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1. Land Information System Of Precision Farming In Mongolia Using Remote Sensing And Geographical Information SystemRemote sensing (RS) and geographic information system (GIS) technologies have been of great use to planners in planning for efficient use of natural resources at national, sub region and rural levels. RS can be used for precision farming in a number of ways for providing input supplies and variability management through decision support system. GIS is the principal technology used to integrate spatial data... B. Erdenee, B. Batbayar, R. Tateishi |
2. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 SurveyThe objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves |
3. NDVI 'Depression' In Pastures Following GrazingPasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespective... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman |
4. Development of a Multiband Sensor for Citrus Black Spot Disease DetectionCitrus black spot (CBS), or Guignardia citricarpa, is known as the most destroying citrus fungal disease worldwide. CBS causes yield loss as a result of early fruit drop, and it leaves severely blemished and unmarketable fruit. While leaves usually remain symptomless, CBS generates various forms of lesions on citrus fruits including hard spot, cracked spot, and virulent spot. CBS lesions often appear on maturing fruit, starting two months before maturity. Warm temperature and sunlight exposure... A. Pourreza, W. Lee, J. Lu, P. Roberts |
5. 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 |
6. Management Zone Delineation for Irrigation Based on Sentinel-2 Satellite Images and Field PropertiesThis paper presents a case study of the first application of the dynamic Variable Rate Irrigation (VRI) System developed by the University of Georgia to cotton. The system consists of the EZZone management zone software, the University of Georgia Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2017 in a cotton field to evaluate the performance of the system in cotton. The field was divided into four parallel strips. All four strips... V. Liakos, G. Vellidis, L. Lacerda, W. Porter, M. Tucker, C. Cox |
7. Canopy Parameters in Coffee Orchards Obtained by a Mobile Terrestrial Laser ScannerThe application of mobile terrestrial laser scanner (MTLS) has been studied for different tree crops such as citrus, apple, olive, pears and others. Such sensing system is capable of accurately estimating relevant canopy parameters such as volume and can be used for site-specific applications and for high throughput plant phenotyping. Coffee is an important tree crop for Brazil and could benefit from MTLS applications. Therefore, the purpose of this research was to define a field protocol for... F. Hoffmann silva karp, A. Feritas colaço, R. Gonçalves trevisan, J.P. Molin |
8. Levels of Inclusion of Crambe Meal (Crambe Abyssinica Hochst) in Sheep Diet on the Balance of Nitrogen and Ureic Nitrogen in the Blood SerumCrambe meal, which is a co-product of biodiesel production, is a potential substitute for conventional protein sources in ruminant diets. The objective of this study was to evaluate the effect of the substitution of crude protein of the concentrate by crude protein of crambe meal with increasing levels (0, 25, 50, and 75%) on nitrogen balance and blood plasma urea nitrogen concentration in sheep. Four male sheep, rumen fistulated, were placed in metabolic crates and distributed in a 4 x 4 Latin... K.K. De azevedo, D.M. Figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, L.N. Rennó, R.A. Santos |
9. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude ProteinThe objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein and... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco |
10. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water StressesThis paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman |
11. Development of a Wireless Sensor Network for Passive in situ Measurement of Soil CO2 Gas Emissions in the Agriculture LandscapeQuantification of soil Greenhouse Gas (GHG) emissions from agricultural fields is essential for understanding the environmental impact of intensive crop and livestock production systems. Current methods of analysis include flux calculations derived from the concentration of gases (CO2, N2O, CH4) exchanged between soil and the atmosphere. Samples of these GHG are obtained manually by closed non-steady state non-flow through,or “static”, chambers and analyzed ex situvia gas... V. Adamchuk, M. Debbagh, C. Madramootoo, J. Whalen |
12. A Passive-RFID Wireless Sensor Node for Precision AgricultureAccurate soil data is crucial for precision agriculture. While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback. In this... P.J. Goodrich, C. Baumbauer, A.C. Arias |
13. Using Prescription Maps for in Field Evaluations of Parameteres Affecting Spraying Accuracy of Self-propelled SprayerWeed presence continues to reemerge year over year, chemical costs continue to increase, and chemical usage continuing to face increasing government oversight, are just a few of the challenges that site-specific weed management intends to address by minimizing wasted application of chemicals and reducing environmental load of active ingredients. Thus, sprayer system manufacturers have developed precision spray systems that allow the individual spray nozzles to be controlled precisely. These spray... J. Mayer, P. Flores, J. Stenger |
