Welcome to Lethbridge Polytechnic’s Farm Field Day. Be ready to explore the latest in irrigation, crop production and sustainability research, with hands-on demonstrations, field trials and practical innovations designed to make a real difference on your farm.

Jump to the project you're looking for:

  1. Sub-surface drip irrigation systems for field crop production
  2. Integrating SEBAL, NDVI and Soil EC for Advanced Crop Yield Prediction with Remote Sensing and GIS
  3. Irrigation scheduling with observations and models
  4. Canadian Nitrous Oxide Collaboration Network for GHG emission reduction
  5. Alberta Cereal Regional Variety Trials
  6. Investigating farm and field profitability under limited irrigation water availability
  7. Collaborative Potato Variety Trial – Alberta

 

 

Sub-surface drip irrigation systems for field crop production

Duration: 2025 - 27

Project Lead: Willemijn Appels

Funders: Results Driven Agriculture Research, with funding from the governments of Canada and Alberta through the Sustainable Canadian Agriculture Partnership (Sustainable CAP).

Project partners: Southern Irrigation Ltd., Valk Land and Cattle

Why is this important?

While subsurface drip irrigation (SDI) could be an interesting technology option for irrigators facing summers with reduced water allocation, different technical specifications of SDI systems (e.g. buried hardware, non-uniform wetting) mean that using this technology in the cropping systems of southern Alberta is not a straightforward replacement for centre pivots. 

 

 

Objectives:

  1. To improve irrigation scheduling methods for subsurface drip irrigation (SDI) systems and provide practical and actionable management strategies to irrigators.
  2. To quantify differences between SDI and centre pivot system performance in terms of water use, water productivity, and nutrient use efficiency.

Methods:

Intensive data collection of soil water balance on SDI experimental field and adjacent centre pivot field at the Lethbridge Polytechnic Research Farm. This includes data from four permanent monitoring stations with observations of soil volumetric water content, matric potential at multiple depths, incoming precipitation, and evapotranspiration. Unmanned aerial vehicle, crop and soil surveys are performed weekly. The data is analyzed with spatial statistics and process computer models. The study builds on experiments that look into the effect of applying liquid fertilizer to crops grown on SDI systems.

Outcomes/Deliverables:

Actionable recommendations for irrigators on how to sample and assess SDI fields for available moisture.

Actionable recommendations for irrigators on how to interpret soil moisture sensor readings for decision making in SDI fields

Integrating SEBAL, NDVI and Soil EC for Advanced Crop Yield Prediction with Remote Sensing and GIS

Duration: 2024–25

Project Lead: Josh Pagdilao

Funders: Lethbridge Polytechnic, Southern Irrigation Ltd.

Project Partners: University of Alberta, Southern Irrigation Ltd.

Why is this important?

Accurate yield prediction and efficient resource management are critical for food security in the face of climate stress, water scarcity and evolving agricultural demands. Traditional models often rely on single data sources and limited spatial coverage. This project aims to integrate remote sensing-based evapotranspiration (ET), normalized difference vegetation index (NDVI) and soil electrical conductivity (EC) to build a robust, spatially informed yield prediction model.

 

 

Objectives:

  1. Estimate actual crop evapotranspiration using surface energy balance algorithm for land (SEBAL) /mapping evapotranspiration at high resolution with internalized calibration (METRIC) with satellite and unmanned aerial vehicle (UAV) imagery.
  2. Derive NDVI from multispectral imagery for crop monitoring.
  3. Measure spatial patterns of soil electrical conductivity using EM38.
  4. Develop a predictive model of crop yield integrating ET, NDVI and EC.

Methods:

  1. Energy balance models were applied to estimate ET for each image date. Temporal gaps were filled by interpolating daily ET using ET fraction and reference ET data.
  2. Satellite and UAV imagery were collected throughout the growing season, targeting key crop growth stages. UAV flights were scheduled to coincide with satellite overpasses and phenological milestones (e.g. emergence, flowering, grain filling).
  3. Electromagnetic surveys and soil sampling were conducted covering 0–120 cm depths for EC, texture, moisture and nutrients.
  4. Develop a multi-variable model to predict crop yield using ET, NDVI, and soil data using statistical and machine learning approaches.

Outcomes/Deliverables:

  • Validated model for predicting yield using remote sensing and soil EC.
  • Seasonal ET and NDVI maps with spatial water stress analysis.
  • Zone-specific soil EC and moisture maps.
  • Practical guidance on using SEBAL/UAV data and EC for field-level decision making.

Irrigation scheduling with observations and models

Duration: 2025-28

Project Lead: Michael Kehoe

Funders: Results Driven Agriculture Research (RDAR)

Project partners: University of Alberta, Agriculture and Agri-Food Canada

 

Why is this important?

Irrigated crop producers get inundated with technology that promises to help reduce water use or increase water use efficiency in their operations. These claims are rarely validated against prevailing irrigation practices. In addition, sensor data do not always clearly align with the condition assessment producers execute when making irrigation decisions. Addressing the challenges of increasing the value of sensing technology to irrigation management requires both strict quantitative assessment of sensor data value as well as on-farm experiments to identify how operational limits affect added value of technology adoption. 



 

Objectives: 

This project aims to create a clearer picture for irrigators on how much to expect from sensing technology and how to use sensor data in their decision-making process.

Methods: 

Intensive data collection of soil water balance on four crops at the Lethbridge Polytechnic Research Farm. Development of a software platform that consists of:

  • a water balance model for a layered rootzone in which a crop develops over time;
  • a forecasting module;
  • an information fusion module to include all or partial data series collected at field sites; and
  • a module for scenario testing. We will use this software platform to evaluate combinations of sensors, data and crops that cannot be tested in the field.

At this stage, the software is not designed for use by producers, but it can be used in workshops and events to explore collaboratively how irrigators can improve their irrigation water management strategies with sensors and models.

Outcomes/Deliverables:

Ranking of various combinations of data types in quantifying rootzone water balance and suitability for adoption.

New crop coefficient curves for four to five crops.

Roadmap for the building of modular software that would meet producer needs during the growing season.

Canadian Nitrous Oxide Collaboration Network for GHG emission reduction

Duration: 2024-28

Project Lead: Claudia Wagner-Riddle 
Local Lead: Willemijn Appels

Funders: Natural Sciences and Engineering Research Council of Canada, Social Sciences and Humanities Research Council of Canada

Project partners: University of Guelph in collaboration with leading experts from five universities, one college, and one polytechnic across Canada with twelve partners spanning industry, government and producer organizations.

 

Why is this important?

Due to the increasing demand for agricultural products to support the growing world population, synthetic nitrogen fertilizer is an essential input for agricultural crops, driving yield gains and subsequently supporting global food security. Inefficiencies in the translation of nitrogen fertilizer to agricultural products result in nitrogen losses through multiple channels, including as the greenhouse gas nitrous oxide (N2O), and represents a significant economic cost to agricultural producers. Therefore, it is crucial that the use of synthetic nitrogen fertilizer follow principles of responsible plant nutrition by striving for improved nutrient use efficiency and reduced environmental losses.

Objectives and expected outcomes:

  1. Develop a roadmap for emission reduction based on regional scaling-up of beneficial management practices, including economic trade-offs and evidence from behavioral experiments with farmers.
  2. Establish a network of benchmark studies across Canada for whole-year measurements of N2O emissions and soil processes in fields with improved nitrogen management in coordination with behavioral and experimental economics studies of decision-making processes.
  3. Develop and validate metrics to track progress towards emission reduction targets based on novel regional tower measurements, database development and improved N2O prediction models.

Methods:

Lethbridge Polytechnic’s Research Farm hosts one of the benchmark sites, where measurements focus on the intersection of irrigation management and nitrogen source (conventional urea vs. dual inhibitor). Year-round instrumentation includes instruments to monitor the soil water balance, and two Eddy Covariance towers and an on-site Trace Gas Analyzer to determine N2O and CO2 emissions at the field scale in a semi-continuous manner. A variety of soil and crop data is collected to allow for multiple lines of investigation, e.g. microbial community dynamics, nitrogen pathways through soil and plant, of project partners.

Alberta Cereal Regional Variety Trials

Duration: 2023-25

Project Lead: Kaydunn Henry
                     and Atta Ur Rahman

Funders: Results Driven Agriculture Research, Western Grains Research Foundation, Alberta Grains, Alberta Oat Growers Association, seed companies

Coordinators: Alberta Regional Variety Advisory Committee, Alberta Grains.

Why is this important?

Regional variety trials are conducted yearly throughout the province as input to the Alberta Seed Guide. Important agronomic characteristics and disease resistance information is provided for varieties of wheat, barley, oat, rye, triticale and flax.

 

Objectives:

To provide information on cereal and flax variety performance in Alberta through annual publication of the Alberta Seed Guide.

