Effect of row spacing and seeding rate to obtain optimal canola yield

Abstract

With a multi-billion dollar industry, canola production in Canada is highly profitable. However, the input cost of canola production has prompted canola growers to plant below the recommendedseedingrateswhichalsoreduce potentialyield. Canolayieldsareoftenbelow their potential because of uneven spatial distribution of plants which results in densities below the optimum for maximum yield. With a rising global demand it is important to produce canola that can meet demands. Eight seeding rates (5, 10, 20, 40, 60, 80, 100, and 140 seeds m-2) with four- row spacing (19, 38, 57 and 76 cm) and six-row spacing (15, 30 ,45, 60, 75 and 90cm) were evaluated in Carman, MB and Kernen, SK respectively, in 2018 and 2019 growing seasons. The first objective was to determine the effect of row spacing and seeding rate to obtain optimal canola yield. Results indicate that row spacing and seeding rate and its interaction positively influenced canola yield. In this research, canola yield response to narrow row spacing has been consistently positive, maximum yield was obtained in 19 cm and 30 cm in Carman and Kernen respectively. Maximum yield can be found at 46 and 58 viable seeds m-2 in Carman and Kernen respectively. The second objective was to determine how canola compensates for row spacing and seeding rate effects. Seeding rate significantly influenced the yield components and phenological traits. Increasing seeding rate led to a decrease in the number of siliques plant-1, number of branches plant-1 and thousand seed weight in one site-year. Row spacing influenced the end of flowering. The third objective is to utilize Unoccupied Aerial Vehicle (UAV) imagery to measure green ground cover to predict canola yield. Images were taken on weekly basis from the seeding until harvest. Images were stitched, calibrated, and analyzed. Using excess green index, the result indicates that UAV can be used to determine green ground cover and can potentially be used to predict yield. Overall, the results of this thesis can be used to update row spacing and seeding rate recommendations for canola cultivation.