Proceedings
Authors
| Filter results53 paper(s) found. |
|---|
1. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial InterpolationStudy on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracting... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang |
2. Optimizing Path Planning By Avoiding Short Corner Tracks... J.P. Molin, M. Spekken |
3. Design Of A Data Acquisition System For Weighing LysimetersThe weighing lysimeter is an important tool for scientists to conduct... C. Zhang, X. Xue, L. Chen, W. Huang |
4. Monitoring Drought Stress Index in Wheat Field of Mongolia Using Remote SensingWater stress during crop growth, even during short periods of a couple of weeks, is a major cause of yield reduction. The complexity in defining the magnitude of such water stress is due to diversity of crops grown in a given location, variability in soil type and conditions, spatial variability of rainfall, delay in timely of agriculture, and diversity in crop management practices. The problem associated with drought is... B.M. Banzragch, N.M. Damdinpurev, E.M. Batzorig |
5. Temporal N Status Evaluation Using Hyperspectral Vegetation Indices in a Potato CropThe amount and timing of nitrogen (N) fertilization represents a leading issue in precision agriculture, especially for potato (Solanum tuberosum L.) crop since N is an essential element for plant growth and tuber yield. Therefore, the ability to assess in-season crop N status from non-destructive methods such as proximal sensing is a promising alternative to optimize N fertilization... A. Cambouris, K. Chokmani, T. Morier |
6. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft SystemsSmall Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infrared... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt |
7. Fungiprecise - A German Project For Precise Real-Time Fungicide Application In Winter WheatRegarding to real-time or online technologies in recent years, new technologies has been introduced into practical farming especially in the field of nitrogen application. These technologies are based on sensors mainly detecting the canopy reflectance. In the field of plant protection, although few sensor-based real-time technologies in weed control and growth regulator application are marked available, solutions for fungicide application are mostly missing currently. Amongst others... P. Leithold, T. Volk, K. Dammer |
8. A Dual Motor Actuator Used To Detach Fruit By Shaking Limbs Of Fruit TreesMechanizing the fruit removal operation during fresh-market apple harvesting will result in considerable cost savings for fruit growers. This study introduces a mechanical fruit removal technique that uses a unique limb shaking mechanism called a Dual Motor Actuator (DMA). The DMA was developed as an infinitely variable end-effector that applies rhythmic motions to a fruiting limb to remove fruit. The novelty of the DMA design is the use of two eccentrics mounted to electric motors... M. De kleine, M. Karkee, Q. Zhang, K. Lewis |
9. Measuring And Mapping Sugarcane GapsSugarcane is an important crop in tropical regions of the world and especially for Brazil, the largest sugar supplier in the market, also running a domestic fleet of flex-fuel driven vehicles based on ethanol. Site specific production management can impact sugarcane production by increasing yield and reducing cost. Sugarcane fields are planted each five years, in average, and an important parameter that is measured after the planting operation is the gaps caused by problems during planting... J.P. Veiga, D.S. Cavalcante, J.P. Molin |
10. Effect Of Time Of Application On Spray Coverage Using Solid Set Canopy Delivery SystemPermanent or solid set canopy delivery system can be used for foliar application in tree fruit orchards. The emitters are placed along the tree rows and are very close to tree canopy. During spray application droplets quickly get deposited on tree canopy and coverage of up to 90% could be achieved. However concerns still exist regarding critical time required to achieve target coverage using SSCD system. This knowledge of selecting an appropriate application time could help growers... M. Karkee, Q. Zhang, A. Sharda |
11. The Use Of A Multirotor And High-Resolution Imaging For Precision Horticulture In Chile: An Industry PerspectiveAs part of the prototype development of a yield forecasting and precision agriculture service for Chilean horticulture, we evaluated the use of an eight-rotor Mikrokopter for high-resolution aerial imaging to support ground-based surveys. Specific considerations for UAV and communications performance under Chilean conditions are windy conditions, limited space for take-off and landing in orchards, tree height and plantation density, and the presence of high metal contents in soils. We discuss... I. Zamora, D. Wulfsohn |
