Summer Maize In China Research Articles

Spatiotemporal drought characteristics during growing seasons of the winter wheat and summer maize in the North China Plain

The North China plain (NCP) is an important production base for winter wheat and summer maize in China. Severe droughts seriously restrict agricultural production in this region, threatening food security. Based on the standardized precipitation evapotranspiration index (SPEI), this study explored the spatial and temporal drought characteristics during the winter wheat and summer maize growing seasons in the region. The study found that: 1) From 1980 to 2013, the drought trend of the winter wheat growing season in the NCP has intensified, with Huang-Huai Plain agricultural area (HH_P) showing the most significant drought trend. However, the summer maize growing season has become wetter, with the Shandong hilly agricultural and forestry area (SD_Q) showing the most significant wetting trend. 2) After the year 2003, the results from Mann-Kendall trend analysis revealed that the drought trend of HH_P during the winter wheat growing season became particularly pronounced, but the wetting trend of SD_Q and HH_P during the summer maize growing season became more evident. 3) The dominant spatial patterns observed in the NCP during the growing seasons of winter wheat and summer maize were marked by a consistent distribution of drought and wetness conditions. For winter wheat, the southern regions of the foothill plain area of Yanshan and Taihang Mountains (YT_P) and the low-lying plain area of Hebei, Shandong, and Henan (JLY_P) were more sensitive to the changes of drought and wet conditions. For summer maize, SD_Q was more sensitive to the changes of the drought and wet conditions. The results of this study could provide references for the formulation of drought relief strategies of winter wheat and summer maize in the NCP.

Growth Indexes and Yield Prediction of Summer Maize in China Based on Supervised Machine Learning Method

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.

Exogenous SA or 6-BA maintains photosynthetic activity in maize leaves under high temperature stress

With global warming, high-temperature (HT) stress has become a major abiotic stress for crops, in particular summer maize in China. Photosynthesis is sensitive to HT. Salicylic acid (SA) and 6-benzyladenine (6-BA) can improve the adaptation of plants to various biotic and abiotic stresses. However, their contribution to maintaining photosynthetic activity and alleviating photoinhibition in maize leaves under HT stress is still unclear. The effects of exogenous SA or 6-BA on growth, photosynthesis capacity, photosystem II (PSII) activity, subcellular ultrastructure, antioxidant system, and plant hormones in maize leaves under HT stress were investigated. Under HT conditions, application of SA or 6-BA up-regulated gibberellin and zeatin content in leaves, increasing leaf area index (LAI). It also expanded the stomata by reducing abscisic acid and jasmonic acid content in leaves, cooling them and increasing CO2 supply to photosynthesis. A higher net photosynthetic rate, combined with increased activity of the antioxidant system, alleviated oxidative stress in maize plants sprayed with SA or 6-BA, allowing them to maintain their chloroplast ultrastructure and PSII activity, in particular electron transfer from QA to QB. The increased LAI and net photosynthetic rate per unit leaf area also resulted in the accumulation of more biomass.

Narrowing Yield Gaps and Enhancing Nitrogen Utilization for Summer Maize (Zea mays L) by Combining the Effects of Varying Nitrogen Fertilizer Input and Planting Density in DSSAT Simulations.

In China, the most common grain crop is maize (Zea mays). The increasing pressure to meet the food demands of its growing population has pushed Chinese maize farmers toward an excessive use of chemical fertilizers, a practice which ultimately leads to a massive waste of resources and widespread environmental pollution. As a result, increasing the yield and improving the nitrogen (N) use efficiency of maize has become a critical issue for agriculture in China. This study, which analyzes the combined data from a simulation carried out using the Decision Support System for Agrotechnology Transfer (DSSAT), a field experiment, and a household survey, explored the effectiveness of several approaches aimed at narrowing the maize yield gap and improving the N utilization efficiency in the Huang-Huai-Hai Plain (HHHP), the most important area for the production of summer maize in China. The various approaches we studied deploy different methods for the integrated management of N fertilizer input and the planting density. The study produced the following results: (1) For the simulated and actual maize yields, the root mean square error (RMSE), the normalized root mean squared errors (NRMSE) and the index of agreement (d) were 1,171 (kg ha–1), 12% and 0.84, respectively. These results show that the model is viable for the experiment included in the study; (2) The potential yield was 15.58 t ha–1, and the yields achieved by the super-high-yield cultivation pattern (SH), the optimized nutrient and density management pattern (ONM), the simulated farmer’s practice cultivation pattern (FP) and actual farmer’s practice (AFP) were 11.43, 11.06, 10.33, and 7.95 t ha–1, respectively. The yield gaps associated with the different yield levels were large; (3) For summer maize, the high yield and a high N partial factor productivity (NPFP) was found when applying a planting density of 9 plants m–2 and an N application amount of 246 kg ha–1. These results suggest that the maximum yield that can actually be achieved by optimizing the N application and planting density is less than 73% of the potential yield. This implies in turn that in order to further narrow the observed yield gaps, other factors, such as irrigation, sowing dates and pest control need to be considered.

