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1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea CropThe software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc |
2. GNSS Tracking Of Livestock: Towards Variable Fertilizer Strategies For The Grazing IndustryThis study reveals the potential for GPS tracking in the grazing industry. By monitoring the locations and movement of livestock, times of peak grazing activity can be identified and these can in turn produce maps of preferred grazing areas, and by examining residency times provide an indication of spatial variability in grazing pressure. A comparison of grazing preference can be made to similarly inferred camping areas to understand the potential redistribution of nutrients within a paddock.... M.G. Trotter, D.W. Lamb, G.N. Hinch, C.N. Guppy |
3. Ultra Low Level Aircraft (ULLA) As A Platform For Active Optical Sensing Of Crop BiomassCrop producers requiring crop biomass maps to support timely application of in-season fertilisers, pesticides or growth regulators rely on either on-ground active sensors or airborne/satellite imagery. Active crop sensing (for example using Yara N-SensorTM, GreenseekerTM or CropcircleTM) can only be used when the crop is accessible by person or vehicle, and extensive, high-resolution coverage is time consuming. On the other hand, airborne or satellite imaging is... D.W. Lamb, M.G. Trotter, D. Schneider |
4. New Power-leds Based Illumination System For Fertilizer Granule Motion EstimationEnvironmental problems have become more and more pressing in the past twenty years particularly with the fertilization operation, one main contributor to environmental imbalance. The understanding of the global centrifugal spreading process, most commonly used in Europe, can contribute to provide essential information about fertiliser granule deposition on the soil. This last one can be predicted using a ballistic flight model and several fertilizer characteristic’s determination... F. Cointault, B. Hijazi, J. Dubois, J. Vangeyte, M. Paindavoine |
5. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol SoilCrop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado |
6. Management Of Remote Imagery For Precision AgricultureSatellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack |
7. Precision Livestock Management: An Example Of Pasture Monitoring In Eastern Australian Pastures Using Proximal And Remote Sensing ToolsPasture monitoring Australian rangelands by Remote Sensing G.E.Donald. CSIRO Livestock Industries, Locked Bag 1, Armidale NSW, 2350 Australia A series of spatial models and datasets were jointly developed to estimate pasture biomass as feed on offer (FOO®) and pasture growth rate (PGR®) in the south-west... G.E. Donald, M.G. Trotter, D.W. Lamb, G. Levow, H.M. Van es |
8. Introducing Precision Agriculture To High School Students In AustraliaThere is a growing need for tertiary qualified graduates in the Australian agricultural industry with only 7% of those employed in the sector holding a tertiary qualification compared to over 25% for the national workforce. With the need to greatly increase food and fibre production to feed and clothe a growing global population, and the adoption of precision agriculture technologies playing a huge part in this task, it is worrying that the demand for tertiary courses in agriculture in Australia... M.G. Trotter, A.M. Cosby |
9. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, CanadaManagement zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath |
10. Proximal Soil Sensing-Led Management Zone Delineation for Potato FieldsA fundamental aspect of precision agriculture or site-specific crop management is the ability to recognize and address local changes in the crop production environment (e.g. soil) within the boundaries of a traditional management unit. However, the status quo approach to define local fertilizer need relies on systematic soil sampling followed by time and labour-intensive laboratory analysis. Proximal soil sensing offers numerous advantages over conventional soil characterization and has shown... A. Biswas, W. Ji, I. Perron, A. Cambouris, B. Zebarth, V. Adamchuk |
11. Delineation of Soil Management Zones: Comparison of Three Proximal Soil Sensor Systems Under Commercial Potato Field in Eastern Canada.Precision agriculture (PA) involves optimization of seeding, fertilizer application, irrigation, and pesticide use to optimize crop production for the purpose of increasing grower revenue and protecting the environment. Potato crops (Solanum tuberosum L.) are recognized as good candidates for the adoption of PA because of the high cost of inputs. In addition, the sensitivity of potato yield and quality to crop management and environmental conditions makes precision management economically... A. Cambouris, I. Perron, B. Zebarth, F. Vargas, K. Chokmani, A. Biswas, V. Adamchuk |
