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China is the largest producer and consumer of vegetables, its vegetable industry is playing an important role in the domestic agricultural sector and global vegetable export market. It is important to promote the long-term sustainable development of Chinese vegetable industry for food security and quality of people’s lives. To find out the intrinsic way to promote the development of Chinese vegetable industry, this paper analyzed the influencing factors of Chinese vegetable production by utilizing the LMDI method and demonstrated the spatial-temporal characteristics of vegetable production through application of the ArcGIS spatial autocorrelation analysis method. The results showed that the influencing factors of vegetable production were the cultivated land area, multiple cropping index, vegetable planting proportion and vegetable yield per hectare in China. The major driving factor had changed from vegetable planting proportion to vegetable yield per hectare. The influencing degrees of factors on vegetable production are different in different regions, regionalization is therefore a major feature of Chinese vegetable production. The government should take production technology, regionalization-driven effect, and marketing integration into consideration to promote the development of Chinese vegetable industry. Keywords: Vegetable production, Influencing factors, Contribution ratio, Logarithmic mean Divisia index (LMDI)

Peaches are a popular fruit appreciated by consumers due to their eating quality. Quality evaluation of peaches is important for their processing, inventory control, and marketing. Eleven quality indicators (shape index, volume, mass, density, firmness, color, impedance, phase angle, soluble solid concentration, titratable acidity, and sugar−acid ratio) of 200 peach fruits (Prunus persica (L.) Batsch “Spring Belle”) were measured within 48 h. Quality indicator data were normalized, outliers were excluded, and correlation analysis showed that the correlation coefficients between dielectric properties and firmness were the highest. A back propagation (BP) neural network was used to predict the firmness of fresh peaches based on their dielectric properties, with an overall fitting ratio of 86.9%. The results of principal component analysis indicated that the cumulative variance of the first five principal components was 85%. Based on k-means clustering analysis, normalized data from eleven quality indicators in 190 peaches were classified into five clusters. The proportion of red surface area was shown to be a poor basis for picking fresh peaches for the consumer market, as it bore little relationship with the comprehensive quality scores calculated using the new grading model.

Tricholoma matsutake (T. matsutake) growing in Tibet is very popular for its high economic and medicinal value, but fresh T. matsutake has an extremely short shelf life. The shelf life of T. matsutake is complex, influenced by product characteristics, surrounding environmental conditions, and spoilage development. The objective of this work was to study the quality characteristics of fresh T. matsutake during its shelf life period in modified atmosphere packaging (MAP) conditions and establish its remaining shelf life prediction models in a cold chain. In this study, we measured and analyzed quality indicators of fresh T. matsutake, including hardness (cap, stipe), color, odor of sensory characteristics, pH, soluble solids content (SSC), and moisture content (MC) of physical and chemical characteristics under the temperature condition of 4 °C and relative humidity (RH) of 90%. The sensory evaluation results showed that the odor indicator in sensory characteristics was more sensitive to the freshness of T. matsutake. The changes of pH, SSC, and MC were divided into three periods to analyze the physiological changes of T. matsutake. The cap spread process could affect the changes of pH, SSC, and MC in period S1, and they changed gradually in period S2. In the period S3, they changed complicatedly because of deterioration. The remaining shelf life prediction model of T. matsutake was established by the back propagation (BP) neural network method to quantify the relationship between the quality indicators and the remaining shelf life. The shelf life characteristics are complex, which were optimized by correlation analysis. Significant benefits of this work are anticipated on the transportation and preservation of fresh T. matsutake to the market and the reduction of its losses in the postharvest chain.

Low-carbon production is one of the dominating issues in the sustainable development of the food industry with high energy consumption, especially in the table grapes cold chain. The aim of this paper is to propose a profit maximization strategy of table grapes cold chain by integrating the carbon footprint to improve the low-carbon production and sustainability of the cold chain system. The carbon footprint was evaluated by life cycle assessment (LCA) in entire cold chain system of table grapes, and the economic order quantity (EOQ) model was used to develop the profit maximization model with minimal carbon footprint and to maintain the optimal balance between stock and cost. The profit optimization performance, the sensitivity performance and the influencing factors of the decay rate, the carbon emission price, and the distance and carbon emission coefficient in refrigerated transport were analyzed according to the profit maximization model and the inventory data in actual cold chain investigated. The sensitivity performance analysis illustrated that the selling price had the highest sensitivity, and the carbon emission coefficient in storage had the lowest sensitivity. The comprehensive analysis results indicated that there is an optimal combination point between the economy and environment in actual cold chain, which not only reduced the carbon emission, but also had minimal impact on the profit in cold chain. The enterprises should integrate the carbon footprint cost into the profit maximization once the carbon emission tax is levied. The proposed strategy of the profit maximization with carbon footprint constraint is also suitable for improving profit maximization of other low-carbon supply chain applications.

