Dataset Information

Comparison of early season crop types for wheat production and nitrogen use efficiency in the Jianghan Plain in China.

ABSTRACT: The rice-wheat (RW) cropping system is one of the most prevalent double-cropping systems used to farm the Jianghan Plain in China. However, it can lead to low wheat yields and reduced nitrogen use efficiency compared with dryland wheat (DW). We evaluated wheat yield and nitrogen use efficiency for two rotations (summer rice-winter wheat and summer soybean-winter wheat) from 2017 to 2019 and applied the results to improve nitrogen management for planting wheat after rice in the Jianghan Plain. Field experiments were conducted over two years with two nitrogen treatments: traditional nitrogen management (M1: 90 kg N ha^-1 was applied at sowing and jointing, respectively ) and optimized nitrogen management (M2: 60 kg N ha^-1 was applied at sowing, wintering and jointing, respectively). The highest total wheat production was achieved under M2 for both cropping systems and the two-year average yield was 6,128 kg ha^-1 in DW and 6,166 kg ha^-1 in RW. The spike number in DW was 15% higher than RW in M1 and 13% higher in M2, but the kernel per spike and 1,000-grain weight was lower than RW. The nitrogen accumulation of DW was 24% higher than RW in M1 and 33% in M2. Compared with RW, DW had higher NO₃ ^- content in the soil surface layer (0-20 cm) and a higher root length density (RLD) in the deeper layer (40-60 cm), which may account for the higher N uptake in DW. Our results show that the grain yield of RW was comparable to that of DW by optimum nitrogen management. The rice-wheat cropping system combined with optimum nitrogen management may be of economic and agronomic benefit to the wheatbelt in the Jianghan Plain in China.

SUBMITTER: Yang R

PROVIDER: S-EPMC8040854 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Accurate and timely nitrogen (N) scheduling requires knowledge of in-season crop N deficit. Therefore, understanding the association between crop growth and crop N demand during its growth period is imperative for fine-tuning N scheduling decisions to actual crop N demand and to enhance N use efficiency. The concept of the critical N dilution curve has been employed to assess and quantify the intensity and time of crop N deficit. However, research regarding the association between crop N deficit and N use efficiency in wheat is limited. The present study was carried out to determine whether there are relationships between the accumulated nitrogen deficit (Nand) and agronomic N use efficiency (AEN) as well as with its components (N fertilizer recovery efficiency (REN) and N fertilizer physiological efficiency (PEN)) of winter wheat and to explore the potential capacity of Nand for predicting AEN and its components. Data acquired from five variable N rates (0, 75, 150, 225, and 300 kg ha−1) field experiments using six winter wheat cultivars were used to establish and validate the relationships between Nand and AEN, REN, and PEN. The results indicated that plant N concentration in winter wheat was significantly affected by N application rates. Nand varied from −65.73 to 104.37 kg ha−1 after Feekes stage 6 under different N application rates. The AEN and its components were also affected by cultivars, N levels, seasons, and growth stages. A positive correlation was observed between Nand, AEN, and its components. Validation using an independent data set showed the robustness of the newly developed empirical models to accurately predict AEN, REN, and PEN with an RMSE of 3.43 kg kg−1, 4.22%, and 3.67 kg kg−1 and RRMSE of 17.53%, 12.46%, and 13.17%, respectively. This indicates that Nand has the potential to predict AEN and its components during the growth period of winter wheat. The findings will assist in improving in-season N use efficiency by fine-tuning N scheduling decisions in winter wheat cultivation.

Project description:The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain.

Project description:Soil labile C and N fractions can change rapidly in response to management practices compared to non-labile fractions. High variability in soil properties in the field, however, results in nonresponse to management practices on these parameters. We evaluated the effects of residue placement (surface application [or simulated no-tillage] and incorporation into the soil [or simulated conventional tillage]) and crop types (spring wheat [Triticum aestivum L.], pea [Pisum sativum L.], and fallow) on crop yields and soil C and N fractions at the 0-20 cm depth within a crop growing season in the greenhouse and the field. Soil C and N fractions were soil organic C (SOC), total N (STN), particulate organic C and N (POC and PON), microbial biomass C and N (MBC and MBN), potential C and N mineralization (PCM and PNM), NH4-N, and NO3-N concentrations. Yields of both wheat and pea varied with residue placement in the greenhouse as well as in the field. In the greenhouse, SOC, PCM, STN, MBN, and NH4-N concentrations were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow. In the field, MBN and NH4-N concentrations were greater in no-tillage than conventional tillage, but the trend reversed for NO3-N. The PNM was greater under pea or fallow than wheat in the greenhouse and the field. Average SOC, POC, MBC, PON, PNM, MBN, and NO3-N concentrations across treatments were higher, but STN, PCM and NH4-N concentrations were lower in the greenhouse than the field. The coefficient of variation for soil parameters ranged from 2.6 to 15.9% in the greenhouse and 8.0 to 36.7% in the field. Although crop yields varied, most soil C and N fractions were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow in the greenhouse than the field within a crop growing season. Short-term management effect on soil C and N fractions were readily obtained with reduced variability under controlled soil and environmental conditions in the greenhouse compared to the field. Changes occurred more in soil labile than non-labile C and N fractions in the greenhouse than the field.

Project description:Producing high economic benefits and high grain yields with limited environmental impacts is crucial for feeding the world's growing population. Yet it remains challenging to improve the performance of one objective without creating unintended consequences for other objectives. This is especially difficult for smallholders navigating a diverse array of environmental and personal demands. This study demonstrates how combining participatory research through the Science and Technology Backyards (STB) approach with Pareto-based ranking modeling can increase smallholder production while also reducing environmental impact. Through an intensive farmer survey in a 1 × 1 km grid in Quzhou County, we demonstrate that farmers engaged in STBs performed better according to multiple objectives (i.e., optimizing overall grain yield, benefit-cost ratio, and GHG emissions, without compromising any one of these objectives) than farmer's not engaged in STBs. Moreover, we used a Pareto optimization approach (OPT) to determine the optimal smallholder scenario. We found that under OPT, grain yield could reach 9.5 t/ha, with a benefit-cost ratio of 2.1, a 100% N recovery efficiency, and 7,395 kg CO2eq ha-1 GHG emissions. With OPT as a final goal, our research team worked with STB farmers to improve economic and environmental outcomes without compromising yield. Our findings demonstrate that no significant difference was obtained between farmers engaged in STBs and these under OPT. Compared with non-STB farmers, STB farmers' grain yield improved by 18%, benefit-cost ratio improved by 26% due to improved N recovery efficiency, and GHG emissions were reduced by 31%. These improvements demonstrate the power of scientist-farmer engagement for optimizing wheat production. Such engagement allows farmers to modify their agronomic practices to more closely match Pareto optimal conditions, thus improving environmental and economic benefits without compromising yield. Our results provide solid evidence of the potential for sustainable wheat production by combining modeling with participatory research.

Dataset Information

Comparison of early season crop types for wheat production and nitrogen use efficiency in the Jianghan Plain in China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets