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2021 4-H Canada Science Fair

Due to the current COVID-19 outbreak, the 2021 4-H Canada Science Fair will take on a virtual format. For more information, please read 4-H Canada’s latest update on the outbreak.

The 2021 4-H Canada Science Fair took place from March 1 to 7, 2021.

7 4-H members came together virtually from across Canada for their chance to earn the top honour within 4-H Canada Science & Technology programming. For months prior, all of our finalists had been exercising their curiosity and demonstrating determination as they worked hard to complete their science fair projects. Each and every one of them exemplifies the problem-solving and leadership skills 4-H’ers are mastering across the country within areas of science, technology, engineering, math and agriculture.

At the 4-H Canada Science Fair, finalists have the chance to meet with their peers, exchange ideas and take part in activities and workshops that foster their knowledge and interest in Science & Technology.

2021 4-H Canada Science Fair Winners

Mac D., British Columbia
A Novel Approach to Improving Biosecurity in Hatching

Biosecurity in hatching operations is a significant concern for the agricultural sector. In addition, the hatching sector is an important contributor to Canada's Economy. The objective of this project is to improve, through innovation and automation, biosecurity in incubators by reducing the number of contaminants with which the eggs come in contact, as well as reduce the opportunity for human error to be a factor.

Mark N., Alberta
A Corrosion Comparison of Agriculture Disinfectants on Metals

The agriculture industry uses many different disinfectants in food production and processing, animal health and treatment and biosecurity. These disinfectants often come into contact with metal surfaces, highlighting the need to understand which disinfectants are most corrosive n which types of metals. This allows the proper selection of disinfectants that cause the least amount of corrosion on a specific metal to preserve the metal surface for as long as possible.

Sophie F., British Columbia
Leaf-Debrief: An Innovative Nitrogen Detector for Rice Paddies Using  Machine Learning

The main question this investigation seeks to answer is the following: How accurately and efficiently can a machine learning model, which analyses image data of rice plant leaves, predict the nitrogen level of the plant through the leaf's chlorophyll correlation as compared to existing, traditional procedures? The introduction of a novel machine learning model for nitrogen detection will not only reduce costs and time in identifying nitrogen levels to improve rice crop yields but will aid in avoiding the detrimental environmental effects of a surplus of nitrogen fertilizer in the local ecosystem.

2021 4-H Canada Science Fair Finalists

Josh K., Manitoba
The K-Brake System

Mac D., British Columbia
A Novel Approach to Improving Biosecurity in Hatching

Mark N., Alberta
A Corrosion Comparison of Agriculture Disinfectants on Metals

Niko V., Ontario
How to Turn Biowaste into Fuel

Sierra C-B & Alice V., Ontario
Effects of the Producer-Consumer Relation Platform on the Producer-Consumer Relationship and Consumer Education

Sophie F., British Columbia
Leaf-Debrief: An Innovative Nitrogen Detector for Rice Paddies Using  Machine Learning

 

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