The objective of this study was to assess the predictive performance of midDRIFTS-PLSR models in quantifying total carbon (TC), total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), hot water extractable carbon and nitrogen (C_HWE, N_HWE), pH, and the clay, silt, and sand content of soils. A total of 68 soil samples were taken across an agroecological region in southwest Iran, and analyzed in the laboratory using mid-DRIFTS-PLSR. midDRIFTS-PLSR calibration models were developed, and external validation was performed for each of the soil properties via an independent algorithm. The calibration and validation models allowed for a sufficient prediction of TC, TIC, and TOC with residual prediction deviations ≥3 and R² values >0.9. The precise prediction ofcarbon fractions, such as TC, TIC, and TOC, in a rapid and inexpensive manner confirmed that midDRIFTS analysis was a rapid-throughput and cost-effective technique for monitoring soil carbon at the regional scale.

这项研究的目的是评估midDRIFTS-PLSR模型在量化总碳（TC），总有机碳（TOC），总无机碳（TIC），总氮（TN），热水可提取碳和氮的预测性能（C _HWE，N _HWE），pH值以及土壤的粘土，淤泥和沙子含量。在伊朗西南部的一个农业生态地区共采集了68个土壤样本，并在实验室中使用DRIFTS-PLSR中段进行了分析。开发了midDRIFTS-PLSR校准模型，并通过独立算法对每种土壤特性进行了外部验证。校准和验证模型可对TC，TIC和TOC进行充分的预测，且残留预测偏差≥3和R ²值> 0.9。以快速，廉价的方式准确预测碳组分（例如TC，TIC和TOC），证实了MidDRIFTS分析是一种快速通量且具有成本效益的技术，可以在区域范围内监测土壤碳。