12. Site-specific Scale Efficiency Determined by Data Envelopment Analysis of Precision Agriculture Field DataSince its inception and acceptance as a benchmarking tool within the economics literature, data envelopment analysis (DEA) has been used primarily as a means of calculating and ranking whole-farm entities marked as decision making units (DMU) against one another. Within this study, instead of ranking the entire farm operation against similar peers that encompass the study, individual data points from within the field are evaluated to analyze the site-specific technical efficiencies estimated... J.L. Maurer, T.W. Griffin, A. Sharda |
13. Positioning Strategy of Maize Hybrids Adjusting Plant Population by Management ZonesChoice of hybrid and accurate amount of plants per area determines grain yield and consequently net incomes. Local field adjustment in plant population is a strategy to manage spatial variability and optimize environmental resources that are not under farmer control (like soil type and water availability). This study aims to evaluate the response of hybrids by levels of plant population across management zones (MZ). Six different hybrids and five rates of plant populations were analyzed starting... A.A. Anselmi, J.P. Molin, M.T. Eitelwein, R. Trevisan, A. Colaço |
14. The Device of Air-assisted Side Deep Precision Fertilization for Rice TransplanterRice is the most important crop in China, which has the largest plant area. Fertilization is an important process of rice production, which directly affects the yield of crops, reasonable and effective use of chemical fertilizer can improve the yield of crops. At present, the mechanization level of rice fertilization is very low in China, and the artificial fertilization requires a large amount of fertilizer which caused the uneven distribution. The rice side deep fertilizing is an ideal way of... C. Zhao, G. Wu, Z. Meng, W. Fu, L. Li, X. Wei |
15. 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 |
16. Surplus Science and a Non-linear Model for the Development of Precision Agriculture TechnologyThe advent of ‘big data technologies’ such as hyperspectral imaging means that Precision Agriculture (PA) developers now have access to superabundant and highly heterogeneous data. The authors explore the limitations of the classic science model in this situation and propose a new non-linear process that is not based on the premise of controlled data scarcity. The study followed a science team tasked with developing highly advanced hyperspectral techniques for a ‘low... M.Z. Cushnahan, I.J. Yule, B.A. Wood, R. Wilson |
17. Development of Land Leveling Equipment Based on GNSSAn attitude adjustable land leveling equipment was designed. The reference elevation of the land to be leveled was generated based on the topographic data which was acquired by the RTK-GNSS technology. The blade lifting mechanism was controlled by comparing the reference elevation and the real-time blade’s elevation and attitude data which was obtained by the dual antenna GNSS receiver and as a result the land leveling operation was implemented. A new algorithm using the electro-hydraulic... W. Fu, G. Wu, H. Bao, X. Wei, Z. Meng |
18. FOODIE Data Model for Precision AgricultureThe agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and temporal... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka |
19. Large-scale UAS Data Collection, Processing and Management for Field Crop ManagementNorth Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twice... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin |
20. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision AgricultureThe agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi |
21. Automated Segmentation and Classification of Land Use from Overhead ImageryReliable land cover or habitat maps are an important component of any long-term landscape planning initiatives relying on current and past land use. Particularly in regions where sustainable management of natural resources is a goal, high spatial resolution habitat maps over large areas will give guidance in land-use management. We propose a computational approach to identify habitats based on the automated analysis of overhead imagery. Ultimately, this approach could be used to assist experts,... C. Pradalier, A. Richard, V. Perez, R. Van couwenberghe, A. Benbihi, P. Durand |
22. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, CanadaManagement zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath |
23. Unmanned Aerial Systems (UAS) for Mitigating Bird Damage in Wine GrapesBird predation is a significant problem in high-value fruit crops, such as apples, cherries, blueberries, and wine grapes. Conventional methods such as netting, falconry, auditory scaring devices, lethal shooting, and visual scare devices are reported to be ineffective, costly, and/or difficult to manage. Therefore, farmers are in need of more effective and affordable bird control methods. In this study, two UAS wasused as a bird-deterring agent in a commercial vineyard. The experimental... S. Bhusal, K. Khanal, M. Karkee, K.M. Steensma, M.E. Taylor |
