Using Quantile Regression Approach to Analyze Price Movements of Agricultural Products in China

This paper studies how the price movements of pork,chicken and egg respond to those of related cost factors in short terms in Chinese market.We employ a linear quantile approach not only to explore potential data heteroscedasticity but also to generate confidence bands for the purpose of price stability study.We then evaluate our models by comparing the prediction intervals generated from the quantile regression models with in-sample and out-of-sample forecasts.Using monthly data from January 2000 to October 2010,we observed these findings：（i） the price changes of cost factors asymmetrically and unequally influence those of the livestock across different quantiles;（ii） the performance of our models is robust and consistent for both in-sample and out-of-sample forecasts;（iii） the confidence intervals generated from 0.05th and 0.95th quantile regression models are good methods to forecast livestock price fluctuation.

Assessment of Flood Catastrophe Risk for Grain Production at the Provincial Scale in China Based on the BMM Method

Flood catastrophe risk assessment is imperative for the steady development of agriculture under the context of global climate change,and meanwhile,it is an urgent scientific issue need to be solved in agricultural risk assessment discipline.This paper developed the methodology of flood catastrophe risk assessment,which can be shown as the standard process of crop loss calculation,Monte Carlo simulation,the generalized extreme value distribution（GEV） fitting,and risk evaluation.Data on crop loss were collected based on hectares covered by natural disasters,hectares affected by natural disasters,and hectares destroyed by natural disasters using the standard equation.Monte Carlo simulation based on appropriate distribution was used to expand sample size to overcome the insufficiency of crop loss data.Block maxima model（BMM） approach based on the extreme value theory was for modeling the generalized extreme value distribution（GEV） of flood catastrophe loss,and then flood catastrophe risk at the provincial scale in China was calculated.The Type III Extreme distribution（Weibull） has a weighted advantage of modeling flood catastrophe risk for grain production.The impact of flood catastrophe to grain production in China was significantly serious,and high or very high risk of flood catastrophe mainly concentrates on the central and eastern regions of China.Given the scenario of suffering once-in-a-century flood disaster,for majority of the major-producing provinces,the probability of 10% reduction of grain output is more than 90%.Especially,the probabilities of more than 15% decline in grain production reach up to 99.99,99.86,99.69,and 91.60% respectively in Anhui,Jilin,Liaoning,and Heilongjiang.Flood catastrophe assessment can provide multifaceted information about flood catastrophe risk that can help to guide management of flood catastrophe.

Price Transmission in China's Swine Industry with an Application of MCM

The paper studies the relationship, adjustment ability, path, efficiency and intensity of price transmission in the swine industry chain in China, which consists of the prices of corn, compound feed for fattening pig, piglet, pig and pork. Monthly prices covering a period of 18 yr （1994-2011） are analyzed using a Market-Chain Cooperated Model （MCM）. The empirical results show that there exists a stable long-term cointegration and short-term dynamic relationship in the price system. First, the adjustment speed of each price series is very slow and the transmission path is top-down and one-way significantly. Second, the price from upstream to downstream lags about 2 mort, while there is no lag in price transmission from midstream to downstream. Third, in terms of price transmission intensity, the price of pig impacted greatly on pork price, not only in the current period but also through the whole period. Besides, the price of corn has the largest lagged effects on pork price. According to the above empirical results, we suggest that government should strengthen monitoring and early warning of the swine industry chain, especially the upstream and midstream, attach great importance to the timely adjustment of feed prices and perfect the measures of price subsidy.

Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China.In the process of determining the structure of the chaotic neural network,the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension,and then the number of hidden layer nodes is estimated by trial and error.Finally,this model is applied to predict the retail prices of eggs and compared with ARIMA.The result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of eggs.The empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.

Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parameters

Waterlogging is becoming an obvious constraint on food production due to the frequent occurrence of extremely high-level rainfall events.Leaf water content(LWC)is an important waterlogging indicator,and hyperspectral remote sensing provides a non-destructive,real-time and reliable method to determine LWC.Thus,based on a pot experiment,winter wheat was subjected to different gradients of waterlogging stress at the jointing stage.Leaf hyperspectral data and LWC were collected every 7 days after waterlogging treatment until the winter wheat was mature.Combined with methods such as vegetation index construction,correlation analysis,regression analysis,BP neural network(BPNN),etc.,we found that the effect of waterlogging stress on LWC had the characteristics of hysteresis and all waterlogging stress led to the decrease of LWC.LWC decreased faster under severe stress than under slight stress,but the effect of long-term slight stress was greater than that of short-term severe stress.The sensitive spectral bands of LWC were located in the visible(VIS,400–780 nm)and short-wave infrared(SWIR,1400–2500 nm)regions.The BPNN Model with the original spectrum at 648 nm,the first derivative spectrum at 500 nm,the red edge position(λr),the new vegetation index RVI(437,466),NDVI(437,466)and NDVI´(747,1956)as independent variables was the best model for inverting the LWC of waterlogging in winter wheat(modeling set:R^(2)=0.889,RMSE=0.138;validation set:R^(2)=0.891,RMSE=0.518).These results have important theoretical significance and practical application value for the precise control of waterlogging stress.

