Proceedings
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| Filter results23 paper(s) found. |
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1. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten |
2. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation IndicesApplication of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US requires... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom |
3. Row-Crop Planter Requirements To Support Variable-Rate Seeding Of MaizeCurrent planting technology possesses the ability to increase crop productivity and improve field efficiency by precisely metering and placing crop seeds. Growing high yielding crops not only requires using the right seed variety and rate but also achieving optimal performance with available planter technology. Planter performance depends on using the correct planter and technology (display and rate controller system) setup which consists of determining optimal settings for different planting... J.P. Fulton, K.S. Balkcom, B.V. Ortiz, T.P. Mcdonald, G.L. Pate, S.S. Virk, A. Poncet |
4. Use Of Active Radiometers To Estimate Biomass, Leaf Area Index, And Plant Height In CottonActive radiometers have been tested extensively as tools to assess in-season nitrogen (N) status of crops like wheat (Triticum aestivum), corn (Zea mays), and cotton (Gossypium hirsutum). Fewer studies target in-season plant growth parameters such as biomass, plant height or leaf area index (LAI). Uses of this plant data include simulation modeling, total N uptake measurements, evapotranspiration (ET) estimates and irrigation... K.R. Thorp, J.W. White, M.M. Conley, J. Mon, K.F. Bronson |
5. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate ChangePhenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller |
6. A Pilot Study on Monitoring Drinking Behavior in Bucket Fed Dairy Calves Using an Ear-Attached Tri-Axial AccelerometerAccelerometers support the farmer with collecting information about animal behavior and thus allow a reduction in visual observation time. The milk intake of calves fed by teat-buckets has not been monitored automatically on commercial farms so far, although it is crucial for the calves’ development. This pilot study was based on bucket-fed dairy calves and intended (1) to evaluate the technical feasibility of using an ear-attached accelerometer (SMARTBOW, Smartbow GmbH, Weibern, Austria)... L. Roland, L. Lidauer, G. Sattlecker, F. Kickinger, W. Auer, V. Sturm, D. Efrosinin, M. Drillich, M. Iwersen, A. Berger |
7. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy CowsThe objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger |
8. Ear-Attached Accelerometer as an On-Farm Device to Predict the Onset of Calving in Dairy CowsThe objective of this study on an ear-attached accelerometer in dairy cows was (1) to determine activity, rumination and lying time of the dams prior to calving, and include group level of measured variables (2) use the data to develop an algorithm to predict calving and (3) to test the performance of this algorithm. Video observations (24h/d) were used as reference for these events. Four weeks before expected calving, an ear-tag integrated tri-axial accelerometer (SMARTBOW system) was attached... S. Krieger, M. Oczak, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger |
9. Evaluation of the Ear-Tag Sensor System SMARTBOW for Detecting Estrus Events in Indoor Housed Dairy CowsLivestock farming technologies have a tremendous potential to improve and support farmers in herd management decisions, in particular in reproductive management. Nowadays, estrus detection in cows is challenging and many detection tools are available. The company Smartbow (Weibern, Austria) developed a novel ear-tag sensor, which consists of a 3D-accelerometer that records head and ear movements of cows as basis for algorithm development and further analyses. Estrus detection by the SMARTBOW system... V. Schweinzer, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger |
10. Evaluation of a Wireless Pulse Oximeter to Measure Arterial Oxygen Saturation and Pulse Rate in Newborn Holstein Friesian CalvesPulse oximetry is a well-established technique in nowadays human and veterinarian medicine. Also in the farm animal sector, it could be a useful tool to detect critical conditions of the oxygen supply and the cardiovascular system of the patient. However, its use in ruminant medicine is still limited to experimental application. The objective of this study was to evaluate the accuracy of a Radius-7 Wearable Pulse Oximeter (Masimo Corporation, Irvine, CA) for monitoring the vital parameters of... P. Kanz, S. Krieger, M. Drillich, M. Iwersen |
11. Snap Bean Flowering Detection from UAS Imaging SpectroscopySclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmanned... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert |
12. Establishment of a Canola Emergence Assessment Methodology Using Image-based Plant Count and Ground Cover AnalysisManual assessment of emergence is a time-consuming practice that must occur within a short time-frame of the emergence stage in canola (Brassica napus). Unmanned aerial vehicles (UAV) may allow for a more thorough assessment of canola emergence by covering a wider scope of the field and in a more timely manner than in-person evaluations. This research aims to calibrate the relationship between emerging plant population count and the ground cover. The field trial took place at the University... K. Krys, S. Shirtliffe, H. Duddu, T. Ha, A. Attanayake, E. Johnson, E. Andvaag, I. Stavness |
13. Can Topographic Indices Be Used for Irrigation Management Zone DelineationSoil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble |
14. Towards a Digital Peanut Profile Board: a Deep Learning ApproachArtificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profile... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui |
15. 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 |
16. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in AlabamaEfficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De oliveira |
17. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in AlabamaHarvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis |
18. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation StrategiesFarmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble |
19. 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 hypothesis... B. Duary, U. Debangshi, W. Dutta, G. Jha |
20. Evaluation of Peanut Response to Soil Water Levels Using the Crop Water Stress Index Generated from Infrared Thermal Sensors and ImageryIn precision agriculture, precise monitoring of crop water stress is crucial for optimizing water use, increasing crop yield, and promoting environmental sustainability. Achieving high water use efficiency in peanut production is key to producing high-quality crop. This study investigates the efficiency of infrared thermal sensors and thermal imagery from satellites and unmanned aerial vehicles (UAVs) for determining peanut crop water stress index (CWSI). Furthermore, this research explores the... B. Parbi, B.V. Ortiz, E. Abban-baidoo , A. Sanz-saez, J.S. Velasco |
21. Using Simulation Modeling to Evaluate the Corn Response to Deficit Irrigation Imposed During Reproductive PeriodIn Alabama, as in many regions of the southeastern states, flash droughts and rising temperatures present significant challenges to the sustainability of agricultural systems. Specifically maize, a crop with a high water demand, faces production risks due to these adverse conditions. The study explores the optimum irrigation scheduling strategies on maize (Zea mays L.) in the reproductive growth stages through the evaluation of the impact of three irrigation treatments, defined by Maximum Allowed... J.S. Velasco, B.V. Ortiz, L. Nunes, R. Prasad, G. Hoogenboom |
22. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management ZonesInvestment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed with... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe |
23. Precision Nitrogen Management Community MeetingAgenda Welcome to the meeting participants by Dr. Brenda Ortiz (Professor at Auburn University) 2022-2024 community leader and incoming leader Dr. Laila Puntel (Syngenta). Brief update of activities and opportunities for the upcoming years (Brenda Ortiz) Strategies to assess precision nutrient management educational needs and networking opportunities among community members and ISPA in general. Discuss possibilities for collaboration... B.V. Ortiz, L.A. Puntel |