水稻中硒的积累已成为全球关注的主要问题。硒对人类有多种健康益处;然而,其摄入不足或过量可能是有害的。因此,确定驱动稻田土壤中硒丰度和生物有效性的因素对于确保人类硒摄入的安全性至关重要。这项研究调查了积累,生物利用度,芦溪县820个水稻土和水稻籽粒样品中硒的分布,中国将评估土壤特性(土壤有机质[SOM],阳离子交换容量[CEC],和pH),地理因素(母体材料,高程,和年平均降水量[MAP]和温度[MAT]),和必需微量营养素(铜[Cu],锌[Zn],和锰[Mn])控制水稻土中硒的积累和生物有效性。结果表明,土壤硒平均含量为0.36mgkg-1,高于中国(0.29mgkg-1)。或者,水稻籽粒平均硒含量为0.032mgkg-1,低于富硒水稻籽粒的最低允许含量(0.04mgkg-1)。5种研究的母体材料均对土壤Se含量有显着影响,但对Se生物有效性影响不大(p<0.05)。CEC,高程,和SOM,以及土壤中的铜含量,Zn,锰与土壤硒含量呈正相关,但pH值,MAP,与MAT呈负相关。相应地,硒生物有效性与SOM和土壤锌含量呈负相关,但与MAP和籽粒Cu含量呈正相关,Zn,和Mn。此外,偏最小二乘路径分析揭示了各影响因素对土壤中硒积累和生物有效性的交互影响。在此基础上,建立了预测水稻土中硒累积量和生物有效性的预测模型,从而为制定有效的控制措施以应对农业中的硒挑战提供理论支持。
Selenium (Se) accumulation in rice (Oryza sativa L.) has become a major global concern. Se offers multiple health benefits in humans; however, its inadequate or excessive intake can be harmful. Therefore, determining the factors driving Se abundance and bioavailability in paddy soils is essential to ensure the safety of human Se intake. This
study investigated the accumulation, bioavailability, and distribution of Se in 820 paddy soil and rice grain samples from Luxi County, China to assess how soil properties (soil organic matter [SOM], cation exchange capacity [CEC], and pH), geographical factors (parent materials, elevation, and mean annual precipitation [MAP] and temperature [MAT]), and essential micronutrients (copper [Cu], zinc [Zn], and manganese [Mn]) govern Se accumulation and bioavailability in paddy soils. Results showed that the average soil Se content was 0.36 mg kg-1, which was higher than that in China (0.29 mg kg-1). Alternatively, the average rice grain Se content was 0.032 mg kg-1, which was lower than the minimum allowable content in Se-rich rice grains (0.04 mg kg-1). Five studied parent materials all had a significant effect on soil Se content but had little effect on Se bioavailability (p < 0.05). CEC, elevation, and SOM, as well as the soil contents of Cu, Zn, and Mn were positively correlated with soil Se content, but pH, MAP, and MAT were negatively correlated. Correspondingly, Se bioavailability was negatively correlated with SOM and soil Zn content, but positively correlated with MAP and grain contents of Cu, Zn, and Mn. Furthermore, partial least squares path analysis revealed the interactive impacts of the influencing factors on Se accumulation and bioavailability in soils. On this basis, prediction models were established to predict Se accumulation and bioavailability in paddy soils, thereby providing theoretical support for developing efficient control measures to meet Se challenges in agriculture.