-30,... O. Unamunzaga, A. Castell, G. Besga, R. Perez-parmo, A. Aizpurua |
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 growth... K.D. Reitsma, T.E. Schumacher |
10. Generating Herbicide Effective Application Rate Maps Based On GPS Position, Nozzle Pressure, And Boom Section Actuation Data Collected From Sprayer Control SystemsThe application of pre- and post- emergence burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials. The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides. While automatic boom section control has provided benefits, pressure differences across... J.D. Luck, A. Sharda, S.K. Pitla, J.P. Fulton, S.A. Shearer |
11. Exploiting the Dmc Satellite Constellation for Applications in Precision AgricultureThis paper presents the unique capabilities of the DMC constellation of optical sensors, and examples of how a number of organisations around the world are exploiting this powerful data source for applications in precision farming. The DMC consists of five satellites built in the UK by Surrey Satellite Technology Ltd, each carrying a wide swath (650km) optical sensor. It is an international programme of satellite ownership and groundstations, with joint campaigns being coordinated centrally... P. Stephens, S. Mackin, G. Holmes |
12. Influence Of Phosphorus Application With Or Without Nitrogen On Oat (Avena Sativa) Grass Nutritive Value And In Situ Digestion Kinetics In Buffalo BullsFodder is the mainstay of ruminant production in majority of developing countries. However, its low yield and poor quality are considered considerable constrains which impede ruminant productivity. Fodder production and its nutritive value can be enhanced by ensuring adequate supply and utilization of nutrients... M.U. Nisa, I. Babar, M. Sarwar, N.A. Tauqir, M.A. Shahzad |
13. Precision Agriculture Initiative for Karnataka – A New Direction for Strengthening Farming CommunityStrengthening agriculture is crucial to meet the myriad challenges of rural poverty, food security, unemployment, and sustainability of natural resources and it also needs strengthening at technical, financial and management levels. In this context... U.K. Shanwad, M.B. Patil, V. H, M. B.g , P. R, R. N.l. , S. S, R. Khosla, V.C. Patil |
14. Ground Level Hyperspectral Imagery For Weeds Detection In Wheat FieldsWeeds are a severe pest in agriculture resulting in extensive yield loss. Applying precise weed control has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically locate and identify weeds in order to allow precise control. The objective of the current work is to detect annual... D.J. Bonfil, U. Shapira, A. Karnieli, I. Herrmann, S. Kinast |
15. Indexes for Targeting Buffer Placement to Improve Water QualityTargeting the placement of vegetative buffers may increase their effectiveness to improve watershed water quality. Several GIS-based indexes have been developed to help planners identify relatively better locations for placing buffers. Conservation planners require consistent and clear recommendations on which index should be used in a given planning... Z. Qiu, M.G. Dosskey |
16. Using Multiplex® to Manage Nitrogen Variability in Champagne Vineyard... L. Marine, M. Manon, G. Claire, P. Laurent, F. Mostafa, C. Zoran, B. Naima, D. Sébastien, G. Olivier |
17. Ultra-low Altitude and Low Spraying Technology Research in PaddyAerial application has characteristics of low-volume, small droplet, and possibility of drift. To control rice planthopper, leaf roller and blast, the research aimed at screening agrichemicals and determining the feasibility of using high concentration of conventional dosage for aerial application. The results showed that... Y. Lan, X. Xue |
18. Comparison of Algorithms for Delineating Management Zones... A.M. Saraiva, R.T. Santos, J.P. Molin |
19. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop ProductivitySite-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang |
20. Precision Sensors For Improved Nitrogen Recommendations In WheatCrop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Montana:... O.S. Walsh, A. Pandey, R. Christiaens |
21. An Evaluation Of HJ-CCD Broadband Vegtation Indices For Leaf Chlorophyll Content EstimationLeaf chlorophyll content is one of the most important biochemical variables for crop physiological status assessment, crop biomass estimation and crop yield prediction in precision agriculture. Vegetation indices were considered effective for chlorophyll content estimation. Although hyperspectral reflectance is proven to be better than multispectral reflectance for leaf chlorophyll content retrieval, the scarcity of available data from satellite hyperspectral... T. Dong, J. Shang, J. Meng, J. Liu |
22. 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 |
23. Performance Evaluation Of Single And Multi-GNSS Receivers In Agricultural Field ConditionsSelection of appropriate receivers and utilization methods of positioning systems are important for better positioning in different applications of precision agriculture. Objective of this research was to evaluate the performance of single and multi-GNSS receivers at stationary and moving conditions in typical Korean agricultural sites such as open field, orchard area, and mountainous area A single-GNSS receiver (Model: R100; Hemisphere GNSS, Scottsdale, AZ, USA) and a multi-GNSS... Y. Kim, M. Song, S. Chung , M.S. Kabir, Y. Huh |
24. Prediction Of Cation Exchange Capacity Using Visible And Near Infrared SpectroscopyCation exchange capacity (CEC) of the soil is a measure of the soil ability to hold positively charged ions and is an important indicator of soil physicochemical characteristic. It is an important property for site specific management of soil nutrients in precision agriculture. The conventional analytical methods used for the determination of CEC are expensive, difficult and time consuming, because different cations must be extracted and determined. Visible and near infrared (vis-NIR) spectroscopy... Y. Ulusoy, Z. Tümsavas, A.M. Mouazen, Y. Tekin |
