Soybean (Glycine max) is a critically important crop for oil, protein, feed, and food security in China. Expanding soybean cultivation into high-latitude regions represents one of the most direct and effective strategies to increase total production. In the present study, we employed KASP (Kompetitive Allele-Specific PCR) marker technology to systematically analyze 18 variant loci across 14 flowering-time genes in 443 soybean germplasm accessions adapted to high-latitude conditions in Arctic Village (Beiji Cun), Mohe City (>53° N), northeastern China. Our results revealed clear functional-tier-dependent selection gradients: key mutation sites (frequency > 96%) in upstream photoreceptors and core circadian clock genes, such as E2 and GmPRR3a, were nearly fixed in the population, whereas downstream flowering genes such as GmFT5b and GmFT2b remained under dynamic selection. Combinatorial analysis of early-maturity allelic variants identified 178 distinct genotype combinations, including six dominant types (n ≥ 10). Field phenotypic analysis demonstrated that the cumulative number of early-maturity alleles was significantly negatively correlated with flowering time, with specific allele combinations such as FT5aA + FKF1b-hap3T exhibiting particularly strong flower-promoting effects. A set of 80 highly enriched super-early-maturity accessions, including extreme materials such as MHL22002, were identified, providing valuable genetic resources and a theoretical framework for elucidating the flowering regulatory mechanisms of high-latitude soybean and for breeding super-early-maturing varieties.

Soil inorganic carbon (SIC) constitutes half of the terrestrial carbon pool and exerts a profound influence on global carbon cycling and ecosystem multifunctionality. Contrary to the view of millennial-scale stability, SIC in cropland are undergoing rapid changes due to intense anthropogenic disturbances. However, the direction, magnitude, and drivers of SIC changes over recent decades remain poorly quantified, especially in entire soil profile. Here, we quantified changes in SIC across a 1-m soil profile across China's upland croplands at 204 matched sites (4,305 soil profiles) in 1980s and 2023, relocated using legacy site descriptions and field verification. Over the past four decades, the mean of surface SIC density (0 to 40 cm) depleted by 0.68 kg m-2, primarily associated with increased precipitation and soil acidification, whereas subsurface SIC density (40 to 100 cm) increased by 0.49 kg m-2, attributed to carbon inputs and an increase in soil pH. Subsurface SIC accumulation amounted to [Formula: see text] Pg, offsetting 44% surface losses within the upper 1 m soil profile. Importantly, this offset reflects vertical redistribution of SIC rather than net carbon sequestration at the ecosystem scale. These findings highlight the need to incorporate depth-resolved SIC dynamics into terrestrial carbon accounting and climate projections.

To address the bottlenecks of low efficiency, poor consistency, and inadequate compatibility with high‑throughput phenotyping pipelines inherent in manual field‑based seed counting during soybean breeding, this study developed and validated an enhanced automatic soybean seed detection and counting model, YOLO‑Soy, tailored for complex field environments. Built on a YOLO11n backbone, the model integrates a Zoom multi‑scale feature fusion module, a C2PSA self‑attention enhancement module, a ScalSeq hierarchical feature sequence aggregation module, and a soybean-specific detection head. These additions systematically enhanced the saliency of tiny-seed features under dense occlusion and complex backgrounds and strengthened the capacity for foreground-background separation. Experiments were conducted using two‑year field imagery (2024–2025) and a year-stratified leave-one-year-out cross-validation strategy for training and validation. Ablation study revealed that the four improved modules are functionally complementary, forming a comprehensive pipeline of interference mitigation, scale adaptation, precise feature fusion, and detection output transformation. A single module exhibited limited effect when acting independently, whereas multi-module synergy produced substantial gains. Test-set results demonstrated that the seed counts predicted by the model were highly consistent with manual ground truth, achieving a coefficient of determination (R²) of 0.934, a mean relative error of 2.446%, a mean average precision (mAP@0.5) of 0.737, and an inference speed of 58.78 FPS. These metrics satisfy the requirements for real-time field detection. The findings indicated that YOLO-Soy can accelerate the seed‑counting step in variety selection processes, greatly reducing manual workload and subjective errors.

