Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy has been used to determine the nitrate content in aqueous solutions. However, the conventional water deduction algorithm indicated considerable limits in the analysis of samples with low nitrate concentration. In this study, FTIR-ATR spectra of nitrate solution samples with high and low concentrations were obtained, and the spectra were then pre-processed with deconvolution curve-fitting (without water deduction) combined with partial least squares regression (PLSR) to predict the nitrate content. The results show that the typical absorption of nitrate (1200−1500 cm⁻¹) did not clearly align with the conventional algorithm of water deduction, while this absorption was obviously observed through the deconvolution algorithm. The first principal component of the spectra, which explained more than 95% variance, was linearly related to the nitrate content; the correlation coefficient (R²) of the PLSR model for the high-concentration group was 0.9578, and the ratio of the standard deviation of the prediction set to that of the calibration set (RPD) was 4.22, indicating excellent prediction performance. For the low-concentration group model, R² and RPD were 0.9865 and 3.15, respectively, which also demonstrated significantly improved prediction capability. Therefore, FTIR-ATR spectroscopy combined with deconvolution curve-fitting can be conducted to determine the nitrate content in aqueous solutions, thus facilitating rapid determination of nitrate in water bodies with varied concentrations.

Nitrogen (N) and phosphorus (P) play vital roles in crop growth. However, conventional fertilizers exhibit low utilization efficiency, making them prone to causing resource wastage and water eutrophication. Although metal–organic frameworks (MOFs) have shown great potential for application in controlled-release fertilizers (CRFs), currently reported MOF-based CRFs suffer from low nutrient content, which limits their further application. To address this issue, this study synthesized a series of hierarchically porous MOFs, denoted as MIL-156(X), using sodium acetate as a modulator under hydrothermal conditions. These materials were subsequently loaded with urea and phosphate from aqueous solution to form MOFs-based CRFs (N-P-MIL-156(X)). Results indicate that MIL-156(X) retain microporous integrity while incorporating abundant mesopores. Increasing modulator content reduced particle size and average pore diameter but increased specific surface area and adsorption capacity for urea and phosphate. MIL-156-H (with a high modulator content addition) exhibited the highest adsorption capacity, conforming to Langmuir isotherm and pseudo-second-order kinetics. The adsorption mechanisms of urea and phosphate involved hydrogen bonding and the formation of Ca intra-spherical complexes, respectively. N-P-MIL-156-H contained 10.8% N and 16.3% P₂O₅, with sustained release durations exceeding 42 days (N) and 56 days (P₂O₅) in an aqueous solution. Pot trials demonstrated significantly higher nutrient use efficiency (N-44.8%, P₂O₅-16.56%) and a 12.22% yield increase compared to conventional fertilization (N-35.6%, P₂O₅-13.32%). Thus, N-P-MIL-156-H-based fertilization significantly promotes rice growth and N/P utilization efficiency, offering a promising strategy for developing controlled-release fertilizers and improving nutrient management.