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1. Canopy Temperature Mapping with a Vineyard RobotThe wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an ... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves |
2. Agricultural Robots: Drivers, Barriers and Opportunities for AdoptionIn the next decades, agriculture is to feed a rapidly growing population, while tackling changes in climate, overexploited resources, changes in markets and competition with other sectors. Agriculture is, therefore, expected to move towards a more sustainable intensification. In this context, robotic technologies are aimed to reduce labor, using fewer resources and improving agricultural productivity. There is growing demand and awareness of the potential use of such technologies in the farmi... K. Rial-lovera |
3. 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) seque... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham |
4. UAV Images As a Source for Retrieval of Machine Tracks and Vegetation Gaps Along Crop RowsThe trend of acquiring equipment and obtaining high resolution remote sensed images by Unmanned Aerial Vehicles (UAV) have been followed by sugarcane producers in Brazil, given its low cost. The images taken from fields have been used for retrieval of information like Digital Terrain Models (DTMs) from stereoscopy of overlapping images and spatial variance of biomass. In sugarcane production, driving deviations occur during planting because of manual steering inaccuracy, sliding of machines s... M. Spekken, J.P. Molin |
5. Economics of Swarm Bot Profitability for Cotton HarvestImproved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row ... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine |
6. High Accuracy Path Tracking for Rice Drill Seeder in Uneven Paddy FieldsHigh accuracy track tracing is a challenging task in paddy fields due to uneven grounds as well as wet soil conditions, thus restricting the development of autonomous rice drill seeder in China. For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven mud paddy fields is introduced in this paper. Combining lateral deviation and heading a... Y. Li, Y. Zhang, X. Liu, C. Liu |
7. Development of a Machine Vision Yield Monitor for Shallot Onion HarvestersCrop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully develop... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller |
8. Computer Vision Techniques Applied to Natural Scenes Recognition and Autonomous Locomotion of Agricultural Mobile RobotsThe use of computer systems in Precision Agriculture (PA) promotes the processes’ automation and its applied tasks, specifically the inspection and analysis of agricultural crops, and guided/autonomous locomotion of mobile robots. In this context, this research aims the application of computer vision techniques for agricultural mobile robot locomotion, settled through an architecture for the acquisition, image processing and analysis, in order to segment, classify and recognize patterns... L.C. Lugli, M.L. Tronco, A.J. Porto |
9. Comparing Profitability of Variable Rate Nitrogen Prescription MethodsVariable rate nitrogen (VRN) prescriptions have been field-tested against uniform N application for over 25 years. VRN prescription algorithms vary in the type and cost of information they require. To date, few studies have compared the benefits and costs of alternative VRN prescription methods. VRN prescriptions draw on diverse information, including soil and tissue N sampling, yield history (YH), and remotely sensed spectral reflectance (such as the Normalized Differen... S. Lee, S.M. Swinton |
10. Yield Analysis in Sugarcane Harvesters Using Design of Experiments (DoE) MethodologyThe sugarcane crop is highlighted in national agribusiness, Brazil is the world’s largest producer of the plant, and the prospection of specialists is of strong growth for the next years. However, in order to increase productivity, technological interventions through of precision agriculture must be implemented. Among them, the management of inputs guided by yield spatial variability for otmizing production and income. This project approaches the implementation of the methodology of ana... M.L. Da silva, J. . Alves de lima, A. Balbinot, J.P. Molin |
11. Interoperability As an Enabler for Principled Decision-making in Irrigation: the Precision Agriculture Irrigation Language (PAIL)Fresh water is a scarce resource, and agriculture consumes a high fraction of it worldwide. As climate change increases the likelihood of high temperatures and droughts, irrigation becomes an increasingly attractive option for managing crop production risks. Unfortunately, and despite decades of efforts by professional associations to promote the use of a principled, data-driven approach to irrigation scheduling often called scientific irrigation scheduling (SIS), the fraction of far... R. Ferreyra, C.C. Hillyer, H.D. Fuller, B. Craker, K. Watanabe |
12. Standards for Data-driven Agrifood Systems, One Year After the ISO Strategic Advisory Group for Smart FarmingThe lack of data interoperability is a major obstacle for the data-driven, principled multi-objective decision-making required for modern agrifood systems to help meet the UN Sustainable Development Goals. Aware of this, the International Organization for Standardization (ISO) chartered a Strategic Advisory Group for Smart Farming (SAG-SF) to survey the existing standardization landscape of the domain within ISO, to identify gaps where additional standardization is needed, and to provide a st... R. Ferreyra, J. Lehmann, J.A. Wilson |
13. Digital Agriculture Driven by Big Data Analytics: a Focus on Spatio-temporal Crop Yield Stability and Land ProductivityIn the ever-evolving landscape of agriculture, the adoption of digital technologies and big data analytics has ushered in a transformative era known as digital agriculture. This paradigm shift is primarily motivated by the pressing imperative to address the growing global population's food requirements, mitigate the adverse effects of climate change, and promote sustainable land management. Canada, a significant player in global food production, has made a substantial commitment to reduci... K. Nketia, T. Ha, H. Fernando, S. Shirtliffe, S. Van steenbergen |
14. Assessing Plant Spacing Inequality and Its Impact on Crop Yield Using Lorenz Curves and Gini IndexPlant spacing is the distance between individual plants in a crop field. It is vital for proper crop establishment as it can influence the spatial and temporal variation in plant emergence. These variations alter how plants interact for light, water, and nutrient resource needs, which, in turn, impact an individual plant's growth conditions and crop yield. Alternatively, studies have associated uniformity in plant spacing with higher yields and increased weed suppression. Modern precision... B. Aryal, A. Sharda, J. Peiretti |