24. Design and Analysis of ISO 11783 Task Controller's Functionality in Server - Client ECU for Agricultural VehiclesA modern agricultural vehicle's electronic control units (ECU) communicated based on the ISO 11783 standards. The connection of different machines, implements, different manufacturers into a single bus for the exchange of control commands and sensor data are a challenge for the precision agriculture. One of main functionality is the Task controller in the intelligent monitoring system. The task controller is to log data and assign set-point values for automated work (task) sequences... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham |
25. Monitoring Potassium Levels in Peat-Grown Pineapple Using Selected Spectral RatiosIn this study, we assessed the biophysical changes within pineapple (var. MD2) in response to different potassium (K) rates using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430 nm and 680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e.... S.K. Balasundram, Y. Chong, A. Mohd hanif |
26. Predicting Dry Matter Composition of Grass Clover Leys Using Data Simulation and Camera-Based Segmentation of Field Canopies into White Clover, Red Clover, Grass and WeedsTargeted fertilization of grass clover leys shows high financial and environmental potentials leading to higher yields of increased quality, while reducing nitrate leaching. To realize the gains, an accurate fertilization map is required, which is closely related to the local composition of plant species in the biomass. In our setup, we utilize a top-down canopy view of the grass clover ley to estimate the composition of the vegetation, and predict the composition of the dry matter of the forage.... S. Skovsen, M. Dyrmann, J. Eriksen, R. Gislum, H. Karstoft, R.N. Jørgensen |
27. Using a Fully Convolutional Neural Network for Detecting Locations of Weeds in Images from Cereal FieldsInformation about the presence of weeds in fields is important to decide on a weed control strategy. This is especially crucial in precision weed management, where the position of each plant is essential for conducting mechanical weed control or patch spraying. For detecting weeds, this study proposes a fully convolutional neural network, which detects weeds in images and classifies each one as either a monocot or dicot. The network has been trained on over 13 000 weed annotations... M. Dyrmann, S. Skovsen, R.N. Jørgensen, M.S. Laursen |
28. Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural NetworksThis paper presents a method which can provide support in determining the grass-clover ratio, in grass-clover fields, based on images from an unmanned aerial vehicle. Automated estimation of the grass-clover ratio can serve as a tool for optimizing fertilization of grass-clover fields. A higher clover content gives a higher performance of the cows, when the harvested material is used for fodder, and thereby this has a direct impact on the dairy industry. An android application... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen |
29. Site-Specific Management Zones Delineation Using Drone-Based Hyperspectral ImageryConventional techniques (e.g., intensive soil sampling) for site-specific management zones (MZ) delineation are often laborious and time-consuming. Using drones equipped with hyperspectral system can overcome some of the disadvantages of these techniques. The present work aimed to develop a drone-based hyperspectral imagery method to characterize the spatial variability of soil physical properties in order to delineate site-specific MZ. Canonical correlation analysis (CCA) was used to extract... H. Agili, K. Chokmani, A. Cambouris, I. Perron, J. Poulin |
30. Delineation of Soil Management Zones: Comparison of Three Proximal Soil Sensor Systems Under Commercial Potato Field in Eastern Canada.Precision agriculture (PA) involves optimization of seeding, fertilizer application, irrigation, and pesticide use to optimize crop production for the purpose of increasing grower revenue and protecting the environment. Potato crops (Solanum tuberosum L.) are recognized as good candidates for the adoption of PA because of the high cost of inputs. In addition, the sensitivity of potato yield and quality to crop management and environmental conditions makes precision management economically... A. Cambouris, I. Perron, B. Zebarth, F. Vargas, K. Chokmani, A. Biswas, V. Adamchuk |
