Seed and foliar application of nano-selenium improves sesame triacylglycerols and oil yield via photosynthetic pigment and enzymatic and chemical antioxidant enhancement revealed by spectrophotometric, UHPLC-analysis and chemometric modeling

通过分光光度法、超高效液相色谱分析和化学计量学模型研究发现,纳米硒的种子和叶面施用可通过增强光合色素、酶促和化学抗氧化作用来提高芝麻三酰甘油和油脂的产量。

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Abstract

The current study aimed to investigate the effects of plant-mediated selenium nanoparticles (SeNPs) on plant growth, photosynthetic pigments, antioxidant activity, and the triacylglycerol profile of sesame (Sesamum indicum L.). The green synthesis of SeNPs was achieved using garlic extract, resulting in spherical nanoparticles with an average size range of 70-75 nm. Three SeNP treatments (T3, 30 ppm; T4, 40 ppm; and T5, 50 ppm) were applied through seed and foliar spray on six sesame varieties (V1, TS-5; V2, TH-6; V3, Til-18; V4, Niab Millennium; V5, Niab Pearl; and V6, NS-16). All enzymatic antioxidant parameters showed an increase in the treated groups, such as SOD (74.4% in V1 at T4), POD (43% in V5 at T5), APX (62% in V1 at T3), and GPX (31.56% in V3 at T4). CAT showed the highest percentage improvement in T5 for V1, V2, V4, and V5, while V3 and V4 exhibited the highest values at T4. Likewise, seed antioxidant parameters also showed increase in antioxidant activity, highest total phenolic content (6.06 mg GAE/g) was found at T5 treatment with percent increase of 27.41%, but the highest percent increase was found to be at T4 treatments in V1 with increase of 46.83%. Percent oil yield was also noted to be higher as highest percent (60%) oil yield was obtained at T4 treatment in V3. Ultra High Performance Mass-Spectrometry (UHPLC-MS) analysis and chemometric modeling suggested a total of 10 triacylglycerol (TG) biomarkers separating untreated groups, with higher relative abundance values at T4 and T5 treatments compared to control. PCA and correlation analysis showed clustering of untreated groups from T4 and T5, which suggests that these two treatments result in higher accumulation of oil. A generalized linear model with ANOVA showed a highly significant impact of treatments on all the growth and oil parameters, with significance involvement of varieties. The interaction between variety and treatment showed no significant effect on the growth and oil biomarkers of sesame. However, it can be concluded that the T4 and T5 treatments (40 ppm and 50 ppm) of SeNPs, applied through seed and foliar methods, have a strong influence on the overall growth and oil yield of sesame. This warrants further transcriptomic and molecular analysis to gain deeper insight into the mechanisms of action of SeNPs.

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