Mass-flowering crops, such as oilseed rape (OSR; Brassica napus), provide pulses of nectar and pollen, helping to support pollinators and their pollination services in agricultural landscapes. Despite their value to declining pollinators, varietal in-field OSR testing focusses on agronomic traits, with floral resources being largely overlooked. OSR has a high varietal turnover, and consequently, floral resource data collected for a specific variety quickly become redundant. Here, we explore the potential to predict floral resource availability using agronomic trait data routinely collected in varietal trials. To build predictive models, we investigated the relationships between agronomic traits and pollen and nectar availability in 19 OSR varieties. Nectar quality was positively influenced by early vigour, as well as winter hardiness in conventional varieties and stem stiffness in hybrid varieties. Pollen quantity was driven by different traits, with early maturation having a negative impact in conventional varieties and resistance to lodging having a positive impact in hybrid varieties. Our study highlights the potential to predict floral resources using agronomic trait data, enabling the rapid assessment of these key resources in future OSR varieties without costly sampling. Agronomic traits relating to increased nectar quality were also agronomically favourable, indicating benefits to both pollinators and growers. The inclusion of modelled floral resource data in recommended varietal lists would enable growers to make informed decisions about varietal selection based on local pollinator populations.

中文翻译：

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油菜（甘蓝型油菜）的农艺性状可以预测昆虫传粉媒介的觅食资源

大量开花的作物，例如油菜（OSR；甘蓝型油菜）），提供花蜜和花粉的脉冲，帮助支持授粉媒介及其在农业景观中的授粉服务。尽管其对减少传粉者的价值，但各种田间OSR测试仍侧重于农艺性状，而花卉资源却被大大忽略。OSR的品种更新率很高，因此，针对特定品种收集的花卉资源数据很快变得多余。在这里，我们探索了使用品种试验中常规收集的农艺性状数据预测花卉资源可用性的潜力。为了建立预测模型，我们调查了19个OSR品种的农艺性状与花粉和花蜜可用性之间的关系。花蜜质量受早期活力，常规品种的冬季耐性和杂交品种的茎刚度的积极影响。花粉数量受不同性状的驱动，早期成熟对常规品种有负面影响，而抗倒伏性对杂种则有正面影响。我们的研究强调了利用农艺性状数据预测花卉资源的潜力，从而无需花费昂贵的采样就可以快速评估未来OSR品种中的这些关键资源。与提高花蜜品质有关的农艺性状在农艺上也是有利的，表明对授粉者和种植者均有利。在推荐的品种清单中包括模型化的花卉资源数据，可使种植者根据当地传粉媒介的种群做出有关品种选择的明智决定。早熟对常规品种有不利影响，而抗倒伏性对杂种则有积极影响。我们的研究强调了利用农艺性状数据预测花卉资源的潜力，从而无需花费昂贵的采样就可以快速评估未来OSR品种中的这些关键资源。与提高花蜜品质有关的农艺性状在农艺上也是有利的，表明对授粉者和种植者均有利。在推荐的品种清单中包括模型化的花卉资源数据，可使种植者根据当地授粉媒介的种群做出有关品种选择的明智决定。早熟对常规品种有不利影响，而抗倒伏性对杂种则有积极影响。我们的研究强调了利用农艺性状数据预测花卉资源的潜力，从而无需花费昂贵的采样就可以快速评估未来OSR品种中的这些关键资源。与提高花蜜品质有关的农艺性状在农艺上也是有利的，表明对授粉者和种植者均有利。在推荐的品种清单中包括模型化的花卉资源数据，可使种植者根据当地传粉媒介的种群做出有关品种选择的明智决定。无需花费高昂的费用即可快速评估未来OSR品种中的这些关键资源。与提高花蜜品质有关的农艺性状在农艺上也是有利的，表明对授粉者和种植者均有利。在推荐的品种清单中包括模型化的花卉资源数据，可使种植者根据当地授粉媒介的种群做出有关品种选择的明智决定。无需花费高昂的费用即可快速评估未来OSR品种中的这些关键资源。与提高花蜜品质有关的农艺性状在农艺上也是有利的，表明对授粉者和种植者均有利。在推荐的品种清单中包括模型化的花卉资源数据，可使种植者根据当地授粉媒介的种群做出有关品种选择的明智决定。