Search

The present study aims to assess the responses of growth, development, and yield of summer maize to the effects of drought–flood abrupt alternation through comparative tests under single flood, single-drought, and drought–flood abrupt alternation treatments with varying degrees from the elongation to the tasseling stage during the 2021 and 2022 growing seasons. In addition, a water production function model for summer maize was preliminarily established based on the results obtained under the drought–flood abrupt alternation scenarios. The results indicated that drought–flood abrupt alternation with early moderate drought had a certain restricting effect on summer maize, while early moderate drought followed by waterlogging had a compensation effect on the cultivated summer maize. Furthermore, both mild and severe drought followed by waterlogging exert a significant combined constraint on the normal growth and development of summer maize, leading to a sharp decline in maize yield, necessitating a shorter timeframe for mitigating and reducing the effects of waterlogging. Additionally, the water production function model established through a multiple linear regression equation exhibits a high degree of fit and demonstrates a strong linear relationship. This study provides crucial insights for agricultural practices and water resource management strategies, particularly in the evaluation of the integrated impacts of drought and waterlogging on crop yields and the formulation of effective disaster risk reduction and mitigation measures in response to these impacts. [ABSTRACT FROM AUTHOR]

Accurate estimation of soil moisture content (SMC) is vital for effective farmland water management and informed irrigation decision-making. The utilization of unmanned aerial vehicle (UAV)-based remote sensing technology to monitor SMC offers advantages such as mobility, high timeliness, and high spatial resolution, thereby compensating for the limitations of in-situ observations and satellite remote sensing. However, previous research has primarily focused on SMC diagnostics for the entire crop growth period, often neglecting the development of targeted soil moisture modeling paradigms that account for the specific characteristics of the canopy and root zone at different growth stages. Furthermore, the variations in soil moisture status between fields, resulting from the hysteresis of water flow in irrigation channels at different levels, may influence the development of soil moisture modeling schemes, an area that has been seldom explored. In this study, SMC models based on UAV spectral information were constructed using Random Forest (RF) and Particle Swarm Optimization-Support Vector Machine (PSO-SVM) algorithms. The soil moisture modeling paradigms (i.e., input–output mapping) under different growth stages and soil moisture conditions of summer maize were systematically compared and discussed, along with the corresponding physical interpretability. Our results showed that (1) the SMC modeling schemes differ significantly across the various growth stages, with distinct input–output mappings recommended for the early (i.e., jointing, tasselling, and silking stages), middle (i.e., blister and milk stages), and late (i.e., maturing stage) periods. (2) these machine learning-based models performed best at the jointing stage, while subsequently, their accuracy generally exhibited a downward trend as the maize grew. (3) the RF model demonstrates superior robustness in estimating soil moisture status across different fields (moisture conditions), achieving optimal estimation accuracy in fields with overall higher SMC in line with the PSO-SVM model. (4) unlike the RF model's robustness in spatial SMC diagnostics, the PSO-SVM model more reliably captured the temporal dynamics of SMC across different growth stages of summer maize. This study offers technical references for future modelers in UAV-based SMC modeling across various spatial and temporal conditions, addressing both the types of models as well as their input features. [ABSTRACT FROM AUTHOR]

The low efficiency of light and nitrogen resources, poor yield and profit, and environmental pollution of maize production are main problems in many areas of China. We hypothesized that optimizing nitrogen fertilizer density management strategies could alleviate the above issues. To address this, a 3-year on-site experiment with three planting densities and four nitrogen rates was conducted in the Sichuan Hilly Region. The results indicated that increasing the planting density could increase the extinction coefficient and solar radiation interception of maize populations as well as enhance the utilization efficiency of light and nitrogen resources and yield. For every 100 kg ha−1 increase in nitrogen fertilizer, RUE increased by 0.16%, NUE decreased by 25.0%, and soil apparent nitrogen loss quantity increased by 67.8 kg ha−1. There was a certain interaction between planting density and nitrogen rate. The appropriate planting density and nitrogen rate combination was 67,500 plants ha−1 with 180 kg N ha−1 under the experimental condition. Excessive close planting in weak-light areas and excessive nitrogen reduction after densification are not advisable. This study indicated that nitrogen–density strategies should be matched with the local natural resources such as sunlight. The results provide a theoretical for high-yield and high-quality maize production in these areas. [ABSTRACT FROM AUTHOR]

The Haihe Plain in China is situated in the world's largest groundwater funnel area, with per capita water resources far below the internationally recognized "extremely water-scarce" standard. To address the issue of water shortage in summer maize-planting areas of the Haihe Plain, we conducted research on the variation of summer maize evapotranspiration using a medium-sized lysimeter. This study aims to provide technical support for water-saving irrigation in summer maize fields. Through path analysis, direct and indirect influencing factors affecting the evapotranspiration of summer maize fields were determined. The results showed that the cumulative evapotranspiration of bare ground and farmland during the entire growth period of summer maize was 173.57 mm and 382.97 mm, respectively, with evapotranspiration intensities of 1.52 mm/d and 3.36 mm/d, respectively. Evapotranspiration during the maturity stage of summer maize was the least, accounting for only 1.82% of total evapotranspiration during the entire growth period. The period from the jointing to milk-ripening stage is when evapotranspiration in maize fields is at its highest. During this period, evapotranspiration in maize fields amounted to 265.58 mm, accounting for 69.35% of total evapotranspiration. The evapotranspiration intensity was 3.59 mm/day, which is 1.34 times higher than that of bare soil. The evapotranspiration intensities during each growth stage were ranked as jointing stage > tasseling-silking stage > seedling stage > milk maturity stage > maturity stage. The daily evapotranspiration of summer maize fields showed a "unimodal" curve with low values in the morning and evening, and high values at noon. Path analysis indicated that daily radiation and maximum daily temperature had the greatest impact on the evapotranspiration of maize fields, with the direct effect of maximum daily temperature being restrictive and the indirect effect being promotive, resulting in an overall promotive effect. [ABSTRACT FROM AUTHOR]

No-tillage of summer maize after the harvest of winter wheat is the primary agricultural practice on the North China Plain. However, prolonged no-tillage without deep tillage practices negatively impacts soil properties, which is detrimental to the growth and yield of summer maize. In this study, Xianyu 688 and Jifeng 2 were used as test maize materials, no-tillage and surface fertilizing with normal nitrogen (N) (BC240), no-tillage and surface fertilizing with N reduction (BC180), subsoiling layered fertilization with normal N (FC240) and subsoiling layered fertilization with N reduction (FC180)were designed, in order to assess root distribution, N utilization and grain yield of summer maize. In the two maize cultivars, the FC240 and FC180 treatments significantly reduced soil bulk density in the 10–50 cm depth soil layer compared to the other two treatments, and also increased total N content in the 20–50 cm depth soil layer. Compare BC 240 treatment, the FC240 treatment significantly increased root length in the 20–40 cm soil layer and root rap bleeding. Additionally, the FC240 and FC180 treatments enhanced dry matter and N accumulation, grain yield, N uptake efficiency and N fertilizer partial factor productivity. In various treatment, Xianyu 688 exhibited increased grain yield, N uptake efficiency and N fertilizer partial factor productivity compare with Jifeng 2. When employing a total N application level of 180–240 kg N/hm2, the synergistic improvement of summer maize grain yield and N efficiency can be achieved by incorporating subsoiling combined with layered nitrogen application. [ABSTRACT FROM AUTHOR]

Summer maize constitutes a major food crop in the Yellow River Basin. Optimizing nitrogen (N) application management for this crop not only elevates its yield but also reduces N leaching, thereby ensuring food security and lessening agricultural surface pollution. Utilizing two years of summer maize field experiments, the soil water heat carbon and N simulator (WHCNS) was calibrated and validated against empirical measurements. Subsequent analyses employed the calibrated WHCNS to analyze 56 different N management scenarios. These scenarios varied in terms of N application levels, basal N to topdress application ratios, and chase ratios. The entropy-weighted TOPSIS method was utilized for the optimization, considering agronomic, environmental, and economic aspects. The model's calibration accuracy was validated by root mean square errors, relative root mean square errors, and mean errors for soil volumetric water content and soil nitrate N content. The calibration results demonstrated that the new model was capable of simulating the soil hydraulic characteristics, N cycling, and the growth and development of summer maize during the reproductive phase in the Yellow River Basin. Scenario analyses revealed that increasing the N application initially elevated, then stabilized, summer maize yields, whereas the N agronomic efficiency first increased and then decreased. Moreover, reducing the basal N to topdress application ratios and increasing the chase ratios during the tasseling and flowering stages could minimize the nitrate N leaching and optimize both the yield and N fertilizer agronomic utilization. Specifically, the optimal N management for the current year involved applying 170 kg·ha−1 of N with a basal N to the topdress N application ratio of 1:5 and a chase ratio of 1:1 during the tasseling and flowering stages. This study lays the foundation for developing N fertilizer management strategies for summer maize cultivation in the Yellow River Basin. Furthermore, the methodology established here can be adapted for optimizing the management of diverse crops in different geographical regions. [ABSTRACT FROM AUTHOR]