Soil acidification is a critical global issue threatening agricultural productivity and ecosystem health. In recent years， human activities have intensified soil acidification， posing significant challenges to food security and sustainable agriculture. Acidified soils are characterized by a decline in pH， increased activity of toxic metal ions， and nutrient depletion， leading to soil structure degradation and restricted plant growth. This article systematically summarizes the main driving factors of soil acidification in farmland， including non-human factors （weathering and leaching， nutrient absorption， organic matter decomposition， root exudates release， lightning volcanic eruption and deposition， microbial activity， etc.） and human factors （unreasonable agricultural management， climate change， etc.）， and further analyzes the main processes of microbial-mediated soil acidification affecting nutrient cycling. To address soil acidification， existing mitigation strategies are summarized， such as lime application， balanced fertilization， organic matter management， biochar application， and the promotion of acid-tolerant crops. However， due to the diversity of soil types， the complexity of acidification processes， and variations in crop types and cultivation practices， the effectiveness of these measures varies significantly. By providing a comprehensive synthesis and outlook and considering the context of climate change， this study explores future research directions， offering both theoretical foundations and practical guidance for the scientific management of soil acidification and the advancement of sustainable agriculture.

Double-season rice fields typically exhibit low soil potassium (K) availability despite abundant straw resources. Whether integrating milk vetch could enhance K retention from straw and improve its uptake by subsequent rice remains unclear. Therefore, we examined how the combined incorporation of straw and milk vetch affects soil K distribution and bioavailability. A field experiment conducted in Jiangxi Province, China, which treatments included single straw incorporation (S) and combined straw plus milk vetch incorporation (S + G). The exchangeable and non-exchangeable K of bulk soil in S + G were higher by 79.33% and 22.26% than the S treatment. Compared with the S treatment, the S + G also improved the exchangeable and non-exchangeable K in > 2 mm, 0.25-2 mm, and 0.053-0.25 mm aggregates. Notably, milk vetch strengthened the linkage between exchangeable K and non-exchangeable K within microaggregates (0.053-0.25 mm). These results demonstrate that integrating straw with milk vetch effectively enhances soil K availability for double-season rice systems.

Timely flowering and maturity are crucial for plant reproduction and environmental adaptation. Light–dark cycle-associated regulatory networks integrate photoperiodic cues with intrinsic developmental programs and play pivotal roles in flowering, maturity and environmental adaptation. Soybean is a short-day crop with strong photoperiod responsiveness; however, the molecular mechanisms by which these networks mediate soybean adaptation to diverse environments remain largely elusive. Here, we combine genome-wide association analysis with deep learning-based assessment of soybean maturity variation and identify GmRVE4d, a homolog of the Arabidopsis clock-associated REVEILLE, as a maturity-associated locus across both field environments. Genetic analysis reveals evidence of domestication-related artificial selection at GmRVE4d and identifies the late-maturing haplotype GmRVE4dH3. Functional analyses further demonstrate that the GmRVE4d protein directly binds to the promoter of GmPRR5a, a soybean homolog of the Arabidopsis clock-associated component PSEUDO-RESPONSE REGULATOR 5, and represses its transcription, thereby delaying soybean flowering and maturity. Taken together, our findings suggest that GmRVE4d is a negative regulator of soybean flowering and maturity that functions by directly repressing GmPRR5a expression and represents a promising molecular target for expanding cultivation latitudes through molecular breeding. Researchers identify GmRVE4d as a gene that delays soybean flowering and maturity by repressing GmPRR5a. This finding highlights GmRVE4d as a potential breeding target for improving soybean adaptation across different latitudes.

