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| Filter results57 paper(s) found. |
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1. Sensing The Inter-row For Real-time Weed Spot Spraying In Conventionally Tilled Corn FieldsThe spatial distribution of weeds is aggregated most of the time in crop fields. Site-specific management of weeds could result in economical and environmental benefits due to he... L. Longchamps, B. Panneton, M. Simard, R. Theriault, T. Roger |
2. Partial Weed Scouting For Exhaustive Real-time Spot Spraying Of Herbicides In CornReal-time spot spraying of weeds implies the use of plant detectors ahead of a sprayer. The range of weed spatial autocorrelation perpendicularly to crop rows is often greater than the space between the corn rows. To assess the possibility of using less than one plant detector scouting each inter-row, a one hectare field was entirely sampled with ground pictures at the appropriate timing for weed spraying. Different ways of disposing the detectors ahead of the sprayer were virtually tested. S... L. Longchamps, B. Panneton, G.D. Leroux, M. Simard, R. Theriault |
3. 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 acro... J.D. Luck, A. Sharda, S.K. Pitla, J.P. Fulton, S.A. Shearer |
4. Effect Of Precision Guided Cultivation On Weed Control In Wide Row Cropping SystemsWide row cropping has been traditionally followed in summer crops but it is also becoming popular in winter crops such as chickpeas and lupins. High precision guidance systems with 2 cm accuracy offer unique opportunities to cultivate closer to the row and increase weed control efficiency in wide row cropping systems. Two field experiments were conducted in chickpeas with a Real Time Kinematic Differential Global Positioning System (RTK-DGPS) controlled mechanical cultivation. Cultivati... M. Gupta, , |
5. Using Soil Attributes To Model Sugar Cane Quality ParametersThe crop area of sugar cane production in Brazil has increased substantially in the last few years, especially to meet the global bioethanol demand. Such increasing production should take place not only in new sugar cane crop areas but mainly with the goal of improving the quality of raw material like sugar content (Pol). Hence, models that can describe the behaviour of the quality parameters of sugar cane may be important to understand the effects of the soil attributes on those parameters. ... F.A. Rodrigues jr., P.S. Magalhães, H.C. Franco, D.G. Cerri |
6. Statistical Procedure to Compare Farming Procedures with the Observation of Spatial Trends and Correlations in On-Farm ResearchModern management and machines have been introduced on a demonstration farm in Ganhe (China). This has led to new methods of cultivation with effects on yields, cost structure and thus also on the economic success of the farm. These effects should be tested with the help of an on-farm trial. The cultivation methods differed in the equipment used, plant protection and fertilisation strategies. In contrast to classical field trials, normal working practice farm machinery and fields are used in ... P. Wagner, M. Langrock |
7. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat YieldIn crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to p... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont |
8. Transient Water Flow Model in a Soil-Plant System for Subsurface Precision IrrigationThe spatial variability of plant-water characteristic in the soil is still unclear. This limits the attempt to model the soil-plant-atmosphere system with this factor. Understanding the non-steady water flow along the soil-plant component is essential to understand their spatial variabili... M.B. Zainal abidin, S. Shibusawa, M. Ohaba, Q. Li, M. Kodaira, M.B. Khalid |
9. A New Approach to Yield Map CreationOne of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field. Numerous data errors in the way the data is collected, poor calibration habits on the part of opera... C. Romier, M. Hyrien, D. Lamker |
10. Evaluation of PRS(TM) Probe Technology and Model for Variable Rate Fertilizer Application in Hummocky Fields in Saskatchewan... K. Greer, J. Burns, E. Bremer |
11. A High-Reliability Database-Supported Modular Precision Irrigation SystemTitle of Abstract: A High-Reliability Database-Supported Modular Precision Irrigation System Authors of Abstract: N. Kamel1, S. Sharaf1, A. El-Shafei... S. Sharaf, A. Elshafie, N.N. Kamel, D.A. Yousef |
12. Maximizing Agriculture Equipment Capacity Using Precision Agriculture TechnologiesGuidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was t... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton |
13. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental ImpactSALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for genera... T. Chou, M. Yeh, J. Chen, B. Basso |
14. Suitability Of Fluorescence Sensors To Estimate The Susceptibility Degree Of Spring Barley To Powdery Mildew And Leaf RustThe overall role of precision agriculture is not restricted to those systems for in-field and in-season sensing of the impact of stresses. Much more, its contribution comprises the prevention of stresses, amongst others by supporting the selection of appropriate and stress-tolerant genotypes in breeding programs. In this context, the development, selection and use of cultivars which are tolerant to pathogens establish an essential tool for a more sustainable and environmental-fr... G. Leufen, G. Noga, M. Hunsche |