Maize is one of the important grain crops grown globally, and growth will directly affect its yield and quality, so it is important to monitor maize growth efficiently and non-destructively. To facilitate the use of unmanned aerial vehicles (UAVs) for maize growth monitoring, comprehensive growth indicators for maize monitoring based on multispectral remote sensing imagery were established. First of all, multispectral image data of summer maize canopy were collected at the jointing stage, and meanwhile, leaf area index (LAI), relative chlorophyll content (SPAD), and plant height (VH) were measured. Then, the comprehensive growth monitoring indicators CGMICV and CGMICR for summer maize were constructed by the coefficient of variation method and the CRITIC weighting method. After that, the CGMICV and CGMICR prediction models were established by the partial least-squares (PLSR) and sparrow search optimization kernel extremum learning machine (SSA-KELM) using eight typical vegetation indices selected. Finally, a comparative analysis was performed using ground-truthing data, and the results show: (1) For CGMICV, the R2 and RMSE of the model built by SSA-KELM are 0.865 and 0.040, respectively. Compared to the model built by PLSR, R2 increased by 4.5%, while RMSE decreased by 0.3%. For CGMICR, the R2 and RMSE of the model built by SSA-KELM are 0.885 and 0.056, respectively. Compared to the other model, R2 increased by 4.6%, and RMSE decreased by 2.8%. (2) Compared to the models by single indicator, among the models constructed based on PLSR, the CGMICR model had the highest R2. In the models constructed based on SSA-KELM, the R2 of models by the CGMICR and CGMICV were larger than that of the models by SPAD (R2 = 0.837), while smaller than that of the models by LAI (R2 = 0.906) and models by VH (R2 = 0.902). In summary, the comprehensive growth monitoring indicators prediction model established in this paper is effective and can provide technical support for maize growth monitoring. [ABSTRACT FROM AUTHOR]

Drip tape layout and flow rate are crucial variables that impact the effects of drip fertigation. To investigate the influence of drip tape layout and flow rate on the soil water and nitrogen transport in summer maize in sandy tidal soil, field experiments were conducted for two years. Two drip tape layouts were set: one tape serving for two crop rows (N) and one tape serving for each crop row (E), with two levels of drip flow rate, i.e., high (2 L/h; H) and low (1.3 L/h; L). The results show that under the same drip tape layout, the lower the drip emitter flow rate, the more upright the shape of wetted soil volume. The maximum vertical and horizontal water transport distance under NL treatment was higher than that under NH, EH, and EL treatments. After surface drip fertigation, nitrate nitrogen accumulated near and at the edge of the wetted soil volume. In 2020, under NL treatment, nitrate nitrogen transported to a 55 cm soil layer, which was 22.22%, 71.42%, and 57.14% deeper than that under NH, EH, and EL treatments, respectively. In 2021, nitrate nitrogen could transport to a 60 cm soil layer in both NL and NH treatments. The maximum concentration of ammonium nitrogen was nearby the emitter. Under NL treatment, ammonium nitrogen was transported to 48 and 60 cm soil layers below the emitter in 2020 and 2021, respectively, which was deeper than that observed under NH, EH, and EL treatments. The soil inorganic nitrogen residue of the NL was lower than that of the NH, EH, and EL treatments. Compared with NH, EH, and EL treatments, the two-year maize yield under NL treatment increased by 11.09%, 13.47%, and 8.66% on average, respectively. NL treatment exhibited the highest water use efficiency and nitrogen fertilizer productivity. Therefore, NL treatment (one drip tape serving for two rows with 1.3 L/h flow rate) could promote the absorption of water and nutrients, reduce inorganic nitrogen residue, and to obtain high maize yield in sandy tidal soil. [ABSTRACT FROM AUTHOR]

Saline-alkali soil is a major threat to global food security. Phosphorus (P) fertilizer is essential for crop growth and yield production. Nevertheless, the optimal phosphate fertilizer application rates for summer maize under coastal saline–alkali soil are still unclear. A field experiment with five phosphate application rates (0, 45, 90, 135, and 180 kg ha−1, referred to as T1, T2, T3, T4, and T5, respectively) was conducted during the 2018–2020 summer maize seasons study the effects of phosphate rates on the grain yield, biomass, and nitrogen (N), P and potassium (K) accumulation, and N, P, and K physiological efficiency (denoted as NPE, PPE and KPE, respectively). Results showed that P application notably improved maize grain and biomass yield, the total uptake of N, P, K, and NPE and KPE across three seasons. As the P addition increased to 135 kg ha−1, the grain yield achieved a maximum of 7168.4 kg ha−1, with an average NPE of 2.15 kg kg−1, PPE of 0.19 kg kg−1, and KPE of 1.49 kg kg−1. However, PPE continuously decreased with the input of phosphate. P application rates exceeding 135 kg ha−1 were not considered effective due to a decline in grain yield, nutrient uptake, and NPE. Furthermore, the effect of the planting season was significant on the total uptake of N and K, and the use efficiency of N, P, and K. TOPSIS revealed that a phosphate application rate of 90–135 kg ka−1 was the optimal pattern for maize production. These results may give a theoretical basis for the phosphate management of maize production in saline–alkali soil. [ABSTRACT FROM AUTHOR]

Precise regional crop yield estimates based on the high-spatiotemporal-resolution remote sensing data are essential for directing agronomic practices and policies to increase food security. This study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), the flexible spatiotemporal data fusion (FSADF), and the spatial and temporal non-local filter based fusion model (STNLFFM) to calculate the normalized differential vegetation index (NDVI) of the summer maize planting area in the Southeast Loess Plateau based on the Sentinel-2 and MODIS data. The spatiotemporal resolution was 10 m and 1 d, respectively. Then, we evaluated the adaptability of the ESTARFM, FSADF, and STNLFFM fusion models in the field from the perspectives of spatial and textural characteristics of the data, summer maize NDVI growing curves, and yield estimation accuracy through qualitative visual discrimination and quantitative statistical analysis. The results showed that the fusion of ESTARFM–NDVI, FSDAF–NDVI, and STNLFFM–NDVI could precisely represent the variation tendency and local mutation information of NDVI during the growth period of summer maize, compared with MODIS–NDVI. The correlation between STNLFFM–NDVI and Sentinel-2–NDVI was favorable, with large correlation coefficients and a small root mean square error (RMSE). In the NDVI growing curve simulation of summer maize, STNLFFM introduced overall weights based on non-local mean filtering, which could significantly improve the poor fusion results at seedling and maturity stages caused by the long gap period of the high-resolution data in ESTARFM. Moreover, the accuracy of yield estimation was as follows (from high to low): STNLFFM (R = 0.742, mean absolute percentage error (MAPE) = 6.22%), ESTARFM (R = 0.703, MAPE = 6.80%), and FSDAF (R = 0.644, MAPE = 10.52%). The FADSF fusion model was affected by the spatial heterogeneity in the semi-humid areas, and the yield simulation accuracy was low. In the semi-arid areas, the FADSF fusion model had the advantages of less input data and a faster response. [ABSTRACT FROM AUTHOR]

To investigate the impact of brackish water irrigation on the multidimensional root distribution and root-shoot characteristics of summer maize under different salt-tolerance-training modes, a micro-plot experiment was conducted from June to October in 2022 at the experimental station in Hohai University, China. Freshwater irrigation was used as the control (CK), and different concentrations of brackish water (S0: 0.08 g·L−1, S1: 2.0 g·L−1, S2: 4.0 g·L−1, S3: 6.0 g·L−1) were irrigated at six-leaf stage, ten-leaf stage, and tasseling stage, constituting different salt tolerance training modes, referred to as S0-2-3, S0-3-3, S1-2-3, S1-3-3, S2-2-3, and S2-3-3. The results showed that although their fine root length density (FRLD) increased, the S0-2-3 and S0-3-3 treatments reduced the limit of root extension in the horizontal direction, causing the roots to be mainly distributed near the plants. This resulted in decreased leaf area and biomass accumulation, ultimately leading to significant yield reduction. Additionally, the S2-2-3 and S2-3-3 treatments stimulated the adaptive mechanism of maize roots, resulting in boosted fine root growth to increase the FRLD and develop into deeper soil layers. However, due to the prolonged exposure to a high level of salinity, their roots below 30 cm depth senesced prematurely, leading to an inhibition in shoot growth and also resulting in yield reduction of 10.99% and 11.75%, compared to CK, respectively. Furthermore, the S1-2-3 and S1-3-3 treatments produced more reasonable distributions of FRLD, which did not boost fine root growth but established fewer weak areas (FLRD < 0.66 cm−3) in their root systems. Moreover, the S1-2-3 treatment contributed to increasing leaf development and biomass accumulation, compared to CK, whereas it allowed for minimizing yield reduction. Therefore, our study proposed the S1-2-3 treatment as the recommended training mode for summer maize while utilizing brackish water resources. [ABSTRACT FROM AUTHOR]

As an important food crop, summer maize is widely planted all over the world. Monitoring its growth and output is of great significance for world food security. With the trend of global warming and deterioration, the frequency of high temperature and heat damage affecting summer corn has been increasing in the past ten years. Therefore, there is an increasing demand for monitoring the high temperature and heat damage of summer maize. At present, there are nearly a hundred indices or methods for research on high temperature and heat damage. However, research based on the vegetation index cannot fully describe the damage caused by high-temperature thermal damage, and there is an obvious asynchrony effect. Research based on hyperspectral remote sensing has many inconveniences in data acquisition and complex physical model construction. Therefore, this study uses remote sensing data, including MODIS surface reflection data, MODIS land surface temperature products, as well as ground observation data and statistical data, combined with multiple remote sensing indices and land surface temperature, to construct a remote sensing index, LSHDI (land surface heat damage index). The LSHDI first searches for a location with the worst vegetation growth conditions in the three-dimensional feature space based on the LST (land surface temperature), the normalized difference vegetation index (NDVI), and the land surface water index (LSWI). Then, it calculates the distance between each point and this location to measure the degree of vegetation affected by high temperature and heat damage. Finally, because there is no reliable disaster verification dataset that has been published at present, this study uses soil moisture as a reference to explain the performance and stability of the LSHDI. The results showed that their coefficient of determination was above 0.5 and reached a significance level of 0.01. The LSHDI can well-reflect the high temperature and heat damage of land surface vegetation and can provide important data support and references for agricultural management departments. [ABSTRACT FROM AUTHOR]

