Olds College Centre for Innovation (OCCI) researchers are evaluating different solutions for the Olds College Smart Farm to collect equipment data for field operations with different manufacturers remotely.
In collaboration with xarvio Digital Farming Solutions, Olds College Centre for Innovation (OCCI) is completing disease identification on Field 18 of the Olds College Smart Farm to display canola disease distribution within the field.
Olds College Centre for Innovation (OCCI) is working with Farm Credit Canada (FCC) to assess best management practices (BMPs) for the removal of marginal cropland from annual production.
Olds College Centre for Innovation (OCCI) partnered with Ember Resources Inc. on a multi-year project to determine if remote sensing technologies could be used for the vegetation assessment component of a Detailed Site Assessment (DSA).
Pan-Canadian Smart Farm Network members are conducting a multi-year project with BioScout to sample this revolutionary technology and help improve Bioscout for use in Western Canadian agriculture.
LI-COR chamber technology will help OCCI collect high quality and high resolution data on how 4R (right rate, right time, right source, right place) nutrient stewardship practices impact N2O emissions — a highly relevant topic for the ag industry.
The Raven OMNiPOWER™ platform represents a significant first-step towards autonomy applied to agricultural operations.
The Bio-Agtive Method is an innovative bio agtech approach which entails emission capture technology and re-purposing of biofuel exhaust emissions into a carbon-based biofertilizer.
Bushel Plus provides a complete combine loss measurement system designed to quickly and accurately quantify harvest loss to assist in the calibration of combine settings during harvest.
Team members are performing Comparable Autonomous Data Collection with an electronic data acquisition instrument called Somat-eDAQ.
Pan-Canadian Smart Farm Network members are conducting a second year of research to compare data collected from weather sensors inside and outside of the crop boundary to produce multiple data sets for analysis, and evaluating how disease development varies within each zone.
Olds College Centre for Innovation (OCCI) is performing intensive one-acre grid scouting for the purpose of identifying disease variability within a field, and comparing the distribution of disease results to other geospatial layers collected within the HyperLayer project.
Carbon Assets Solutions (CAS) is a new Canadian company that uses Mobile Inelastic Neutron Scattering (MINS) technology to determine carbon content in soils that may help producers access carbon credits.
Olds College is performing a historical data correlation analysis in partnership with Agriculture Financial Services Corporation (AFSC) to learn from existing data sources what variables matter most to forage growth.
Olds College and Agriculture Financial Services Corporation (AFSC) are continuing their work together to determine if high definition imaging from unmanned aircraft vehicles (drones) can be used to classify hail damaged areas within crop fields.
The In-Bin Drying Monitor is a technology developed by Top Grade Ag that uses a proprietary algorithm with pressure, temperature and humidity sensors to optimize grain drying procedures.
Olds College is working with local Saskatchewan partners to gather historical and current information from the fields on the Saskatchewan Smart Farm for baseline data collection.
Olds College is working with TELUS Agriculture on assessing the return on investment of variable rate technology (VRT) which is a precision-ag approach allowing producers to manage defined areas of their fields differently.
The Weather Station Array provides a comparison of functionality, platform navigation, installation/uninstallation, reliability of data, user experience, and connectivity of commercially available weather stations.
The HyperLayer Data Concept is a process that allows the Olds College Smart Farm to compile, analyze, and use virtually every type of agricultural data.
Olds College researchers are working alongside TELUS Agriculture to improve cellular service in rural Alberta in order to utilize smart ag technologies.
Olds College is evaluating the TeleSense Spider product, a technology for the remote monitoring of commodity storage in bins, and its user interface to provide unbiased information on the functionality and general experience working with the product.
Olds College is evaluating the functionality, effectiveness and experience of ChrysaLabs soil nutrient probe in numerous field types and environmental conditions (soil moisture, soil temperature, ambient temperature, frozen soil).
The Crop Scan 3300H Grain Analyzer is an agricultural digital technology that is installed on the college’s combine, and is capable of measuring protein and moisture content of harvested grain, oil seeds, and pulse crops in near-real time.
element 4 produces self-powered, wireless modular sensor technology that is adaptable to most environments. Olds College of Agriculture & Technology is working alongside element 4 to further improve and develop their IoT devices and autonomous sensors — featuring unique energy harvesting and storage technologies — for use in commercial settings.
Olds College is collecting a data package of weather information and crop measurements for Metos Canada to validate their yield calculator, and provide additional measurements to further develop the algorithm into a crop growth model.
Olds College of Agriculture & Technology, TELUS Business and TELUS Agriculture are researching solutions to improve cellular service in rural Alberta to better utilize smart ag technology in the future. Currently researchers are assessing the effectiveness of the Zetifi ZetiCell and ZetiRover technologies in improving connectivity by LTE to WiFi technology in a typical rural prairie setting.
Olds College is assessing the second version of the Snow Acres Canada soil moisture sensor system “The Well” as it’s in the final stages of product development.
Olds College is comparing the accuracy and functionality of soil sensors and their capabilities to measure soil properties, such as moisture and salinity, to allow for faster and informed decision making.
Olds College is evaluating how the Spornado Sampler contributes to the canola fungicide application decision process. The College will evaluate how Spornado lab results influence the timing, speed, ease, confidence, and final recommendation of the fungicide application decision making process in canola.
Olds College is working with METOS Canada on their platform utility for sclerotinia disease prediction modelling in canola by collecting data with multiple Pessl Metos in-field weather stations.
Olds College is gathering independent data on the functionality and accuracy of soil nutrient sensors over a two-year period.
Olds College is assessing the WeatherFlow Tempest Weather station on the Smart Farm in partnership with TELUS Agriculture. Researchers will provide an evaluation of Tempest data accuracy (rainfall, wind speed and direction, and temperature).
Olds College is conducting in-field trials for fungicide/desiccant variable rate technology (VRT) applications to determine how they affect production costs, profitability, and operational requirements.
Olds College is reviewing existing precision Ag and GIS software systems to determine the percent overlap reduction based on as-applied or task data from equipment typically used for sectional control applications in Western Canada.
Uploading and utilizing prescription files for variable rate (VR) fertilizing, seeding and spraying is challenging due to different file formats and various models of displays being used in the field.
Olds College Smart Farm deploys numerous weather stations for farm management decisions, research, and demonstration purposes.
In partnership with TELUS Agriculture, researchers are evaluating variable rate technology (VRT) for fertilizer applications on the Smart Farm with a focus on nitrogen.