25. Refractive Index Based Brix Measurement System for Sugar and Allied IndustriesAn attempt has been made to design optimization of Refractormetric based method for the measurement of Brix. Optimization of various constructional parameters including selection and location of source, prism and detector, position of source, angular position and height of source from prism plane, divergent angle of source, refractive index of prism, size of prism, the location of detector to pick up the optimum reflected light, refractive index of sample, critical angle, choice of suitable... M.L. Dongare, B.T. Jadhav, A.D. Shaligram |
26. Wireless Sensor System for Variable Rate IrrigationVariable rate irrigation (VRI) systems use intelligent electronic devices to control individual sprinklers or groups of sprinklers to deliver the desired amount irrigation water at each specific location within a field according to VRI prescriptions. Currently VRI systems, including software tools for generate prescription maps, are commercially available for VRI practices. However, algorithms and models are required to determine the desired amount of water that needs to be applied based on the... R. Sui, J. Baggard |
27. Barriers to Adoption of Smart Farming Technologies in GermanyThe number of smart farming technologies available on the market is growing rapidly. Recent surveys show that despite extensive research efforts and media coverage, adoption of smart farming technologies is still lower than expected in Germany. Media analysis, a multi stakeholder workshop, and the Adoption and Diffusion Outcome Prediction Tool (ADOPT) (Kuehne et al. 2017) were applied to analyze the underlying adoption barriers that explain the low to moderate adoption levels of smart farming... M. Gandorfer, S. Schleicher, K. Erdle |
28. Farm Soil Moisture Mapping Using Reflected GNSS SNR Data Onboard Low Level Flying AircraftSoil moisture/water content monitoring (spatial and temporal) is a critical component of farm management decision primarily for crop/plant growth and yield improvement, but also for optimization of practice such as tillage and field treatments. Satellite humidity probes do not deliver the relevant resolution for farming purposes. Ground moisture probes only provide punctual measurements and do not reflect the true spatial variability of soil moisture. Previous studies have demonstrated... L. Ameglio, J. Darrozes, J. Dreyer |
29. Improving Yield Prediction Accuracy Using Energy Balance Trial, On-the-Go and Remote Sensing ProcedureOur long term experience in the ~23.5 ha research field since 2001 shows that decision support requires complex databases from each management zone within that field (eg. soil physical and chemical parameters, technological, phenological and meteorological data). In the absence of PA sustainable biomass production cannot be achieved. The size of management zones will be ever smaller. Consequently, the on the go and remote sensing data collection should be preferred. The... A. Nyéki , G. Milics, A.J. Kovács, M. Neményi, I. Kulmány, S. Zsebő |
30. Snap Bean Flowering Detection from UAS Imaging SpectroscopySclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmanned... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert |
31. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management strategies... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus |
32. Feature Extraction from Radial Descriptor Lines for Body Condition Scoring of CowsBody condition score (BCS) is considered as one of the most important indices for managing dairy cows, which is used to evaluate fat cover and changes in body condition. Dairy farmers should be aware of their cows BCS to be able to identify the patient cows on time and manage diets when needed. In this study, we have introduced a new index which uses Radial Descriptor Lines (RDL) for BC scoring. Based on the fact that the fatter the cow the smoother the back surface, we hypothesised that the changes... A. Jafari, F. Karimi, A. Werner, S. Ghoreishi, S. Kargar |
33. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision AgriculturePrecision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protein... J. Sheppard, A. Peerlinck, B. Maxwell |
34. Map Whiteboard As Collaboration Tool for Smart Farming Advisory ServicesPrecision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook. The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr. |
35. Fruit Fly Electronic Monitoring SystemInsects are a constant threat to agriculture, especially the cultivation of various types of fruits such as apples, pears, guava, etc. In this sense, it is worth mentioning the Anastrepha genus flies (known as fruit fly), responsible for billionaire losses in the fruit growing sector around the world, due to the severity of their attack on orchards. In Brazil, this type of pests has been controlled in most product areas by spraying insecticides, which due to the need for prior knowledge regarding... C.L. Bazzi, F.V. Silva, L. Gebler, E.G. Souza, K. Schenatto, R. Sobjak, R.S. Dos santos, A.M. Hachisuca, F. Franz |
36. Micro-climate Prediction System Using IoT Data and AutoMLMicroclimate variables like temperature, humidity are sensitive to land surface properties and land-atmosphere connections. They can vary over short distances and even between sections of the farm. Getting the accurate microclimate around the crop canopy allows farmers to effectively manage crop growth. However, most of the weather forecast services available to farmers globally, either by the meteorological department or universities or some weather app, provide weather forecasts for larger... A. Sharma, R.S. Jalem, M. Dash |
