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1. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision AgricultureIn this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a lon... S.P. Nayse, A.S. Mohammad |
2. Rapidscan And CropCircle Radiometers: Opportunities And Limitation In Assessing Wheat Biomass And NitrogenRemote sensing is a promising technology that provides information about the crop's physiological and phenological status. This information is based on the spectral absorption and scattering features of the plants. Many different vegetation indices (VI) have been developed, and are in use to estimate quantitatively the relationship between multi and hyper-spectral reflectance and effective crop physiological parameters, i.e. nitrogen (N) content, biomass, leaf area index (LAI). The C... A.A. Gitelson, D.J. Bonfil |
3. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North DakotaA recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indic... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen |
4. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation ApproachesNitrogen (N), an essential element, is often limiting to plant growth. There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses. Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs. Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen |
5. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut TreesA knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightb... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo |
6. Using Precision Agriculture And Remote Sensing Techniques To Improve Genotype Selection In A Breeding ProgramPrecision Agriculture (PA) and Remote Sensing (RS) technologies are increasingly being used as tools to assess crop and soil properties by breeders and physiologists. These technologies are showing potential to improve genotype selections over their traditional field measurements, by providing quick access to crop properties throughout the crop cycle and yield estimation. The objective of this work was to use vegetation indices (VIs) and soil apparent electrical conductivi... F.A. Rodrigues junior, I. Ortiz-monasterio, P.J. Zarco-tejada, K. Ammar, B.G. Gérard |
7. Development Of An Index-Based Insurance Product: Validation Of A Forage Production Index Derived From Medium Spatial Resolution fCover Time SeriesAn index-based insurance solution is developed by Pacifica Crédit Agricole Assurances and Astrium GEO-Information to estimate and monitor the near real-time forage production in France. In this system, payouts are indexed on an indicator, called Forage Production Index (FPI), calculated using a biophysical characterization of the grassland from medium spatial resolution remote sensing time series. We used the Fraction of green Vegetation Cover (fCover) integral ... A. Jacquin, G. Sigel, O. Hagolle, B. Lepoivre, A. Roumiguié, H. Poilvé |
8. Detection Of Drainage Failure In Reconstructed Cranberry Soils Using Time Series AnalysisA cranberry farm is often a semi-closed water system, where water is applied by means of irrigation and drained using an artificial drainage system. Cranberry bogs must be drained to the water level inside the surrounding ditches in order to maintain an optimal pore pressure within the root zone, which is important for a number of reasons. First of all, Phytophthara causing root rot are commonly associated with irrigation with contaminated surface water (Oudemans, 1999)... S.J. Gumiere, Y. Périard, J. Caron, D.W. Hallema, J.A. Lafond |
9. Comparison Of Calibration Models Developed For A Visible-Near Infrared Real-Time Soil SensorThe visible-near infrared (Vis-NIR) based real-time soil sensor (RTSS) is found to be a great tool for determining distribution of various soil properties for precision agriculture purposes. However, the developed calibration models applied on the collected spectra for prediction of soil properties were site-specific (local). This is found to be less practical since the RTSS needs to be calibrated separately for every field. General calibration approach is expected to ... S. Shibusawa, M. Kodaira, I. Kana, S.N. Baharom |
10. Cotton Field Relations Of Plant Height To Biomass Accumulation And N-Uptake On Conventional And Narrow Row SystemsAlthough studied for decades, cotton field management remains a challenge for growers, especially due to spatial variability of soil conditions and crop growth, which demands the use of variable rate application technology (VRT) for nitrogen and growth regulators to improve yields and quality and/or save inputs. Canopy optical reflectance sensors are being studied as an option to detect infield variability but may have some limitations due to the known effect of signal saturation when us... N. . Vilanova jr., J.P. Molin, C. Portz, L.V. Posada, G. Portz, R.G. Trevisan |
11. X-Ray Computed Tomography For State Of The Art Plant And Root AnalysisDuring the last years, the formerly in medical applications established technique of X-ray computed tomography (CT) is used for non-destructive material analysis as well. Adapting this technique for the visualization and analysis of growth processes of plants above and underneath the soil enables new possibilities in the so called smart agriculture. Using State-of-the-art CT systems the computed 3D volume datasets allows the visualization and virtual analysis of hidden structures like ro... S. Reisinger, N. Uhlmann, R. Hanke, S. Gerth |
12. Evaluation Of In-Field Sensors To Monitor Nitrogen Status In SoybeanIn recent years, active optical crop sensors have been gaining importance to determine in-season nitrogen (N) fertilization requirements for on-the-go variable rate application. Although most of these active in-field crop sensors have been evaluated in corn and wheat crops, they have not yet been evaluated in soybean production systems in North Dakota. Recent research from both South Dakota and North Dakota indicate that in-season N application in soybean can increase soybean yield... J. Nowatzki, S. Bajwa, S. Sivarajan, M. Maharlooei, H. Kandel |
13. Crop Circle Sensor-Based Precision Nitrogen Management Strategy For Rice In Northeast ChinaGreenSeeker (GS) sensor-based precision N management strategy for rice has been developed, significantly improved N fertilizer use efficiency. Crop Circle ACS-470 (CC) active sensor is a new user configurable sensor, with a choice of 6 possible bands. The objectives of this study were to identify important vegetation indices obtained from CC sensor for estimating rice yield potential and rice responsiveness to topdressing N application and evaluate their potential improvements over GS no... Q. Cao, Y. Miao, J. Shen, S. Cheng, R. Khosla, F. Liu |
14. Design And Construction Of An Ultrasonic Cutting Width Sensor For Full-Feed Type Mid-Sized Multi-Purpose CombinesPrecision agriculture analyzes the spatial variability according to the characteristics of an optimum setting of agricultural materials. To raise the profitability of agriculture and to reduce the environmental impact, technological research and development of precision agriculture has been conducted. In Asian countries such as Ja... Y. Huh, S. Chung, Y. Chae, J. Lee, S. Kim, M. Choi, K. Jung |
15. Design And Implementation Of Agricultural Sensor Data Of Multiple And Heterogeneous Access ArchitectureFor the moment, the Internet of things system oriented to the whole industry chain is gradually established in some fields of agriculture; At the same time, traditional management style of agricultural sensor data lack effective sharing mechanism, that can not meet the demand of agricultural network system for the multiple and heterogeneous sensor data. Especially with the growing the demand of agricultural products quality safety supervision system to the monitoring of agricult... T. Chen, D. Chen, J. Dong, S. Jiang |
16. Towards Automated Pneumatic Thinning Of Floral Buds On Pear TreesThinning of pome and stone fruit is an important horticultural practice that is used to enhance fruit set and quality by removing excess floral buds. As it is still mostly conducted through manual labor, thinning comprises a large part of a grower’s production costs. Various thinning machines developed in recent years have clearly demonstrated that mechanization of this technique is both feasible and cost effective. Generally, these machines still lack sufficient selectivi... N. Wouters, R. Van beers, B. De ketelaere, T. Deckers, J. De baerdemaeker, W. Saeys |
17. Using Imagery As A Proxy Yield Map And Scouting ToolCombine yield maps represent a post-mortem quantification of the spatial variability in crop vigor that occurred during the growing season. The spatial resolution of yield maps is defined by the width of the combine header but the length of the cell depends on the ground-speed of the implement and how long it takes for the grain t... J.S. Schepers, A.R. Schepers |
18. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane FieldsNitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, de... G.M. Sanches, R. Otto, F.R. Pereira |
19. A Passive-RFID Wireless Sensor Node for Precision AgricultureAccurate soil data is crucial for precision agriculture. While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback. In thi... P.J. Goodrich, C. Baumbauer, A.C. Arias |
20. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use EfficiencyCurrent tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR). Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmenta... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey |
21. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and IndianaPrecision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minne... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor |
22. Nitrogen Fertilization of Potato Using Management Zone in Prince Edward Island, CanadaPotato is sensible to nitrogen (N) and optimal N fertilization improve the tuber yield and its quality. Potato crop N response varies widely within fields. It is also well recognized that significant spatial and temporal variation in soil N availability occurs within crop fields. However, uniform application of N fertilizer is still the most common practice under potato production. Management zone (MZ) approach can help growers to achieve a part of this. The goal of the project is to compare ... A. Cambouris, M. Duchemin, N. Ziadi |
23. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine LearningPrecision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li |
24. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 ImageryPasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of th... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães |
25. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping SystemNitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application&... E.A. Flint, M. Yost, B.G. Hopkins |
26. Evaluation of Nitrogen Recommendation Tools for Winter Wheat in NebraskaAttaining both high yield and high nitrogen (N) use efficiency (NUE) simultaneously remains a current research challenge in crop production. Digital ag technologies for site-specific N management have been demonstrated to improve NUE. This is due to the ability of digital technologies to account for the spatial and temporal distribution of crop N demand and available soil N in the field which varies greatly according t... J. Cesario pereira pinto, L. Thompson, N. Mueller, T. Mieno, G. Balboa, L. Puntel |
27. Nitrogen Placement Considerations for Maize Production in the Eastern US CornbeltProper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production.&... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer |
28. In-season Nitrogen Management of Maize Based on Nitrogen Status and Lodging Risk PredictionDevelopment of effective precision nitrogen (N) management strategies is crucially important for food security and sustainable development. Lodging is one of the major constraints to increasing maize yield that can be induced by strong winds, and is also influenced by management practices, like N rate. When making in-season N application decisions, lodging risk should be considered to avoid yield loss. Little has been reported on in-season N management strategies that also incorporate lodging... R. Dong, Y. Miao, X. Wang |
29. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter WheatOptimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequentl... D. Ghimire |
30. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather DataNitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by c... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia |