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| Filter results7 paper(s) found. |
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1. Wheat Growth Stages Discrimination Using Generalized Fourier Descriptors In Pattern Recognition Context... F. Cointault, A. Marin, L. Journaux, J. Miteran, R. Martin |
2. Using Crop Budgeting Spreadsheets Can Assist Producers In Evaluating The Cost Effectiveness Of Adoption Of The Various Precision Agriculture TechnologiesProducers asked the question which Precision Agriculture Technologies can be economical in my farming operation? The use of easily modified crop budgets can help the producer evaluate the technologies and how they affect the profitability of one’s agricultural enterprise.... R.N. Klein, R. Wilson |
3. 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 |
4. Realising the Potential of Agricultural Robotics and AI: The Ethical ChallengesRecent advances in AI and robotics may dramatically transform agriculture by greatly expanding the number of contexts in which the techniques of precision agriculture may be applied. Inevitably, this next agricultural revolution will generate profound ethical issues: opportunities as well as risks. Clever applications of AI and robotics may allow agriculture to be more sustainable by facilitating more precise applications of water, fertilisers, and herbicides. Robots may take some of the drudgery... R. Sparrow |
5. Sensor Based Fertigation ManagementSensor-based fertigation management (SBFM) is a relatively new technology for directing nitrogen (N) decisions, specifically tailored for delivery of N via center pivot irrigation systems (fertigation). The development of SBFM began in 2018 at the University of Nebraska-Lincoln with the help of cooperating producers across the state. Over two dozen field sites provided testbeds for the development and evaluation of the technology. The key technique in this fertigation approach is the... J. Stansell, J.D. Luck, T. Cross, K.J. Bathke, T. Smith |
6. 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 |
7. Sentinel Fertigation - Sponsor PresentationSentinel’s N-Time software leverages imagery and agronomic data to provide nitrogen application scheduling and rate recommendations to agronomists and farmers. Recommendations from the system have demonstrated profitability improvements of $24/ac and Nitrogen use efficiency (NUE) improvements of 30% in on-farm research studies since 2021. This presentation will discuss the function of N-Time, highlight the advantages of the management system it enables, and briefly discuss on-farm research... J. Stansell |