重新導向訊息

肥料产品中的水分分析

AN-NIR-079

2020-01

zh

Results in seconds with NIR Spectroscopy

水分含量是经常测量的肥料属性之一。在环球范围内,针对不同肥料的规定各不相同,但当地的法律限制确保不得超过zui大含水量。与这些方法相比,近红外光谱法(NIRS)具有特定的优势:它能在几秒钟内得出靠谱的结果,同时不会产生化学废物。本应用说明介绍了近红外光谱如何快速、无试剂地分析各种化肥产品中的水分含量。

Moisture content is one of the most commonly measured properties of fertilizers. Globally, regulations for different fertilizers vary, but local legal limits ensure that the maximum amount of water must not be exceeded. A number of analytical techniques are available for this purpose. Next to gravimetric methods, Karl Fischer titration is often used for accurate moisture determination.

Compared to these methods, near-infrared spectroscopy (NIRS) offers unique advantages: it generates reliable results within seconds, and at the same time does not create chemical waste. This Application Note explains how NIRS can offer fast, reagent-free analysis of moisture content in various fertilizer products.

Figure 1. The DS2500 Solid Analyzer was used to collect the spectra of fertilizer samples.

Different fertilizer product types with varying moisture content from 0.12% to 3.82% were measured using a Metrohm DS2500 Solid Analyzer. To overcome sample inhomogeneity, the measurement was performed with a large sample cup in rotation. Data collection and model development was carried out with the Vision Air complete package. Reference values were obtained by coulometric KF-titration coupled with KF oven. The NIRS prediction model was created with the settings described in the following table and validated using a cross validation algorithm.

Pre-Processing Algorithm Validation Type
2nd derivative PLS Cross validation
Figure 2. Raw spectra of different fertilizer products with varying water content.

The obtained graph displays a high correlation (R2 = 0.98) between moisture predicted by the NIRS model and the KF-titration method. Although different fertilizer types were used to create the prediction model, a close ratio between SEC and SECV values proves the validity of the model.

# Factors R2 SEC SECV
3 0.98 0.29% 0.32%
Figure 3. Correlation graph for moisture predicted by NIRS vs titration.

         

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