The purpose of this study was to produce rendering animal carcass residue char (RACR-C) by pyrolyzing the solid residues of low-recyclable rendered pig carcasses and to evaluate their cadmium (Cd) adsorption characteristics and mechanisms. As the pyrolysis temperature increased, the inorganic content of RACR-C increased, while the carbon content decreased. In particular, the surface structure and chemistry of RACR-Cs prepared at different pyrolysis temperatures were well described by SEM-EDS, XRD, XRF, TGA, and FTIR. The Cd adsorption characteristics of RACR-C were in good agreement with the Langmuir isotherm and pseudo-second-order models, and the Cd adsorption capacities of RACR-Cs prepared at various pyrolysis temperatures were in the order of RACR-C500 (73.5 mg/g)> RACR-C600 (53.8 mg/g)> RACR-C400 (41.5 mg/g) " RACR-C250 (15.9 mg/g). The intraparticle diffusion model suggested that the adsorption of Cd by RACR-C is greatly influenced by internal diffusion as well as external boundary. Since the Cd adsorption capacity of RACR-C is greatly influenced by the initial dosage, pH, and co-existing metals, it is necessary to manage these influencing factors when treating wastewater containing heavy metals. Our results suggest that Cd adsorption by RACR-C is a complex adsorption phenomenon by various mechanisms such as adsorption by functional group (C˭C and C-O), precipitation of Cd-P and ion exchange reaction by exchangeable cation occurring rather than by a single specific mechanism.

Applying soil amendments such as biochar has been proposed as a means to improve soil properties and reduce greenhouse gas emission from agricultural soils. The objective of this study was to evaluate and compare the effects of biochar and straw application on rice yield, select soil properties, global warming potential (GWP), and greenhouse gas intensity (GHGI) over the 3-year period. The study treatments included control (CN), barley straw biochar (BC, 2,000 kg ha⁻¹), barley straw (BS, 2,000 kg ha⁻¹), and BC+BS (each 1,000 kg ha⁻¹). During the rice-growing season, significant interactive effects of BC and BS treatment were observed in major soil properties. The average rice yields in BC, BS, and BC+BS treatments increased by 4.6%, 4.7%, and 18.7%, compared with CN treatment, respectively. Also, BC+BS treatment produced relatively stable yield during the 3-year study. Both BC and BS applications, either alone or in combination, lowered soil bulk density values compared to the CN treatment. Further, BC application produced a low total CH₄ flux than other treatments. The total produced GWP over the 3 years occurred in the order: BS ≧ CN > BC+BS > BC treatment. These results clearly demonstrate the advantages of biochar and straw applications in improving rice yield and soil fertility while reducing GWP and GHGI.

Soil analysis is fundamental to sustainable agriculture; however, traditional laboratory methods are time-consuming, expensive, and environmentally hazardous. Spectroscopy techniques, particularly Near-Infrared (NIR), have gained considerable attention because they require minimal sample preparation, no chemicals, and predict multiple soil properties with a single scan. However, selecting appropriate equipment remains critical, as previous studies have reported inconsistent performance between conventional Near-Infrared (NIR) spectroscopy and advanced Fourier-Transform Near-Infrared (FT-NIR) spectroscopy. Therefore, this study aimed to compare the predictive performance of conventional NIR and advanced FT-NIR spectroscopy for sixteen soil properties. Soil samples (n = 567) were collected from different land-use types across South Korea at a depth of 0–20 cm and analyzed using laboratory methods and spectroscopy techniques. Five models, including partial least squares regression (PLSR), Cubist, support vector machine (SVM), random forest (RF), and memory-based learning (MBL), were evaluated using 15-fold cross-validation to assess prediction accuracy. Overall, conventional NIR spectroscopy yielded consistently higher accuracy for all soil properties than FT-NIR. Strong predictive accuracy was achieved for EC (R² = 0.84), OM (R² = 0.84), avl. P (R² = 0.77), TN (R² = 0.84), and CEC (R² = 0.76). In contrast, FT-NIR provided good prediction accuracy only for Ex. K (R² = 0.72) and TN (R² = 0.84). The average performance of NIR (R² = 0.67) outperformed FT-NIR spectroscopy (R² = 0.63) across all soil properties. These findings demonstrate that, despite their lower spectral resolution, NIR spectra provide robust predictive capability across a wide range of soil properties, which can significantly reduce the investment cost of advanced equipment such as FT-NIR for routine soil analysis.

South Korea is one of countries that have high application rate of inorganic fertilizer and is known to cause significant environmental issues. The inorganic fertilizer to the soil has led to a nutrient supply that exceeds the nutrient requirements of crops, resulting in an excess of nutrients in agricultural soil. Hence, many agricultural policies have been legislated to reduce the fertilizer application rate since the 1990s. In this study, we investigated changes of fertilizer type and usage on fruit crops (pear, grape, apple, peach, jujube, persimmon, kiwi) in 2018 and 2022. In results, the average of total fertilizer inputs (N-P 2 O5-K 2 O) increased to 15.0-6.1-4.5 kg 10a-1 in 2022. Based on N, the total fertilizer usage of jujube was higher than other crops in 2018 and 2022. Moreover, the fertilizer usage for all crops exceeded the recommended levels. The order of contribution to total fertilizer use was compost > organic fertilizer > inorganic fertilizer. As a result, a primary concern of excess and use of fertilizers was focused on compost and organic fertilizers. Because of the high nutrient content of compost, the application rate of compost should be controlled and monitored. Therefore, the proper training and monitoring is required to reserve environmental sustainability and understand nutrient characteristics of fertilizer in fruit crop cultivation.

Infrared (IR) spectroscopy has emerged as a rapid, cost-effective, and reliable alternative to traditional methods, enabling real-time, indirect monitoring of nutrients. Most reviews have discussed visible-near-infrared (Vis-NIR) and mid-infrared (MIR) spectroscopy individually for soil analysis. This review highlights the application of IR spectroscopy, particularly Vis-NIR, MIR spectroscopy, and their data fusion, coupled with chemometrics and spectral preprocessing for estimating soil attributes. Additionally, the crucial functions of assessing model accuracy and validating model estimates of soil properties are discussed. Partial least squares regression (PLSR) was used in more than 100 studies in 2022. Based on the literature published from 2020 to 2025, the data fusion method predicts soil properties more accurately. This review also sheds light on recent advances in spectroscopic methods, including improvements in speed (e.g., MIR spectroscopy is up to 12 times faster than traditional methods), instrument miniaturization, and integration with portable devices, which can make field analysis more affordable. However, the sensitivity of IR spectroscopy to soil moisture, sample heterogeneity, vegetation cover, and calibration transfer issues remains a significant challenge in certain studies. Therefore, a discussion on the challenges in implementing this technique is included in this review, and future perspectives, such as integration of various sensors and portable devices for real-time soil assessment, are successively discussed.

RACR-C application rate (%, w/w) 0 1 2 5 1 0 NH 4 NO 3-extractable Cd concentration (mg kg-1