31. Ground Vehicle Mapping of Fields Using LiDAR to Enable Prediction of Crop BiomassMapping field environments into point clouds using a 3D LIDAR has the ability to become a new approach for online estimation of crop biomass in the field. The estimation of crop biomass in agriculture is expected to be closely correlated to canopy heights. The work presented in this paper contributes to the mapping and textual analysis of agricultural fields. Crop and environmental state information can be used to tailor treatments to the specific site. This paper presents the current results... M.P. Christiansen, M.S. Laursen, R.N. Jørgensen, S. Skovsen, R. Gislum |
32. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine LearningThe ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop |
33. 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 et... G. Bareth, A. Jenal, H. Hüging |
34. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding ProgramIn plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland |
35. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter SurvivalAlfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc |
36. Automated Lag Phase Detection in Wine GrapesCrop yield estimation, an important managerial tool for vineyard managers, plays a crucial role in planning pre/post-harvest operations to achieve desired yield and improve efficiency of various field operations. Although various technological approaches have been developed in the past for automated yield estimation in wine grapes, challenges such as cost and complexity of the technology, need of higher technical expertise for their operation and insufficient accuracy have caused major concerns... P. Upadhyaya, M. Karkee, X. Zhang, S. Kashetri |
37. Diagnosis of Grapevine Nutrient Content Using Proximal Hyperspectral ImagingNutrient deficiencies on grapevines could affect the fruit yield and quality, which is a major concern in vineyards. Nutrient deficiencies may be recognizable by foliar symptoms that vary by mineral nutrient and stress severity, but it is too late to manage when visible deficiency symptoms become apparent. The nutrient analysis in the laboratory is the way to get an accurate result, but it is time and cost-intensive. The differences in leaf nutrient levels also alter spectral characteristics outside... C. Kang, M. Karkee, Q. Zhang, N. Shcherbatyuk, P. Davadant, M. Keller |
38. Precision Tools for Monitoring Experimental Irrigation Treatments in California VineyardsPrecision farming techniques, such as zonal management and variable rate nutrient delivery, have been used to manage spatial variability in many crops. Wine grapes, and most permanent crops, have been slower than row crops or agronomic crops to take advantage of these techniques, though there are barriers to implementing these methods when compared to agronomic crops. The objective of this project is to show how a suite of monitoring and management tools can be used to evaluate the performance... B. Sams, P. Previtali, J. Mezger, M. Aboutalebi, L. Sanchez, N. Dokoozlian |
39. The Evaluation of NDVI Response Index Consistency Using Proximal Sensors, UAV and SatellitesThe Response Index NDVI (RINDVI) is described as the response of crops to additional nitrogen (N) fertilizer. It is calculated by dividing the NDVI of the high-N plot (N-rich strip) by the NDVI of the zero-N plot or farmer's practice where less pre-plant N was applied (Arnall and al., 2016). RI values are used to predict yield and monitor top dress N fertilization. Many research has been carried out to determine the difference... S. Phillips, B. Arnall, M. Maatougui |
40. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane FeedstockPredicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland |
41. Drought Tolerance Assessment with Statistical and Deep Learning Models on Hyperspectral Images for High-throughput Plant PhenotypingDrought is an important factor that severely restricts blueberry growth, output and adversely impacts the desirable physiologic quality. Considering the challenges posed by climate change and erratic weather patterns, evaluating the drought tolerance of blueberry plants is not only vital for the agricultural industry but also for ensuring a consistent supply of these nutritious berries to consumers. Blueberry plants have a relatively ineffective water regulation mechanism due to their shallow... M. Rahman, S. Busby, A. Sanz-saez, S. Ru, T. Rehman |
42. Relationship Between Water Use Efficiency, Daily Stomatal Conductance Trend and Evaporation of Maize and Soybean CropsWater Use Efficiency (WUE) represents the biomass production per unit of water and is commonly affected by temperature, carbon dioxide concentration, and water availability. Plants regulate the water transpiration efficiency through the opening and closing of stomata. Farmers can save water and maintain yield by improving crop's WUE during the period of drought through proper field management. The calculation of WUE requires the information of crop weight and irrigation volume, which is difficult... J. Zhang, N. Chamara, G. Bai, Y. Ge |
43. 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 |