Rhizospheric C, N, and P stoichiometry embodies the dynamic equilibrium between nutrient release through mineralization and the retention of elements during organic matter turnover. Yet, global quantitative assessments of how rhizospheric processes reshape soil and microbial elemental ratios across agricultural ecosystems remain scarce. To address this, we conducted a synthesis of 1,683 data points collected from 122 peer-reviewed studies worldwide. The meta-analysis revealed that rhizospheric processes significantly increased soil C:N, C:P, and N:P ratios by 5.1%, 5.9%, and 3.4%, respectively, relative to bulk soil. In contrast, microbial biomass C:P and N:P ratios decreased by 15.1% and 12.4% under rhizospheric conditions. Importantly, no significant overall effect of the rhizosphere was detected for microbial biomass C:N ratios. The enhancement of soil C:N ratio was most evident under humid climates and mildly acidic soils (pH 5.5–6.5). Conversely, reductions in microbial biomass C:N ratios were less apparent in humid environments with higher ammonium-N availability. Vegetable systems and the rapid growth phase of crops enhanced rhizospheric soil C:N by approximately 8.8% and 4.3%, respectively, whereas microbial C:N declined by 23.3% and 6.3%. Additionally, organic fertilizer raised the soil C:N ratio by about 8.9%, whereas nitrogen fertilization reduced it by roughly 6.0% (P < 0.05), however, neither treatment significantly affected the microbial biomass C:N ratio. Among environmental variables, soil organic carbon and ammonium-N emerged as primary drivers of stoichiometric variation for soil and microbial C:N ratio, explaining 30.6% and 24.1% of total variability, respectively. Collectively, this global synthesis reveals that rhizospheric regulation of carbon–nitrogen stoichiometry operates through distinct pathways in soil and microbial pools, advancing our understanding of plant–microbe interactions as a central mechanism governing nutrient cycling in agricultural systems worldwide.

REVEILLE (RVE) transcription factors, belonging to the CCA1/LHY-like MYB family, are conserved across the plant lineage and play central roles in regulating the plant circadian oscillator, with emerging functions extending beyond clock regulation to stress modulation. Here, we synthesize recent advances on the evolution, structural architecture, and functional characterization of RVE proteins across plant species. We highlight the functions of RVEs as essential transcriptional activators within the circadian oscillator, as rhythmic chromatin remodelers, and as components of feedback loops that orchestrate day-night gene expression. We discuss the non-circadian functions of RVE genes in plants, including plant growth regulation, metabolic coordination, hormone signaling, and their coordinated roles in responses to cold, salt, and heat stressors. Furthermore, we discuss the emerging functions of RVE genes in soybean and their potential regulation of legume symbiosis. We identify unresolved controversies that warrant further investigation and propose future research directions to address these knowledge gaps. Finally, we outline a research roadmap and discuss the potential of RVE-mediated strategies for soybean trait improvement.

Inorganic amendments, including lime, gypsum, and calcium-based soil conditioners, are widespread for soil acidification mitigation, enhancing nutrient availability, and boosting crop productivity. However, their impacts on soil organic carbon (SOC) remain inconsistent and incompletely quantified worldwide. To evaluate the global influence of inorganic amendments on SOC dynamics and crop productivity in acidic agroecosystems, we examined data from 269 independent field experiments, encompassing 6034 observations, via meta-analysis. Our findings indicate that inorganic amendments significantly increased SOC concentration by an average of 2.8 % and crop yield by 14.6 %. These SOC alterations are impacted by crop types, duration, initial SOC, CaO input, and aridity index. Crop rotation and composite amendment are critical for enhancing organic carbon levels. Applying inorganic amendments to chemically fertilized soil is more effective at elevating SOC than when applied to organically fertilized soil. The changes in critical factors between these two fertilizer types highlight the importance of soil nutrient levels and microbial activity in carbon cycling. Moreover, the positive correlation between response ratios (RR) of SOC and RR of yield indicates that enhancing organic carbon can improve soil productivity. Overall, inorganic amendments are a viable management strategy for increasing soil carbon sequestration in acidic agroecosystems and are essential for predicting carbon feedback in upcoming global acidification scenarios.

