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| Filter results11 paper(s) found. |
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1. Affordable Multi-Rotor Remote Sensing Platform for Applications In Precision Horticulture.Satellite and aerial imaging technologies have been explored for a long time as an extremely useful source of collecting cost-effective data for agricultural applications. In spite of the availability of such technologies, very few growers are using the technology... R. Ehsani, S. Sankaran, J.M. Maja, J.C. Neto |
2. Estimation of Leaf Nitrogen Concentration in Barley with In Situ Hyperspectral MeasurementsLeaf nitrogen concentration (LNC), a good indicator of nitrogen status in crop, is of special significance to diagnose nutrient stress and guide nitrogen fertilization in fields. Due to its non-destructive and quick advantages, hyperspectral remote sensing plays a unique role... J.M. Wang, C.M. Li, X.M. Yang, W.M. Huang, H.M. Yang, X.M. Xu |
3. Predicting Winter Wheat Biomass And Grain Protein ContentDynamic crop models such as EPIC [1], SALUS [2], and STICS [3] are non-linear models that describe the growth and development of a crop interacting with environmental factors (soil and climate) and agricultural practices (crop species, tillage type, fertilizer amount…). They are developed to predict crop yield and quality or to optimize the farming practices in order to satisfy agricultural objectives, as the reduction of nitrogen lixiviation. More recently, crop... M.M. Mansouri |
4. Spatial Dependence Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar For Sandy SoilThe Currently practiced mechanization for the production of sugar cane involves a heavy traffic of machinery and equipment. Studying the culture in its development environment generates a huge amount of information to fit the top managements and varieties for specific environments. The sugar cane cultivation has a heavy traffic of machinery and equipment, having more than 20 operations per cycle, and being more intense during harvest, providing increasing... I. Marasca, F.C. Masiero, D.A. Fiorese, S.S. Guerra, K.P. Lancas |
5. Spatial Variability Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar Land Clay SandyThe assessment of soil compaction levels and choosing the best management system are very important in modern agriculture, aiming to prevent or at least restore their physical conditions to a satisfactory level. The renewal of sugar cane plantation happens on average every 5 or 6 years. The current way repeats a sequence compaction and decompaction events during successive cycles of sugarcane, which promotes breakdown of soil structure. During the harvesting and transportation, the... F.C. Masiero, B.B. Fernandes, S.P. Guerra, K.P. Lanças, I. Marasca |
6. Yield Maps, Soil Maps, and Technical Efficiency: Evidence from U.S. Corn FieldsYield maps and GPS-based soil maps have been increasingly used in U.S. agriculture but little research has explored the economic relationship between mapping technologies and agricultural productivity. Research on this relationship is lacking, perhaps because maps are information inputs that do not directly enter the production function in a comparable way to conventional inputs. A stochastic frontier model was used to evaluate one potential avenue through which mapping technologies may influence... J. Mcfadden, A. Rosburg |
7. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision AgriculturePrecision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protein... J. Sheppard, A. Peerlinck, B. Maxwell |
8. Constraint of Data Availability on the Predictive Ability of Crop Response Models Developed from On-farm ExperimentationDue to the variability between fields and across years, on-farm experimentation combined with crop response modeling are crucial aspects of decision support systems to make accurate predictions of yield and grain protein content in upcoming years for a given field. To maximize accuracy of models, models fit using environmental covariate and experimental data gathered up to the point that crop responses (yield/grain protein) are fit repeatedly over time until the model can predict future crop responses... P. Hegedus, B. Maxwell |
9. Ecological Refugia As a Precision Conservation Practice in Agricultural SystemsCurrent global agriculture fails to meet the basic food needs of 687.7 million people. At the same time, our food system is responsible for catastrophic losses of biodiversity. Precision conservation solutions offer the potential to benefit both production systems and natural systems. Transforming low-producing areas on farm fields into ecological refugia may provide small-scale habitat and ecosystem services in fragmented agricultural landscapes. We collaborated with three precision agriculture... H. Duff, B. Maxwell |
10. Generation of Site-specific Nitrogen Response Curves for Winter Wheat Using Deep LearningNitrogen response (N-response) curves are tools used to support farm management decisions. Conventionally, the N-response curve is modeled as an exponential function that aims to identify an important threshold for a given field: the economic optimum point. This is useful to determine the nitrogen rate beyond which there is no actual profit for the farmers. In this work, we show that N-response curves are not only field-specific but also site-specific and, as such, economic optimum points should... G. Morales, J.W. Sheppard, A. Peerlinck, P. Hegedus, B. Maxwell |