Department of Chemistry, University of Pavia, Viale Taramelli 12, Pavia, 27100, Italy.
Plant Physiology and Functional Genomics Research Unit, Institute of Biotechnology of Sfax, University of Sfax, BP "1175", Sfax, Tunisia.
Sci Rep. 2024 Oct 15;14(1):24162. doi: 10.1038/s41598-024-75236-0.
Simple physico-chemical techniques can be used to evaluate the composition, structure, and characteristics of plant seeds to determine their viability, quality, and possible uses in agriculture. Advanced analytical techniques, including thermo gravimetric analysis (TGA), electron paramagnetic resonance (EPR), and high-pressure liquid chromatography (HPLC), provide completely new insights and more precise information. They can be integrated to build up seed quality profiles, with great advantage to assess water content, organic compounds, and inorganic metals without the need to carry out many extraction procedures, as requested by more conventional methods. In this study, seed lots from three different plant species such as Triticum turgidum L. subsp. durum (wheat), Trigonella foenum graecum L. (trigonella or fenugreek), and Atriplex halimus L. (saltbush or sea orach) have been used to test the potential of TGA, EPR, and HPLC to discriminate between seed-specific features. A key finding of this study is that HPLC is essential in Principal Component Analysis (PCA) because various seeds (from the same species or other species) may contain compounds with varying polarity groups. The reported data confirm the efficacy of this approach. These data, fully available for other users, are coherently constructed and provide a proof of concept for future seed quality control studies.
简单的物理化学技术可用于评估植物种子的组成、结构和特性，以确定其活力、质量和在农业中的可能用途。先进的分析技术，包括热重分析（TGA）、电子顺磁共振（EPR）和高压液相色谱（HPLC），提供了全新的见解和更精确的信息。它们可以集成起来建立种子质量概况，具有很大的优势，可以评估水分含量、有机化合物和无机金属，而无需像更传统的方法那样进行许多提取程序。在这项研究中，来自三个不同植物物种的种子，如 Triticum turgidum L. subsp. durum（小麦）、Trigonella foenum graecum L.（三叶草或葫芦巴）和 Atriplex halimus L.（盐生植物或海甘蓝），已被用于测试 TGA、EPR 和 HPLC 区分种子特异性特征的潜力。这项研究的一个重要发现是，HPLC 在主成分分析（PCA）中是必不可少的，因为不同的种子（来自同一物种或其他物种）可能含有具有不同极性基团的化合物。报告的数据证实了这种方法的有效性。这些数据完全可供其他用户使用，它们是一致构建的，并为未来的种子质量控制研究提供了一个概念证明。
