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Aims: Root system architecture (RSA) is important for nutrient and water acquisition efficiency. The adaptation of root growth and RSA to soil structure under conservative strip tillage (ST) system warrants further investigation. Methods: A three-year field experimentation was conducted in Northeast China to investigate the RSA and dynamic root growth of rain-fed maize under ST system by comparison with the conventional tillage (CT). Results: Grain yield in ST and CT was not significantly different, but their yield components differed. Compared to CT, grain number per ear was reduced by 4.4%, while 1000-grain weight was increased by 6.6% in ST. Root growth in ST plants was inhibited in the vegetative stage, as indicated by the reduced total root length (by 27.7–40.1%) compared to CT. During post-silking stage, the total root length was not different between ST and CT plants but the root xylem bleeding rate in ST plants was 70.7%-449.9% greater than that in CT. The uneven horizontal distribution of soil bulk density and soil temperature made the RSA of ST plants steeper compared to CT. Moreover, the D95 of root distribution in ST plant roots was greater. Conclusions: In ST system, colder, more compacted soil in the inter-row soil likely caused the lower root growth and consequently lower shoot dry matter during the vegetative stage. However, root senescence was delayed which was beneficial for water and nitrogen acquisition during grain filling. Strategies to improve early root growth may increase maize productivity in ST systems. [ABSTRACT FROM AUTHOR]

Plant genotypes shape root‐associated microbiota that affect plant nutrient acquisition and productivity. It is unclear how maize hybrids modify root‐associated microbiota and their functions and relationship with nitrogen use efficiency (NUE) by regulating rhizosphere soil metabolites. Here, two N‐efficient (NE) (ZD958, DMY3) and two N‐inefficient (NIE) maize hybrids (YD9953, LY99) were used to investigate this issue under low N (60 kg N ha−1, LN) and high N (180 kg N ha−1, HN) field conditions. NE hybrids had higher yield than NIE hybrids under LN but not HN. NE and NIE hybrids recruited only distinct root‐associated bacterial microbiota in LN. The bacterial network stability was stronger in NE than NIE hybrids. Compared with NIE hybrids, NE hybrids recruited more bacterial taxa that have been described as plant growth‐promoting rhizobacteria (PGPR), and less related to denitrification and N competition; this resulted in low N2O emission and high rhizosphere NO3−‐N accumulation. NE and NIE hybrids had distinct rhizosphere soil metabolite patterns, and their specific metabolites were closely related to microbiota and specific genera under LN. Our findings reveal the relationships among plant NUE, rhizosphere soil metabolites, root‐associated microbiota, and soil nutrient cycling, and this information is informative for breeding NE crops. [ABSTRACT FROM AUTHOR]

Mixed application of controlled‐release and normal urea (MCU) is considered as a promising alternative to farmers' practice with one‐time nitrogen fertilization (FP) and optimal split nitrogen fertilization (OPT). In this study, MCU effectiveness on maize (Zea mays L.) were investigated by conducting 2‐yr field experiments on sandy and clay soils. Across the 2 yr, grain yields in MCU increased by 22 and 18% relative to FP on sand and clay soils, respectively, and net returns increased by 65 and 19%, respectively, while total N losses reduced by 228 and 193 kg N ha−1, respectively. In general, MCU showed significant advantages in agronomic, economic, and environmental benefits relative to FP across soil types, and the advantages were more remarkable on sandy soil. Although OPT also showed better effectiveness relative to FP, while its performances were similar to MCU on clay soil but slightly less effective on sandy soil. Compared to FP, the lower N rate and optimized N management in MCU and OPT effectively reduced N loss and ensured sufficient soil N availability to meet maize N demand at the later growth stage, accumulated more dry matter (DM) and N in plants that associated with larger post‐silking ratios, and consequently improved grain yield and nitrogen recovery efficiency (REN). Our results demonstrated that MCU is an effective and promising method to concurrently meet smallholders' requirement for simplified fertilization and the optimal N management strategy, could replace OPT as an optimal N management method for maize on both two soil types, especially on sandy soil. [ABSTRACT FROM AUTHOR]

To increase crop productivity while reducing environmental costs, an integrated soil–crop system management (ISSM) strategy was developed and successfully adopted in China. However, little information is available on the long-term ISSM effects on maize agronomic and environmental performance. Therefore, we evaluated the effects of ISSM with combining inorganic and organic fertilizers on maize productivity, N use efficiency (NUE) and N balance and losses as compared with farmers' practice (FP) and high-yielding practice (HY), based on an 11-year field experiment in Northeast China. Maize yield in ISSM (11.7–14.3 Mg ha−1) achieved 97.7% of that in HY and was increased by 27% relative to FP. The excellent yield performance in ISSM was mainly attributed to optimum plant population structure and yield components. Annual N surplus in ISSM was only 7 kg ha−1, which was considerably lower than that in FP (52 kg ha−1) and HY (109 kg ha−1). Consequently, ISSM obtained significantly lower N losses and greenhouse gases emissions and higher NUE. In contrast to FP, crop performance in ISSM showing better sustainability and inter-annual stability. In conclusion, ISSM is an effective strategy to achieve long-term sustainable high crop yields and NUE with less environmental costs in the intensive agricultural system. [ABSTRACT FROM AUTHOR]