Soil acidification reduces phosphorus availability, and inorganic amendments are key tools to mitigate soil acidification. However, the effects of such amendments on available phosphorus (AP) and the factors driving AP changes are not fully understood. The present meta-analysis quantifies the impact of inorganic amendments on AP and uses a random forest model to identify the primary factors influencing AP response ratios. The results indicate that inorganic amendments significantly increase AP compared to untreated soils, with climate, soil initial properties, and management practices playing crucial roles. The most significant improvements were observed when lime and gypsum were applied together at rates of 0.8-1.6 t ha-1 over 1-3 years. The highest increase in AP occurred in soils with initial AP levels below 10 mg kg-1 and pH values between 4.5 and 5.5. Random forest analysis revealed that initial AP content and inorganic amendment type were the most influential factors for upland and paddy soil. Optimizing the type, quantity, and method of applying inorganic amendments, in conjunction with appropriate land use type and fertilization strategies, is critical for mitigating soil acidification and improving phosphorus utilization.

Lime and crop straw are widely applied to mitigate soil acidification and improve soil fertility. However, how different lime materials interact with straw to influence greenhouse gas (GHG) emissions from acidic upland soils remains poorly understood. This study explored how different lime materials and their interaction with straw affect GHG emissions. Here, we conducted incubation experiments with acidic red soil to investigate the individual and combined effects of liming materials, including Ca(OH)2, CaO, and CaCO3, as well as rice straw addition on nitrous oxide (N2O) and carbon dioxide (CO2) emissions. Our findings demonstrated that in the absence of straw, liming increased N2O emission by 20.3% (CaO) to 78.2% (Ca(OH)2). CaCO3 application raised CO2 emissions by 182.7%, while CaO and Ca(OH)2 decreased CO2 emissions by 37.3% and 43.2%, respectively. Adding straw alone enhanced N2O and CO2 emissions by 80.69% and 302.7%, respectively. When combined with straw, liming further increased N2O emissions by 85.0% to 140.1%, with Ca(OH)2 causing the highest emissions. CaCO3 increased CO2 emissions by 37.3% when combined with straw, whereas CaO and Ca(OH)2 reduced CO2 emissions by 31.6% and 32.2%, respectively. Straw addition significantly increased global warming potential (GWP). Applying CaO and Ca(OH)2 decreased GWP, whereas CaCO3 increased it with straw application. Compared to CaCO3, CaO and Ca(OH)2 application resulted in a lower GWP, making them optimal lime materials for reducing acidification and mitigating GHG emissions. Linear regression and partial least squares path (PLS-PM) analyses indicated that soil carbon, nitrogen, and microbial biomass significantly influenced N2O emissions under lime and straw application, while CO2 emissions were unaffected by these soil properties. Both lime and straw addition increased microbial biomass carbon (MBC) and nitrogen (MBN), dissolved organic carbon (DOC), and NH4+-N contents, but decreased NO3--N content, leading to higher N2O emissions. CO2 emissions were influenced by the chemical reactions of various lime materials in the soil. These findings suggest that selecting appropriate lime materials can significantly mitigate greenhouse gas emissions from acidic soils, contributing to more sustainable agricultural practices.

Highly laborious plating of cultures onto solid media is inevitable in conventional yeast two-hybrid systems. We have successfully developed Liquid Y2H-Seq, a method that replaces solid media with liquid media for culturing and displaces visual inspection of colonies with sequencing. Soybean (Glycine max) is a typical photoperiod-sensitive crop, meaning that a specific duration of light regime has a huge impact on soybean flowering and production. We obtained a lot of putative interactions for soybean flowering genes. Finally, these reports introduce a labor-reducing and time-saving method for identifying protein-protein interactions, based on simple modifications to a ubiquitous protocol in life science research.