Methods: 

Plot trials of up to 24 varieties of six grain crops are laid out in a randomized complete block design and managed under irrigated conditions. Data collection focuses on crop productivity – height, thousand kernel weight, yield. Lethbridge Polytechnic currently conducts tests for Canada Western Red Spring, Canada Prairie Red Spring and Durum wheat.

Outcomes/Deliverables:

Data from the cereal trials are published in the Alberta Seed Guide.

Investigating farm and field profitability under limited irrigation water availability

Duration: 2025-27

Project Lead: Selin Karatepe Yurdal

Funders: Alberta Innovates

Why is this important?

Southern Alberta farmers face increasing pressure from limited water allocations, requiring strategic decisions about crop selection, rotation planning and resource optimization to maintain farm profitability. Understanding how different water availability scenarios impact farm revenues and identifying optimal strategies is critical for agricultural sustainability in the region.

Objectives:

Develop a library of water-yield functions using generalized additive mixed models (GAMMs) to capture how different crops respond to varying irrigation levels across southern Alberta. Define representative farm, crop and water scenarios that reflect southern Alberta agricultural conditions.⁠⁠​ Optimize farm revenues and water use through mathematical modeling of crop rotation strategies under varying water allocation constraints.⁠⁠​ Develop actionable recommendations for producers and policymakers on profitable farming strategies under water limitations.⁠

Methods: 

Data collection of historical yield data, climate variables and water-yield responses from public sources to develop GAMMs. Additional data collection of historical crop prices, production costs, and other economic indicators from public sources and relevant literature. A regional producer survey to capture crop selection processes, planning behavior and farm/ field-level constraints. Development of mixed integer linear programming optimization models, incorporating crop rotation dynamics and water allocation constraints. Scenario analysis simulating farm performance under varying water availability, commodity prices and crop choices.

Outcomes/Deliverables:

GAMM-derived water-yield function library representing crop response under different water scenarios. Mathematical optimization framework for farm-level decision making under water constraints. Quantitative findings summarizing optimal rotation plans, projected revenues, and water use across scenarios. Actionable recommendations for producers and policymakers. Dissemination via stakeholder reports, industry presentations, and academic publications.

Collaborative Potato Variety Trial – Alberta

Duration: 2023-28

Project Lead: Dr. Chandra Singh

Funders and project sponsors: This national project is coordinated by the Fruit and Vegetable Growers of Canada and is supported financially by Agriculture and Agri-Food Canada’s (AAF C) Growing Forward 4 Science Cluster, Results Driven Agriculture Research via the Sustainable Canadian Agriculture P artnership, Lethbridge Polytechnic, University of Lethbridge, the Potato Growers of Alberta and through cash and in-kind cont ributions in 2024-25 from potato industry partners: McCain Foods, Lamb Weston, Old Dutch Foods, Edmonton Potato Growers, T uberosum Technologies, and Rockyview Seed Potatoes.

Why is this important?

The project is part of a larger national study under Agriculture and Agri-Food Canada’s Growing Forward 4 Science Cluster program to improve environmental sustainability and the resilience of producer operations.

Evaluation of breeding material in a regional setting is crucial for determining the potential “fit” of new varieties for various end-uses.

 

Objectives:

Field evaluation

  1. To grow new industry and AAFC potato lines alongside check varieties to provide data to AAFC and variety developers to assist in decision-making.
  2. Compare the yield, size distribution and specific gravity attributes of new varieties with those of standard varieties.

Agronomic evaluation

  1. Provide preliminary agronomic data (spacing, N-response, time of harvest) to assist producers with adoption of new cultivars.

Post-harvest evaluation

  1. Provide material to generate preliminary post-harvest data (bruising, dormancy, frying quality) to assist producers with adoption of new cultivars.
  2. Address the gap between identifying promising new varieties from breeding programs and the adoption of varieties for use in the industry.

Methods:

Includes variety evaluations relative to check graded according to end-use.

Sponsors can select fertility, plant spacing and time of harvest options. 2025 entries were grown in replicated plots under pivot irrigation at Lethbridge Polytechnic’s Research Farm (18 French Fry, 7 Fresh Market and 7 Chipping varieties from the AAFC Breeding Program plus 22 industry entries will be on display.)

Outcomes/Deliverables:

Relevant information about entries (emergence, stand, vigor and maturity data; yield by size category, specific gravity, defects and deformities) will be provided to sponsors. Hosting Farm Field Day on Aug. 21, 2025, to allow stakeholders to evaluate the cultivars. Sponsors will also have the opportunity to view the growing crop and check cultivars from the demo rows during the season.