Using the DSSAT model to simulate wheat yield and soil organic carbon under a wheat-maize cropping system in the North China Plain

Crop modelling can facilitate researchers＇ ability to understand and interpret experimental results, and to diagnose yield gaps. In this paper, the Decision Support Systems for Agrotechnology Transfer 4.6 （DSSAT） model together with the CENTURT soil model were employed to investigate the effect of low nitrogen （N） input on wheat （Triticum aestivum L.） yield, grain N concentration and soil organic carbon （SOC） in a long-term experiment （19 years） under a wheat-maize （Zea mays L.） rotation at Changping, Beijing, China. There were two treatments including NO （no N application） and N150 （150 kg N ha-1） before wheat and maize planting, with phosphorus （P） and potassium （K） basal fertilizers applied as 75 kg P205 ha-1 and 37.5 kg K^O ha-~, respectively. The DSSAT-CENTURY model was able to satisfactorily simulate measured wheat grain yield and grain N concentration at NO, but could not simulate these parameters at N150, or SOC in either N treatment, Model simulation and field measurement showed that N application （N150） increased wheat yield compared to no N application （NO）. The results indicated that inorganic fertilizer application at the rates used did not maintain crop yield and SOC levels. It is suggested that if the DSSAT is calibrated carefully, it can be a useful tool for assessing and predicting wheat yield, grain N concentration, and SOC trends under wheat-maize cropping systems.

Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework

The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was

Review on the Work of Agriculture Ontology Research Group

This paper introduces efforts and achievements of Agriculture Ontology Service Research Group of Agricultural Information Institute of Chinese Academy of Agriculture Sciences in last 10 years. It summarizes the research on ontology construction methodology, ontology management system, ontology application and etc.

Is the crop insurance program effective in China? Evidence from farmers analysis in five provinces

This paper aims to evaluate the effectiveness of the Chinese crop insurance program in terms of farmers＇ utility and welfare. A simulation model based on the power utility function was first developed to evaluate the effectiveness of crop insurance. Then, the Monte Carlo approach was used to generate the datasets of area, price, yield, cost, and income based on the characteristics of representative farmers, which were clustered and calibrated using the farm-level data of 574 individual farmers from five Chinese provinces. Finally, the effectiveness of Chinese crop insurance was evaluated by comparing the certainty equivalence（CE） of farmers＇ utility/welfare under alternative crop insurance scenarios. Government subsidy is a necessary premise for implementing the crop insurance program. The government should subsidize more than 50% of the crop insurance premium to motivate more farmers to participate in the program. The findings also show that the current crop insurance program in China has increased the farmers＇ welfare but still need to be improved to achieve the Pareto improvement and to make full use of the financial fund of the government. This paper is believed to not only extend academic research but also has significant implications for policymakers, especially in the context of rapid development of Chinese crop insurance with much issues such as rate, subsidy and coverage level needed to be improved.

Urban Residents' Consumption Risk Perception about the Dairy Products

Based on the continuous downturn puzzle of Chinese dairy consumption,with the perception of consumption risk as a starting point,the paper deeply analyzes the main factors which cause the downturn of dairy product consumption of Chinese residents. The results show that the income elasticity of dairy consumption of Chinese urban residents is still notable; the occurrence of dairy safety incidents improves the perception of consumption risk,and accordingly it reduces the promoting role of income to the dairy consumption; the safety incident is the key factor which leads to the fall of dairy consumption of urban residents in recent years,and the perception of consumption risk of lower income group is clearly higher than that of higher income group.

Research and Analysis on Difference in Per Capita Net Income of Chinese Rural Residents

The study aims to understand the variation of difference in per capita net income of rural residents during China's economic development in recent years. The writer studies and analyzes rural residents' income gap between 1997 and 2008 with relevant theories of income difference and the calculation of absolute difference index as well as relative difference index and obtains the conclusion that absolute difference of Chinese rural residents' income experienced an upward trend while relative difference generally remained constant with slight fluctuation and growth, which reflects that rural residents' income gap is increasing gradually. The writer also puts forward some related proposals and countermeasures.

Personalized topic modeling for recommending user-generated content

User-generated content(UGC) such as blogs and twitters are exploding in modern Internet services. In such systems, recommender systems are needed to help people filter vast amount of UGC generated by other users. However, traditional recommendation models do not use user authorship of items. In this paper, we show that with this additional information, we can significantly improve the performance of recommendations. A generative model that combines hierarchical topic modeling and matrix factorization is proposed. Empirical results show that our model outperforms other state-of-the-art models, and can provide interpretable topic structures for users and items. Furthermore, since user interests can be inferred from their productions, recommendations can be made for users that do not have any ratings to solve the cold-start problem.