Amino resins are produced by two main processes: the strong acid process and the alkaline-acid process. Both use formaldehyde and a base (e.g. sodium hydroxide) in their formulation. In this work, Forward Interval Partial Least Squares methodology was applied to create prediction models for the determination of the concentration of formaldehyde and residual methanol (that is present in the formaldehyde solution) used in the production of amino resins. Near infrared (NIR) spectra were acquired at two different temperatures: 18 and 35°C. A Partial Least Squares calibration models were established with the measured values from reference methods: namely, sodium sulfite (formaldehyde) and gas chromatography (methanol). The performances of the best models were compared using the root mean square error of cross validation (RMSECV) and coefficient of determination for prediction (r²). The best results obtained a r² above 0.994. The RMSECV values obtained were 0.063% (m/m) and 0.031% (m/m) for the formaldehyde and methanol concentration, respectively. External validation was performed using different formaldehyde solution samples. The NIR methodology presented in this work proved to be effective and enables a significant time reduction, when compared to the reference methods, in the measurement of formaldehyde and methanol concentrations.

氨基树脂通过两种主要工艺生产：强酸工艺和碱酸工艺。两者都在其配方中使用甲醛和碱（例如氢氧化钠）。在这项工作中，应用正向区间偏最小二乘法创建预测模型，用于确定氨基树脂生产中使用的甲醛和残留甲醇（存在于甲醛溶液中）的浓度。在两种不同的温度下获得近红外 (NIR) 光谱：18 和 35°C。使用参考方法的测量值建立偏最小二乘校准模型：亚硫酸钠（甲醛）和气相色谱法（甲醇）。² )。获得的最佳结果 ar ²高于 0.994。对于甲醛和甲醇浓度，获得的 RMSECV 值分别为 0.063% (m/m) 和 0.031% (m/m)。使用不同的甲醛溶液样品进行外部验证。与参考方法相比，这项工作中提出的 NIR 方法在甲醛和甲醇浓度的测量中被证明是有效的，并且能够显着减少时间。