Strategic management of nitrogen fertilizers can not only mitigate agricultural nitrogen pollution but also significantly enhance crop yield and nitrogen use efficiency. This study was designed to determine the optimal nitrogen fertilizer management strategy for the Yellow River irrigation area. Leveraging two years of field data related to soil water nitrogen and summer maize growth indices, parameters for the Root Zone Water Quality Model 2 (RZWQM2) were calibrated and validated. Subsequently, various scenarios were generated to simulate the impacts of different nitrogen application rates and basal chasing ratios on summer maize yield, nitrogen agronomic efficiency, nitrogen physiological efficiency, and nitrogen apparent recovery rate. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed for a comprehensive evaluation. RZWQM2 can effectively simulate the dynamic changes in soil moisture and nitrogen in the Yellow River irrigation area, and the results indicated that the mean relative error (MRE) between the simulated and observed values varied from 5.77% to 14.09%, and 4.36% to 33.01%, while the root mean square error (RMSE) ranged from 0.016 to 0.037 cm3/cm3, and 0.111 to 1.995 mg/kg. The normalized root mean square error (NRMSE) varied between 6.20% to 14.42% and 5.24% to 17.84%, respectively. The results validate the model's effectiveness in simulating summer maize yields and nitrogen metrics under varying nitrogen fertilizer management practices. A nitrogen application rate of 180–200 kg/hm2 (expressed in terms of pure nitrogen) in the Yellow River irrigation area could adequately meet the requirements for summer maize production. The recommended nitrogen fertilizer management strategy in the Yellow River irrigation area involves applying 200 kg/hm2 of nitrogen in a 1:2:1 ratio during the sowing, trumpeting, and anthesis stages. [ABSTRACT FROM AUTHOR]

Co-application of organic-chemical fertilizer (CAOFCF) has attracted wide attention in China in recent years. However, its short-term effect on topsoil quality and maize yield in a medium-productivity meadow-cinnamon soil is not clear. In order to address this problem, a 3-year (2019–2021) field trial was established by arranging the following five treatments: (1) CF, applying chemical fertilizer alone; (2) OFCF1, 15% organic fertilizer + 85% chemical fertilizer; (3) OFCF2, 30% organic fertilizer + 70% chemical fertilizer; (4) OFCF3, 45% organic fertilizer + 55% chemical fertilizer; (5) OFCF4, 60% organic fertilizer + 40% chemical fertilizer. The results showed that short-term CAOFCF treatments were beneficial to the topsoil aggregate stability by increasing the percentage and mean weight diameter of macro-aggregate in topsoil. In addition, lower soil bulk density and higher soil organic carbon sequestration in topsoil were observed under the CAOFCF treatments. There was no difference in rhizosphere microbial diversity among all treatments. Compared to CF, OFCF1 and OFCF2 improved the activities of some key enzymes, including sucrase, urease, and acid phosphatase. Moreover, higher relative abundance of Actinobacteria and Chloroflexi were observed under the CAOFCF treatments. The root-shoot dry matter and maize grain yield were obviously higher in OFCF1 and OFCF2 than in CF; however, no significant difference was found in the OFCF3 and OFCF4 treatments compared to CF. The analysis of correlation suggested that there were no direct correlations between maize yield and various soil indexes measured. Nevertheless, root dry weight and root-shoot ratio were positively correlated with the activities of urease and sucrase. Meanwhile, the relationships between root dry weight, root-shoot ratio, shoot dry weight, and grain yield were all significant. In conclusion, short-term co-application of organic and chemical fertilizer (i.e., replacing 15–30% chemical fertilizer with organic fertilizer with an equal N rate) was beneficial to soil properties and maize grain yield in a medium-productivity meadow-cinnamon soil. The higher grain yield was associated with a strong maize root system, which was driven by the improved rhizosphere urease and sucrase activities. [ABSTRACT FROM AUTHOR]

Rapid and accurate crop chlorophyll content estimation and the leaf area index (LAI) are both crucial for guiding field management and improving crop yields. This paper proposes an accurate monitoring method for LAI and soil plant analytical development (SPAD) values (which are closely related to leaf chlorophyll content; we use the SPAD instead of chlorophyll relative content) based on the fusion of ground–air multi-source data. Firstly, in 2020 and 2021, we collected unmanned aerial vehicle (UAV) multispectral data, ground hyperspectral data, UAV visible-light data, and environmental cumulative temperature data for multiple growth stages of summer maize, respectively. Secondly, the effective plant height (canopy height model (CHM)), effective accumulation temperature (growing degree days (GDD)), canopy vegetation index (mainly spectral vegetation index) and canopy hyperspectral features of maize were extracted, and sensitive features were screened by correlation analysis. Then, based on single-source and multi-source data, multiple linear regression (MLR), partial least-squares regression (PLSR) and random forest (RF) regression were used to construct LAI and SPAD inversion models. Finally, the distribution of LAI and SPAD prescription plots was generated and the trend for the two was analyzed. The results were as follows: (1) The correlations between the position of the hyperspectral red edge and the first-order differential value in the red edge with LAI and SPAD were all greater than 0.5. The correlation between the vegetation index, including a red and near-infrared band, with LAI and SPAD was above 0.75. The correlation between crop height and effective accumulated temperature with LAI and SPAD was above 0.7. (2) The inversion models based on multi-source data were more effective than the models made with single-source data. The RF model with multi-source data fusion achieved the highest accuracy of all models. In the testing set, the LAI and SPAD models' R2 was 0.9315 and 0.7767; the RMSE was 0.4895 and 2.8387. (3) The absolute error between the extraction result of each model prescription map and the measured value was small. The error between the predicted value and the measured value of the LAI prescription map generated by the RF model was less than 0.4895. The difference between the predicted value and the measured value of the SPAD prescription map was less than 2.8387. The LAI and SPAD of summer maize first increased and then decreased with the advancement of the growth period, which was in line with the actual growth conditions. The research results indicate that the proposed method could effectively monitor maize growth parameters and provide a scientific basis for summer maize field management. [ABSTRACT FROM AUTHOR]

In the North China Plain, the excessive application of nitrogen (N) fertilizer for ensuring high yield and a single application at sowing for simplifying management in farmer practice lead to low N use efficiency and environmental risk in maize (Zea mays L.) production. However, it is unclear whether and how late split application with a lower level of N fertilizer influences maize yield. To address this question, a two-year field experiment was conducted with two commercial maize cultivars (Zhengdan 958 and Denghai 605) using a lower level of N input (180 kg ha−1) by setting up single application at sowing and split application at sowing and later stages (V12, R1, and R2) with four different ratios, respectively. The maize yield with split-applied 180 kg ha−1 N did not decrease compared to the average yield with 240 kg ha−1 N input in farmer practice, while it increased by 6.7% to 11.5% in the four N split-application treatments compared with that of the single-application control. Morphological and physiological analyses demonstrated that late split application of N (i) increased the net photosynthetic rate and chlorophyll content and thus promoted the photosynthetic efficiency during the reproductive stages; (ii) promoted the sink capacity via improved kernel number, endosperm cells division, and grain-filling rate; and (iii) increased the final N content and N efficiency in the plant. Therefore, we propose that late split application of N could reduce N fertilizer input and coordinately improve N efficiency and grain yield in summer maize production, which are likely achieved by optimizing the source–sink relations during the grain-filling stage. [ABSTRACT FROM AUTHOR]

In the production of summer maize, the problems of excessive fertilizer input and low fertilizer utilization rate are common, resulting in the waste of resources and environmental pollution. In order to explore the optimal fertilization mode of summer maize, a field experiment with eight treatments was designed in which sowing and fertilization were carried out by different machines. The effects of the two fertilization methods, i.e., hole fertilization and strip fertilization; two fertilization positions, i.e., side-position fertilization and positive-position fertilization; and two fertilization depths, i.e., 10 cm and 15 cm, on the summer maize yield, plant nitrogen, phosphorus, and potassium nutrient accumulation, and aboveground biomass were studied. The results show that different fertilization modes had significant effects on summer maize yield, nitrogen, phosphorus, and potassium nutrient accumulation, and aboveground biomass. In general, when the strip fertilization method was used, 15 cm deep positive-position fertilization was superior. When the hole fertilization method was used, 15 cm deep side-position fertilization was superior. [ABSTRACT FROM AUTHOR]

The assessment of crop water productivity (CWP) is of practical significance for improving regional agricultural water use efficiency and water conservation levels. The remote sensing method is a common method for estimating large scale CWP, and the assessment errors in CWP by remote sensing originate mainly from remote sensing inversion errors in crop yield and evapotranspiration (ET). The phenological period is the important factor in crop ET and yield estimation. The crop coefficient (Kc) and harvest index (HI), which are closely related to different phenological periods, are considered during the processes of crop ET and yield estimation. The crop phenological period is detected from enhanced vegetation index (EVI) curves using Moderate Resolution Imaging Spectroradiometer (MODIS) data and Sentinel-2 data. The crop ET is estimated using the surface–energy balance algorithm for land (SEBAL) model and Penman‒Monteith (P-M) equation, and the crop yield is estimated using the dry matter mass–harvest index method. The CWP is calculated as the ratio of the crop yield to ET during the growing season. The results show that the daily ET and crop yield estimated from remote sensing images are consistent with the measured values. It is found from the variation in daily ET that the peaks appear at the heading period of wheat and maize, which are in good agreement with the rainfall and growth characteristics of the crop. The relationship between crop yield and ET shows a negative parabolic correlation, and that between CWP and crop yield shows a linear correlation. The average CWPs of wheat and maize are 1.60 kg/m3 and 1.39 kg/m3, respectively. The results indicate that the phenology-based remote sensing inversion method has a good effect on the assessment of CWP in Lixin County. [ABSTRACT FROM AUTHOR]

Spring wheat–summer maize (SWSM) annual crop systems were formed to satisfy the maize grain mechanized harvest thermal requirement in the thermal–resource–limited region of the North China Plain. However, the nitrogen (N) application rate effect on SWSM annual yield formation, N accumulation and utilization were barely evaluated. Two–year field experiments were conducted to evaluate the effects of the N application rate on the annual yield of SWSM, observe N accumulation and utilization, and identify the optimized N application. The experiments were conducted under 5 N levels of 0 (N0), 180 (N180), 240 (N240), 300 (N300), and 360 (N360) kg ha−1. The results showed that spring wheat, summer maize and annual cereal yield under the N240 and N480 treatments obtained the highest grain yield (GY) of 5038, 1282 and 16,320 kg ha−1, respectively, and the optimal N application rate was estimated using a linear–plateau model to be 231–307, 222–337 and 463–571 kg ha−1 with maximum GY of 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1, respectively. With the increase in the N application rate, the dry matter accumulation (DM) were significantly increased by 16.9–173.5% for spring wheat and 11.1≈–76.8% for summer maize, respectively; and the annual cereal DM was 15.1–179.7% greater than that with N0 treatment, respectively. Spring wheat, summer maize and the annual cereal total N accumulation (TN) under N360 and N720 treatments were significantly increased by 5.4–19.1%, 16.6–32.3% and 11.5–26.2%, respectively, compared to the other treatments; however, N use efficiency for biomass and grain production (NUEbms and NUEg) were decreased significantly by 10.9–13.6% and 8.9–20.7%, 6.8–13.8% and 12.2–15.6%, and 5.5–11.7% and 10.0–16.0%, respectively. Meanwhile, the N partial factor productivity (PFPN), N agronomy use efficiency (ANUE), N recovery efficiency (NRE) and N uptake efficiency (NEupk) under the N240 treatment for spring wheat and summer maize obtained high levels of 20.99 and 47.01 kg−1, 9.27 and 16.35 kg−1, 32.53% and 32.44%, and 0.85 and 0.72 kg−1, respectively. Correlation analysis showed that the N application rate, TN and NEupk played significantly positive roles on GY, spring wheat spilke grain number, summer maize ear grain number and 1000–grain weight, DM LAImax and SPADmax, while NUEbms, NUEg, PFPN and ANUE always played negative effects. These results demonstrate that spring wheat, summer maize and annual cereal obtained the highest GY being 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1 with the optimal N application rate 231–307, 222–337 and 463–571 kg ha−1, respectively, which provide N application guidance to farmer for spring wheat–summer maize crop systems to achieve annual mechanical harvesting in the thermal–resource–limited region of the North China Plain. [ABSTRACT FROM AUTHOR]

Leaf area index and dry matter mass are important indicators for crop growth and yields. In order to solve the problem of predicting the summer maize growth index and yield under different soil quality and field management conditions, this study proposes a prediction model based on the supervised machine learning regression algorithm. Firstly, the data pool was constructed by collecting the measured data for maize in the main planting area. The total water input (rainfall plus irrigation water), fertilization, soil quality, and planting density were selected as the training set. Then, the maximum leaf area index (LAImax), maximum dry material mass (Dmax), and summer maize yields (Y) in the data pool were trained by using Gaussian regression (rational quadratic kernel function and Matern kernel function), support vector machine (SVM) and linear regression models. The training models were verified with the data-set not included in the data pool, and the water and fertilizer coupling functions were developed. The prediction results showed that compared to the support vector machine models and the linear regression models, the Gaussian regression prediction models comprising the rational quadratic and Matern kernel functions had good prediction accuracy. The coefficients of determination (R2) of the prediction results were 0.91, 0.89 and 0.88; the root-mean-square errors (RMSEs) were 0.3, 1138.6 and 666.16 kg/hm2; and the relative root-mean-square errors (rRMSEs) were 6.3%, 5.94% and 6.53% for LAImax, Dmax and Y, respectively. The optimal total water inputs and nitrogen applications indicated by the prediction results and the water and fertilizer coupling functions were consistent with the measured range from the field tests. The supervised machine learning regression algorithm provides a simple method to predict the yield of maize and optimize the total water inputs and nitrogen applications using only the soil quality and planting density. [ABSTRACT FROM AUTHOR]

Water scarcity is the most significant constraint for grain production in the North China Plain (NCP). Water-saving irrigation technology is a valuable tool for addressing the NCP's water scarcity. Drip irrigation is considered as one of the most water-saving irrigation technologies. However, drip irrigation is not now commonly used in NCP field grain crops (particularly maize). Fertilizers are accurately administered to summer-maize root soil by recycling the drip-irrigation system of winter wheat. To increase the water and fertilizer-use efficiency of summer-maize fields, the coupling body of root-zone soil water and fertilizer for summer maize was thoroughly adjusted using a combination of emitter flow rate, irrigation quota, and fertilizer frequency. In this experiment, a split plot design with randomized blocks was employed. The primary plot was emitter flow rate (0.8 and 2.7 L/h), the subplot was irrigation water quota (120 and 150 m3/hm2, 1 hm2 = 10,000 m2), and the final plot was fertigation frequency (7, 14, and 28 days). The grain yield, water-use efficiency and fertilizer-use efficiency of summer maize were measured in this study. The results showed that grain yield and water-use efficiency (WUE) of the small-flow drip-irrigation treatment (emitter flow rate < 1 L/h) were significantly higher than the large-flow treatment (emitter flow rate > 1 L/h); the rates of grain yield increase were 8.2% and 13.3% and WUE were 3.5% and 8.0%, respectively. A higher irrigation quota can increase the yield of summer maize. The maximum yield and WUE were observed at the fertigation frequency of 7 days under small-flow drip-irrigation conditions. All comparisons and analyses showed that small-flow drip irrigation combined with high fertigation frequency could obtain higher yield and WUE in the NCP. This study proposes a new way to improve water and fertilizer utilization efficiency to achieve the goal of "increasing grain yield by fertilizing" and "adjusting the quality by fertilizing", from the perspective of winter wheat–summer maize no-tillage annual rotation planting. [ABSTRACT FROM AUTHOR]

Non-destructive acquisition and accurate real-time assessment of nitrogen (N) nutritional status are crucial for nitrogen management and yield prediction in maize production. The objective of this study was to develop a method for estimating the nitrogen nutrient index (NNI) of maize using in situ leaf spectroscopy. Field trials with six nitrogen fertilizer levels (0, 75, 150, 225, 300, and 375 kg N ha−1) were performed using eight summer maize cultivars. The leaf reflectance spectrum was acquired at different growth stages, with simultaneous measurements of leaf nitrogen content (LNC) and leaf dry matter (LDW). The competitive adaptive reweighted sampling (CARS) algorithm was used to screen the raw spectrum's effective bands related to the NNI during the maize critical growth period (from the 12th fully expanded leaf stage to the milk ripening stage). Three machine learning methods—partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM)—were used to validate the NNI estimation model. These methods indicated that the NNI first increased and then decreased (from the 12th fully expanded leaf stage to the milk ripening stage) and was positively correlated with nitrogen application. The results showed that combining effective bands and PLS (CARS-PLS) achieved the best model for NNI estimation, which yielded the highest coefficient of determination (R2val), 0.925, and the lowest root mean square error (RMSEval), 0.068, followed by the CARS-SVM model (R2val, 0.895; RMSEval, 0.081), and the CARS-ANN model (R2val, 0.814; RMSEval, 0.108), which performed the worst. The CARS-PLS model was used to successfully predict the variation in the NNI among cultivars and different growth stages. The estimated R2 of eight cultivars by the NNI was between 0.86 and 0.97; the estimated R2 of the NNI at different growth stages was between 0.92 and 0.94. The overall results indicated that the CARS-PLS allows for rapid, accurate, and non-destructive estimation of the NNI during maize growth, providing an efficient tool for accurately monitoring nitrogen nutrition. [ABSTRACT FROM AUTHOR]

