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

油是菜籽油最有价值的附加值产品，菜籽油的质量是确定其价值的一个重要因素。早些时候的一次审查发现了几个影响油菜籽含油量的环境和农艺因素，并得出结论，菜籽油含油量、叶绿素和脂肪酸组成最近的变化主要是由于气象条件，进一步分析气象对油菜籽质量的影响将是有用的。本研究利用现有的几个数据库，目的是量化生长季节天气对油菜籽品质的影响，以便在收获前预测油菜籽的品质。这些数据库包括加拿大谷物委员会收成调查和位于加拿大西部的一些气象站的天气数据库。将根据收成调查数据库中特定样本的位置的天气数据库重建每日天气状况。每个样本地点的每日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和水压力。这些将被用作统计分析中的自变量，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。在此分析中产生的方程将可用于测试，以确定其可靠性，以根据生长季节天气并在收获调查结果可用之前预测未来作物的油菜籽质量。油菜籽质量的预测对行业具有重要价值，因为它允许时间确定最合适的物流，以满足特定客户的需求，以满足所需的质量规格。这样做的效率越高，流入加拿大西部谷物行业的资金就越多。

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.