Abstract. The stoichiometry of the rhizosphere, particularly concerning carbon (C), nitrogen (N), and phosphorus (P), reflects the balance between nutrient mineralization and retention during organic matter decomposition. However, the magnitude and underlying mechanisms of rhizospheric influences on soil and microbial stoichiometry remain insufficiently quantified at the global scale across diverse agroecosystems. This study synthesizes data from 113 peer-reviewed sources, encompassing 882 individual observations. The results reveal that the rhizosphere significantly increases soil C:N, C:P, and N:P ratios, while concurrently decreasing microbial C:N, C:P, and N:P ratios relative to bulk soil conditions. Notably, the rhizospheric effects on soil C:N ratios is amplified in humid regions and diminished in arid environments. In contrast the influence on microbial C:N exhibits a positive correlation with increasing soil organic C and ammonium N concentrations. Moreover, sensitive crops such as maize and vegetables enhance the rhizospheric soil C:N ratio by 5.68 % and 8.91 % respectively, while reducing the microbial C:N ratio by 11.00 % and 19.44 %. Soil organic C and ammonium N emerge as key determinants of rhizospheric soil and microbial C:N ratios, contributing 37.9 % and 30.3 % to their varations, respectively. The study establishes a coupled relationship between rhizospheric soil and microbial stoichiometry. These findings offer critical insights into rhizospheric nutrient cycling, which are essentials for improving soil health and optimizing nutrient use efficiency through targeted management practices.

Previous studies reported a reduction in N2O emissions following lime application. However, the mechanisms underlying N2O reduction under different soil acidifications are not clear and require further investigation. As a result, it is imperative to gain insights into how lime application affects N2O emissions and associated microbial activities under varying soil acidification and other factors. Only studies obtained from the agroecosystems were considered for the current meta-analysis. Accordingly, this meta-analysis was conducted with 684, 141, 149, and 94 paired observations for the response variables of N2O emissions, archaeal amoA gene abundance, bacterial amoA gene abundance, and nosZ gene abundance, respectively, obtained from 39 peer-reviewed studies. The current meta-analysis findings indicated that the lime application reduced soil N2O emissions by 46.63 % and raised soil pH by 27.63 % across all paired observations compared to control. Overall, lime application also increased the abundance of bacterial amoA and nosZ genes by 101.17 % and 49.63 %, respectively, while decreasing the abundance of archaeal amoA by 6.39 %. Our structural equation modeling (SEM) suggested that the differences in the reduction of N2O emission magnitudes under different lime rates are due to differences in the degree of soil pH manipulation. Lime application rate was identified as the primary factor influencing the response of soil N2O emissions to lime, followed by soil pH. Our results from SEM indicated that the main drivers of the variable responses in soil N2O emissions to lime application under different soil acidifications are the variable responses of N2O-associated microbial activities and substrate availability. The greater reduction in N2O emissions under neutral soil conditions, compared to acidic conditions, is primarily attributed to a pH-driven shift in microbial activity, evidenced by a larger increase in nosZ gene abundance and a decrease in bacterial amoA gene abundance. Grain yields of wheat, rice, and maize increased by 9.42 %, 11.40 %, and 62.42 %, respectively, following lime application compared to the control. Based on our findings, we concluded that applying lime to acidic soils is a suitable option for reducing soil N2O emissions by affecting the activity of associated microbial functional genes and substrate availability in agricultural ecosystems.

Soybean has been grown across diverse latitudes; however, its adaptation to low-latitude, high-altitude environments with short days and low temperature remains unclear. To understand the genetic basis of adaptation, we screened 200 diverse cultivars and conducted genome-wide association studies (GWAS) in Bamei and Xianshui, Daofu country, Sichuan Province, China, in 2019 and 2023, respectively. Six agronomic traits: flowering time (DTF), maturity time, node number on main stem (NNM), plant height (PH), effective number of pods per plant and 100-seed weight (HGW) were evaluated. Five MG I-II cultivars (Bamei) and 17 MG II-V cultivars (Xianshui) were screened as adaptive, exhibiting late flowering and maturity, tall stature, and high node and pod numbers. Adaptive cultivars predominantly carried the allelic combinations E1/e2-ns/e3-tr/E4 and E1/e2-ns/E3/E4 (Bamei), and only E1/e2-ns/E3/E4 (Xianshui). GWAS identified 9, 6, and 2 genomic regions associated with DTF, NNM and PH, respectively, with two regions linked to both DTF and PH. Most QTNs associated with DTF were located near known loci or Arabidopsis flowering gene homologues. Non-synonymous mutations in GmPIE1, GmFY and GmIAA31 were associated with delayed flowering and taller plants. The adaptive cultivars, markers, and genes identified offer valuable resources for improving soybean adaptation to low-latitude, high-altitude regions.