Increasing planting density is an effective way to improve maize yield, but high plant populations often cause a lodging problem. This experiment was conducted to investigate the effect of increasing planting density on stalk lodging resistance and grain yield, and to explore the effects on stalk and yield properties of spraying ethephon in densely planted summer maize. The summer maize hybrid, Xundan20 (XD20), was used as experimental material. It was grown by spraying water (CK) or ethephon (E) at BBCH (BASF, Bayer, Ciba-Geigy and Hoechst) 17 under three different planting densities of 60,000 plants ha−1 (L), 75,000 plants ha−1 (M) and 90,000 plants ha−1 (H) in order to explore the possibility of synergistic improvement in stalk lodging resistance and grain yield. The results from this experiment suggested that the gravity center height of densely planted summer maize was significantly increased, the stem diameter, area and number of vascular bundles were significantly decreased and the dry weight per unit internode was significantly decreased, thereby weakening the stalk rind penetration strength and bending performance, resulting in a significant increase in lodging percentage. The ear height was significantly decreased and the SPAD (soil and plant analysis development) and canopy light transmittance were increased after spraying ethephon; then, the internode dry weight per unit length was increased and the stalk rind penetration strength and bending performance were enhanced so as to significantly reduce the lodging percentage and increase the grain yield. The correlation analysis further showed that lodging percentage was significantly negatively correlated with stem diameter, area and number of vascular bundles and stalk bending performance, but there were no strong relationships with grain yield. This suggested that the synergistic improvement in stalk lodging resistance and grain yield was not contradictory. Under the experiment conditions, the effect of spraying ethephon was most significant when the planting density was 90,000 plants ha−1. At the time, the lodging percentage and grain yield were 12.2% and 11,137.5 kg ha−1, which were decreased by 44.6% and increased by 8.0% compared with the control treatment. Scientific chemical regulation could significantly improve the stalk lodging resistance and grain yield of densely planted summer maize. [ABSTRACT FROM AUTHOR]

In order to explore the effects of nitrapyrin (N-Serve) application on greenhouse gas emission and nitrogen (N) leaching of a waterlogged maize (Zea mays L.) field, we investigated the effects of applying nitrapyrin on soil ammonium (NH4+-N) and nitrate nitrogen (NO3−-N) content, nitrous oxide (N2O) fluxes, and the warming potential (GWPN2O) in a waterlogged maize field. The design included three treatments: waterlogging treatment with only urea application (V-3WL), waterlogging treatment with urea and nitrapyrin application (V-3WL+N), and no waterlogging treatment applying only urea (CK). Our results revealed that waterlogging led to the increase of nitrate concentrations across the soil profile, thus potentially increasing N leaching and decreasing N use efficiency. The accumulated N2O emissions increased significantly in waterlogged plots compared to control plots, and maximum N2O emission fluxes occurred during the process of soil drying after waterlogging; this resulted in an increase in GWPN2O and N2O greenhouse gas intensity (GHGIN2O) by 299% and 504%, respectively, compared to those of CK. However, nitrapyrin application was able to reduce N2O emissions. Nitrapyrin application was also good for decreasing GWPN2O and GHGIN2O by 34% and 50%, respectively, compared to V-3WL. In addition, nitrapyrin application was conducive to reduce N leaching and improve N use efficiency, resulting in a yield increase by 34%, compared to that of V-3WL. The application of nitrapyrin helped to mitigate agriculture-source greenhouse effects and N leaching induced by waterlogging, and was a high N-efficient fertilizer method for a waterlogged field. [ABSTRACT FROM AUTHOR]

Mulches combined with drip irrigation techniques have been widely applied in China for higher yield and water use efficiency (WUE). To develop an efficient strategy that can improve maize yield and save water in the North China Plain (NCP), we conducted a two-year field experiment, using transparent plastic film mulching (T), black plastic film mulching (B), and straw mulching (S) and non-mulching (N) for spring maize in 2019 and summer maize in 2020, and high drip irrigation amount (H) and low drip irrigation amount (L) were also considered in 2019. We mainly studied the effects of mulches on soil water content, soil temperature, crop growth rate, grain yield, and water use efficiency (WUE). The results indicated that T and B treatment increased soil water content (SWC) and topsoil temperature. The T treatment promoted the growth rate significantly more than N treatment, by 27.7–43.4% at the early stage in two years. The grain yield under TH treatment was significantly (p < 0.05) higher than that of other treatments, by 9.8–17.4% for spring maize in 2019, and significantly (p < 0.05) higher under both TH and BH than under NH, by 8.9% and 4.7% for summer maize in 2020. There was a significant quadratic parabola relationship between ET and grain yield in 2019, and the correlation between SEAT of 0–10 cm soil depth with grain yield or with biomass was positive. These results indicate that the transparent plastic film with high drip irrigation amount treatment (TH) can be recommended for spring maize, and both transparent and black film mulch treatments (TH and BH) can be recommended for summer maize in the NCP. [ABSTRACT FROM AUTHOR]

Global warming increases the risk of high-temperature injury to maize. Inter- and mixed-cropping of maize varieties with different genotypes is one way to effectively alleviate the high-temperature injury during the flowering period. However, the mitigation effect of different varieties and intercropping modes on high-temperature injury is still unclear. Based on previous years of field production, Denghai 605, which is more sensitive to high temperatures during the flowering period, was determined as the main test variety, and Zhengdan 958, Dedan 5, Weike 702, and Xianyu 335, which have great genotypic differences, were used as auxiliary varieties. The main test varieties and auxiliary varieties were intercropped and mixed cropped, respectively. Plant height, ear height, leaf area index, population light transmittance, ear characteristics, and yield were measured, and the land equivalent ratio (LER) was calculated. The plant height of Denghai 605 intercropped with Zhengdan 958 and Dedan 5 and mixed with Weike 702 and Xianyu 335 decreased significantly. The population light transmittance of the bottom or middle layer in Denghai 605 increased significantly when intercropped with other varieties. The grain number per ear increased significantly under inter- and mixed cropping with Zhengdan 958 and Weike 702. Except under intercropping with Dedan 5, the yield of Denghai 605 increased significantly, by 8.8–28.0%, under inter- and mixed cropping. Under intercropping with Zhengdan 958 and inter- and mixed cropping with Weike 702 and Xianyu 335, respectively, the group land equivalent ratio was greater than 1.1, indicating that under the combination of these varieties, inter- and mixed cropping effectively reduced the impact of high temperatures during flowering. [ABSTRACT FROM AUTHOR]

Summer maize crop development, yield, and water use characteristics under water deficit conditions at different growth stages were investigated in this study using different irrigation regime treatments at the seedling (S), jointing (J), tasseling (T), and grain filling stages (F) in 2018 and 2019 in China. Ten different irrigation treatments were set, including three-irrigation application intervals (JTFi, STFi, SJFi, SJTi), two-irrigation applications (STi, JTi, JFi), and single-irrigation applications (Ti, Ji). These were compared to the control treatment (CK), which had sufficient irrigation provided at four intervals (SJTFi). The results showed that compared to CK, a water deficit at the seedling and jointing stages had a greater effect on plant height, whereas a water deficit at the tasseling and filling stages had a greater effect on the leaf area index, and a continuous water deficit had an effect on the stem diameter of summer maize. Limitations in terms of the growth and development of summer maize increased with less frequent irrigation. As irrigation decreased, the grain yield decreased, and the water use efficiency increased, and a water deficit at the tasseling stage had the greatest effect on the yield and water use efficiency. The JTFi treatment was the optimal irrigation regime with a yield decline, and its water consumption was reduced by 16.9% (p < 0.05) on average. However, compared to CK, the water use efficiency of the JTFi treatment increased by 17.3% (p < 0.05). Moreover, the JTFi treatment had the smallest maize yield response factor value (Ky) of 0.16, and its comprehensive score was the second highest after CK. [ABSTRACT FROM AUTHOR]

Humic acid plays an important role in improving grain yield and reducing N losses. In order to explore the effects of humic acid added to controlled-release fertilizer on summer maize yield, nitrogen use efficiency (NUE) and the characteristics of greenhouse gas (GHG) emissions in maize farmland soil, a two-year field experiment was set up. The treatments consisted of two fertilizers: 3% humic acid added to controlled-release fertilizer (HACRF), controlled-release fertilizer (CRF) and a control (without N fertilizer, N0). The results demonstrate that the yield and NUE of summer maize were significantly increased with the addition of humic acid in N fertilizer. Compared with N0 and CRF, the yield of maize was increased by 99.1% and 5.0%, respectively. Compared with CRF, the contents of soil ammonium–nitrogen (NH4+-N) and nitrate–nitrogen (NO3−-N) in HACRF were higher during early maize growth stage but lower during the late grain-filling stage. The NUE and soil nitrogen interdependent rate of HACRF were significantly increased by 4.6–5.4% and 7.2–11.6%, respectively, across the years compared with those of CRF. Moreover, the annual cumulative N2O emissions in HACRF were decreased by 29.0% compared with the CRF. Thus, the global warming potential and greenhouse emission intensity of HACRF were significantly decreased by 29.1% and 32.59%, respectively, compared with CRF. In conclusion, adding humic acid to controlled-release fertilizer can result in higher yield and nitrogen uptake, improve nitrogen use efficiency and reduce greenhouse gas emissions, which have better yield and environmental effects. [ABSTRACT FROM AUTHOR]

Crop phenology is a significant factor that affects the precision of crop area extraction by using the multi-temporal vegetation indices (VIs) approach. Considering the phenological differences of maize among the different regions, the summer maize cultivated area was estimated by using enhanced vegetation index (EVI) time series images from the Moderate Resolution Imaging Spectroradiometer (MODIS) over the Huanghuaihai Plain in China. By analyzing the temporal shift in summer maize calendars, linear regression equations for simulating the summer maize phenology were obtained. The simulated maize phenology was used to correct the MODIS EVI time series curve of summer maize. Combining the mean absolute distance (MAD) and p-tile algorithm, the cultivated areas of summer maize were distinguished over the Hunaghuaihai Plain. The accuracy of the extraction results in each province was above 85%. Comparing the maize area of two groups from MODIS-estimated and statistical data, the validation results showed that the R2 reached 0.81 at the city level and 0.69 at the county level. It demonstrated that the approach in this study has the ability to effectively map the summer maize area over a large scale and provides a novel idea for estimating the planting area of other crops. [ABSTRACT FROM AUTHOR]