Energy consumption is one of the most crucial issues in the table grapes supply chain. However, the potential for energy conservation assessment is still limited because of the complexity of the process. The aim of this paper is to propose an energy conservation potential assessment method in order to increase energy consumption transparency and help managers take appropriate energy conservation measures to reduce the energy consumption in the table grapes supply chain. The conservation potential assessment in three kinds of the supply chain modes (the normal chain, the cold insulation chain and the cold chain), were realized by integrating the actual energy consumption investigated with the unified energy consumption per unit energy factor that represents the energy consumption throughout the entire product lifecycle. According to the comprehensive analysis of the energy consumption compared with the energy conservation potential in actual supply chain of table grapes, the proposed energy conservation potential assessment method could provide a unified method for evaluating the energy conservation potential in different supply chain mode of table grapes. The energy conversation potential in cold insulation chain, which was about 0.985, was the highest and that in cold chain, which was about 0.935, was the smallest. However, the cold chain was still the optimal supply chain for the table grapes because of the characteristics of the longest storage shelf life and the lowest quality decay, and the cold chain energy consumption would be further reduced by adopting the more advanced refrigeration and preservation technologies. The proposed energy conservation potential assessment method could be extended for other supply chain applications to evaluate their own energy conservation potential, and thus, reduce their energy consumption. [ABSTRACT FROM AUTHOR]

We estimated the risk posed by hydroxybenzene in farm-raised Crucian carps (Carassius carassius) from a pond on a fish farm in Beijing, China, by analyzing a time-series of observed hydroxybenzene concentrations in fish within a culturing season in year 2006. We used the basic linear regression to model the data and forecast the probability of hydroxybenzene concentration in pond fish exceeding selected health effect criteria (the risk) using Monte Carlo simulation. The risk is highly correlated with the time a fish stays in the pond. The results indicate that the risk-days in pond relationship resembles a sigmoid function with an inflection point around 150 days. The resulting model can be used to demonstrate the benefit of improving water quality in terms of increased fish production. [ABSTRACT FROM AUTHOR]

Variable rate pesticide application holds great potential in precision agriculture where application efficiency depends mainly on plant recognition. The segmentation of the plant from the background is key to plant recognition. The work presented in this paper is a real-time segmentation algorithm that was developed to improve the quality of plant segmentation under natural outdoor light conditions. The plant images were greyed with the colour features H, a*, 13 and Cr respectively, and the plant was segmented from the grey images with a threshold that was computed by an iterative method. Experiments showed that segmentation was generally of good quality if the background was bare soil. The quality of segmentation declines if the images are greyed by H and Cr, and the quality remains stable if they are greyed by a* and 13 when the background is complicated, and, especially with heavy shadows. With respect to segmentation speed, that greyed by Cr was the fastest and that greyed by a* was slowest amongst the four. [ABSTRACT FROM AUTHOR]

E-learning, as an innovative and alternative way of distance learning, provides a strong challenge to traditional learning with its unique advantage. This paper, on the diffusion of e-learning adoption in China, investigates people's perceptions and attitudes toward adopting e-learning, and explores the factors affecting the e-learning adoption behaviour from an innovation adoption perspective. Based on the model of Rogers' innovation adoption theory, every factor of perceived innovative attributes influencing the individual adoption behaviour, namely perceived relative advantage, perceived compatibility, perceived trialability, and perceived observability, will be analysed to test the relationship between the perceived innovative attributes and adoption intention of e-learning. The result shows that the four perceived innovative attributes do have certain influences on people's adoption of e-learning. [ABSTRACT FROM AUTHOR]

Domain concepts acquisition is a key step of knowledge acquisition. In this paper we propose a new method for computing the relationship of domain concepts of China's vegetable supply chain using WordNet and Locally Linear Embedding (LEE) Arithmetic. WordNet is used to construct the high dimension description of the domain concepts and LLE is used to compute the relationship of concepts in low dimension space. The concepts description in the high dimension is in accord with human cognition and the low dimension relationship can reflect the degree of correlation of domain concepts clearly. A computer can deal with domain concepts directly after dimensional transformation. The experiment proves the efficiency of this method. The method can be expanded to deal with other examples of domain concepts acquisition. [ABSTRACT FROM AUTHOR]

The paper analyses the impacts of alteration of agricultural domestic supports on state welfare adopting partiaI equilibrium theory. In order to find out the appropriate levels of agricultural domestic supports in China, a nonlinear programming approach was utilised, based on constraints of the annual financial budget and the Uruguay Round Agreement on Agriculture, to build an optimisation model for levels of China agricultural domestic support was built to aim at the maximum welfare. The result shows that the maximum levels of China "amber box" support are 50 billion dollars from welfare maximisation in the international agricultural product trade. The amber box support is about 174 billion RMB yuan according to the de minimis levels of China with 8.5%. The national annual budgetary expenditure for agriculture was 175.445 billion RMB yuan approximately in 2003, the amber box support of which was only 55.143 billion RMB yuan. [ABSTRACT FROM AUTHOR]

A new type of roof structure was developed for the shade room in a double-slope greenhouse used for mushroom-vegetable planting. A simulation model was developed to evaluate the thermal performance of the new roof with an insulation thickness of 0.12 m in Beijing, China. The results showed that (1) the indoor air temperature of the shade room with the newly implemented shade roof was 2.7°C-4.9°C higher than that of an ordinary shade room during the winter months; (2) The indoor air temperature of the solar room adjacent to the shade room with the new roof was higher than that of the ordinary solar room and the minimum indoor air temperature of the solar room was increased 1.9°C at winter night; (3) the indoor temperature of the shade room with the new roof design was 2°C-4°C lower than that of the ordinary shade room during the summer months; (4) Under factory production conditions, which were conducted in a controlled environment to promote the annual growth of the edible fungus, the heating energy consumption of the shade room after the implementation of the new roof structure was reduced by 69.3%, the amounted to total energy savings of 61.3% per year. The new roof structure provided a significant improvement in the thermal environment compared to an ordinary shade room, improved the vegetable growth in the winter, and also significantly reduced the energy consumption and production costs. [ABSTRACT FROM AUTHOR]