Adjusting sowing date and cultivar shift improve maize adaption to climate change in China

This study investigates the impact of climate change on spring and summer maize (Zea mays) yield and evaluates several adaptation measures to overcome the negative impact of climate change on maize production in China. The results showed that the grain-filling duration of maize would be shortened 6–15 days in the future as a result of climate change. Thus, potential maize yield would decrease by 2–32%, and rainfed maize yield would decrease by 0–24% during 2010–2099 relative to 1976–2005. In response to climate change, adaptive measures should be taken to overcome its projected impact. The adoption of new cultivars while maintaining the same pre-flowering and post-flowering duration in the future as in the present would help to improve potential maize yield by 50–61% in three time slices (2030s, 2050s, and 2070s) and would be a better choice for high yields in the future. The cultivars that would maintain the same post-flowering duration in the future as in the present would be a better choice than the cultivars that would maintain the pre-flowing periods for summer maize in China. Adjusting sowing dates would be another important way to extend post-flowering periods and further improve maize yield. If the maize cultivar currently used was adopted, delaying the sowing date would improve the potential maize yield by 2–25%. If future maize cultivars that maintained the growing period even as warmer temperatures accelerate phenological development were adopted, delaying the sowing date would improve the potential maize yield by 0–8.9%. The interactive effect of sowing and cultivars was quantified. Based on the findings of this study, future maize cultivars maintaining the growing period were adopted, and delaying the sowing date could still improve potential maize yield worldwide. Two regional adaptation strategies to climate change could offset the potential reduction of maize production worldwide, which would provide farmers and policy-makers with explicit guidance.

Root-zone fertilization improves crop yields and minimizes nitrogen loss in summer maize in China

It is urgently to minimize nitrogen (N) loss while simultaneously ensuring high yield for maize in China. A two-year field experiment was conducted to determine the effects of root-zone fertilization (RZF) and split-surface broadcasting (SSB) on grain yield, N use efficiency (NUE), and urea-15N fate under different N rates (135, 180 and 225 kg ha−1). Results showed that RZF increased grain yield by 11.5%, and the N derived from fertilizer (Ndff%) by 13.1–19.6%, compared with SSB. The percentage of residual 15N in the 0–80 cm soil was 37.2–47.4% after harvest; most 15N (64.4–67.4%) was retained in the top 20 cm. RZF significantly increased the N apparent recovery efficiency (NARE) and 15N recovery in maize by 14.3–37.8% and 21.9–30.0%, respectively; while decreased N losses by 11.2–24.2%, compared with SSB. The RZF of urea can be considered a slow-release fertilizer, which better matches maize N demand and effectively reduces N losses. Overall, RZF achieved yields as high as the SSB, but with a 20–25% reduction in N application. These results help improve our understanding of N fate in the maize cropping system, and may help guide recommendations for N management in southeastern China.

Nutrient Expert Improves Nitrogen Efficiency and Environmental Benefits for Summer Maize in China

Core Ideas Nutrient expert is a nutrient decision support tool and this study confirmed that it could be used in north‐central China. The continual performance of nutrient expert was evaluated through multiple‐point field experiments. This is the first report of nutrient expert on improving environmental benefits of summer maize. Modern agriculture needs environmentally friendly approaches to increase production, improve nitrogen use efficiency (NUE), and promote ecologically sustainable agriculture. This study was conducted from 2010 to 2014 in 389 farmers’ fields across major summer maize growing regions in north‐central China to evaluate the continual performance of the nutrient expert (NE) system for improving NUE and environmental benefits. Results indicated that NE significantly increased grain yield and profitability by reducing N fertilizer rate by 35.1% (84.6 kg N ha−1), increasing the K rate by 68.1% (25.8 kg K2O ha−1), and keeping the P rate the same as the farmers’ practice (FP). On average, NUE achieved in the NE treatment was significantly higher than for FP and fertilizer recommendation based on soil testing (OPTS). The NE increased agronomic efficiency of nitrogen (AEN) by 50.8 and 17.3%, recovery efficiency of nitrogen (REN) by 67.7 and 15.9%, and partial factor productivity of nitrogen (PFPN) by 43.8 and 21.2% compared with FP and OPTS, respectively. Furthermore, the calculated total N2O emission, total greenhouse gas (GHG) emission, and GHG emission intensity were 35.1 and 17.5%, 35.2 and 18.4%, and 37.3 and 17.4% lower in the NE treatment when compared with FP and OPTS, respectively. The differences in yield, economic benefits, NUE, and GHG emission among NE, FP, and OPTS treatments confirmed that NE is a promising nutrient decision support tool and has the potential to improve NUE and environmental benefits for summer maize (Zea mays L.) in north‐central China.

