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The sustainability of growing a maize—winter wheat double crop rotation in the North China Plain (NCP) has been questioned due to its high nitrogen (N) fertiliser use and low N use efficiency. This paper presents field data and evaluation and application of the soil–vegetation–atmosphere transfer model Daisy for estimating crop production and nitrate leaching from silty loam fields in the NCP. The main objectives were to: i) calibrate and validate Daisy for the NCP pedo-climate and field management conditions, and ii) use the calibrated model and the field data in a multi-response analyses to optimise the N fertiliser rate for maize and winter wheat under different field managements including straw incorporation. The model sensitivity analysis indicated that a few measurable crop parameters impact the simulated yield, while most of the studied topsoil parameters affect the simulated nitrate leaching. The model evaluation was overall satisfactory, with root mean squared residuals ( RMSR ) for simulated aboveground biomass and nitrogen content at harvest, monthly evapotranspiration, annual drainage and nitrate leaching out of the root zone of, respectively, 0.9 Mg ha −1 , 20 kg N ha −1 , 30 mm, 10 mm and 10 kg N ha −1 for the calibration, and 1.2 Mg ha −1 , 26 kg N ha −1 , 38 mm, 14 mm and 17 kg N ha −1 for the validation. The values of mean absolute deviation, model efficiency and determination coefficient were also overall satisfactory, except for soil water dynamics, where the model was often found erratic. Re-validation run showed that the calibrated Daisy model was able to simulate long-term dynamics of crop grain yield and topsoil carbon content in a silty loam field in the NCP well, with respective RMSR of 1.7 and 1.6 Mg ha −1 . The analyses of the model and the field results showed that quadratic, Mitscherlich and linear-plateau statistical models may estimate different economic optimal N rates, underlining the importance of model choice for response analyses to avoid excess use of N fertiliser. The analyses further showed that an annual fertiliser rate of about 300 kg N ha −1 (100 for maize and 200 for wheat) for the double crop rotation with straw incorporation is the most optimal in balancing crop production and nitrate leaching under the studied conditions, given the soil replenishment with N from straw mineralisation, atmospheric deposition and residual fertiliser. This work provides a sound reference for determining N fertiliser rates that are agro-environmentally optimal for similar and other cropping systems and regions in China and extends the application of the Daisy model to the analyses of complex agro-ecosystems and management practices under semi-arid climate. [ABSTRACT FROM AUTHOR]

In this paper, we employ a trans -log production function model for China’s agricultural sector, with capital, labor and energy as input factors. The output elasticity, substitution elasticity and relative difference in technical progress among the factors are analyzed. The results show that during the period 1980–2012 the growth of the agricultural economy in China benefited from the combined effects of factors accumulation and technical progress. Among the factors, the output elasticity of labor is the largest, followed by capital and energy. Capital, labor and energy are substitutes for one another, but the elasticity of substitution between capital and energy is the highest, with a value of 1.1. In the meantime, the relative difference in technical progress among these factors is insignificant and there is a convergence trend over time. We suggest increasing technological innovation in order to improve the contribution of technology progress as well as allocating more capital into the agricultural sector in order to alleviate the shortage of energy supply and the current problem of “hollow” in the rural labor force. This is of great significance to reducing energy consumption and improving the total factor productivity in the China’s agricultural sector. [ABSTRACT FROM AUTHOR]

The yield gap (YG) between the potential yields (Yp) and the average on-farm yields (Ya) is an indicator of the potential improvement for crop production. Understanding how large the current gap is and how this gap has changed over the past few decades is essential for increasing wheat production to meet increased food demand in China. This paper describes a study conducted using an APSIM-Wheat model and farm-level crop yield to analyze the spatio-temporal distribution of the yield gap of winter wheat from 1981 to 2010 in the North China Plain. Nine varieties were calibrated and evaluated based on the data from 16 agro-meteorological experimental sites and then potential yields were estimated considering cultivar replacement. In addition, a trend pattern analysis of on-farm yields for the period 1981-2010 was conducted. Results revealed an estimated yield gap across the entire North China Plain region of 1140-6810 kg ha-1, with a weight average of 3630 kg ha-1 in 1981-2010. Expressed as a relative yield (yield gap % of potential yields), the range was 15-80%, and the weight average was 45%. Despite the negative effects of increasing temperature and decreasing radiation, the potential yields significantly increased by 45 kg ha-1 per year due to cultivar improvement. On-farm yields increased even more notably because of new cultivar selection, increased fertilizer application and other management improvements, but were stagnating in 32.3% of wheat areas, located mainly in Hebei province, Shandong province, Beijing and Tianjin. The improvement of on-farm yields have substantially contributed to yield gap spatio-temporal variation. As a result, the yield gap decreased from 4200 kg ha-1 (56%) in 1981-1990 to 3000 kg ha-1 (35%) in 2001-2010 at a rate of -69 kg ha-1 per year. However, yields stagnation will expand to the northern Henan province without cultivar potential productivity improving, where yield gap was close to or less than 20% of the potential yields and proved difficult to reduce. To further improve the total production of winter wheat in the coming decades, efforts should be paid to break the potential ceiling and reduce the yield gap by breeding higher yield variety and introduction of new agricultural technology. [ABSTRACT FROM AUTHOR]