In recent years, yield instability of spring maize becomes increasingly pronounced under the traditional cropping system. In 2014 and 2015, short-term effects of tillage (plow-till, rotary-till and no-till) and residue (removal and incorporation) on soil properties, maize growth and yield were investigated in a brown soil region. Our results indicated that short-term reduced tillage (rotary-till and no-till) and residue incorporation promoted soil properties and maize growth. Compared with plow-till, rotary-till and no-till decreased soil bulk density and compaction below the plough layer (~30 cm). The soil organic carbon (SOC), total nitrogen and C:N of surface soil layers increased under the rotary-till (0–20 cm) and no-till (0–10 cm), which were higher in 0–30 cm soil layers for residue incorporation. For both years, root characteristics of root diameter (RAD) and root surface area density (RSD), biomass indexes of root biomass (RB), shoot biomass (SB) and root-shoot ratio (R:S) were increased under these short-term treatments. Although there were positive relationships between soil water content (SWC), C:N, RAD, RSD, RB, SB, R:S and yield, structural equation modeling showed maize yield was directly controlled by R:S. These findings will have important implications for improving the current cropping system (i.e., plow-till with residue removed) in this area.

Soil micro-food webs play an essential role in maintaining or improving the stability of agricultural soils, and they can be influenced by tillage. However, little is known with respect to soil microbial and faunal communities and their relationships shaped by long-term tillage practices. The goal of this study was to investigate the impact of 38 years of no-tillage (NT), subsoil tillage (ST), moldboard plow tillage (MP), and rotary and ridge tillage (CT) practices on soil microbial and faunal communities, and their relationships with soil properties using high-throughput sequencing technology and structural equation modeling (SEM) at 2 soil depths (0–20 cm and 20–40 cm). The results indicate that, after the 38-year (1983–2020) period, the bacterial, fungal, protozoan, and metazoan gene copy numbers under the NT treatment at 0–20 cm were 1.31–6.13 times higher than those under the other treatments. Conversely, the microbial and protozoan alpha diversities were reduced under the NT treatment compared with the CT treatment. However, MP significantly increased microbial and faunal gene copy numbers at 20–40 cm. Moreover, the bacterial community composition remarkably varied relative to the community composition of the fungi and fauna in response to the tillage practices and soil depths. Additionally, the highest and lowest average connectivities of the soil micro-food web networks were observed under the ST and MP treatments, respectively. The SEM demonstrated that tillage practices and soil depths explained 73–98% of the microbial and faunal abundances, diversities, and compositions. Additionally, tillage and depth demonstrated direct quantitative effects and indirect quantitative effects by altering the soil mean weight diameter of aggregates, soil organic carbon, and total nitrogen. Overall, subsoil tillage is recommended as the optimal practice for application in northeast China, and it could improve soil properties and aid in forming a more complex soil micro-food web structure.

A field experiment was conducted to evaluate the effect of different tillage structures on soil physical properties, soil chemical properties, maize root morphological and physiological characteristics, and yield. Four tillage structures were designed. Soil tillage plays a prominent role in agricultural sustainability. The different tillage layer structures affected soil physical properties. An enhancement in the optimal tillage layer structure improved soil structure. The MJ tillage layer structure created an improved soil structure by regulating the soil physical properties so that the soil compaction and soil bulk density would be beneficial for crop growth, increase soil water content, and adjust the soil phrase R value and GSSI. Soil nutrients are significantly affected by soil depth, with the exception of available potassium. However, soil nutrients are influenced by different tillage layer structures with soil depth. Soil nutrient responses with depth are different for MJ layer treatment compared with other tillage layer structures. Soil organic matter (SOM) is affected with an increase in depth and is significantly influenced by different tillage layer structures, except at 20–30 cm soil depth. MJ treatment increased by 10–20% compared with other tillage layer structures. In addition, QS treatment enhanced the increased pH value in soil profile compared to others. The root morphology characteristics, including root length, root ProjArea, root SurfArea, root AvgDiam, and root volume, were affected by years, depth, and the tillage layer structures. The MJ tillage layer structure enhanced root growth by improving tillage soil structure and increasing soil air and water compared with other tillage layer treatments. Specifically, the MJ layer structure significantly increased root length and root volume via deep tillage. However, the differences in root physiological properties were not significant among treatments. The root dry weight decreased with an increase in soil depth. Most of the roots were mainly distributed in a 0–40 cm soil layer. The MJ treatment enhanced the increase in root dry weight compared with others by breaking the tillage pan layer. Among the different tillage layer structures, the difference in root dry weight was smaller with an increase in soil depth. Moreover, the MJ treatment significantly improved maize yield compared with others. The yield was increased by 14.2% compared to others under MJ treatment via improvements in the soil environment. In addition, the correlation relationship was different among yield and root morphology traits, root physiology traits, soil nutrients, and soil physical traits. So, our results showed that the MJ tillage layer structure is the best tillage structure for increasing maize yield by enhancing soil nutrients, improving the soil environment and root qualities.