15. Elimination of Spatial Variability Using Variable Rate Drip Irrigation (VRDI) in VineyardsVineyards worldwide are subjected to spatial variability, which can be exhibited in both low and high yield areas meaning that the vineyard is not achieving his full yield potential. In addition, the grapes quality is not uniformed leading to different wine qualities from the same plot. The assumption is that a variability in available water for the plant due to soil variability leads to the observed yield variability. A variable rate drip irrigation (VRDI) concept was developed to reduce suc... I. Nadav |
16. 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 t... R. Sui, J. Baggard |
17. 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 stri... V. Liakos, G. Vellidis, L. Lacerda, W. Porter, M. Tucker, C. Cox |
18. Variable Rate Irrigation Management Using NDVICenter pivot irrigation systems are commonly used for corn and cotton production in the southeast USA. Technology for variable rate water application with center pivots is available; however, it is not widely used due to increased management requirements. Methods to develop dynamic in-season prescriptions in response to changing crop conditions are needed to move this technology forward. The objective of this research was to evaluate the potential of using normalized difference vegetative ind... K.C. Stone, P.J. Bauer |
19. High Resolution Soil Moisture Monitoring Using Active Heat Pulse Method with Fiber Optic Temperature Sensing at Field ScaleKnowledge of spatial and temporal variability of soil moisture is critical for site specific irrigation management at field scale. However, installation feasibility, cost and between-sensor variability restrict the use of many point–based sensors at field scale. Active heat pulse method with fiber optic temperature sensing (AHFO) has shown a potential to provide soil moisture data at sub-meter intervals along a fiber optic cable to a distance >10000 meters. Despite the limited number... A. Biswas, D.N. Vidana gamage, I.B. Strachan |
20. Water Use Efficiency of Precision Irrigation System Under Critical Water-Saving ConditionNon-transpiration water loss is often neglected when evaluating water use efficiency (WUE) of precision irrigation system, due to the difficulties in determining water loss from the root zone. The objective of this study is to investigate the feasibility of a new water saving approach by controlling soil water retention around root zone during the plant growth. We grew two tomato cultivars (Anemo, Japanese variety) in an environmental controlled growth chamber, with previously oven dried and ... Q. Li, T. Sugihara, M. Kodaira, S. Shibusawa |
21. Effect of Irrigation Scheduling Technique and Fertility Level on Corn Yield and Nitrogen MovementFlorida has more first magnitude springs that anywhere in the world. Most of these are located in north Florida where agricultural production is the primary basis for the economy. Irrigated corn has become a popular part of the crop rotation in recent years. This project is a study of a corn and peanut rotation investigating Best Management Practices (BMPs) of nitrogen fertility level (336, 246, 157 kg/ha) and irrigation strategies as follows: (i) GROW, mimicking grower’s practice... M. Dukes, M. Zamora, D. Rowland |
22. Application of a Systems Model to a Spatially Complex Irrigated Agricultural System: A Case StudyAlthough New Zealand is water-rich, many of the intensively farmed lowland areas suffer frequent summer droughts. Irrigation schemes have been developed to move water from rivers and aquifers to support agricultural production. There is therefore a need to develop tools and recommendations that consider both water dynamics and outcomes in these irrigated cropping systems. A spatial framework for an existing systems model (APSIM Next Generation) was developed that could capture the variability... J. Sharp, C. Hedley |
23. Application of Variable-Rate Irrigation for Potato ProductivityVariable-rate irrigation (VRI) has the potential to increase yields and reduce water consumption and energy costs. Spatial and temporal variability of soil and field properties can impact the efficiency of irrigation and crop yield. The VRI technology allows for the precise application of irrigation to meet crop water demands in controlled amounts prescribed for specific management zones within a field. Sensitivity to over and under-irrigation and the high-water requirements of potato make th... A. Yari, C. Madramootoo, S.A. Woods, V.I. Adamchuk, L. Gilbert |
24. Survey Shows Specialty and Commodity Crop Retailers Use Precision Agriculture DifferentlyThe 2021 CropLife-Purdue Survey of precision agricultural practices by US agricultural input dealers serving the American grain and oilseed sector shows that most of them use GPS guidance and related technologies like sprayer boom control, most provide variable rate fertilizer services, and the majority say that fertilizer decisions are influenced by grower data. In contrast, dealers serving horticultural and specialty crop farms indicate comparatively modest adoption of many precision agricu... B.J. Erickson, J. Lowenberg-deboer |