This study evaluates the performance of structural, chlorophyll-based, and photochemical indices to detect maize water status and to assess production based on five years of field experiments (2013–2017) during the primary growth stages. We employed three categories of indicators, including water condition and productive and thermal indicators, to quantify the responses of summer maize under continuous water stress from drought to waterlogging conditions. Furthermore, we adopted several spectral indices to assess their sensitivity to three categories of metrics. The results showed the association is the best between the treatment level and Leaf Water Content (LWC). The waterlogging treatment influenced Leaf Water Potential (LWP) in moderate drought stress. Severe drought stress caused the strongest reduction in productivity from both Leaf Area Index (LAI) and chlorophyll content. In terms of sensitivity of various indices, red-edge-position (REP) was sensitive to maize water conditions LWP, LAI and chlorophyll content. Photochemical Reflectance Index (PRI) and Normalized Difference Vegetation Index (NDVI) were the most and second most sensitive indices to productive indicators, respectively. The results also showed that no indices were capable of capturing the information of Crop Water Stress Index (CWSI). [ABSTRACT FROM AUTHOR]

The summer maize yields and partial factor productivity of nitrogen (N) fertilizer (PFPN, grain yield per unit N fertilizer) on smallholder farms in China are low, and differ between farms due to complex, sub-optimal management practices. We collected data on management practices and yields from smallholder farms in three major summer maize-producing sites—Laoling, Quzhou and Xushui—in the North China Plain (NCP) for two growing seasons, during 2015–2016. Boundary line analysis and a Proc Mixed Model were used to evaluate the contribution of individual factors and their interactions. Summer maize grain yields and PFPN ranged from 6.6 t ha−1 to 14.2 t ha−1 and 15.4 kg kg−1 to 96.1 kg kg−1, respectively, and averaged 10.5 t ha−1 and 49.1 kg kg−1, respectively. The mean total yield gap and PFPN gap were 3.6 t ha−1 and 43.3 kg kg−1 in Laoling, 2.2 t ha−1 and 24.5 kg kg−1 in Xushui, and 2.8 t ha−1 and 41.1 kg kg−1 in Quzhou. A positive correlation was observed between the yield gap and PFPN gap; the PFPN gap could be reduced by 6.0 kg kg−1 (3.6–6.6 kg kg−1) by reducing the yield gap by 1 t ha−1. The high yield and high PFPN (HH) fields had a higher plant density and lower N fertilization rate than the low yield and low PFPN (LL) fields. Our results show that multiple management factors caused the yield gap, but the relative contribution of plant density is slightly higher than that of other management practices, such as N input, the sowing date, and potassium fertilizer input. The low PFPN was mainly attributed to an over-application of N fertilizer. To enhance the sustainable production of summer maize, the production gaps should be tackled through programs that guide smallholder farmers on the adoption of optimal management practices. [ABSTRACT FROM AUTHOR]

Climate change has and will continue to exert significant effects on social economy, natural environment, and human life. Research on the climatic suitability of crops is critical for mitigating and adapting to the negative impacts of climate change on crop production. In the study, we developed the climate suitability model of maize and investigated the climate suitability of summer maize during the base period (1981–2010) and two future periods of 2031–2060 (2040s) and 2071–2100 (2080s) in the North China Plain (NCP) based on BCC-CSM2-MR model (BCC) from the Coupled Model Comparison Program (CMIP6) under two Shared Socioeconomic Pathways (SSP) 245 and SSP585. The phenological shift of maize under future climate scenarios was simulated by the Agricultural Production Systems Simulator (APSIM). The results showed that the root mean square errors (RMSE) between observations and projections for sunshine suitability (SS), temperature suitability (ST), precipitation suitability (SP), and integrated climate suitability (SZ) during the whole growth period were 0.069, 0.072, 0.057, and 0.040, respectively. Overall, the BCC projections for climate suitability were in suitable consistency with the observations in the NCP. During 1981–2010, the SP, ST, and SZ were high in the north of the NCP and low in the south. The SP, ST, and SZ showed a downward trend under all the future climate scenarios in most areas of NCP while the SS increased. Therein, the change range of SP and SS was 0–0.1 under all the future climate scenarios. The ST declined by 0.1–0.2 in the future except for the decrease of more than 0.3 under the SSP585 scenario in the 2080s. The decrease in SZ in the 2040s and 2080s under both SSP scenarios varied from 0 to 0.2. Moreover, the optimum area decreases greatly under future scenarios while the suitable area increases significantly. Adjusting sowing data (SD) would have essential impacts on climate suitability. To some extent, delaying SD was beneficial to improve the climate suitability of summer maize in the NCP, especially under the SSP585 scenario in the 2080s. Our findings can not only provide data support for summer maize production to adapt to climate change but also help to propose agricultural management measures to cope with future climate change. [ABSTRACT FROM AUTHOR]

The intensive use of groundwater and nitrogen fertilizer has led to serious negative impacts on the environment of the North China Plain (NCP). Water footprint is an emerging approach to assess the consumptive water use and the environmental impacts on winter wheat-summer maize systems. A seven-year rotation experiment was conducted to collect data on wheat and maize growth response to nitrogen rates and irrigation schedules and to explore how the water footprint was affected, using DSSAT 4.6 Wheat and Maize crop models. Results showed that the increase in farm inputs contributed greatly to the increase in water footprint, primarily through the grey water footprint. The water footprints of maize and wheat were more sensitive to the nitrogen rate and irrigation, respectively. An irrigation of 160 mm produced a minimum total water footprint and higher yield for wheat. The grey water footprint of maize increased linearly when the nitrogen rate applied to maize exceeded 60 kg ha−1. Water-saving irrigation with 300 kg ha−1 of nitrogen can maintain a higher grain yield and have little impact on the environment. The approach used and the results can help to develop management strategies to maintain high yields while minimizing the water footprint in NCP. [ABSTRACT FROM AUTHOR]

Stalk lodging in Huang-Huai-Hai summer maize is a serious problem that reduces maize yields and precludes the use of mechanical grain harvesting equipment. In order to determine the effect of nitrogen management on the lodging resistance of maize stalk, three nitrogen application rates of 150, 250, and 350 kg ha−1 (denoted as N150, N250, and N350), and different nitrogen application periods (sowing, 6-leaf, 12-leaf, silking) were set. Plant morphology, stalk mechanical strength, total carbohydrate, nitrogen content, and yield were measured in the different treatments. The results showed that as the nitrogen application rate increased and nitrogen application was postponed, the stalk breaking force, plant height, ear height, center of gravity height, stalk basal internode diameter, rind penetration strength, content of carbohydrate, and total N of maize stalk also increased. The stalk lodging resistance was improved by the increased nitrogen application rate and postponed nitrogen application by increasing the stalk material accumulation and mechanical strength. The nitrogen application rates had no significant effect on grain yield. Under N250 and N350, the treatments with no base fertilizer significantly decreased the kernel number per ear, reflected in some in grain yield. In summary, under the conditions of integrated water and fertilizer drip irrigation and fractional nitrogen fertilizer applications, increased nitrogen fertilizer input can stimulate the growth of high-quality maize populations, significantly improve stalk lodging resistance in the early growth stage, delay stalk senescence, improve stalk strength and influence stalk composition in later growth stages. Based on the summer maize grain yield and stalk lodging resistance, under N250 treatment, a base fertilizer combined with topdressing at the 12-leaf and silking stages was beneficial to the growth of summer maize. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Increasing planting density is an important ways to increase maize yield. A hot topic of conversation in the current research is how to improve crop light efficiency and yield potential by optimizing the cultivation mode under high density planting is a hot topic in current research. Thus, in this study, a field experiment was conducted to explore the effects of stereo-planting patterns on water and the utilization light resource and maize yields. Planting patterns included the conventional flat planting pattern (as the control, CK) and the stereo-planting in ridge and furrow (T). Each planting pattern had three planting densities, i.e., 60,000 plants ha−1 (D1), 75,000 plants ha−1 (D2) and 90,000 plants ha−1 (D3). The results showed that stereo-planting affected the physiological characteristics of plants by changing the spatial distribution of soil moisture. At the silking stage (R1), photosynthetic rate (Pn) of plants on the ridge was similar to CK, and transpiration rate (Tr) was significantly lower than that of CK. Pn of maize in the furrow was significantly higher than that of CK, and Tr was similar to CK. Stereoscopic planting had different effects on intraspecific competition intensity in maize population in different growing stages. In the six-leaf stage (V6), stereo-planting increased competition intensity of maize on the ridge, but lowered that of maize in the furrow by affecting the spatial distribution of soil moisture. During the R1 stage, stereo-planting increased the light transmittance rate within the canopy and eased the plant's competition for light by reducing plant height and leaf area of maize under three density conditions. Stereo-planting had no effect on grain yield and dry matter accumulation of ridge-planted maize in the later growing stage, but it did increased the dry matter accumulation and grain yield of furrow-planted maize due to the improvement of the light environment and photosynthetic characteristics of the population. In two test years, stereo-planting increased 5.0–11.0% average yield of maize compared to CK under three density conditions. These results indicate that stereo-planting can reduce the plant's competition for light and water resources and improve its physiological traits of plant by optimizing its spatial distribution of soil moisture and canopy structure, thus further increasing grain yield of maize under high-density planting conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The scale effect problem is one of the most challenging issues in remote sensing studies. However, the research on the methodology and theory of the scale effect is scarcely applied in practice. To this end, in this study, 3 years of field experimental data of continuous water stresses on summer maize were used for this purpose. Furthermore, the Prospect and Sail models were employed to investigate the scale effects of reflectance characteristics and vegetation indexes. The results indicated that the spectral characteristics of canopy and leaf of summer maize were similar under continuous water stresses at various stages. The reflectance at the canopy level was distinct from that at the leaf level, considering the soil background differences. From leaf to canopy scales, with the increase in the leaf area index (LAI), the spectral reflectance of all treatments in the visible band decreased, but increased in the near-infrared band, and the reflectance was saturated when LAI increased to 5. The reflectance difference caused by LAI variation was enlarged as the drought stress intensified in the short-wave infrared band. The spectral reflectance in the near-infrared band was susceptible to leaf inclination angle (LIA) variation and changed significantly, especially in the closed canopy. With the increase in LAI, the difference vegetation index (DVI) and normalized difference vegetation index (NDVI) values under each treatment showed a gradually increasing trend. With the increase in LIA, the DVI value decreased gradually, and the DVI value under the saturated canopy was significantly higher than that under the unclosed canopy. However, the NDVI values of all treatments did not change with LIA, mostly under the closed canopy. Overall, the results demonstrated that LAI had a more significant influence on canopy reflectance than LIA. In addition, NDVI was not able to capture the LAI and LIA information when the canopy was closed, but DVI performed better. [ABSTRACT FROM AUTHOR]