The mixture of controlled-release urea (CRU) and normal urea (MCU) applied as one-time basal fertilizer is a convenient and effective alternative to traditional split-nitrogen (N) fertilization, can ensure a sufficient late-season N supply to increase maize yield. However, the effects of MCU ratios on maize root development, post-silking growth, and grain-filling process remain poorly understood. In this study, 3-year field experiments were conducted on sandy and clay soils in Northeast China, to evaluate maize yield responses to different MCU ratios (from 0% to 60% at 15% intervals). Four key treatments, i.e., N omission (N0), MCU0%, MCU30%, and MCU60%, were then selected to investigate root traits, post-silking plant growth and N uptake, grain-filling parameters, and their relationships with grain yields. Across different soils and years, grain yields showed a parabolic curve with increasing MCU ratios, with the highest yields obtained in MCU30%. On average, MCU30% increased grain yield by 22.3% and 11.7% on sandy and clay soils, respectively, relative to MCU0%. The appropriate early-N supply in MCU30% promoted root growth by allocating more dry matter (DM) to roots, while increasing total root length by producing more and longer crown roots, as well as higher lateral root length. The well-developed roots in MCU30% increased post-silking plant N uptake under sufficient late-N supply, thereby delayed leaf senescence and improved DM production for grain-filling, ultimately increased kernel weight and grain yield. Compared to MCU30%, MCU60% showed similar growth and yield performances on clay soil. In contrast, MCU60% performed notably worse on sandy soil due to limited CRU-N release at early period under inherently lower soil moisture and fertility levels. Our measurements and correlation analysis support the conclusion that MCU30% effectively sustain leaf longevity and increase post-silking DM by optimizing root growth and morphology under an optimal N supply pattern during maize growing season, thus improving grain-filling and final yield. The results advance our understanding of how MCU method affects maize post-silking growth and yield formation, providing important insights for optimizing crop N management by regulating root development, especially on lower fertility soils. • Higher yield in MCU30% was driven by increased post-silking DM and improved grain-filling rate. • Compared to MCU30%, maize plants in MCU60% performed equally on clay soil, but worse on sandy soil. • MCU30% increased root length by producing more, longer crown roots while elongating lateral roots. • The well-developed root enhanced post-silking N uptake and reduced vegetative-N mobilization. [ABSTRACT FROM AUTHOR]

• Rectangular MZs providing a basis for site-specific management in the maize field. • Correlations of soil-crop attributes and yield varied across MZs and growth stages. • Main factors' contributions to yield had various characteristics among MZs. Spatial variability of soil properties, crop performance, fertilization management, and tillage methods play an important role in yield prediction and improvement. However, the farm nutrient management in most regions of the world is still based on conventional and uniform management strategies, without take into consideration the spatial variability of the above factors. Therefore, the objectives of this study were to delineate potential management zones (MZs), with the considering of spatial variability of soil properties, crop performance, fertilization management, tillage methods, and investigate their relationships with yield, and their contributions to yield in each management zone. A 1.60 ha maize field with fertilizer and tillage management, in Lishu County, Jilin Province, China, was selected as the study area and soil samples with soil organic matter, total nitrogen and soil pH measured values, crop samples with crop height, leaf nitrogen content, above ground biomass at V6, silking, and maturity growth stages, and yield measured values were collected in 2019 and 2020. Firstly, the rectangular MZs were defined to divide the study area into relatively homogeneous areas based on the spatial variability of soil properties, crop performance, and yield of 2019 and 2020. Secondly, the correlations of soil properties and crop performance with yield were obtained across MZs and growth stages in 2019 and 2020. Lastly, the yield prediction models were established based on the above four types of factors by using random forest (RF) model and the contributions of main factors were obtained quantitatively across different MZs and years. The results showed that (1) the small maize field was divided into three rectangular MZs and most of the soil and crop attributes presented homogeneous characteristics in each zone; (2) correlations of soil properties and crop performance with yield varied across different MZs and growth stages, and even different years; (3) RF model obtained good performance across MZs and years, with R2 = 0.86 and RMSE = 0.77 kg/ha in 2019 and R2 = 0.89 and RMSE = 1.04 kg/ha in 2020 both for the whole field. The contribution of main factors for yield varied across both MZs and years, while some characteristics of the main factors' contributions remain unchanged. This study would open the opportunity to farmers and agricultural experts for site-specific nutrient management in the maize field. [ABSTRACT FROM AUTHOR]

• Crop height explained the most variability in maize AGB estimation of V6 stage. • EVI and VARI were selected as the most important narrowband VIs at the R1 stage. • mSR 705 , Vi opt , SRPI, REIP-LI, NDI, Maccioni were important VIs at the R3 stage. • XGBoost model outperformed stepwise and RF regression model in maize AGB estimation. • UAV-based hyperspectral imagery has some advantages for AGB estimation. Monitoring the aboveground biomass (AGB) of maize is essential for improving site-specific nutrient management and predicting yield to ensure food safety. A low-altitude unmanned aerial vehicle (UAV) was employed to acquire hyperspectral imagery of the maize canopy at three growth stages (V6, R1, R3) to estimate the maize AGB. Five maize nitrogen (N) rate experiments were conducted in Lishu County, Jilin Province, Northeastern China, to create different biomass conditions. Combined with crop height data obtained from the field measurements, 30 narrowband vegetation indices (VIs) were extracted using surface reflectance data from the hyperspectral imagery. Stepwise regression, random forest (RF) regression and XGBoost regression models were used to predict the fresh and dry AGB of the 2019 growth season. The study revealed that (1) crop height explained the most variability (60–70%) in the maize dry and fresh AGB estimation of the V6 growth stage, while different VIs exhibited various importance for AGB estimation at other maize growth stages; (2) XGBoost regression models demonstrated high prediction accuracy in both fresh and dry AGB estimation, compared with stepwise regression and RF models. (3) XGBoost models also presented high prediction accuracy at each single-growth stage and the whole-growth stage, with the highest accuracy for the dry AGB at V6 growth stage (R2 = 0.81, RMSE = 0.27 t/ha). This study demonstrated the capability of UAV-based hyperspectral imagery for estimating maize AGB at the field scale, which can be used to assist precision agriculture. [ABSTRACT FROM AUTHOR]