25. Farmers’ and Experts’ Perceptions of Precision Farming Impacts on Economic Efficiency, Food Security, Climate and Environmental Sustainability“Global food security could be in jeopardy, due to mounting pressures on natural resources and to climate change, both of which threaten the sustainability of food systems at large. Excessive fertilizer use can contribute to problems of eutrophication, acidification, climate change and the toxic contamination of soil, water and air. Lack of fertilizer application may cause the degradation of soil fertility. Agricultural production systems need to focus more on the effective co... C.I. Anaba |
26. Robot Safety Issues in Field Crops - EU Regulatory Issues and Technical AspectsThe use of robots in Precision Agriculture is becoming of great interest, but they introduce a new kind of risk in the field due to their self-acting and self-driving capability. Safety issues appear with respect to people working in the same field in human-robot collaboration (HRC) framework or to the accidental presence of humans or animals. A robot out of control may also invade other areas causing unpredictable harm and damage. Currently, the safety of highly automated agricultu... M. Canavari, P. Lattanzi, G. Vitali, L. Emmi |
27. Geographic Database in Precision Agriculture for the Development of AI ResearchAgriculture 4.0 has profoundly transformed production processes by incorporating technologies such as Precision Agriculture, Artificial Intelligence, the Internet of Things, and telemetry. This evolution has enabled more accurate and timely decision-making in agriculture. In response to this movement, the Precision Agriculture Laboratory (AgriLab) of UTFPR, located in Medianeira, proposes the establishment of a consistent and standardized database. This database is continually updated with su... E.N. Avila, C.L. Bazzi, W.K. Oliveira, K. Schenatto, R. Sobjak, D.M. Rocha |
28. Automatic Body Condition Score Classification System for Individual Beef Cattle Using Computer VisionBody condition scoring (BCS) is a widely used parameter for assessing the utilization of energy reserves in the fat and muscle of cattle. It fulfills the needs of animal welfare and precision livestock farming by enabling effective monitoring of individual animals. It serves as a crucial parameter for optimizing nutrition, reproductive performance, overall health, and economic outcomes in beef cattle. The precise and consistent assessment of BCS relies on personal experience using visuals tha... M. Islam, J. Yoder, H. Gan |
29. Variable Rate Application to Improve Cro Protection in Orchards and Vineyards. Prescription Maps and Satellites to Accomplish EU Farm to Fork StrategyAccurate canopy characterization is crucial for a targeted application of plant protection products following variable rate application (VRA) concept. Remote sensing offers a robust and rapid monitoring tool that allows determining the characteristics of the vegetation from aerial platforms at different spatial resolutions. Previous work have demonstrated that drone-based imagery can be used to estimate canopy height, width, and canopy volume accurately enough to allow a full automation of VR... E. Gil, F. Garcia-ruíz, J. Biscamps, R. Salcedo, J. Campos |
30. Explainable Neural Network Alternatives for Ai Predictions: Genetic Algorithm Quantitative Association Rule MiningNeural networks in one form or another are common precision agriculture artificial intelligence techniques for making predictions based on data. However, neural networks are computationally intensive to train and to run, and are typically “black-box” models without explainable output. This paper investigates an alternative artificial intelligence prediction technique, genetic algorithm quantitative association rule mining, which creates explainable output with impacts directly qua... M. Everett |
31. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV ImageryPollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness ... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack |
32. Application Accuracy of Two Different Sprayer Flow Control Systems During Site-specific Pesticide ApplicationsPrecise and efficient pesticide applications are crucial aspects of modern agriculture to effectively manage pests throughout the season while also reducing the negative impacts of pesticides on the environment. Recent advancements in spray technology, such as pulse width modulation (PWM) and individual nozzle control, have enabled capabilities for site-specific pesticide applications on modern application equipment. With the increasing interest of industry and growers in site-specific pestic... R.K. Meena, S. Virk, C. Byers, G. Rains |
33. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning ApproachWheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao |
34. 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 ... C. Ottley, M. Kudenov, P. Balint-kurti, R. Dean, C. Williams |