Soil evaporation (Es) and crop transpiration (Tc) are important components of water balance in cropping systems. Comparing the accurate calculation by crop models of Es and Tc to the measured evaporation and transpiration has significant advances to the optimal configuration of water resource and evaluation of the accuracy of crop models in estimating water consumption. To evaluate the adaptation of APSIM (Agricultural Production Systems simulator) in calculating the Es and Tc in Nanjing, APSIM model parameters, including the meteorological and soil parameters, were measured from a two-year field experiment. The results showed that: (1) The simulated evaporation was basically consistent with the measured Es, and the regulated model can effectively present the field evaporation in the whole maize growth period (R2 = 0.85, D = 0.96, p < 0.001); and (2) The trend of the simulated Tc can present the actual Tc variation, but the accuracy was not as high as the evaporation (R2 = 0.74, D = 0.87, p < 0.001), therefore, the simulation of water balance process by APSIM will be helpful in calculating Es and Tc in a humid area of Nanjing, and its application also could predict the production of maize fields in Nanjing. [ABSTRACT FROM AUTHOR]

Supplying adequate nitrogen (N) to meet crop demand is critical for enhancing agricultural sustainability. Not only fertilizer N, but also N from other available sources should be considered in N supply capacity. We conducted a 10-year farming experiment using a split-plot design with two different main fertilizer management approaches and three N application strategies as add-on sub-treatments. Based on the experiment, we estimated the total N supply (TNsupply) for the summer maize cropping system, through considering environmental, soil, crop residue, and fertilizer N sources. An appropriate TNsupply was established by correlating TNsupply with the relative yield (RY), N input and output, and N use efficiency (NUE). The results revealed a wide variation in TNsupply (from 88 to 755 kg ha−1). The RY, N input, and N output fitted well to TNsupply using linear-plateau, linear, and linear-plateau models, respectively. The lower limits of TNsupply for achieving the maximum RY and N output were 361 and 358 kg ha−1, respectively. The relationship between N input and N output was described as linear-plateau. We determined the slope of the linear curve (55.4%) as the lower limit of NUE, beyond which the upper limit of TNsupply was determined to be less than 497 kg ha−1. Thus, appropriate TNsupply values ranged from 325 to 497 kg ha−1 for summer maize production, which could ensure enough N supply for higher yields and avoid excessive N input for higher NUE and lower environmental N loss. Our findings highlight that TNsupply can be an alternative indicator for evaluating N management. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the effect of sowing methods and deficit irrigation on weed dynamics, yield and water-use efficiency (WUE) of the maize–cowpea system during the summer and monsoon seasons, respectively. The field experiment was carried out for two years (2015 and 2016) using a split design with three replicates under irrigated (maize) and rainfed (cowpea) conditions on vertisols of a semi-arid region. Treatments included three sowing methods [i.e., broad bed and furrow (BBF), corrugated furrow (CF) and ridges and furrow (RF)] and four irrigation levels [i.e., irrigation once in 10 days (I10D), irrigation at 40% (I40), at 50% (I50) and at 60% (I60) depletion]. The results indicated that, regardless of weed flora (monocots, dicots and sedges), the RF method produced higher weed density (2.09–2.98 No. m−2) compared to CF (2.00–2.80 No. m−2) and BBF (1.85–2.64 No. m−2) in maize at 30 and 60 days after sowing (DAS). The RF method with irrigation at I40 and I50 recorded significantly higher weed density, followed by the CF and BBF method. A similar trend was also observed with dry weight of weeds (monocot; 24.19%, dicot; 25.52%, and sedges; 29.80%) in maize at 30 and 60 DAS. Higher weed density and dry weight of weeds in the RF method with I40 was due to higher soil moisture availability and higher nutrient uptake due to larger lateral wetting of the soil and greater water use (29.27%). However, the BBF method favoured the growth of weeds (9.33–16.60%) in cowpea at 55 DAS and coped under rain-fed situation over CF and RF. The CF with moderate depletion (I50) method produced significantly higher maize equivalent yield (MEY) of cowpea (10,000 kg ha−1) with considerable reduction in the total water usage (19.33%). Therefore, under a water scarcity situation, growers can practice CF and I50 for higher yield and WUE of maize–cowpea sequence cropping. [ABSTRACT FROM AUTHOR]

The predicted increase in the frequency of extreme climatic events in the future may have a negative effect on cereal production, but our understanding of the historical trends of high-temperature events associated with climate change and their long-term impact on summer maize yield is limited. Based on an analysis of historical climate and summer maize yield data from 1980 to 2016 in the Huang-Huai-Hai (3H) region of China, we calculated two high-temperature event indices, namely, high-temperature hours (HTH) and high-temperature degrees (HTD, the sum of the differences between 35 °C and above), and then investigated the temporal trend of high-temperature events from maize heading to maturity and their impact on the yield of summer maize. Our results indicated that the air temperature showed a significant upward trend when heading into the maturity period of summer maize in the 3H region from 1980–2016 and that the increase was greater in the northern Huang-Huai-Hai (N3H) region than in the southern Huang-Huai-Hai (S3H) region. The intensity of high-temperature events when heading into the maturity period increased considerably from 1980 to 2016 in the 3H region, especially in the S3H region. The HTH and HTD increased by 1.30 h and 0.80 °C per decade in the S3H region, respectively. Moreover, a sensitivity analysis of panel data showed that the increases in HTH and HTD when heading into the maturity period had a consistent negative effect on yield in S3H and N3H regions; this effect was more obvious in the S3H region. In the S3H region, a 1 h increase in HTH was found to be associated with a 0.45–1.13% decrease in yield and a 1 °C increase in HTD could result in a yield loss of 1.34–4.29%. High-temperature events were detrimental to summer maize production, and the severity of this effect was projected to increase in the 3H region. In this study, we used two indices (HTH and HTD) to quantify the impact of high-temperature events on summer maize yield during the critical growth phase (heading to maturity) at a small timescale (hours and days). The results of this study can provide a reference for policymakers to use in the formulation of corresponding climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

Drought and uneven distribution of precipitation during stages of crop growth exert a severe reduction on crop yield. It is therefore necessary to evaluate the impact of drought on crop yields. In this study, data from a two-year (2016 and 2017) field experiment were used to calibrate and evaluate the parameters of the Decision Support System for the Agrotechnology Transfer (DSSAT) model. The evaluation model was then employed to analyze the impact of potential drought on the yield of summer maize (Zea mays L.) over different growth stages for 46 years (1970–2015). The simulated summer maize flowering and harvest date differed by three and one days of the observed in 2017. The d-index value and the normalized root-mean-square error (nRMSE) of the simulated and measured values were 0.90 and 3.72%, 0.95 and 10.21%, and 0.92 and 13.12%, for summer maize yield, soil water content, and leaf area index, respectively. This indicates that the parameters of the DSSAT model were extremely reliable and that the simulation results were better. The yield reduction of summer maize was concentrated within the range of 0–40% from 1970 to 2015, and the two-stage yield reduction was higher than the one-stage yield reduction. The highest probability of yield reduction occurs if drought occurs during jointing and heading stages. Irrigation is therefore recommended during jointing stage or heading stage. If local irrigation conditions permit, irrigation can be carried out both at the jointing and heading stages. This study provides a theoretical basis for drought resistance management and scientific irrigation of summer maize in the western Guanzhong plain. [ABSTRACT FROM AUTHOR]

