Huhmann Linden B, Harvey Charles F, Gross Jason, Uddin Anjal, Choudhury Imtiaz, Ahmed Kazi M, Duxbury John M, Bostick Benjamin, van Geen Alexander
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Geoderma. 2021 Jan 15;382. doi: 10.1016/j.geoderma.2020.114755. Epub 2020 Oct 19.
Rice is the primary crop in Bangladesh and rice yield is diminished due to the buildup of arsenic (As) in soil from irrigation with high-As groundwater. Soil testing with an inexpensive kit could help farmers target high-As soil for mitigation or decide to switch to a different crop that is less sensitive to As in soil. A total of 3,240 field kit measurements of As in 0.5 g of fresh soil added to 50 mL of water were compared with total soil As concentrations measured on oven-dried homogenized soil by X-ray fluorescence (XRF). For sets of 12 soil samples collected within a series of rice fields, the average of kit As measurements was a linear function of the average of XRF measurements (r=0.69). Taking into account that the kit overestimates water As concentrations by about a factor of two, the relationship suggests that about a quarter of the As in paddy soil is released in the kit's reaction vessel. Using the relationship and considering XRF measurements as the reference, the 12-sample average determined correctly whether soil As was above or below a 30 mg/kg threshold in 86% of cases where soil As was above the threshold and in 79% of cases where soil As was below the threshold. We also used a Bayesian approach using 12 kit measurements to estimate the probability that soil As was above a given threshold indicated by XRF measurements. The Bayesian approach is theoretically optimal but was only slightly more accurate than the linear regression. These results show that rice farmers can identify high-As portions of their fields for mitigation using a dozen field kit measurements on fresh soil and base their decisions on this information.
水稻是孟加拉国的主要作物,由于使用高砷地下水灌溉导致土壤中砷(As)积累,水稻产量因此下降。使用廉价试剂盒进行土壤检测可以帮助农民针对高砷土壤采取缓解措施,或者决定改种对土壤中砷不太敏感的其他作物。将总共3240次对添加到50毫升水中的0.5克新鲜土壤中砷的现场试剂盒测量结果,与通过X射线荧光(XRF)对烘干后的均质土壤测量的总土壤砷浓度进行了比较。对于在一系列稻田中采集的每组12个土壤样本,试剂盒砷测量的平均值是XRF测量平均值的线性函数(r = 0.69)。考虑到试剂盒高估水中砷浓度约两倍,这种关系表明稻田土壤中约四分之一的砷在试剂盒的反应容器中释放。利用这种关系并将XRF测量结果作为参考,在土壤砷高于阈值的情况下,12个样本平均值在86%的情况下正确判断土壤砷是否高于或低于30毫克/千克的阈值;在土壤砷低于阈值的情况下,在79%的情况下正确判断。我们还使用贝叶斯方法,利用12次试剂盒测量来估计土壤砷高于XRF测量所指示的给定阈值的概率。贝叶斯方法在理论上是最优的,但仅比线性回归稍微准确一点。这些结果表明,稻农可以通过对新鲜土壤进行十二次现场试剂盒测量来识别田间高砷区域以采取缓解措施,并据此做出决策。