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通过近程传感器快速准确评估钙和镁含量,对农用和非农用石灰进行清洁质量控制。

Clean quality control of agricultural and non-agricultural lime by rapid and accurate assessment of calcium and magnesium contents via proximal sensors.

作者信息

Benedet Lucas, Silva Sérgio Henrique Godinho, Mancini Marcelo, Andrade Renata, Amaral Francisco Hélcio Canuto, Lima Geraldo Jânio, Carneiro Marco Aurélio Carbone, Curi Nilton

机构信息

Dept. of Soil Science, Federal University of Lavras, P.O. Box 3037, 37200-900, Lavras, State of Minas Gerais, Brazil.

Agriculture and Livestock Farming Analyses, 3rlab. Lavras, State of Minas Gerais, Brazil.

出版信息

Environ Res. 2023 Mar 15;221:115300. doi: 10.1016/j.envres.2023.115300. Epub 2023 Jan 14.

Abstract

Ca and Mg are the most important chemical elements in lime. Properly measuring Ca and Mg contents is essential to assess the quality of lime products. Quality control guarantees the adequate use of lime in industrial processes, in soils, and helps avoiding adulteration. Proximal sensors can aid in this process by determining Ca and Mg contents easily, rapidly and without producing chemical waste. The objective of this study was to evaluate the use an environmentally-friendly method of analyzing the quality of lime. We studied 1) the use of portable X-ray fluorescence (pXRF) to predict concentrations of Ca and Mg in lime, 2) tested if NixPro™ sensor can improve prediction accuracy and 3) tested if sample preparation methods (grinding) affect analyses. 74 samples of lime were analyzed by two different laboratories (lab. 1 = 38, lab. 2 = 36). All samples submitted to pXRF and NixPro™ analyses. Sensor analyses were done in whole (CP) and ground (AQ) samples to test the effect of sample preparation in prediction performance. High correlation was found between Ca and Mg contents measured via pXRF and laboratory analyses. Mg-CP presented the highest correlation coefficient (r = 0.81); Mg-AQ, the lowest (0.57). Predictions presented good performance (R > 0.68); Mg had the best results (0.86). Separating models per laboratory showed that some datasets are harder to model, probably due to variability in the source material (limestone). The addition of NixPro™ data contributed to improve prediction accuracy, although slightly. Predictions using CP samples presented the best results, especially for Mg, indicating that grinding is not necessary. This pioneer study demonstrated that fused proximal sensors can be used to rapidly and easily determine contents of Ca and Mg in soil amendments without producing chemical waste.

摘要

钙和镁是石灰中最重要的化学元素。准确测量钙和镁的含量对于评估石灰产品的质量至关重要。质量控制可确保石灰在工业生产过程和土壤中得到充分利用,并有助于避免掺假。近程传感器可以通过轻松、快速地测定钙和镁的含量且不产生化学废料来辅助这一过程。本研究的目的是评估使用一种环境友好型方法来分析石灰质量。我们研究了:1)使用便携式X射线荧光光谱仪(pXRF)预测石灰中钙和镁的浓度;2)测试NixPro™传感器是否能提高预测准确性;3)测试样品制备方法(研磨)是否会影响分析结果。两个不同实验室(实验室1 = 38个样本,实验室2 = 36个样本)对74个石灰样本进行了分析。所有样本都进行了pXRF和NixPro™分析。传感器分析在完整样本(CP)和研磨样本(AQ)上进行,以测试样品制备对预测性能的影响。通过pXRF测定的钙和镁含量与实验室分析结果之间存在高度相关性。镁 - CP的相关系数最高(r = 0.81);镁 - AQ的相关系数最低(0.57)。预测表现良好(R > 0.68);镁的结果最佳(0.86)。按实验室分别建立模型表明,一些数据集更难建模,可能是由于原材料(石灰石)的变异性。添加NixPro™数据有助于提高预测准确性,尽管提升幅度较小。使用CP样本进行的预测结果最佳,尤其是对于镁,这表明无需研磨。这项开创性研究表明,融合近程传感器可用于快速、轻松地测定土壤改良剂中钙和镁的含量,且不产生化学废料。

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