Modified (metal oxide) biochar is widely used for the remediation of degraded soils, but there has been limited research work on its effect on phosphorus fractionation and biochemical properties under different soil conditions. Therefore, this study examined the effects of a nonmodified wheat straw biochar (WBC) and a magnesium-modified wheat straw biochar (Mg-WBC) on phosphorus fractions, soil chemical properties, enzyme activity and microbial biomass in Qiyang (QY) and Harbin (HAR) soils. The study included a control, two WBC doses (1 and 2.5

This study investigated the effects of pristine biochar (BC) and magnesium-treated biochar (Mg-BC), applied at 0%, 1%, and 2.5% (w/w), on the relationship between P fractions and GHG emissions in two degraded soils. Soil physiochemical properties were improved in response to BC and Mg-BC treatments. Enzyme activities increased with BC and Mg-BC treatments, where Mg-BC showed better effects. Similarly, increasing biochar did increase the labile-P pool while decreasing the moderately labile P (MP) and residual P pools in both soils, and the effects observed under Mg-BC treatment were more pronounced than those in the BC treatment. Compared to CK, BC and Mg-BC increased CO2 emissions by 76%-138% and 44%-127% in red soil, and by 14%-33% and 8%-23% in black soil, respectively. In contrast, N2O emissions decreased by 11%-29% and 17%-44% in red soil, and by 12%-23% and 16%-31% in black soil, respectively. Multivariate redundancy analysis revealed that biochar-induced improvement in labile P, enzyme activities, and soil properties were positively correlated with CO2, whereas negatively associated with N2O emission. The structural equation modeling (SEM) revealed that biochar type and dose had a minor influence on CO2 emissions, but on the other hand, considerably decreased N2O emissions (R 2 = 0.82-0.89) by increasing soil nutrients (SOC, NH4, AP, and LP) in black soil, and pH, enzymes, and soil nutrients in red soil. Our results demonstrated that biochar application reduces N2O emissions by improving soil pH, nutrients, and enzyme activities in degraded soils, with a greater impact under Mg-BC treatment.

In plants, numerous non-Mendelian inherited dominant effects, including over-, incomplete-, and co-dominance, are frequently observed, yet they remain insufficiently understood. A novel phenotype has been identified in specific soybean transformants overexpressing a single 35S::GmFT2a copy: super-early flowering dominance is exclusively observed in hemizygotes, not in homozygotes. Homozygous individual exhibits siRNA-mediated DNA methylation, causing epigenetic transcriptional silencing, whereas no such effect occurs in hemizygotes. Intriguingly, two distinct rounds of DNA methylation establishment occur, each mediated by a different mechanism. The homozygotes that derived from the hemizygous mother plants carrying 35S::GmFT2a locus was associated with the initiation of CHH-context DNA methylation at 35S promoters mediated by 21 and 22 nucleotide (nt) siRNAs. Subsequently, 24 nt siRNAs contribute to additional CHG- and CG-context DNA methylation at 35S promoters during the homozygosity of genes in plants already homozygous in maternal lineage. Reducing DNA methylation levels can be achieved by generating a hemizygous genotype through a crossing experiment with a recessive genotype. This research has unveiled a phenomenon: hemizygote-dependent dominance resulting from transcriptional silencing in homozygote offsprings. It provides new insights into the molecular mechanism underlying dominant effects.