This study investigates the effects of different tillage practices on soil quality and maize yield in black soil farmland. Based on an eight-year continuous field plot experiment initiated in 2017, we examined the impacts of five tillage methods: conventional tillage (CT), no-tillage with straw mulching (NTS), subsoiling tillage with straw mulching (STS), harrow tillage with straw mulching and incorporation (HTS), and moldboard plowing tillage with straw incorporation (MPS). The focus was on soil structure, hydrothermal characteristics, organic matter, and nutrient content within the 0–40 cm soil layer, as well as maize dry matter accumulation and grain yield. The results indicate that, in 2023, compared to CT, STS significantly improved the soil structure and hydrothermal characteristic quality index (SHQI) in the 0–40 cm soil layer. Additionally, NTS, STS, HTS, and MPS significantly enhanced the soil organic matter and nutrient quality index (ONQI) in the 0–40 cm soil layer. NTS and STS increased the soil quality index (SQI) by 9.0% to 16.6% compared to the other treatments. Additionally, NTS, STS, HTS, and MPS significantly enhanced the soil organic matter and nutrient quality index (ONQI) in the 0–40 cm soil layer. In 2024, NTS and STS increased the soil quality index (SQI) by 9.0% to 16.6% compared to the other treatments. Furthermore, NTS and MPS significantly improved the SHQI in the 0–40 cm soil layer compared to CT. NTS and STS also significantly enhanced the ONQI in the 0–40 cm soil layer, while NTS, STS, and MPS increased the SQI by 7.3% to 22.6% compared to the other treatments. STS and MPS treatments significantly increased both hundred-kernel weight and grain yield compared to CT and NTS. Correlation and redundancy analyses revealed that SHQI in the 10–40 cm soil layer is a crucial factor affecting dry matter accumulation, yield, and its components in maize. In summary, in the semi-humid region of Northeast China, STS and MPS are cultivation techniques that optimize black soil quality and enhance maize grain yield.

The integration of appropriate tillage practices with straw returning can effectively mitigate soil degradation in Northeast China. However, limited research has explored the impacts of different tillage practices combined with varying straw incorporation depths on the structure and diversity of soil microbial communities. In 2016, a field experiment was initiated using a two-factor split-plot design, featuring six treatments: two tillage depths of 10 cm (D10) and 30 cm (D30) combined with three straw management practices—straw mixing incorporation (SM), straw deep burial (SB), and straw removal (SR). Soil samples collected in 2019 were analyzed for multiple soil properties and microbial indices. Results indicated that both straw returning and tillage depth significantly influenced soil organic carbon (SOC), soil total nitrogen (STN), total phosphorus (TP), and total potassium (TK), with the D30 treatment combined with straw returning optimizing soil nutrient contents most effectively. Under straw returning, D10 significantly increased urease activity in the 0–10 cm soil layer, whereas D30 enhanced this enzyme activity in the 10–30 cm soil layer, while β-glucosidase activity was less responsive to tillage depth. For the D10 treatment with straw returning, acid phosphatase activity was markedly higher than that in the straw removal treatment, whereas N-acetyl-β-D-glucosaminidase activity exhibited the opposite trend. Straw-returning methods had no significant effects on the bacterial and fungal Chao1 indices, while the Shannon index was positively correlated with key soil properties. Redundancy analysis (RDA) of microbial community composition at the phylum level and soil environmental factors revealed that soil nutrients in the 0–10 cm soil layer were positively correlated with Actinobacteriota, Ascomycota, and Basidiomycota, whereas the explanatory power of soil nutrients for microbial community variation decreased in the 10–30 cm soil layer. Our results highlight that tillage depth and straw returning can regulate soil microbial community composition and enhance soil nutrient cycling, thereby providing a theoretical basis for optimizing the combined application mode of tillage and straw-returning practices in Northeast China.

Accurately quantifying the amount of corn straw returned to the field is crucial for evaluating conservation tillage measures and phaeozem protection. This study proposes a framework for quantitatively estimating the amount of corn straw returned to the field based on UAV multispectral imaging, integrating a standardized spectral correction strategy, a novel straw index (SI), and an improved deep learning model (convolutional neural network-straw, CNN-Straw). By combining multispectral images acquired by UAVs with ground-measured straw weight data, regression datasets covering autumn and spring conditions were constructed. The proposed straw index aims to enhance the spectral differences between non-photosynthetic straw residues and living vegetation. Furthermore, the CNN-Straw model, combining frequency domain convolution and local spatial attention mechanisms, has an improved ability to represent the complex texture of straw features. Experimental results show that CNN-Straw outperforms traditional machine learning models, including random forest (RF), support vector regression (SVR), and XGBoost, achieving a high coefficient of determination (R²) of 0.82 on different seasonal datasets and effectively reducing the root mean square error (RMSE) and mean absolute error (MAE). Cross-seasonal experiments further demonstrate the stable performance of the framework under different environmental conditions. The proposed method provides an efficient and scalable solution for the quantitative assessment of straw return to the field, supporting precision agricultural management and phaeozem conservation practices.