35. Quantifying Constant Rate and Sensor-based Variable Rate Nitrogen (N) Fertilizer Response on Crop Vigor and YieldAgricultural fertilizer application is one of the essential components of crop production. It enhances crop growth, yield, and quality of the crop. The most widely used methods for nutrient application are the constant rate and variable rate application. An improper supply of fertilizer can potentially hamper crop growth and reduce the quality of the crop. Therefore, there is a need to select the best optimum nutrient application method for proper utilization of the nutrients. Therefore, the ... R. Singh, A. Sharda |
36. Deep Learning for Predicting Yield Temporal Stability from Short Crop RotationsInvestigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris |
37. Enhancing Agricultural Feedback Analysis Through VUI and Deep Learning IntegrationA substantial amount of information relies on consumers, influencing aspects from product adoption to overall satisfaction. Similarly, the agricultural sector is entirely dependent on farmers, who dictate the success of products and highlight associated challenges. Our study aligns with this perspective, recognizing the significance of understanding farmers' needs to assist tractor manufacturing industries. As these industries aim for widespread adoption of their products among farmers, i... S. Kaushal, A. Sharda |
38. Assessing Spray Coverage Variability of an Under-canopy Robotic Sprayer System in Sorghum CropAn under-canopy robotic sprayer system was developed for site-specific pest management in row crops. However, the effect of nozzle type and spray coverage variability at different points within the plant canopy was unknown. The objective of this study was to quantify the spray coverage at multiple locations within the sorghum crop canopy to determine the effectiveness of such robotic systems. The experiments were conducted in a sorghum field in Ashland, Kansas, using XR8001 flat fan and TXVS6... P. Pokharel, A. Sharda, M. Gadhwal, B. Aryal |
39. Design and Development of a Spraying System for Under Canopy Rover and Its Integration with Computer Vision SystemChemical spraying such as herbicides, insecticides are essential in any agricultural field for controlling pest, weed etc. and ultimately increasing yield. About one-third of agricultural yields rely on the utilization of pesticides. However, around 3 billion kilograms of pesticides are used worldwide every year and effective utilization of it is merely 1%. The precise application of these chemicals is necessary to reduce negative impacts on environment as well as human health. The applicatio... N.K. Piya, A. Sharda, J.R. Persch, D. Flippo, R. Harsha chepally |
40. An Open Database of Crop Yield Response to Fertilizer Application for SenegalFood security is one of the major global challenges today. Africa is one of the continents with the largest gaps in terms of challenges for food security. In Senegal, about 60% of the population resides in rural areas and the cropping systems are characterized as a low productivity system, low input and in reduced areas, smallholder subsistence systems. Increasing crop productivity would have a positive impact on food security in this country. One of the main factors limiting crop produ... F. Gomez, A. Carcedo, A. Diatta, L. Nagarajan, V. Prasad, Z. Stewart, S. Zingore, I. Ciampitti, P. Djighaly |
41. On Data-driven Crop Yield Modelling, Predicting, and Forecasting and the Common Flaws in Published StudiesThere has been a recent surge in the number of studies that aim to model crop yield using data-driven approaches. This has largely come about due to the increasing amounts of remote sensing (e.g. satellite imagery) and precision agriculture data available (e.g. high-resolution crop yield monitor data), and abundance of machine learning modelling approaches. This is a particular problem in the field of Precision Agriculture, where many studies will take a crop yield map (or a small number), cr... P. Filippi, T. Bishop, S. Han, I. Rund |
42. Development and Evaluation of a Novel Variable-orifice Nozzle Flow and Droplet Size Control SystemSpray drift from crop production operations has been a critical concern across the U.S. as evidenced by the EPA’s efforts to mitigate pesticide drift. Recently, a novel spray control system was developed and evaluated which provided real-time control of both spray droplet size and flow rate. This was achieved via electromechanical control of a variable orifice nozzle along with a novel control system which incorporates real-time weather data to vary system pressure and orifice size and ... T. Monroe, J.D. Luck, S. Marx |
43. Generative Modeling Method Comparison for Class Imbalance CorrectionAn image dataset, for use in object detection of hay bales, with over 6000 images of both good and bad hay bales was collected. Unfortunately, the dataset developed a class imbalance, with more good bale images than bad bales. This dataset class imbalance caused the bad bale class to over train and the good bale class to under train, severely impacting precision, and recall. To correct this imbalance and provide a comparison of differing generative modeling methods; three di... B. Vail, Z. Oster, B. Weinhold |
44. 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-t... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff |
