Growing season weather impacts on canola (Brassica napus) quality in western Canada

菜籽油是菜籽油最有价值的增值产品，菜籽油的质量是决定这一价值的重要因素。一项较早的审查发现，一些环境和农艺因素影响了油分含量，并得出结论，菜籽油的油分含量、叶绿素和脂肪酸组成最近的变化主要是由于气象条件，进一步分析气象对菜籽油质量的影响将是有用的。本研究利用了几个现有的数据库，目的是量化生长季节天气对油菜籽质量的影响，以便在收获前预测油菜籽质量。这些数据库包括加拿大谷物委员会的收成调查和位于加拿大西部的气象站的一些天气数据库。将从收获调查数据库中特定样本位置的天气数据库重建每日天气条件。每个取样地点的日常天气将有助于计算一套以天气为基础的参数，以表征降水状况以及热胁迫和水分胁迫。这些将用作统计分析中的独立变量，以确定生长季节特定时间的特定天气条件与收获调查提供的各种油菜籽质量参数之间的关系。在此分析中生成的方程将用于测试，以确定其在收获调查结果可用之前根据生长季节天气预测未来作物油菜籽质量的可靠性。油菜籽质量预测对该行业具有重要价值，因为它允许时间来确定最合适的物流采购油菜籽所需的质量规格，以满足特定客户的需求。这样做的效率越高，流入加拿大西部粮食工业的资金就越多。

Oil is the most valuable value-added product of canola and the quality of canola oil is a significant factor in the determination of that value. A earlier review found several environmental and agronomic factors that impacted on the oil content and concluded that recent variations in oil content, chlorophyll and fatty acid composition of canola oil are due mostly to meteorological conditions and that further analysis of meteorological impacts on canola quality would be useful. This study takes advantage of several existing databases with the objective to quantify the effects of growing season weather on canola quality for the purpose of canola quality prediction prior to harvest. These databases include the Canadian Grain Commission harvest survey and a number of weather databases from stations located across western Canada. Daily weather conditions will be reconstructed from the weather databases for the locations of specific samples in the harvest survey database. The daily weather at each sample location will facilitate the calculation of a suite of weather-based parameters to characterize the precipitation regime as well as heat and water stress. These will be used as independent variables in statistical analysis to determine relationships between specific weather conditions at specific times during the growing season to various canola quality parameters provided by the harvest survey. The equations generated in this analysis will be available for testing to determine their reliability for predicting canola quality of future crops based on growing season weather and prior to the availability of results from the harvest survey. A prediction of canola quality has significant value to the industry because it allows time to determine the most appropriate logistics for sourcing canola with the needed quality specifications to meet the demands of specific customers. The more efficiently this can be done, the more money that flows into the grain industry in western Canada.