12. Integration of Proximal and Remote Sensing Data for Site-Specific Management of Wild BlueberryIn Saguenay-Lac-St-Jean, there are nearly 27,000 ha of wild blueberries (Vaccinium angustifolium Ait.). This production is carried out in fields with heterogeneous growing conditions due to the local changes in topography, key soil properties, and crop density. The main objective of this study was to develop a regression-based approach to site-specific management (SSM) by integrating proximally and remotely sensed data layers, namely, apparent soil electrical conductivity (ECa), field elevation,... A. Johnston, V. Adamchuk, A. Biswas, A. Cambouris, J. Lafond, I. Perron |
13. Implementation of a CAN Bus System to Monitor Hydroponic SystemsControlled Area Network (CAN) bus systems designed for greenhouse monitoring have been proposed to measure soil moisture content, yet they are still absent from hydroponic systems. In this study, irrigation control, monitoring of substrate moisture levels and temperature were achieved using a CAN bus system connected to hydroponic beds. In total, five nodes were mounted on five hydroponic beds and two irrigation methods were compared on lettuce and kale: first, where a pre-set timer activated... P. Tikasz, R.M. Buelvas, M. Lefsrud, V. Adamchuk |
14. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer ManagementDetermination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi |
15. Development of a Soil ECa Inversion Algorithm for Topsoil Depth CharacterizationElectromagnetic induction (EMI) proximal soil sensor systems can deliver rapid information about soil. One such example is the DUALEM-21S (Dualem, Inc. Milton, Ontario, Canada). EMI sensors measure soil apparent electrical conductivity (ECa) corresponding to different depth of investigation depending on the instrument configuration. The interpretation of the ECa measurements is not straightforward and it is often site-specific. Inversion is required to explore specific depths. This inversion process... E. Leksono, V. Adamchuk, W. Ji, M. Leclerc |
16. Analysis of Soil Properties Predictability Using Different On-the-Go Soil Mapping SystemsUnderstanding the spatial variability of soil chemical and physical attributes allows for the optimization of the profitability of nutrient and water management for crop development. Considering the advantages and accessibility of various types of multi-sensor platforms capable of acquiring large sensing data pertaining to soil information across a landscape, this study compares data obtained using four common soil mapping systems: 1) topography obtained using a real-time kinematic (RTK) global... H. Huang, V. Adamchuk, A. Biswas, W. Ji, S. Lauzon |
17. Comparison of the Performance of Two Vis-NIR Spectrometers in the Prediction of Various Soil PropertiesSpectroscopy has shown capabilities of predicting certain soil properties. Hence, it is a promising avenue to complement traditional wet chemistry analysis that is costly and time-consuming. This study focuses on the comparison of two Vis-NIR instruments of different resolution to assess the effect of the resolution on the ability of an instrument to predict various soil properties. In this study, 798 air dried and compressed soil samples representing different agro-climatic conditions across... M. Marmette, V. Adamchuk, J. Nault, S. Tabatabai, R. Cocciardi |
18. Development of a Manual Soil Sensing System for Measuring Multiple Chemical Soil Properties in the FieldVariable Rate Fertilizer Application (VRA) requires the input of soil chemical data. One of the preferred methods for analyzing soil chemical properties in the field is by using Ion Selective Electrodes (ISEs). To accommodate portability in soil measurements, a manual soil sampling system was developed. Nitrate, Phosphate and pH ISEs were integrated to provide a general outlook on the condition of essential soil nutrients. These ISEs were placed on a modified hand-held soil sampler equipped... E. Leksono, V. Adamchuk, J. Whalen, R. Buelvas |
19. Development of a Wireless Sensor Network for Passive in situ Measurement of Soil CO2 Gas Emissions in the Agriculture LandscapeQuantification of soil Greenhouse Gas (GHG) emissions from agricultural fields is essential for understanding the environmental impact of intensive crop and livestock production systems. Current methods of analysis include flux calculations derived from the concentration of gases (CO2, N2O, CH4) exchanged between soil and the atmosphere. Samples of these GHG are obtained manually by closed non-steady state non-flow through,or “static”, chambers and analyzed ex situvia gas... V. Adamchuk, M. Debbagh, C. Madramootoo, J. Whalen |
20. On-Farm Experimentation and Decision-Support WorkshopThis 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta-analyses... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk |
21. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course FairwaysTurfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky |
22. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture PurposesThe amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul |
23. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter SurvivalAlfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc |