Shi Zhuolin, Ren Zhaoxia, Yang Zengling, Cai Linwei, Huang Yuanping, Ge Chenjun, Han Lujia
Engineering Laboratory for AgroBiomass Recycling & Valorizing, College of Engineering, China Agricultural University, Beijing 100083, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2024 Nov 5;320:124620. doi: 10.1016/j.saa.2024.124620. Epub 2024 Jun 6.
Developing timely, convenient, and low-cost methods for high-frequency characterization of soil nutrients is necessary for implementing precise soil nutrient management. With the current availability of numerous calibration models of laboratory benchtop near-infrared (NIR) spectrometers for rapid soil nutrient characterization and the appearance of low-cost, convenient miniaturized NIR spectrometers, this study proposes an efficient deployment strategy to address model failure due to inter-device variation based on spectral transfer. The strategy involves using Direct Standardization (DS) to migrate the spectra from multiple miniaturized NIR spectrometers with a laboratory benchtop NIR spectrometer and then directly applying the existing calibration models of the laboratory benchtop instrument to the transferred spectra for soil nutrient analysis. The results indicated that the DS method successfully transferred the spectra of miniaturized devices to be consistent with the spectra of the laboratory benchtop instrument. The soil organic matter (SOM) predictions using the transferred spectra and the calibration models of the laboratory benchtop instrument were even more accurate than those using the respective models developed for each miniaturized devices, with root mean square error (RMSE) of 0.177 %, 0.177 %, and 0.150 %, respectively, while the performances of total nitrogen (TN) predictions were comparable to those using the respective models, with RMSE of 0.013 %, 0.012 %, and 0.010 %, respectively. Bland-Altman plots demonstrated good consistency between the strategy proposed in this study and the strategy of developing respective models for each miniaturized device, with no difference in predictions for the independent validation set compared to the laboratory benchtop instrument. This study proved the feasibility of deployment strategy of multiple miniaturized NIR spectrometers based on spectral transfer, offering a new solution for high-frequency on-site soil nutrient characterization.
开发及时、便捷且低成本的土壤养分高频表征方法对于实施精准土壤养分管理至关重要。鉴于目前有众多用于快速土壤养分表征的实验室台式近红外（NIR）光谱仪校准模型，以及低成本、便捷的小型化NIR光谱仪的出现，本研究提出了一种基于光谱转移的高效部署策略，以解决因设备间差异导致的模型失效问题。该策略包括使用直接标准化（DS）方法将多个小型化NIR光谱仪的光谱与一台实验室台式NIR光谱仪的光谱进行迁移，然后将实验室台式仪器的现有校准模型直接应用于转移后的光谱进行土壤养分分析。结果表明，DS方法成功地将小型化设备的光谱转移至与实验室台式仪器的光谱一致。使用转移后的光谱和实验室台式仪器的校准模型对土壤有机质（SOM）的预测甚至比使用为每个小型化设备开发的各自模型更准确，均方根误差（RMSE）分别为0.177%、0.177%和0.150%，而总氮（TN）预测的性能与使用各自模型的性能相当，RMSE分别为0.013%、0.012%和0.010%。Bland-Altman图表明本研究提出的策略与为每个小型化设备开发各自模型的策略之间具有良好的一致性，与实验室台式仪器相比，独立验证集的预测没有差异。本研究证明了基于光谱转移的多个小型化NIR光谱仪部署策略的可行性，为高频现场土壤养分表征提供了一种新的解决方案。