15. Almonds and Pistachios: Sustaining Legacy, Innovations, and Nutritional Advancements in CaliforniaCalifornia's unique Mediterranean climate has made it the global epicenter for tree nut production, providing nearly 99 percent of the nation’s almond and pistachio supply. The California tree nut industry is characterized by its deep-rooted heritage, with 90% of its farms being family-owned and operated, often spanning multiple generations. These farmers have been at the forefront of agricultural innovation, investing approximately millions of dollars annually in scientific researc... H. Kulhandjian, S. Asci |
16. Predicting Water Potentials of Wild Blueberries During Drought Treatment Using Hyperspectral Sensor and Machine LearningDetecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) us... Y. Zhang, U.R. Hodeghatta, V. Dhiman, K. Barai, T. Trang |
17. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean YieldClimate is one of the primary factors that affects agricultural production. Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effec... R. Dhillon, G. Takoo |
18. Environmental Characterization for Rainfed Maize Production in the US Great Plains RegionIdentifying regions with similar productivity and yield-limiting climatic factors enables the design of tailored strategies for rainfed maize (Zea mays L.) production in vulnerable environments. Within the United States (US) Great Plains region, rainfed maize production in Kansas is susceptible to weather fluctuations. This study aims to delimit environmental regions with similar crop growth conditions and to identify the main climatic factors limiting rainfed maize yield, using the ... L.N. Lingua, A. Carcedo, V. Gimenez, G. Maddonni, I. Ciampitti |
19. A Digital Interactive Decision Dashboard to Analyze, Store and Share Year-to-year Crop Genotype YieldThe lag time between data collection and sharing is a critical bottleneck in order to make impactful decision at farmer field-scale. Following this line, there is a need for developing a digital interactive decision dashboard for sharing results of crop trials, in parallel to establish a database for storing data. These crop trials, invaluable for farmers seeking to determine the optimal genotype for their crops, are at risk of becoming obsolete due to the current format and the lack of more ... P. Magalhaes cisdeli, G.N. Nocera santiago, I. Ciampitti, C. Hernandez |
20. Can Soil Fertility Data and Topography Predict Yield Stability Zones for Corn Fields in New York?Yield monitor systems play a vital role in precision agriculture given their ability to capture and map within-field yield variability. When three or more years of yield data are available, yield stability zone maps can be generated to show both the spatial and temporal variability of yield within a field. Based on the farm’s overall temporal mean and standard deviation for a specific crop, we can classify areas in the field as consistently high- (Q1) or low-yielding (Q4), and variably ... M. Marcaida, X. Zhang, S. Srinivasagan, S. Shajahan, Q. Ketterings |
21. Private Simple Databases for Digital Records of Contextual Events and ActivitiesFarmers’ commitment and ability to keep good records varies tremendously. Records and notes are often cryptic, misplaced, or damaged and for many, remain unused. If such information were recorded digitally and stored in the cloud, we immediately solve some access and consistency issues and make this data FAIR (findable, accessible, interoperable, reusable). More importantly, interoperable digital formats can also enable mining for insights and analysi... M.S. Basir, J. Krogmeier, Y. Zhang, D. Buckmaster |
22. Assessing the Variability in Cover Crop Growth Due to Management Practices and Biophysical Conditions Using a Mixed Modeling ApproachPlanting winter cover crops provides numerous agronomic and environmental benefits. Cereal rye, which is a commonly planted cover crop in Ohio, when established, offers advantages such as recycling residual nitrogen in the soil, enhancing soil organic matter, and reducing nutrient loss. However, understanding cover crop growth is challenging due to field management and weather conditions, and insights using traditional methods are limited. Remote sensing offers a cost-effective and timely alt... K. Kc, S. Khanal, N. Bello, S. Culman |
23. Analytics Model for Predicting Sucrose Percentage in Sugarcane Using Machine Learning TechniquesSucrose is one of the most important indicators in the final profitability of Colombian sugar mills, therefore, its understanding and forecast are fundamental for the business. In this work, a proposal is formulated for an analysis model that allows predicting the percentage of sucrose based on historical data from mechanically harvested farms with the objective of knowing the numerical value of sucrose for each month of milling and be able to plan monthly and annual sugar production. ... P. Valencia ramirez |
24. Computer Vision by UAVs for Estimate Soybean Population Across Different Physiological Growth Stages and Sowing SpeedsSoybean (Glycine max (Linnaeus) Merrill) production in the United States plays a crucial role in agriculture, occupying a considerable amount of cultivated land. However, the costs associated with soybean production have shown a notable increase in recent years, with seed-related expenses accounting for a significant proportion of the total. This increase in costs is attributed to a number of factors, including the introduction of patented and protected genetic traits, as well as inflationary... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. Deri setiyono, S. campos |
25. Ground-based Imagery Data Collection of Cotton Using a Robotic PlatformIn modern agriculture, technological advancements are pivotal in optimizing crop production and resource management. Integrating robotics and image processing techniques allows the efficient collection, analysis, and storage of high-resolution images crucial for monitoring crop health, identifying pest infestations, assessing growth stages, making precise management decisions and predicting yield potential. The objective of this project is to utilize the Farm-NG Amiga robot to develop an imag... O. Fernandez, M. Bhandari, J.L. Landivar-scoot, M. Eldefrawy, L. Zhao, J. Landivar |