Wang Meng-Meng, He Meng-Yuan, Su De-Chun
Beijing Key Laboratory of Farmland Pollution Prevention Control and Remediation, College of Resource and Environmental Sciences, China Agricultural University, Beijing 100193, China.
Huan Jing Ke Xue. 2018 Apr 8;39(4):1918-1925. doi: 10.13227/j.hjkx.201709039.
Rice is a crop with the potential for high accumulation of Cd, which can be affected by many factors. Sixty pairs of soil and rice samples from different plots were collected and analyzed, in order to understand the quantitative relationships between the Cd content in soil and the properties of soil and the Cd content in rice grains under field conditions, by simple and multiple regression analyses. The results showed that the Cd contents in soil and rice grains ranged from 0.15-2.54 mg·kg and 0.02-2.00 mg·kg, respectively. According to the result of simple regression analysis, there were significantly positive correlations (<0.01) between the Cd contents in soil and rice grains (=0.392); the pH, SOM, and CEC in soil also had certain effects on Cd accumulation in rice grains, which were not significant, however. When the soil pH was<6.5, the Cd content in rice grains increased with increasing soil pH, but decreased with increasing soil pH when the soil pH was>6.5. The Cd content, pH, SOM, and CEC in the soil and the Cd content in rice grains were analyzed by multiple regression analysis, and five equations, which all reached extremely significant levels (<0.01), were obtained. The equation that included the four variables (Cd content, pH, SOM, and CEC in soil) had the most , and it could predict the Cd content in rice grains better, given the conditions of the present study.
水稻是一种具有高镉积累潜力的作物，其受多种因素影响。采集并分析了来自不同地块的60对土壤和水稻样本，通过简单回归分析和多元回归分析，以了解田间条件下土壤中镉含量与土壤性质以及水稻籽粒中镉含量之间的定量关系。结果表明，土壤和水稻籽粒中的镉含量分别为0.15 - 2.54 mg·kg和0.02 - 2.00 mg·kg。根据简单回归分析结果，土壤和水稻籽粒中的镉含量之间存在显著正相关（<0.01）（=0.392）；土壤中的pH值、土壤有机质（SOM）和阳离子交换量（CEC）对水稻籽粒中镉的积累也有一定影响，但不显著。当土壤pH值<6.5时，水稻籽粒中的镉含量随土壤pH值升高而增加，而当土壤pH值>6.5时，随土壤pH值升高而降低。通过多元回归分析土壤中的镉含量、pH值、SOM、CEC以及水稻籽粒中的镉含量，得到了五个均达到极显著水平（<0.01）的方程。包含四个变量（土壤中的镉含量、pH值、SOM和CEC）的方程拟合度最高，在本研究条件下能更好地预测水稻籽粒中的镉含量。
