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巴西作物的叶面元素分析:便携式 X 射线荧光光谱法。

Foliar Elemental Analysis of Brazilian Crops via Portable X-ray Fluorescence Spectrometry.

机构信息

Department of Soil Science, Federal University of Lavras - UFLA, Doutor Sylvio Menicucci Avenue, Lavras 37200-900, Minas Gerais State, Brazil.

Department of Plant and Soil Science, Texas Tech University, Bayer Plant Science Building, Room 211A, 2911 15th Street, Lubbock, TX 79409-2122, USA.

出版信息

Sensors (Basel). 2020 Apr 29;20(9):2509. doi: 10.3390/s20092509.

Abstract

Foliar analysis is very important for the nutritional management of crops and as a supplemental parameter for soil fertilizer recommendation. The elemental composition of plants is traditionally obtained by laboratory-based methods after acid digestion of ground and sieved leaf samples. This analysis is time-consuming and generates toxic waste. By comparison, portable X-ray fluorescence (pXRF) spectrometry is a promising technology for rapid characterization of plants, eliminating such constraints. This worked aimed to assess the pXRF performance for elemental quantification of leaf samples from important Brazilian crops. For that, 614 samples from 28 plant species were collected across different regions of Brazil. Ground and sieved samples were analyzed after acid digestion (AD), followed by quantification via inductively coupled plasma optical emission spectroscopy (ICP-OES) to determine the concentration of macronutrients (P, K, Ca, Mg, and S) and micronutrients (Fe, Zn, Mn, and Cu). The same plant nutrients were directly analyzed on ground leaf samples via pXRF. Four certified reference materials (CRMs) for plants were used for quality assurance control. Except for Mg, a very strong correlation was observed between pXRF and AD for all plant-nutrients and crops. The relationship between methods was nutrient- and crop-dependent. In particular, eucalyptus displayed optimal correlations for all elements, except for Mg. Opposite to eucalyptus, sugarcane showed the worst correlations for all the evaluated elements, except for S, which had a very strong correlation coefficient. Results demonstrate that for many crops, pXRF can reasonably quantify the concentration of macro- and micronutrients on ground and sieved leaf samples. Undoubtedly, this will contribute to enhance crop management strategies concomitant with increasing food quality and food security.

摘要

叶片分析对于作物的营养管理非常重要,并且可以作为土壤肥料推荐的补充参数。植物的元素组成传统上是通过实验室方法获得的,即用酸消解研磨和过筛后的叶片样品。这种分析既耗时又会产生有毒废物。相比之下,便携式 X 射线荧光(pXRF)光谱仪是一种快速表征植物的有前途的技术,可以消除这些限制。本研究旨在评估 pXRF 对巴西重要作物叶片样品元素定量的性能。为此,从巴西不同地区采集了 28 个植物物种的 614 个叶片样品。采集的叶片样品经研磨和过筛后,一部分用酸消解(AD),然后用电感耦合等离子体光学发射光谱法(ICP-OES)定量分析,以确定大量营养元素(P、K、Ca、Mg 和 S)和微量营养元素(Fe、Zn、Mn 和 Cu)的浓度。同样的植物养分也可以通过 pXRF 直接在研磨后的叶片样品上进行分析。使用 4 种植物标准参考物质(CRMs)进行质量保证控制。除了 Mg 之外,pXRF 和 AD 之间的相关性对于所有植物养分和作物都非常强。方法之间的关系取决于养分和作物。特别是对于桉树,除了 Mg 之外,pXRF 和 AD 之间存在最佳相关性。与桉树相反,甘蔗除了 S 之外,所有评估元素的相关性都最差,而 S 的相关性系数非常强。结果表明,对于许多作物来说,pXRF 可以合理地定量测定研磨和过筛后的叶片样品中大量和微量养分的浓度。毫无疑问,这将有助于增强作物管理策略,同时提高食品质量和粮食安全。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af2e/7249210/bbd792ac232d/sensors-20-02509-g001.jpg

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