Female panicles (FPs) play an important role in the formation of yields in maize. From 40 days after sowing to the tasseling stage for summer maize, FPs are developing and sensitive to drought. However, it remains unclear how FPs respond to drought stress during FP development. In this study, FP differentiation was observed at 20 and 30 days after drought (DAD) and agronomic trait changes of maize ears were determined across three treatments, including well-watered (CK), light drought (LD), and moderate drought (MD) treatments at 20, 25, and 30 DAD. RNA-sequencing was then used to identify differentially expressed genes (DEGs) in FPs at 30 DAD. Spikelets and florets were suppressed in LD and MD treatments, suggesting that drought slows FP development and thus decreases yields. Transcriptome analysis indicated that 40, 876, and 887 DEGs were detected in LD/CK, MD/CK, and MD/LD comparisons. KEGG pathway analysis showed that 'biosynthesis of other secondary metabolites' and 'carbohydrate metabolism' were involved in the LD response, whereas 'starch and sucrose metabolism' and 'plant hormone signal transduction' played important roles in the MD response. In addition, a series of molecular cues related to development and growth were screened for their drought stress responses. [ABSTRACT FROM AUTHOR]

Climate change, especially precipitation change, will significantly change soil moisture, which then influences root growth, further affecting yield and grain quality. Previous studies focused on the drought or flood effects on summer maize growth. However, few studied the effects of drought-flood abrupt alternation (DFAA) on the growth of summer maize. We explored the DFAA impacts on the roots, leaf area index (LAI), yield, and grain quality in field. The main results show that DFAA had different impacts on the summer maize growth in the seeding-jointing stage (SJS) and tasseling-grain filling stage (TGS). In general, the DFAA reduced the yield. Roots at the depth of 40 cm had obviously positive impacts on the yield. The DFAA reduced the LAI and promoted the maximum LAI achieving in advance. The grain crude protein augmented under DFAA. The drought had evidently negative impacts on the grain crude fat in the TGS, while it had no obvious influence in the SJS. DFAA had no apparent impact on the grain crude starch. These results could provide some references for the effects and adaptation-strategies study of extreme climate events and their impacts on growth of summer maize. [ABSTRACT FROM AUTHOR]

Improvement in fertilization methods, including the optimal matching of nutrient supply and root nutrient absorption by applying nitrogen (N) in the root zone of crop, is necessary to improve N use efficiency (NUE), maintain high stable yield cultivation of maize, and contribute toward future environmental protection. The current practice of split surface broadcasting (SSB) of N is labor-intensive and the surface broadcasting causes a large amount of N to leach into the environment, yet it does not substantially increase maize yield. Root zone fertilization (RZF) has been identified as an efficient way to solve such problems. However, information on the appropriate amount of N fertilizer under RZF for summer maize remains limited. Therefore, in this study, a two-year consecutive field experiment was conducted during 2015–2016 in Anhui province, China, to investigate the effect of N rate and application method on grain yield, nutrient uptake, and NUE of summer maize. The method chosen is not only important to increase grain yield but also critical for reducing N rate and potential loss in the maize cropping system. The experiment comprised six N rates (90, 135, 180, 225, 270, and 360 kg N hm−2) and two N application methods in both 2015 and 2016. The two N application methods included SSB and one-time RZF. Results showed that grain yield of summer maize increased first and then decreased with the increase of N rate; however, when the N rate increased to 270 kg hm−2, the grain yield increased slowly or even decreased. Compared with SSB, RZF increased grain yield by 4%, and the effect of N on grain yield was mainly related to the number of kernels per ear and 1000-seed weight. One-time RZF increased N apparent recovery efficiency by 18% (7.2 percentage points) compared with SSB and also improved the N agronomic efficiency, N physiological efficiency, and N partial factor productivity. In the comprehensive consideration of yield target, NUE, and soil N balance, the optimal N rate for summer maize in the vertisol soil of Anhui province was 180–225 kg hm−2 for one-time RZF, which reduced N fertilizer by 14% compared with the SSB. Overall, one-time RZF has great potential for green and sustainable agriculture, and thus fertilization machines are worthy of development and application in maize cropping systems. [ABSTRACT FROM AUTHOR]

A dual crop coefficient approach was validated experimentally to estimate evapotranspiration of drip-irrigated summer maize with partial mulch and no mulch in an arid region in Aksu, Xinjiang, China, during 2016–2017. In this study, five treatments were established based on fixed or variable irrigation cycles. Summer maize transpiration and evapotranspiration were estimated by the dual crop coefficient approach. Evapotranspiration was validated, and a positive regression with those values was obtained using the water balance method, with a root mean square error (RMSE) of 10 mm. The estimated transpiration also had a positive regression with measurements obtained by the stable carbon isotope technique, with a RMSE of 20 mm. By analyzing the RMSE, regression coefficients, and concordance index, we suggest that the dual crop coefficient approach is an effective method to estimate and partition evapotranspiration. Across the entire growing season for partially mulched summer maize, the estimated crop transpiration accounted for 78.7% and 76% of the total evapotranspiration in 2016 and 2017, respectively. For non-mulched summer maize, the estimated crop transpiration accounted for 64.9% of the total evapotranspiration over the entire growing season, which implied that the soil evaporation was about 12% higher than that of the partially mulched treatments. Water consumption with partial mulching was reduced by about 10%, compared with non-mulching, which indicated that mulching improved the use of water during irrigation. [ABSTRACT FROM AUTHOR]

Global warming and dimming/brightening have significant implications for crop systems and exhibit regional variations. It is important to clarify the changes in regional thermal and solar radiation resources and estimate the impacts on potential crop production spatially and temporally. Based on daily observation data during 1961–2015 in the North China Plain (NCP), the impacts of climate change associated with climate warming and global dimming/brightening on potential light–temperature productivity (PTP) of summer maize were assessed in this study. Results show that the NCP experienced a continuous warming and dimming trend in maize growing season during the past 55 years, and both ATT10 and solar radiation had an abrupt change in the mid-1990s. The period of 2000–2015 was warmer and dimmer than any other previous decade. Assuming the maize growing season remains unchanged, climate warming would increase PTP of summer maize by 4.6% over the period of 1961–2015, which mainly occurred in the start grain filling–maturity stage. On the other hand, as negative contribution value of solar radiation to the PTP was found in each stage, dimming would offset the increase of PTP due to warming climate, and lead to a 15.6% reduction in PTP in the past 55 years. This study reveals that the changes in thermal and solar radiation have reduced the PTP of summer maize in the NCP. However, the actual maize yield could benefit more from climate warming because solar radiation is not a limiting factor for the current low production level. [ABSTRACT FROM AUTHOR]

Summer maize (Zea mays L.) is a widely cultivated crop in the arid and semi-arid Guanzhong region of China. However, due to the spatial and temporal variation in rainfall, the seasonal maize yield varies substantially and occasionally is not economical for poor farmers to produce. Recent water-saving agricultural practices were developed by the government to make it possible to apply supplementary irrigation at optimum sowing dates to maximize maize production under limited rainfall in the region. CERES (Crop Estimation through Resource and Environment Synthesis)-maize model was used to identify the appropriate irrigation strategies, crop growth stages and sowing dates for sustainable maize production. Model calibration process were carried out for full irrigation treatments of four growing seasons, (2012–2015). The data used for calibration included: Crop phenology, grain yield, aboveground biomass and leaf area index. The calibration phase model showed good agreement between simulated and observed values, with normalized root mean square error (nRMSE) ranging from 4.51% to 14.5%. The performance of the calibrated model was evaluated using the field data of grain yield, aboveground biomass, leaf area index and water use efficiency. The performance of the model during evaluation was satisfactory with acceptable nRMSE error ranging from 7% to 10%. Soil moisture content was evaluated for full irrigation treatments for both 2012 and 2013 seasons. With results showing that soil moisture content below 35 cm layer was well simulated with nRMSE, 0.57 to 0.86 respectively. Appropriate simulated sowing dates for higher production and water productivity were from 14 to 24 June. The proper amount and timing of irrigation water application was 100 mm at the flowering stage, and 100 mm at the grain filling stage respectively. Summer maize yield can be improved by adjusting the sowing date and applying supplementary irrigation when precipitation cannot meet the crop water demand in the Guanzhong Plain. [ABSTRACT FROM AUTHOR]

Droughts occur frequently during summer maize growth in the Huaihe River Basin, China. Identifying the critical precipitation thresholds that can lead to drought is conducive to drought monitoring and the creation of early warning systems. Based on meteorological data from 66 stations from 1961 to 2015 in areas of the Bengbu Sluice in the Huaihe River Basin (BHR), and using correlation analysis between maize climatic yield and water deficit index at different growth stages, the critical period of water deficit in summer maize growth was determined. Twenty-eight types of distribution functions were used to fit the precipitation sequence during the critical period for water during summer maize growth. By applying Akaike Information Criterion and Bayesian Information Criterion, an optimal probability distribution model was established. The precipitation thresholds (Define R as the precipitation thresholds) for each level of drought for summer maize were then quantified based on the precipitation probability quantile method, and the rationality of the index was verified. The results were as follows: (1) The stage of tassel appearance-maturity was the critical period for water during summer maize growth. (2) There was a significant difference in the optimal probability distribution model at the 66 typical sites in the precipitation sequence during the critical period of water during summer maize growth. (3) In this paper, we identified a rapid and effective method for assessing agricultural drought in summer maize, which is based on the precipitation thresholds and dividing the different levels of drought. The precipitation thresholds of a drought disaster for summer maize at the 66 sites varied greatly from region to region. By using the Thiessen polygon method, the precipitation thresholds of a drought disaster during the critical water period during summer maize growth in the Huaihe River Basin were mild drought: 139 ≤ R < 169 mm, moderate drought: 108 ≤ R <139 mm, severe drought: 81 ≤ R < 108 mm, and extreme drought: R < 81 mm. [ABSTRACT FROM AUTHOR]