Climate-associated distribution of summer maize in China from 1961 to 2010

A quantitative description of the change in the cultivation distribution of summer maize under climate change can provide a scientific basis for optimizing the distribution of maize production in China and making countermeasures to cope with climate change. In this paper, we studied the relationship between the cultivation distribution of summer maize and climate in China and investigated the decadal change of cultivation distribution of summer maize and the change in climatic suitability from 1961 to 2010. The results indicate that there has been significant decadal change in the cultivation distribution and climatic suitability of summer maize in China. The most climate-suitable planting area for summer maize exhibited an obvious trend of eastward expansion, reaching its maximum area (3.4×107hm2) in the 1990s; the climate-suitable planting area exhibited a trend of southward expansion, the magnitude of which was relatively large in the last 20 years, approaching about 1.6×108hm2 in the last 10 years. The least climate-suitable planting area was the largest and generally exhibited a fluctuating change with a decrease-increase-decrease-increase pattern, with the largest magnitude of fluctuation reaching 2.9×107hm2; the climate-unsuitable area generally exhibited a downward trend, except for a slight increase in the 1970s. In the past 50 years, the arable area of summer maize clearly moved northward. Before the 1990s, expansion in a northwestern direction dominated; since the 1990s, expansion was mainly to the northeast. It indicated that there remains a very large potential of yield increase for summer maize in China against the background of climate change, which primarily concentrates in Northern China.

Determining the optimal nitrogen rate for summer maize in China by integrating agronomic, economic, and environmental aspects

Abstract. The concept of high yield with a goal of minimum environmental cost has become widely accepted. However, the trade-offs and complex linkages among agronomic, economic, and environmental factors are not yet well understood. In this study, reactive nitrogen (Nr) losses were estimated using an empirical model, and an economic indicator and an evaluation model were used to account for the environmental costs of N fertilizer production and use. The minimum N rate to achieve the maximum yield benefit (agronomically optimal N rate), maximum economic benefit (economically optimal N rate: economic benefit was defined as yield benefit minus N fertilizer cost), and maximum net benefit (ecologically optimal N rate: net benefit was defined as yield benefit minus N fertilizer and environmental costs) were estimated based on 91 on-farm experiment sites with five N levels for summer maize production on the North China Plain. Across all experimental sites, the agronomically, economically, and ecologically optimal N rates (Nagr, Neco, and Necl, respectively) averaged 289, 237, and 171 kg N ha−1, respectively. Necl management increased net benefit by 53% with a 46% decrease in total environmental costs, and a 51% decrease in Nr loss intensity from N fertilizer use (47, 65, and 38% for N2O emission, N leaching, and NH3 volatilization, respectively) and maintained grain yield, compared with Nagr management. Compared with Neco management, Necl increased net benefit by 12%, with a 31% decrease in total environmental costs and a 33% decrease in Nr loss intensity from N fertilizer use, and maintained economic benefit and grain yield. No differences in Necl were observed between soil types or years, but significant variation among counties was revealed. Necl increased with the increase in N-derived yield with an R2 of 0.83. In conclusion, Necl was primarily affected by N-derived yield and could enhance profitability as well as reduce Nr losses associated with the maize grain yield.

Analysis on yield components of elite maize variety Xundan 20 with super high yield potential

Xundan 20 was released by Hebi Academy of Agricultural Sciences in 2003. The stability, adaptation and yield components of Xundan 20 were analyzed using data from Huanghuaihai national tests in 2001 and 2002 and from high yield trials from 2005 to 2010. The results showed that variety Xundan 20 yielded most and increased significantly than Nongda 108 (Control, CK) in Huanghuaihai national tests in 2001 and 2002. The yield potential of variety Xundan 20 was so high that it created a series of new record in China. The yield of variety Xundan 20 of 15971.7 kg/ha created the highest record of summer maize in China in 2007, with the yield components of 77835 plant/ha, 205.2 g/ear, 596.16 grains/ear and 350 g per 1000-grain. The variation coefficient of variety Xundan 20 was small and its yield was stable. It is based on excellent comprehensive resistance of variety Xundan 20 to main disasters in Huanghuaihai region such as diseases, pests and lodging. Key words: Maize, Xundan 20, stability, wide adaptability, yield components, super high-yield.