44. Comparison of NDVI Values at Different Phenological Stages of Winter Wheat (Triticum Aestivum L.)The main objective of this study is to monitor, detect and quantify the presence of live green vegetation with the MicaSense RedEdge-MX Dual Camera System (MS) mounted on a DJI Matrice 210 V2 and GreenSeeker HCS 250 (GS) in winter wheat (Triticum aestivum L.) by using Normalized Difference Vegetation Index (NDVI). Surveys were conducted in the North-Western part of Hungary, in Mosonmagyaróvár on six different dates. A small-scale field trial in winter wheat was constructed as a randomized... S. Zsebő, G. Kukorelli, V. Vona, L. Bede, D. Stencinger, A. Kovacs, G. Milics, I.M. Kulmany, B. Horváth, G. Hegedűs, J.A. Abdinoor |
45. Partial Fruitlet Cutting Approach for Robotic Apple ThinningEarly season thinning of apple fruitlets is a crucial task in commercial apple farming, traditionally accomplished through chemical sprays or labor-intensive manual operations. These methods, however, are faced with the challenges of diminishing labor availability as well as environmental and/or economic sustainability. This research examines 'partial fruitlet cutting,' a novel nature-assisted strategy, as an alternative method for automated apple thinning in orchards. The study hypothesized... R. Sapkota, M. Karkee |
46. Fostering Student Engagement and Leadership Development in Integrative Precision Agriculture Across BordersEfforts to advance integrative precision agriculture technologies are growing exponentially across the globe with the common interest of upholding food security and developing more sustainable food and fiber production systems. Countries such as the United States and Brazil are among the biggest crop producers in the world and will play an even bigger role in food security in the next decades. It is of utmost importance that countries can advance together to overcome future food production challenges... L. Lacerda, A. Felipe dos santos, E. Bedwell, A. Jakhar, T.O. Costa barboza, M. Ardigueri |
47. High Throughput Phenotyping of the Energy Cane Crop UAV-based LiDAR, Multispectral and RGB DataEnergy cane is a hybrid of sugarcane cultivated for their high biomass and fiber instead of sugar. It is used for production of biofuels and as feedstock for animals. As a relatively new crop, accurate knowledge of biophysical parameters such as height and biomass of different genotypes are pertinent to cultivar development. Such knowledge is also crucial to manage crop health, understand response to environmental effects, optimize harvest schedules, and estimate bioenergy yield. Nonetheless,... B. Ghansah, I. Khuimphukhieo, J.L. Scott, M. Bhandari, J. Foster, J. Da silva, H. Li, M. Starek |
48. Deep Learning to Estimate Sorghum Yield with Uncrewed Aerial System ImageryIn the face of growing demand for food, feed, and fuel, plant breeders are challenged to accelerate yield potential through quick and efficient cultivar development. Plant breeders often conduct large-scale trials in multiple locations and years to address these goals. Sorghum breeding, integral to these efforts, requires early, accurate, and scalable harvestable yield predictions, traditionally possible only after harvest, which is time-consuming and laborious. This research harnesses high-throughput... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff |
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. Estimating Real-time Soil Water Content (SWC) in Corn and Soybean Fields Using Machine Learning Models, Proximal Remote Sensing, and Weather DataSoil Water Content (SWC) is crucial for precise irrigation management, especially in center-pivot systems. Real-time estimation of SWC is vital for scheduling irrigation to prevent overwatering or underwatering. Proper irrigation yields benefits such as improved water efficiency, enhanced crop yield and quality, minimized environmental impact, optimized labor and energy costs, and improved soil health. Various in-situ techniques, such as Time-domain reflectometry (TDR), frequency-domain... N. Chamara, Y. Ge, F. Bai |
51. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of SowsThe lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D computer... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre |
52. Driving Growth Through Precision Agriculture: the Evolution of the Nebraska On-farm Research NetworkThe Nebraska On-Farm Research Network (NOFRN), allows farmers to answer production, profitability and sustainability questions in their own field. The University of Nebraska (USA) sponsors the NOFRN and provides technical support in the experimental design, execution, data analysis and results dissemination. In recent years, precision agriculture technologies have expanded network capabilities through an increasing number of experiments and provided new avenues for data analyses. The goal is... G. Balboa, B. Tobaldo, T. Lexow, J.D. Luck |
53. Asia and Oceania Regional Meeting... S.K. Balasundram |