Year
| Filter results363 paper(s) found. |
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1. 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 |
2. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal DatesCrop planting and harvest dates are a major component affecting agricultural productivity, risk, and nutrient cycling. The ability to track these cardinal dates allows researchers to investigate strategies to manage risk and adapt to climate change. This study was conducted to determine whether nonlinear statistical models combined with remotely sensed data from satellites can be used to estimate planting and harvest dates. Time of planting and harvest were reported by farmers for 16 commerci... C.L. Dos santos, F. Miguez, L. Puntel, D. Bullock |
3. 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 |
4. A Case for Increased Precision Pesticide Application Adoption in California Perennial Specialty Crop ProductionMaintaining high and quality crop yields in California’s diverse agriculture requires both good crop care through nutrient management and water management and effective crop protection through integrated pest management (IPM). Despite the promotion and adoption of non-chemical IPM practices in California such as sanitation and biological control, pesticide use remains inevitable in many cases. According to the 2021 California Pesticide Use Report, 37,444,331 kg of pesticide was used in ... P.A. Larbi |
5. A Data Retrieval System to Support Observational Research of On-Farm ExperimentationObservational research is a powerful methodology, capable of rapidly identifying trends and patterns present in complex systems. New work seeks to apply these techniques to agronomic production systems. While data generated from on-farm experimentation are often considered anecdotal, these data hold significant importance for farmers because they originate from their distinctive agricultural systems. Combining the large volumes of farmer-collected data with remote sensing, environmental, and ... P. Lanza, A. Yore, L. Longchamps |
6. A Decision-support Tool to Optimize Mid-season Corn Nitrogen Fertilizer Management from Red, Green, Blue SUAS ImagesCorn receives more nitrogen (N) fertilizer per unit area than any other row crop and optimized soil fertility management is needed to help maximize farm profitability. In Arkansas, N fertilizer for corn is delivered in two- or three-split applications. Three-split applications may provide a better match to crop needs and contribute to minimizing yield loss from N deficiency. However, the total amounts are selected based on soil texture and yield goal without accounting for early-season losses... A. Poncet, T. Bui, W. France, T. Roberts, L. Purcell, J. Kelley |
7. 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 |
8. A Digital Twin for Arable Crops and for GrassThere is an opportunity to use process-based cropping systems models (CSMs) to support tactical farm management decisions, by monitoring the status of the farm, by predicting what will happen in the next few weeks, and by exploring scenarios. In practice, the responses of a CSM will deviate more and more from reality as time progresses because the model is an abstraction of the real system and only approximates the responses of the real system. This limitation may be overcome by using the CSM... F. Van evert, P. Van oort, B. Maestrini, A. Pronk, S. Boersma, M. Kopanja, G. Mimić |
9. A Flexible Software Architecture for General Precision Agriculture Decision Support SystemsAgricultural data management is a complex problem. Both the data and the needs of the users are diverse. Given the complexity of the problem, it's easy to ascertain that a single solution will not be able to meet the needs of all users. This paper presents a software architecture designed to be extensible as well as flexible enough to provide agricultural management tools for a wide variety of users. The solution is based on a microservice architecture, which allows for the creation of ne... W. Neils, D. Mommen |
10. A Fusion Strategy to Map Corn Crop ResiduesAccess to post-harvest residue coverage information is crucial for agricultural management and soil conservation. The purpose of this study was to present a new approach based on an ensemble at the decision level for mapping the corn residue. To this end, a set of Landsat 8 imagery and field data including the Residue Cover Fraction (RCF) of corn (149 samples), were used. Firstly, a map of common spectral indices for RCF modeling was prepared based on the spectral bands. Then, the efficiency ... S. Fathololoumi, M.K. Firozjaei, A. Biswas, P. Daggupati |