ABSTRACT

Irrigation with contaminated Arsenic (As) water is greatly correlated with increased soil As along with enhanced uptake in plants, which in turn biologically accumulates in different parts of the plant at toxic levels. The current study is aimed at characterization and mitigation of Arsenic contamination through irrigation and varietal selection. Characterization of arsenic was done through staggered random sampling. Experimental plots were laid in highly As contaminated farmer’s field with three rice varieties and three moisture regime in randomized block design keeping summer rice as standing crop. According to the Artificial Neural Network (ANN) study, soil phosphorus, followed by soil pH, Nitrogen, and Potassium have been found to be more sensitive in regulating soil As. The Alternate Wetting Drying (AWD) irrigation regime has significantly less arsenic concentration in rice when compared with Saturation (SAT)<Continuous Submergence (CS). Interestingly, maximum transfer of arsenic from soil to grain has been observed in AWD, with the least use of contaminated irrigation. Transfer factors (TFs) for As was least in cultivar IET-17430 as compared with IR-36> IET-4786.

摘要

污染的砷（As）水灌溉与增加的土壤As以及增加的植物吸收密切相关，而植物体内的吸收又以有毒水平生物累积在植物的不同部位。当前的研究旨在通过灌溉和品种选择来表征和减轻砷污染。砷的表征是通过交错随机抽样进行的。实验地块放置在高度受污染的农民田地上，具有三个水稻品种和三个水分状况，采用随机区组设计，使夏季水稻作为常年作物。根据人工神经网络（ANN）的研究，发现土壤磷，其次是土壤pH值，氮和钾对调节土壤As更为敏感。与饱和（SAT）<连续浸水（CS）相比，交替湿法干燥（AWD）灌溉方式的水稻中砷浓度显着降低。有趣的是，在AWD中已观察到砷从土壤到谷物的最大转移，而污染灌溉的使用最少。与IR-36> IET-4786相比，品种IET-17430中As的转移因子（TFs）最少。