Responses of Phosphate-Solubilizing Microorganisms Mediated Phosphorus Cycling to Drought-Flood Abrupt Alternation in Summer Maize Field Soil

Soil microbial communities are essential to phosphorus (P) cycling, especially in the process of insoluble phosphorus solubilization for plant P uptake. Phosphate-solubilizing microorganisms (PSM) are the dominant driving forces. The PSM mediated soil P cycling is easily affected by water condition changes due to extreme hydrological events. Previous studies basically focused on the effects of droughts, floods, or drying-rewetting on P cycling, while few focused on drought-flood abrupt alternation (DFAA), especially through microbial activities. This study explored the DFAA effects on P cycling mediated by PSM and P metabolism-related genes in summer maize field soil. Field control experiments were conducted to simulate two levels of DFAA (light drought-moderate flood, moderate drought-moderate flood) during two summer maize growing periods (seeding-jointing stage, tasseling-grain filling stage). Results showed that the relative abundance of phosphate-solubilizing bacteria (PSB) and phosphate-solubilizing fungi (PSF) increased after DFAA compared to the control system (CS), and PSF has lower resistance but higher resilience to DFAA than PSB. Significant differences can be found on the genera Pseudomonas, Arthrobacter, and Penicillium, and the P metabolism-related gene K21195 under DFAA. The DFAA also led to unstable and dispersed structure of the farmland ecosystem network related to P cycling, with persistent influences until the mature stage of summer maize. This study provides references for understanding the micro process on P cycling under DFAA in topsoil, which could further guide the DFAA regulations.

Responses of Cereal Yields and Soil Carbon Sequestration to Four Long-Term Tillage Practices in the North China Plain

Current tillage practices in the important winter wheat–summer maize double cropping system of the North China Plain are under debate because of negative effects on soil quality and crop yield. Therefore, a long-term experiment was conducted from 2001 to 2018 to determine the effects of soil conservation practices on crop yield and soil quality. The treatments were imposed following maize harvest and prior wheat seeding, and were defined as follows: (1) moldboard ploughing (0–20 cm) following maize straw removal (CK); (2) moldboard ploughing (0–20 cm) following maize straw return (CT); (3) rotary tillage following maize straw return (RT); and (4) no tillage with maize straw covering the soil surface (NT). Wheat straw was chopped and spread on the soil in all treatments and maize seeded without prior tillage. Wheat yields were higher in CT than RT and NT treatments (p < 0.05); NT had 18% lower wheat yields than CT. No significant differences were found between treatments in summer maize yields. The soil organic carbon (SOC) content in the surface layer (0–5 cm) was higher in NT and RT compared to CT and CK. However, SOC content in the 10–20 cm and 20–30 cm layers was lower in NT and RT compared to CT and CK. Similarly, available phosphorus in the surface soil was higher in NT and RT than in CT and CK. but the opposite was true for the lower soil layers. SOC stocks (0–30 cm) increased in all treatments, and were initially faster in NT and RT than in CT and CK. However, SOC stocks were higher in CT than in other treatments at the end of the experiment. This finding indicates that no tillage and reduced tillage decreased both wheat yields and soil C sequestration over time; it also indicates that CT was the most robust in terms of crop yields and soil C sequestration.

Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data

Global climate change and the spread of COVID-19 have caused widespread concerns about food security. The development of smart agriculture could contribute to food security; moreover, the targeted and accurate management of crop nitrogen is a topic of concern in the field of smart agriculture. Unmanned aerial vehicle (UAV) spectroscopy has demonstrated versatility in the rapid and non-destructive estimation of nitrogen in summer maize. Previous studies focused on the entire growth season or early stages of summer maize; however, systematic studies on the diagnosis of nitrogen that consider the entire life cycle are few. This study aimed to: (1) construct a practical diagnostic model of the nitrogen life cycle of summer maize based on ground hyperspectral data and UAV multispectral sensor data and (2) evaluate this model and express a change in the trend of nitrogen nutrient status at a spatiotemporal scale. Here, a comprehensive data set consisting of a time series of crop biomass, nitrogen concentration, hyperspectral reflectance, and UAV multispectral reflectance from field experiments conducted during the growing seasons of 2017–2019 with summer maize cultivars grown under five different nitrogen fertilization levels in Beijing, China, were considered. The results demonstrated that the entire life cycle of summer maize was divided into four stages, viz., V6 (mean leaf area index (LAI) = 0.67), V10 (mean LAI = 1.94), V12 (mean LAI = 3.61), and VT-R6 (mean LAI = 3.94), respectively; moreover, the multi-index synergy model demonstrated high accuracy and good stability. The best spectral indexes of these four stages were GBNDVI, TCARI, NRI, and MSAVI2, respectively. The thresholds of the spectral index of nitrogen sufficiency in the V6, V10, V12, VT, R1, R2, and R3–R6 stages were 0.83–0.44, −0.22 to −5.23, 0.42–0.35, 0.69–0.87, 0.60–0.75, 0.49–0.61, and 0.42–0.53, respectively. The simulated nitrogen concentration at the various growth stages of summer maize was consistent with the actual spatial distribution.