14. Printed Nitrate Sensors for In-soil MeasurementsManaging nitrate is a central concert for precision agriculture, from delineating management zones, to optimizing nitrogen use efficiency through in-season applications, to minimizing leaching and greenhouse gas emissions. However, measurement methods for in-soil nitrate are limiting. State-of-the-art soil nitrate analysis requires taking soil or liquid samples to laboratories for chemical or spectrographic analysis. These methods are accurate, but costly, labor intensive, and cover limited geographic... C. Baumbauer, P. Goodrich, A. Arias |
15. Scaling Up Window-based Regression for Crop-row DetectionCrop-row detection is a central element of weed detection and agricultural image processing tasks. With the increased availability of high-resolution imagery, a precise locating of crop rows is becoming practical in the sense that the necessary data are commonly available. However, conventional image processing techniques often fail to scale up to the data volumes and processing time expectations. We present an approach that computes regression lines over... A.M. Denton, G.E. Hokanson, P. Flores |
16. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach OrchardCanopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen |
17. Comparison and Validation of Different Soil Survey Techniques to Support a Precision Agricultural SystemThe data need of precision agriculture has resulted in an intensive increase in the number of modern soil survey equipment and methods available for farmers and consultants. In many cases these survey methods cannot provide accurate information under the used environmental conditions. On a 36 hectare experimental field, several methods have been compared to identify the ones which can support the PA system the best. The methods included contact and non contact soil scanning, yield mapping, high... V. Lang, G. Tóth, S. Csenki, D. Dafnaki |
18. Increasing the Accuracy of UAV-Based Remote Sensing Data for Strawberry Nitrogen and Water Stress DetectionThis paper presents the methods to increase the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data for the determination of plant nitrogen and water stresses with increased accuracy. As the demand for agricultural products is significantly increasing to keep up with the growing population, it is important to investigate methods to reduce the use of water and chemicals for water conservation, reduction in the production cost, and reduction in environmental impact. UAV-based remote... S. Bhandari, A. Raheja |
19. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
20. Evaluating the Potential of Integrated Precision Irrigation and Nitrogen Management for Corn in MinnesotaThe environmental impact of irrigated agriculture on ground and surface water resources in Minnesota is of major concern. Previous studies have focused on either precision irrigation or precision nitrogen (N) management, with very limited studies on the integrated precision management of irrigation and N fertilizers, especially in Minnesota. The Dualex Scientific sensor is a leaf fluorescence sensor that has been used to diagnose crop N... A. Elvir flores, Y. Miao, V. Sharma, L. Lacerda |
21. Farmer Charlie - Low Cost Data Analytics for Farmers Accessible in the FieldFarmer Charlie, a spin-off of AB5 Consulting Ltd, is based on an affordable business model including five elements: a data analytics platform, an agribusiness ecosystem app, capable of connecting with local third-party apps; weather and in field sensors; wi-fi Internet connectivity; and power to the field and farms via solar panels, where necessary. Farmer Charlie brings information to farmers in their own fields, in an easy plug and play solution, affordable to the farmers and addressing their... B. Bonnardel |
22. Farmer Charlie - Low Cost Smart Local Data Available to Remote FarmersFarmer Charlie brings connectivity and information to farmers, who receive tailored agronomic data to improve their agricultural practice. Farmer Charlie is based on on-site sensors through which soil data can be detected, gathered, and processed by a dedicated server. Broadband communication allows farmers to receive real-time, localised information on tablet or mobile phone. Farmer Charlie is a low-cost solution, it can be adapted to various crops and to detect soil humidity, pH, temperature,... B. Bonnardel |
23. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern GhanaThe rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retrieved... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff |
24. Land Cover and Crop Types Classification Using Sentinel-2A Derived Vegetation Indices and an Artificial Neural NetworkDevelopments in remote sensing data acquisition capabilities, data processing and interpretation of ground-based, airborne and satellite observations have made it possible to couple remote sensing technologies and precision crop management systems. Land cover and crop types classification is a fundamental task in remote sensing and is crucial in various environmental and agricultural applications. Accurate and timely information on land cover and crop types is essential for land management, land-use... B. Bantchina |
