Growing season weather impacts on canola phenological development and quality
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Date
2014-01-15
Authors
Dickson, Taryn Jaye
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Abstract
This project investigated the phenological development of canola through the 2009 growing season in the western Canadian prairies and quantified the effects of 624 weather parameters on nine canola quality parameters from 247 samples of Canada No. 1 canola. Predictive models were created to utilize as few of the most strongly correlated weather predictors as possible to explain a maximum amount of variation in each of the quality parameters.
An intensive field study carried out at seven sites across Manitoba measured weather conditions and followed canola crop development from seeding through swathing, harvest or physiological maturity. These data were used to produce an index with six Physiological Day (P-Day) thresholds corresponding to specific growth stages. A comparison to the thresholds determined from a previous study suggested that current varieties require fewer heat units for early vegetative growth stages, more heat units during reproductive stages, and slightly greater P-Day accumulations to reach maturity.
Canola samples from the field study were combined with western Canadian canola samples from collaborating companies and the 2008 and 2009 Canadian Grain Commission Harvest Surveys for quality analysis. The samples were analysed for oil content, protein content, oleic, linoleic, linolenic, and total saturated fatty acid contents and iodine value. Weather data from the intensive field study, collaborating companies, the Canadian Wheat Board and Environment Canada weather stations nearest each canola sample were compiled and arranged from the seeding to swathing date of each canola sample. These data were then used to calculate the accumulation of P-Day values from seeding until each of the six phenological growth stages. Partial Least Squares analysis was utilized to produce predictive models for each of the nine quality parameters.
The results indicated that environmental parameters, especially temperature, had a significant impact on canola quality. The predictive models explained between 7 and 49% of the variation in individual quality parameters. The models for saturated fatty acids, glucosinolates and iodine value explained the highest amount of variation and the model for chlorophyll explained the least. Oil content was positively impacted by a longer duration of temperatures below 11-14oC throughout the reproductive stage, while protein was positively impacted by cool temperatures at early flowering and high temperatures throughout pod and seed development. Chlorophyll was strongly impacted by the moisture balance throughout early to mid reproductive stages and glucosinolates content was affected by conditions that impacted nutrient availability.
Total saturated fatty acid content was positively impacted by cool temperatures throughout late vegetative and early reproductive stages. Moderate predictability of the individual fatty acid content models may have been indicative of either successful breeding of current canola varieties with relatively stable quality characteristics across a range of growing conditions or the complex interactions between oil content and the individual fatty acids measured.
Producers looking to maximize canola quality and canola breeders interested in creating varieties more resistant to the specific weather conditions which impact canola quality could benefit from this study. Predictions of crop quality would also be an asset to those marketing Canadian canola as an export.
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Keywords
canola, agrometeorology, agronomy