Mid-infrared (MIR) spectroscopy models have been developed for rapid assessment of soils but are often soil and instrument specific because of differences in laboratory conditions and sensor setup. Calibration transfer is required to apply a spectral model such as partial least squares (PLS) regression developed from a primary instrument to a spectral dataset measured by a secondary instrument with statistically retained accuracy and precision. The study aimed to compare the performance of three transfer methods (i.e., direct standardization [DS], piecewise direct standardization [PDS], and spectral space transfer [SST]) and investigate the effects of transfer sample size and sample selection methods. The transfer methods were developed for predicting total C, clay, silt, and sand contents, cation exchange capacity (CEC), pH in water (pH_W) and CaCl₂, CaCO₃ equivalent, and −1,500-kPa water retention using spectral measurements of a secondary instrument. Calibration transfer methods of three PLS models for estimating soil properties with a high (total C), intermediate (clay content), and low (pH_W) predictability were discussed. The effect of sample size required for the development of the calibration transfer and the selection method of the transferred samples were investigated. It was found that SST was most favorable for a relatively small sample size used in calibration transfer (≤12 samples). The performance of transfer methods was optimal when the transfer samples accounted for the variability of MIR spectra from the secondary instrument. We conclude that SST and PDS have the potential to be applied in spectroscopy for predicting soil properties using secondary instruments.

中文翻译：

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使用中红外光谱评估土壤性质预测的三种校准传递方法

中红外 (MIR) 光谱模型已开发用于快速评估土壤，但由于实验室条件和传感器设置的差异，通常是特定于土壤和仪器的。需要校准传输才能将光谱模型（例如从主要仪器开发的偏最小二乘 (PLS) 回归）应用到由具有统计保留精度和精度的辅助仪器测量的光谱数据集。该研究旨在比较三种转移方法（即直接标准化 [DS]、分段直接标准化 [PDS] 和光谱空间转移 [SST]）的性能，并研究转移样本大小和样本选择方法的影响。开发了转移方法来预测总碳、粘土、淤泥和沙子的含量、阳离子交换容量 (CEC)、水中的 pH 值 (pH_W ) 和 CaCl ₂、CaCO ₃等价物和 -1,500-kPa 保水性，使用辅助仪器的光谱测量。三种 PLS 模型的校准传递方法，用于估算高（总 C）、中等（粘土含量）和低（pH _W）土壤特性) 的可预测性进行了讨论。研究了开发校准转移所需的样本大小的影响以及转移样本的选择方法。发现 SST 最有利于校准转移中使用的相对较小的样本量（≤12 个样本）。当转移样品考虑到来自辅助仪器的 MIR 光谱的可变性时，转移方法的性能是最佳的。我们得出结论，SST 和 PDS 有可能应用于光谱学，以使用二级仪器预测土壤特性。