25. Evaluation of a Single Transect Method for Collecting Grape Samples Based on Sentinel-2 Imagery for the Characterization of Overall Vineyard PerformanceCommercial vineyards are streamed into different wine programs based on analysis of grape or juice samples collected from the field, but spatial and temporal variability can lead to sub-optimal tiering of grapes. This is a particularly difficult problem to overcome in the typically large vineyards of California’s Central Valley. Due to economic and laboratory constraints on sample collection, processing, and analysis, a single sample is often expected to represent the overall fruit quality... B. Sams, M. Aboutalebi, L. Sanchez, N. Dokoozlian, R. Bramley |
26. Dynamic Management Zones for Real-time Precision Agriculture OptimizationPrecision agriculture is an evolving management approach aimed at optimizing resource utilization, enhancing financial returns, and mitigating environmental impacts. The dynamic nature of agricultural conditions throughout a growing season necessitates the integration of innovative remote sensing and precision agriculture techniques. This research explores the creation of dynamic management zones (DMZ) that adapt in real-time to evolving soil and crop conditions. This study focuses on the establishment... A.H. Rabia, E. Eldeeb |
27. Modelling Hydrological Processes in a Wadi Basin in Egypt: Wadi Kharouba Case StudyWadi Flash Flood (WFF) is one of the most crucial problems facing the north‐western coastal region in Egypt. Water harvesting (WH) approaches may be an effective tool to reduce the WFF risk while storing the runoff water for agricultural activities. In this study, the Agarma sub-catchment of the Wadi Kharouba was taken as a reference investigation site to study terraced WA systems. The main problem in this area is that local farmers independently build terraces using traditional knowledge to... A.H. Rabia, E. Eldeeb, A. Coppola |
28. Capacity Building of African Young Scientists in Precision Agriculture Through Cross-regional Academic Mobility for Enhanced Climate-smart Agri-food System: an Intra Africa Mobility Project on Precision AgricultureClimate change is one of the main problems affecting food and nutrition globally, particularly in sub-Saharan Africa. Adapting to and/or mitigating climate change in the agri-food sector requires merging information technologies, genetic innovations, and sustainable farming practices to empower the agricultural youth sector to create effective and locally adapted solutions. Precision Agriculture applied to crops (PAAC), has been advocated as a strategic solution to mitigate/adapt agriculture at... N. Fassinou hotegni, A. Karangwa, A. Manyatsi, K.A. Frimpong, M. Amri, D. Cammarano, C. Lesueur, J. Taylor, S. Phillips, E. Achigan-dako |
29. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in VineyardsThis paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg. ... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat |
30. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic ParametersThe environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States in... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe dos santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando costa barboza |
31. Comparative Analysis of Spray Nozzles on Drones: Volumetric Distribution at Different HeightsAgricultural drones are emerging as a revolutionary tool in modern agriculture, aiming to enhance precision and efficiency in crop management. One of their main advantages is the ability to operate in adverse soil and canopy height conditions, making them a valuable instrument for the application of agrochemicals. In this context, the optimization of spraying systems plays a critical role, with the goal of ensuring the effective application of agrochemicals, aiming to maximize productivity and... A. Felipe dos santos, J.E. Silva, O.P. Costa, F.D. Inácio , R. Oliveira, W. Silva, L. Lacerda, T. Orlando costa barboza |
32. Decision Support Tools for Developing Aflatoxin Risk Maps in Peanut FieldsAspergillus flavus and Aspergillus parasiticus hereafter referred to jointly as A. flavus, are soil fungi that infect and contaminate preharvest and postharvest peanuts with the carcinogenic secondary metabolite aflatoxin. A. flavus can cause extensive economic losses to peanut growers and shellers by contaminating peanut kernels with aflatoxins. In the southeastern U.S., contamination from aflatoxin continues to be a major threat to the peanut industry and... G. Vellidis, M. Abney, T. Burlai, J. Fountain, R.C. Kemerait, S. Kukal, L. Lacerda, S. Maktabi, A. Peduzzi, C. Pilcon, M. Sysskind |
33. Real Time Application of Neural Networks and Hardware Accelerated Image Processing Pipeline for Precise Autonomous Agricultural SystemsModern agriculture is increasingly turning to automation and precision technology to optimize crop management. In this context, our research addresses the development of an autonomous pesticide spraying rover equipped with advanced technology for precision agriculture. The primary goal is to use a neural network for real-time aphid detection in Sorghum crops, enabling targeted pesticide application only to infested plants. To accomplish this, we've integrated cutting-edge technologies and... J. Raitz persch, R. Harsha chepally, N.K. Piya |
34. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision ExperimentationAssessing the spatial variability of soil properties represents an important issue for on-farm sustainable management owing to high cost of sampling densities. Actual methods of soil properties measurement are based on conventional soil sampling of one sample per ha, followed by laboratory analysis, requiring many soil extraction processes and harmful chemicals. This conventional laboratory analysis does not allow exploring spatial variation of soil properties at desired fine spatial scale. Thus,... A. Cambouris, M. Duchemin, E. Lord, N. Ziadi, B. Javed, J.D. Nze memiaghe, D.A. Ramirez-gonzalez |
35. 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 |
36. Using Remote Sensing to Benchmark Crop Coefficient Curves of Sweet Corn Grown in the Southeastern United StatesIrrigation is responsible for over 75% of global freshwater use, making it the largest consumer of the world’s freshwater resources. With freshwater scarcity increasing worldwide, increased efficient irrigation water use is necessary. Smart irrigation is described as ‘the linking of technology and fundamental knowledge of crop physiology to significantly increase irrigation water use efficiency'. Irrigation scheduling tools such as smartphone applications have become... E. Bedwell, L. Lacerda, T. Mcavoy, B.V. Ortiz, J. Snider, G. Vellidis, Z. Yu |
37. Evaluating the Impact of Vegetation Indices on Plant Nitrogen Uptake Prediction: a Comparative Study of Regression Models at Various Growth StagesNitrogen and water play crucial roles in impacting both the health and yield of corn crops. However, their demands vary under different soil and weather conditions. Unfortunately, current nitrogen management practices in irrigated fields in the state of Georgia overlook this variability. Thus, this oversight may lead to insufficient nitrogen application, causing plant stress or excessive nitrogen application that can lead to environmental impact. To address this challenge, a precise assessment... B. Ghimire, L. Lacerda, T. bourlai |
38. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal SensorThe Crop Circle Phenom (CCP) is an innovative integrated proximal sensor that can be potentially used to perform in-season diagnosis of nitrogen and water status. In addition to measuring spectral reflectance in several bands including the red, red edge, and near-infrared wavelengths, the CCP can also measure canopy and air temperatures and provides several parameters that can be associated with chlorophyll content, crop vigor, and water status. These capabilities differentiate the CCP from other... L. Lacerda, Y. Miao, V. Sharma, A. E. flores, A. Kechchour, J. Lu |
39. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote SensingFor irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang |
40. Field Mapping for Aflatoxin Assessment in Peanut Crops Using Thermal ImageryAflatoxin is a toxic carcinogenic compound produced by certain species of Aspergillus fungi, which has a significant impact on peanut production. Aflatoxin levels above a certain threshold (20 ppb in the USA and 4 ppb in Europe) make peanuts unsuitable for export, resulting in significant financial losses for farmers and traders. Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular for remote sensing applications in agriculture. Leveraging this advancement, UAV-based thermal imaging... S. Shrestha, L. Lacerda, G. Vellidis, C. Pilcon, S. Maktabi, M. Sysskind |
41. Utilizing Thermal and RGB Imaging for Nutrient Deficiency and Chlorophyll Status Evaluation in PlantsAs global population growth and climate change continue to challenge food security, addressing agricultural issues efficiently and cost-effectively is vital for enhancing productivity. Integrating technology into agriculture, particularly through timely interventions, offers promising solutions to mitigate challenges before they escalate. This study investigates the feasibility of using thermal and RGB imaging as efficient, non-destructive methods to assess nutrient deficiencies and chlorophyll... A.H. Rabia, D.G. Allam, E.F. Abdelaty, E.A. Abderaouf |
42. Potato Disease Detection Using Laser Speckle Imaging and Deep LearningEarly detection of potato diseases is essential for minimizing crop loss. Implementing advanced imaging techniques can significantly improve the accuracy and efficiency of disease detection in potato crops. Leveraging machine learning algorithms can further enhance the speed and precision of disease identification, enabling timely intervention measures. This work presents a novel potato disease detection technique using whole-potato speckle imaging and deep learning. Laser Speckle Imaging (LSI),... A.H. Rabia, M.A. Salem |
43. Development of a High-throughput UAV System for Precision Weed Detection and Control Using Laser Speckle Imaging and UV-C IrradiationTraditional weed control methods, predominantly reliant on herbicides or labor-intensive ground robots, present notable environmental and efficiency challenges within agricultural practices. To address these concerns, this study introduces an innovative approach utilizing unmanned aerial vehicles (UAVs) for autonomous weed detection and control in agricultural fields. Our proposed system depends on the agility of UAV platforms, integrating two primary technologies. Firstly, Laser Speckle Imaging... M.A. Salem, A.H. Rabia |
44. North Dakota State University - Sponsor Presentation... L. Schumacher, P. Flores, R. Sun, A. Reinholz |