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.

Soil organic carbon (SOC) can be accumulated through various organic inputs such as organic fertilizers, compost, and biochar. While organic fertilizers are effective in supplying nutrients, they have limitations in stable carbon sequestration compared to biochar. Therefore, this study aimed to determine the optimal mixing ratio of organic fertilizer and biochar that can supply nutrients while ensuring sustained and stable carbon sequestration. The growth of lettuce, soil chemical properties, and soil carbon sequestration were evaluated through a pot experiment based on the mixing ratios of organic fertilizer and biochar derived from agricultural waste. The treatments in the pot experiment included no fertilizer (NF), inorganic fertilizer (IF), and biochar mixed organic fertilizer (BAOF), mixing ratios of organic fertilizer:biochar = 100:0, 90:10, 80:20, 70:30. The results showed that leaf length and width of lettuce increased by 1.70-1.84 and 1.58-1.78 times, respectively, in BAOF treatments compared to NF. The highest yield was observed in BAOF (100:0). The organic matter content increased with higher mixing ratio of biochar. SOC stock was observed in the following order: 11.93 (BAOF70:30) > 11.22 (BAOF80:20) > 10.35 (BAOF90:10) > 10.26 (BAOF100:0) t C ha-1. In conclusion, mixing biochar with organic fertilizers promoted lettuce growth and led to increased soil carbon sequestration. These results indicated that the optimal mixing ratio was determined to be BAOF70:30.

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.

Effect of Different Type of Organic Matter Application on Rice Yield and Soil Organic Carbon Stock in Paddy Soil-Manure compost,Organic matter,Rice straw,Rice yield,Soil organic carbon

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.