Comparison of Multi-Methods for Identifying Maize Phenology Using PhenoCams

Accurately identifying the phenology of summer maize is crucial for both cultivar breeding and fertilizer controlling in precision agriculture. In this study, daily RGB images covering the entire growth of summer maize were collected using phenocams at sites in Shangqiu (2018, 2019 and 2020) and Nanpi (2020) in China. Four phenological dates, including six leaves, booting, heading and maturity of summer maize, were pre-defined and extracted from the phenocam-based images. The spectral indices, textural indices and integrated spectral and textural indices were calculated using the improved adaptive feature-weighting method. The double logistic function, harmonic analysis of time series, Savitzky–Golay and spline interpolation were applied to filter these indices and pre-defined phenology was identified and compared with the ground observations. The results show that the DLF achieved the highest accuracy, with the coefficient of determination (R2) and the root-mean-square error (RMSE) being 0.86 and 9.32 days, respectively. The new index performed better than the single usage of spectral and textural indices, of which the R2 and RMSE were 0.92 and 9.38 days, respectively. The phenological extraction using the new index and double logistic function based on the PhenoCam data was effective and convenient, obtaining high accuracy. Therefore, it is recommended the adoption of the new index by integrating the spectral and textural indices for extracting maize phenology using PhenoCam data.

Effects of Partial Blackwater Substitution on Soil Potential NI-Trogen Leaching in a Summer Maize Field on the North China Plain

In China, promoting harmless blackwater treatment and resource utilization in rural areas is a priority of the “toilet revolution”. Exploring the effects of blackwater application in arid areas on soil nitrogen losses can provide a basis for more effective water and fertilizer management. This study analyzed nitrogen leaching and maize yield under blackwater application in the summer maize season of 2020. A total of 5 treatments were used: no fertilizer, single chemical fertilizer application (CF), single blackwater application (HH), and combined chemical fertilizer and blackwater application ratios of 1:1 (CH1) and 2:1 (CH2). The total nitrogen leached from the fertilization treatments was 53.14–60.95 kg·ha−1 and the leached nitrate nitrogen was 34.10–40.62 kg·ha−1. Nitrate nitrogen accounted for 50–62% of the total leached nitrogen. Compared with blackwater treatments, nitrate nitrogen moved into deeper soil layers (80–100 cm depth) during the CF treatment. Compared with CF, HH significantly reduced the maize yield by 24.39%. The nitrogen surplus of HH was higher than that of other fertilizer treatments. Considering nitrogen leaching, maize yield, and economic benefits, the CH2 treatment presented the optimal results. These findings address knowledge gaps and assist in guiding policy-makers to effectively promote China’s “toilet revolution”.

The Optimal Cultivar × Sowing Date × Plant Density for Grain Yield and Resource Use Efficiency of Summer Maize in the Northern Huang–Huai–Hai Plain of China

In order to explore the optimal cultivar × sowing date × plant density for summer maize (Zea mays L.) in the Northern Huang–Huai–Hai (HHH) Plain of China, field experiments were conducted over two consecutive years (2018–2019) on a loam soil in the Northern HHH Plain. A split–split plot design was employed in this study, and the main plots included three cultivars (HM1: early-maturing cultivar; ZD958: medium-maturing cultivar; DH605: late-maturing cultivar); subplots consisted of three sowing dates (SD1: June 10; SD2: June 17; SD3: June 24); sub-sub plots include two plant densities (PD1: 6.75 × 104 plants ha−1; PD2: 8.25 × 104 plants ha−1). The results showed that the effects of cultivar and plant density on grain yield of summer maize were not significant, and the sowing date was the major factor affecting the grain yield. Delayed sowing significantly decreased the grain yield of summer maize, this was due mainly to the reduced kernel weight, which is associated with the lower post-anthesis dry matter accumulation. Moreover, radiation use efficiency (RUE), temperature use efficiency (TUE), and water use efficiency (WUE) were significantly affected by cultivar, sowing date, and plant density. Selecting early- and medium-maturing cultivars was beneficial to the improvements in RUE and TUE, and plants grown at earlier sowing with higher plant density increased the RUE and TUE. The interactive analysis of cultivar × sowing date × plant density showed that the optimum grain yields of all tested cultivars were observed at SD1-PD2, and the optimum RUE and TUE for HM1, ZD958, and DH605 were observed at SD1-PD2, SD2-PD2, and SD2-PD2, respectively. The differences in the optimum grain yield, RUE, and TUE among the tested cultivars were not significant. These results suggested that plants grown at earlier sowing with reasonable dense planting had benefits of grain yield and resource use efficiency. In order to adapt to mechanized grain harvesting, early-maturing cultivar with lower grain moisture at harvest would be the better choice. Therefore, adopting early-maturing cultivars grown with earlier sowing with reasonably higher plant density would be the optimal planting pattern for summer maize production in the Northern HHH Plain of China in future.