基于规划的农业信息服务组合研究

将面向服务的计算模型应用于实体动态协作的过程管理,实现各个实体间动态发现、整合和协调互动,提出一种实体信息描述模型和一种分层的实体发现机制,从实体状态与能力信息2个层面实现实体资源的发现,将所得到的实体资源信息与领域本体相结合,把实体目标实现方案的制定问题归结为所得行为与资源的规划问题,并调用B lackBox规划机求解,快速抽取出完成实体目标的方案。     

政府在我国农业保险市场中的作用探析

回顾了我国农业保险的发展历程,介绍并分析了我国农业保险的现状及存在的问题,重点探析政府在发展农业保险市场中的重要作用,最后提出促进我国农业保险发展的政策建议。     

基于贝叶斯分类的农作物产品质量挖掘研究

采用贝叶斯算法的基本原理,并结合农作物生长环境数据的特点,分析和预测了农作物的产品质量。采用随机选取的样本组进行试验预测,预测准确率高,表明该算法是有效的。     

《安徽农业科学}2010年文献计量学分析

以2010年《安徽农业科学》所刊载的学术论文为研究对象,运用文献计量学方法,从载文、作者及引文3个方面进行了统计分析,从中总结一些特点和发展规律,为该刊的编辑和学科工作者进行信息交流提供参考。     

农业清洁生产的逆向选择分析

在农业清洁生产过程中,存在着不完全信息的情况。这种不完全信息的存在将使生产者和消费者产生逆向选择,最终影响农业清洁生产的发展。用信息经济学的理论,分析农业清洁生产中的不完全信息问题,并提出解决建议。     

农业环境资源保护视野下的环境公益诉讼制度

介绍了农业环境资源现状和环境公益诉讼的基本内涵,指出环境诉讼是农业环境资源的重要保障,并就起诉人的资格、受案范围、举证责任的分担、诉讼费用的分摊、救助额度与就济方式的确定问题建构了环境公益诉讼制度。     

关于我国农产品品牌建设的思考

农产品品牌建设有助于提高农产品的竞争力,特别是在我国加入世贸组织之后,进行农产品品牌建设有利于抵御国外农产品的冲击,为农产品出口,占领国际市场提供重要途径.本文主要讨论了农产品品牌建设的意义、存在的问题,提出了农产品品牌建设应采取的主要措施.     

农产品及其加工品中生物胺检测技术的研究进展

对生物胺的来源、种类、作用和危害进行了简要描述,并对农产品及其加工品中生物胺的检测技术做了简要总结。     

Optimized EIF-SLAM algorithm for precision agriculture mapping based on stems detection

Precision agricultural maps are required for agricultural machinery navigation, path planning and plantation supervision. In this work we present a Simultaneous Localization and Mapping (SLAM) algorithm solved by an Extended Information Filter (EIF) for agricultural environments (olive groves). The SLAM algorithm is implemented on an unmanned non-holonomic car-like mobile robot. The map of the environment is based on the detection of olive stems from the plantation. The olive stems are acquired by means of both: a range sensor laser and a monocular vision system. A support vector machine (SVM) is implemented on the vision system to detect olive stems on the images acquired from the environment. Also, the SLAM algorithm has an optimization criterion associated with it. This optimization criterion is based on the correction of the SLAM system state vector using only the most meaningful stems - from an estimation convergence perspective - extracted from the environment information without compromising the estimation consistency. The optimization criterion, its demonstration and experimental results within real agricultural environments showing the performance of our proposal are also included in this work.     

Development of a row guidance system for an autonomous robot for white asparagus harvesting

The special cultivation features of white asparagus pose new challenges to the research and development of the row guidance control. This paper presents a row tracking system of a two-layer structure for an autonomous robot developed to harvest white asparagus. At the low level, two independent speed control loops are suggested to ensure the actual revolutions of the drive motors to follow their demanded values. A cascade control structure, consisting of an inner orientation error controller and an outer lateral offset controller, is proposed for the high level to drive the robot to track the desired trajectory. The most important advantage of the cascade structure is that the inner loop directly regulates the most significant error (the orientation error), which minimizes the impact of the external disturbances upon the outer loop. Moreover, the cascade scheme allows the orientation angle to be limited within a given range. That ensures a collision-free tracking. The controllers are designed based on the traditional proportional-integral-derivative (PID) algorithms. The control parameters are selected by using root locus analysis, which guarantees the system stability. The effectiveness of the proposed control regime is evaluated by numerical simulations and validated by experiments. The experimental results demonstrate that with the suggested row guidance strategy a satisfactory tracking accuracy of ±0.5 cm is achieved.