Sustainable rice production requires not only high yields but also reduced environmental impacts and improved economic outcomes. However, sustainability assessments often overlook key indicators such as the carbon footprint (CF), nitrogen footprint (NF), and net ecosystem economic benefit (NEEB). This study, therefore, aims to comprehensively evaluate the long-term effectiveness of substituting green manure (GM) for chemical nitrogen fertilizer (CNF) in improving productivity, nitrogen use efficiency, and NEEB, while simultaneously reducing CF and NF in a double rice cropping system. The experimental treatments included: no CNF (N0), conventional CNF (N100), N100 plus GM (GN100), 80 %N100 plus GM (GN80), 60 %N100 plus GM (GN60), and N0 plus GM (GN0). Annually, substituting GM for 20 % of N100 (GN80) increased grain yield by 12.2 %-99.1 %, harvest index by 3.4 %-20.8 %, nitrogen recovery efficiency by 38.5 %-148.0 % and NEEB by 19.0 %-129.0 % compared with N0, N100, GN100, GN60, and GN0 treatments. The results also revealed a strong positive correlation between CF and NF under GN80 and GN60 but showed trade-off relationships under N100 and GN100, indicating that reduced CNF substitution by GM can simultaneously mitigate CF and NF. In this study, methane emissions were the primary contributors to CF, while reactive nitrogen losses were the main drivers of NF. Compared with GN100 and GN0, GN80 significantly reduced annual CF by 24.1 % and 28.2 %, respectively. It also substantially lowered annual NF and yield-scaled NF by 17.3 % and 37.5 % relative to N100, and by 27.7 % and 31.3 % relative to GN100. Furthermore, GN80 notably decreased annual yield-scaled CF by 22 % compared to N0 and by up to 50 % compared to GN0. Therefore, we recommend the GM substitution for 20 % of N100 to enhance environmental sustainability without sacrificing yield or NEEB. These findings broaden our understanding of how substituting GM for CNF influences CF and NF, offering new insights for promoting sustainable double rice production.

The intensification of agricultural production has significantly reduced land availability, necessitating continuous cropping cycles that degrade soil quality and inhibit crop growth. While the short-term use of soil amendments has shown significant potential for mitigating these challenges, few studies have explored their long-term effects on acidified soils and heavy metal accumulation. Between 2013 and 2018, a field experiment was conducted in the peanut (Arachis hypogaea L)-growing region of Jinxian County, Jiangxi Province, to investigate the long-term effects of oyster shell powder applied to upland red soil. Before the experiment, the soil properties were as follows: pH, 4.54, total soil cadmium (Cd) content, 0.49 mg kg-¹; and available Cd content, 0.25 mg kg-¹. The experiment included three treatments combining chemical fertilizers with oyster shell powder at application rates of 750, 1500, and 2250 kg ha-¹ (L750, L1500, L2250) and a control with only chemical fertilizer (L0). From 2013 to 2018, peanut yield among all treatments was assessed at maturity. Soil pH was then measured using a pH meter with a 2.5:1 water-to-soil ratio. Exchangeable hydrogen and aluminum were determined using the potassium chloride exchange-neutralization titration method. Meanwhile, available Cd content was extracted using 0.1 M CaCl2 and measured with a flame atomic absorption spectrophotometer. While all treatments showed an annual decline in peanut yield from 2013 to 2018, but oyster shell applications significantly reduced the rate of crop yield decline. Compared to L0, the yields of L750, L1500, and L2250 treatments increased by 5.55%-19.42%, 8.64%-28.74%, and 15.43%-37.01%, respectively. Soil pH values in the L750, L1500, and L2250 treatments were higher than the L0 treatment by 0.03-0.31, 0.16-0.48, and 0.28-0.65 units, respectively. Their exchangeable hydrogen contents decreased by 10.17%-24.24%, 16.67%-27.94%, and 23.40%-29.44%. In addition, exchangeable aluminum contents decreased by 5.05%-26.09%, 23.23%-46.27%, and 39.73%-66.97%. In contrast, soil available Cd contents in the L750, L1500, and L2250 treatments were lower than the L0 treatment by 7.96%-19.29%, 9.56%-30.71%, and 13.94%-34.65%, respectively. Correlation analysis revealed that soil pH was positively associated with peanut yield and negatively correlated with exchangeable hydrogen, exchangeable aluminum, and available Cd. For every 0.1 unit increase in soil pH, peanut yields increased by 119.62-389.82 kg ha-¹, while available Cd decreased by 0.06-0.12 mg kg-¹. Therefore, these findings demonstrate the efficacy of continuous oyster shell powder application in controlling soil acidification and reducing Cd levels in upland red soil.