37. Investigating the Potential of Visible and Near-infrared Spectroscopy (VNIR) for Detecting Phosphorus Status of Winter Wheat Leaves Grown in Long-term TrialThe 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 |
38. Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat ProductionField-specific fertilizer rate optimization is known to be beneficial for improving farming profit, and profits can be further improved by dividing the field into smaller plots and applying site-specific rates across the field. Finding optimal rates for these plots is often based on data gathered from said plots, which is used to determine a yield response curve, telling us how much fertilizer needs to be applied to maximize yield. In related work, we use a Convolutional Neural Network, known... A. Peerlinck, J. Sheppard, G.L. Morales luna, P. Hegedus, B. Maxwell |
39. Multi-sensor Imagery Fusion for Pixel-by-pixel Water Stress MappingEvaluating water stress in agricultural fields is fundamental in irrigation decision-making, especially mapping the in-field water stress variability as it allows real-time detection of system failures or avoiding yield loss in cases of unplanned water stress. Water stress mapping by remote sensing imagery is commonly associated with the thermal or the short-wave-infra-red (SWIR) bands. However, integration of multi-sensors imagery such as radar imagery or sensors with only visible and near-infra-red... O. Beeri, R. Pelta, Z. Sade, T. Shilo |
40. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-upThe concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta |
41. Teaching Mathematics Towards Precision Agriculture Through Data Analysis and ModelsPrecision agriculture is used in a wide variety of field operations and agricultural practices that affect our daily lives. Many fields of agriculture are increasingly adopting equipment automation, robotics, and machine learning techniques. These all lead to recognize that data collection and exploitation is a valuable tool assisting in real-time farming and livestock decisions. Thus, the immediate need to empower students in Agriculture Sciences with mathematical tools using data analysis is... R. Sviercoski |
42. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm ResearchCrop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed to... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa |
43. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management NebraskaA statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%), intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies. ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti |
44. 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 |
45. 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 |
46. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, RiversideFunded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus |
47. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico ApproachWater stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad |
48. Supervised Hyperspectral Band Selection Using Texture Features for Classification of Citrus Leaf Diseases with YOLOv8Citrus greening disease (HLB), a disease caused by bacteria of the Candidatus Liberibacter group, is characterized by blotchy leaves and smaller fruits. Causing both premature fruit drop and eventual tree death, HLB is a novel and significant threat to the Florida citrus industry. Citrus canker is another serious disease caused by the bacterium Xanthomonas citri subsp. citri (syn. X. axonopodis pv. citri) and causes economic losses for growers from fruit drops and blemishes. Citrus canker... Q. Frederick, T. Burks, P.K. Yadav, M. Dewdney, J. Qin, M. Kim |
49. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |
50. Crop and Water Monitoring Networks with Low-cost, Internet of Things TechnologyMaking meaningful changes in agroecosystems often requires the ability to monitor many environmental parameters to accurately identify potential areas for improvement in water quality and crop production. Increasingly, research questions are requiring larger and larger monitoring networks to draw applicable insights for both researchers and producers. However, acquiring enough sensors to address a particular research question is often cost-prohibitive, making it harder to draw meaningful conclusions... A.J. Brown, E. Deleon, E. Wardle |
51. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging TechniquesThe precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and automated... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan |
52. Utilizing ArUco Markers to Define Implement BoundariesJohn Deere and Blue River Technology’s autonomous tillage system combines multidisciplinary efforts and cutting-edge technology to achieve Level 5—Unsupervised Autonomy. To create this engineering marvel, countless parameters need defined to ensure safe operation of the system; some of these parameters are static, while other of these parameters are dynamic. One particular set of parameters define the tillage implement’s boundaries for the software stack to utilize, and today... R. Sleichter |
53. Comparing Proximal and Remote Sensors for Variable Rate Nitrogen Management in CottonSensing and variable rate technology are becoming increasingly important in precision agriculture. These technologies utilize sensors to monitor crop growth and health, enabling informed decisions such as diagnosing nitrogen (N) stress and applying variable rates of N. Sensor-based solutions allow for customized N applications based on plant needs and environmental factors. This approach has led to notable reductions in N application rates, minimized N losses by improving N use efficiency (NUE),... A. Bhattarai, A. Jakhar, L. Bastos, G.J. Scarpin |
54. TEG Automation Solutions - Sponsor Presentation... V. Oliveira |