基于模型和WebGIS数字农作支持系统的设计与实现

基于系统用户需求及现有农作模型特点,研究GIS技术与农作模型集成的机制与方法,提出了"XML技术+自定义地图引擎"的技术思路,设计了合理的系统体系结构。运用软构件技术,基于B/S(Browser/Server)的分布式网络技术,以WebGIS为空间信息管理平台,建立了基于模型和WebGIS的数字农作支持系统(MGDFSS)。该系统实现了基本地图操作、农作空间信息管理、作物生态区划、种植制度设计、栽培方案设计、生长模拟预测、管理策略分析、生长监测与调控、精准农作处方、生产力分析、专家咨询以及系统维护等综合功能。该系统的建立和应用可显著提升农作生产过程的数字化表达与信息化管理,促进数字农作技术的发展。

Bio-Economic Strategy to Combat Non-Point Pollution in China

While non-point pollution from agriculture has become an increasingly serious problem in China, some progress has been made in studying the causal biophysical processes. However, few studies have assessed the economic consequences of non-point pollution in China or the policy options that could be employed to combat it. In this work a sustainable strategy to control non-point pollution from crop production, which involved taxing excessive inputs of irrigation water and fertilizer, was proposed. The approach taken to assess these measures combined biophysical and economic models,having a trade-off between economic returns and an improved environment. A proven and practical spatially referenced water and nutrient management model was used to determine the quantities of excessive irrigation water and fertilizer for specific soil and land use. Also, a set of indicators were proposed for evaluating the effects of agricultural economic output and agricultural practices on the environment.

Using Logistic Regression to Identify the Entrepreneurial Capability of Thai Agricultural Cooperatives Members on Their Farm Management

This study elaborates three things： Firstly is the current agricultural cooperatives management and their low farm performance in eight provinces in the eastern of Thailand where are the bases of Thailand famous fruits products. Secondly is to point out the key concepts of the theory of entrepreneur and the strength of it to assist the community development, to teach young people, adults and cooperatives members to prepare them to pertain good entrepreneurship that meets cooperatives concepts and principles. Thirdly is to give an example of research study that describes how to identify entrepreneurial capability of agricultural cooperatives members in Thailand, dependent variable is qualitative or binary, we use ＂odds value＂ or probability of success over the probability of failure to identify the set of odds value, and use exponential function to transform the odds value to be the log of odds or Logit model. If probability of entrepreneur is over the cutting point of 0.8, it implied that members are pertained high entrepreneurial capability and vise versa. The first step of research is the analysis of five year panel secondary data during 2011-2015, collected from Cooperatives Auditing Department. Eight groups of 679 numbers of data from 215 cooperatives were calculated, data were divided by the number of member. These eight independent variables are Total income per member, Total equity per member, Net profit per member, Co-ops operating capital per member, Total cooperatives capital per member, Total deposit per member, Total asset per member, Number of member. Qualitative data are the four sizes of cooperatives： large, big, medium, and small. Qualitative data are the only one intervening variable in the model. Secondary data found that only four quantitative independent variables effect to entrepreneurial capability. Total asset per member, and Total income per member had negative effect, but Net profit per member, and Cooperatives capital per member had positive effect. It means that if cooperatives acquire more and more asset, cooperatives will have more burden of debt or equity and probability of entrepreneur will be decreased. If cooperatives gain more and more income to the firm, it means the complex organization or the cooperatives will success but the individual member who is individual finn will get loss. Cooperatives capital per member and Net profit per member have positive effect. Because cooperatives capital were gained from residual and after the allocation of cooperatives surplus to be patronage refund according to the volume of business which member had done with the cooperatives and dividend pay out to member according to the number of stocks they held for their saving with the cooperatives. For qualitative variable, large and medium size of cooperatives had no any effects, but small size of cooperatives had more effect than the big size. It implied that big cooperatives who had more and more number of members have more and more burden. Small size of cooperatives is similar to individual firm of each member. Thus, optimum size of cooperatives is suitable for their service and efficient management, if the size of business volume increasing continuously, the quality of service will decrease, because almost cooperatives organization is pricing at break even point. Second step is a primary survey of data from Rayong province. Seventy-five samples of cooperatives members have not recorded their business information, both revenue and cost. We cannot use logistic regression to run the second model, but only Multiple Regression Analysis （MRA）. MRA results identify that the cooperatives profit of each member depends on three variables： （1） sales, （2） member responsibility （not board member responsibility or Management responsibility）, （3） member＇s level of education. Suggestion and recommendation is that agricultural cooperatives members in Thailand still have to improve their entrepreneurial capability by recording all information related to business functions and prepare financial record to represent efficient use of resources to meet member and community＇s needs.

Modeling Farm Management Modernization： Case Study of Japanese Rice Farming Corporations

While conventional family-owned and family-operated farms remain the most common structure, the number of Japanese agricultural corporations has increased in recent years as a result of changing policies. Some of them are possibly starting to adopt modem corporate management practices to remain viable in a more competitive environment. However, changes in the business structure have not always been accompanied by changes in farm management practices. This study represents a theoretical and empirical investigation into farm modernization practices to provide perspective and recommendations to enhance farm business. Various aspects of farm modernization were considered, including temporal, economic and functional modernization. Critical elements of farm modernization were examined using a structural equation model of surveys, wherein questionnaires were delivered to 2,260 agricultural corporations across Japan in 2014 and 2016, generating 669 usable responses from rice farming corporations. Overall, these corporations demonstrated moderate degrees of modernization, indicating that they have not yet completely transitioned from conventional management styles to modem corporate management and that the farm-household complex system still exists for many of them. It was also found that farm modernization is significantly affected by both production and business management systems, although it was unclear whether a farmer＇s managerial capabilities were critical for farm modernization. The findings of this study indicate that current farming corporations may benefit from incorporating additional modernization practices. The analytical framework and results will help farmers to better understand their management practices and can be used to provide ideas for policy development to promote competitive farm businesses.

Production response to price risk and market liberalization of Nigerian major agricultural crops

This study models supply response for major agricultural crops in Nigeria which include the standard arguments and price risk. The data comes from Central Bank of Nigeria annual reports and statement of account, National Bureau of Statistics＇ abstract of statistics and annual Agricultural survey manual. The data are analyzed using autoregressive distributed lag and cointegration and error correction models. The results indicate that producers are responsive not only to price but also to price risk and exchange rate.