Dissecting trial-related from generalized effects of biostimulants: a case study on heat-stressed maize and sunflower using metabolomics coupled with machine learning

Supplementary materials.
Table S1 Metabolomics dataset of Maize plants under normal, heat stress, and combination with organic matter
Table S2 Metabolomics dataset of Sunflower plants under normal, heat stress, and combination with organic matter
Table S3 Statistical analysis from AMOPLS-DA model for both Mazie and Sunflower, shared and separately
Table S4 VIP markers name and values of the most significant contribution to pairwise comparisons
Table S5 Statistical analysis from Random Forest model for both Mazie and Sunflower

补充材料。
表S1 正常、热胁迫及配施有机质条件下玉米植株代谢组学数据集
表S2 正常、热胁迫及配施有机质条件下向日葵植株代谢组学数据集
表S3 针对玉米与向日葵的自适应多变量正交偏最小二乘判别分析（AMOPLS-DA）模型统计分析（含共享与独立分析结果）
表S4 变量重要性投影（Variable Importance in Projection，VIP）标记物名称及其在组间两两比较中的显著贡献值
表S5 针对玉米与向日葵的随机森林（Random Forest）模型统计分析