45. Machine Vision in Hay Bale ProductionThe goal of this project is to develop a system capable of real-time detection, pass/fail classification, and location tracking of large square hay bales under field conditions. First, a review of past and current methods of object detection was carried out. This led to the selection of the YOLO family of detectors for this project. The image dataset was collected through help from our sponsor, collection of images from the K-STATE research farm, and images collected from th... B. Vail |
46. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial IntelligenceThe Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power inf... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos |
47. Quantifying Boom Movement in Agricultural Sprayer Booms Using Neural Networks for Real-world Field ScenariosApplication rate errors in self-propelled agricultural sprayers remain a significant concern, necessitating a comprehensive understanding of boom movement during actual field operating scenarios. This study introduces new objectives to quantify boom movement across commercial sprayers when operated by different individuals and compares these movements among various machines. The goal is to develop a metric that identifies potential improvement needs for boom height control system. The approac... T. Kaloya, A. Sharda, A. Dalal |
48. Fungicide Application Methods and Corn Variety Effect on Corn Silage Deoxynivalenol LevelsMycotoxin contamination is a major challenge for dairy producers. Deoxynivalenol, (DON) a mycotoxin produced by the fungus Fusarium graminearum, can infect both the corn stalk and ear. Studies have found that 86% of corn silage samples have some concentration of DON. Deoxynivalenol causes major issues in the dairy industry causing decreased milk production, lower components, higher SCC, and decreased reproductive performance. The objective of this research project was to dete... J.M. Hartschuh, R. Minyo |
49. Machine Learning Model to Predict Total Nozzle Volume Delivery for Pulse Width Modulated Flow ControllersProduct flow rate in the Pulse Width Modulation (PWM) variable rate technologies depends on the duty cycle. However, the actual product flow rate at any duty cycle depends on pressure rise, stable pressure during the cycle, fall time and pressure drop across the nozzle body. The current controller does not consider the pressure drops and the estimation of actual flow during each cycle at any duty cycle cannot be estimated with capturing high-frequency pressure data. Knowledge of volume delive... S. Dua, A. Sharda |
50. Wheat Spikes Counting Using Density Prediction Convolution Neural NetworkVision-based wheat spikes counting can be valuable for pre-harvest yield estimation for growers and researchers. In this study, wheat spike counting convolutions neural networks were implemented to solve the problem of vision-based wheat yield prediction problem. Encoder-decoder style convolutional neural networks (CNN) were developed with a Global Sum Pooling (GSP) layer as its output layer and trained to produce a density map which predicts the pixelwise wheat spikes density. Thi... C. Liew, S. Pitla |
51. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask LearningRapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches wi... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat |
52. 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 (LS... A.H. Rabia, M.A. Salem |
53. 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 Imag... M.A. Salem, A.H. Rabia |
54. Application of Advanced Soft Computing to Estimate Potato Tuber Yield: a Case Study from Atlantic CanadaThe potato crop plays a crucial role in the economy of Atlantic Canada, particularly in Prince Edward Island and New Brunswick, where it contributes significantly to potato production. To help farmers make informed decisions for sustainable and profitable farming, this study was conducted to examine the variations in potato tuber yield based on thirty soil properties collected over four growing seasons through experimental trials. The study employed an advanced and explainable ensemble model ... Q.U. Zaman, A. Farooque, M. Jamei, T.J. Esau |
55. 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 comp... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre |
56. Integration of Post Emergence Herbicide (PoE) with Nano-urea for Optimized Management of Weed in Indian Black Mustard (Brassica Juncea L.)Nano-urea (NU) is gaining attention due to its environmental benefits and precise application. Unlike traditional urea fertilizers, NU is engineered at the nanoscale, which increases its efficiency and reduces environmental impacts. However, limited research has been done to evaluate the combined effect of herbicides and NU. Therefore, the overarching goal of our study is to conduct field trials to understand the optimization rates of the synergized composition of herbicide and NU. Our hypoth... B. Duary, U. Debangshi, W. Dutta, G. Jha |
57. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable SensorsLameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model pe... N. Mhlongo, H. De knegt, W.F. De boer, F. Van langevelde |