Proceedings
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| Filter results12 paper(s) found. |
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1. On-Farm Trials Using Precision Ag in Northeast LouisianaThe availability of yield monitors and precision application equipment on producers’ farms have made it much easier for researchers to take the results from experiment station trials and apply them to producers’ fields. Treatments/methods are applied in strips, by prescription, embedded plots or in combination. Fields are divided into zones for analyzing the harvest yield data. These can include soil type, soil Ec, or other criteria. Treatments are analyzed... D. Burns, D. Overstreet, D. Kruse, R. Frazier, D. Blanche |
2. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui |
3. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate FactorsEffective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability. The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measured... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi |
4. On-The-Go pH Sensor: An Evaluation in a Kentucky FieldA commercially available on-the-go soil pH sensor measures and maps subsurface soil pH at high spatial intensities across managed landscapes. The overall purpose of this project was to evaluate the potential for this sensor to be used in agricultural fields. The specific goals were to determine and evaluate 1) the accuracy with which this instrument can be calibrated, 2) the geospatial structure of soil pH measurements,... T. Mueller, E. Gianello, B. Mijatovic, E. Rienzi, M. Rodrigues |
5. Soil Organic Carbon Multivariate Predictions Based on Diffuse Spectral Reflectance: Impact of Soil MoistureSpatial predictions of soil organic carbon (OC) developed with proximal and remotely sensed diffuse reflectance spectra are complicated by field soil moisture variation. Our objective was to determine how moisture impacted spectral reflectance and Walkley-Black OC predictions. Soil reflectance from the North American Proficiency Testing... T. Mueller, C. Matocha, F. Sikora, B. Mijatovic, E. Rienzi |
6. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial InformationFarmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farmland.... Y. Dong, Y. Wang, X. Song, X. Gu |
7. Climate Change And Sustainable Precision Crop Production With Regard To Maize (Zea Mays L.)Precision crop production research activities were started during the mid-‘90s at the Institute of Biosystems Engineering, Faculty of Agricultural and Food Sciences, University of West Hungary. On the basis of the experiences with DSSAT (Decision Support System for Agrotechnology Transfer) the impact of climate change on maize yield (three soil types) was investigated until 2100. DSSAT crop growth model is used worldwide. The coupled model intercomparison project... A.J. Kovács, A. Nyéki, G. Milics, M. Neményi |
8. A Method To Estimate Irrigation Efficiency With Evapotranspiration DataIrrigation efficiency is defined as the ratio of irrigation water consumed by the crops to the water diverted (Wg) from a river or reservoir or wells. This terminology serves for better irrigation systems designation and irrigation management practices improvement. But it is hard or high cost with labor intensity to estimate irrigation efficiency from field measurement. This paper proposes an estimating method of irrigation efficiency at the scale of irrigation... H. Zeng, B. Wu, N. Yan |
9. Spatial and Temporal Variation of Soil Nitrogen Within Winter Wheat Growth SeasonThis study aims to explore the spatial and temporal variation characteristics of soil ammonium nitrogen and nitrate nitrogen within winter wheat growth season. A nitrogen-rich strip fertilizer experiment with eight different treatments was conducted in 2014. Soil nitrogen samples of 20-30cm depth near wheat root were collected by in-situ Macro Rhizon soil solution collector then soil ammonium nitrogen and nitrate nitrogen content determined by SEAL AutoAnalyzer3 instrument. Classical statistics... X. Song, G. Yang, Y. Ma, R. Wang, C. Yang |
10. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning AlgorithmsMachine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expensive... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre |
11. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter WheatNitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng |
12. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWANThe widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenting... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen |