农林环境机器视觉导航路径生成算法及应

提出两种自然环境中的路径导航线生成算法:对于矮小作物规则分布的农田场景,在标准Hough变换的基础上,预先检测共线点峰值的限定偏角阈值,以迅速检测关键信息;对于林地环境及类林地环境的高大作物农田场景,寻找树干与地面的交点,形成机器人行走的左右边界,再求两边交点的中值产生一列点簇.对该列点簇进行Hough变换检测直线作为导航线,或应用最小二乘法拟合左右边界,求其中线作为路径导航线.Matlab对比仿真表明,几种算法对各自适用的场景具有可靠稳定的路径辨识能力,可对图像进行有效的批量处理.     

浅述旋耕刀设计技术的发展

我国是一个农业大国,旋耕机是主要的农田耕作机械.旋耕刀作为旋耕机的重要部件,一直是旋耕机设计者研究的主要内容[1].提高效率、降低功耗是旋耕刀设计的两个主要目标.针对这两个目标,浅述了国内外的主要研究成果.随着科学技术的发展,旋耕刀的设计研究手段也发生了变化,以计算机模拟技术和网络CAD系统为例,来说明数字化设计技术已逐步被引用到旋耕刀的设计制造领域.数字化设计技术将会使旋耕刀的设计及制造发生革命性的变化.     

农作物固体废弃物致密成型燃料能量学对比分析

选取主要农作物固体废弃物为研究对象,综合考虑其热力学特性以及成型设备工程技术参数,对农作物的固体废弃物致密成型燃料与煤的能量学进行了比较研究。结果表明,对于秸秆类的固体废弃物致密成型燃料,由于其生产耗能高,仅当煤从生产地到使用地之间的输送距离超过4 000 km时,此类固体废弃物致密成型燃料与煤具有近似同等的能量竞争力;而对于果壳类的固体废弃物致密成型燃料,其生产耗能较低,临界输送距离较短。当煤从生产地到使用地之间的输送距离超过2200 km时,基于果壳类的固体废弃物致密成型燃料比煤更有能量优势;当煤从生产地到使用地之间的输送距离处于1500～2200 km时,基于果壳类的固体废弃物致密成型燃料与煤具有近似同等的能量竞争力;当煤从生产地到使用地之间的输送距离小于1000 km时,则基于果壳类的固体废弃物致密成型燃料失去了能量优势。     

“农民参与式”木薯研究与推广的10年实践探讨

本文就中国热带农业科学院品资所于1994-2003年间所采用的“农民参与式”在木薯推广中的方法、过程、结果和成果进行了总结,并探讨成功的协作模式及解决存在问题的良策;概括“农民参与式”的概念、作用、意义。指出其发展前途。     

美法两国区域农业的发展及对中国农业发展的启示

中国是一个农业大国,区域差异明显;不同的区域,其农业发展方向与重点也有所不同;与国外发达国家相比,我国的区域农业并没有得到很好的发展。本文从对美、法两国的区域农业专业化发展进行分析,论述美、法区域农业专业化发展的做法和措施;其中包括：农业的科技推广、教育、以及政府的支持等方面;从而得到一些对中国区域农业发展的启示。     

农业非点源污染国内外研究进展

农业非点源污染正日益成为水体富营养化最主要的污染源,并已成为当前限制我国经济可持续发展的重要因素。笔者从农业非点源污染物迁移转化机制、非点源污染物的防控机制、非点源污染模型模拟、农业非点源污染研究中的尺度问题等方面对国内外研究进展进行了论述。提出我国非点源污染研究需在以下方面有所加强：（1）非点源污染物耦合作用下的运移;（2）转化机理及其界面行为过程机制研究;（3）不同空间尺度和格局农业非点源污染物的迁移转化规律;（4）适合我国不同区域特色的非点源污染机理模型研究。     

基于应用型人才培养教学中思政教育的融入策略实施

思政教育是高职院校教学的重点内容,对学生的思想、行为会产生直接影响,同时与工匠精神存在紧密关系,需要对其予以融合。为了提升高职机械类专业教学的质量,引入思政教育极为重要,其在推动学生全面发展方面也发挥出了重要作用。基于此,主要以机械基础类专业教学为例,分析了高职机械类专业课程与思政教育的联系为切入点。同时,通过调整教学思路与路径,结合机械发展史展开思政教育,引入大国重器实际研发案例,落实全面评价这些思政教育的融入策略。     

The concept of habitat specificity revisited

Habitat specificity indices reflect richness (α) and/or distinctiveness (β) components of diversity. The latter may be defined by α and γ (landscape) diversity in two alternative ways: multiplicatively () and additively (). We demonstrate that the original habitat specificity concept of Wagner and Edwards (Landscape Ecol 16:121–131, 2001) consists of three independent components: core habitat specificity (uniqueness of the species composition), patch area and patch species richness. We describe habitat specificity as a family of indices that may include either area or richness components, or none or both, and open for use of different types of mean in calculation of core habitat specificity. Core habitat specificity is a beta diversity measure: the effective number of completely distinct communities in the landscape. Habitat specificity weighted by species number is a gamma diversity measure: the effective number of species that a patch contributes to landscape richness. We compared 12 habitat specificity indices by theoretical reasoning and by use of field data (vascular plant species in SE Norwegian agricultural landscapes). Habitat specificity indices are strongly influenced by weights for patch area and patch species richness, and the relative contribution of rare vs. common species (type of mean). The relevance of properties emphasized by each habitat specificity index for evaluation of patches in a biodiversity context is discussed. Core habitat specificity is emphasized as an ecologically interpretable measure that specifically addresses patch uniqueness while habitat specificity weighted by species number combines species richness and species composition in ways relevant for conservation biological assessment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Modeling the water budget in a deep caldera lake and its hydrologic assessment: Lake Ikeda, Japan

The hydrologic assessment of a lake water budget can be helpful in achieving proper water management and sustainable water use. A model to analyze a lake water budget was developed and verified for Lake Ikeda, Japan. Lake evaporation was estimated by numerical analyses of lake water temperature and the lake energy budget. Inflow from the lake catchment area and leakage from the lake bottom were estimated based on the tank model and Darcy's law, and the model parameters were optimized by the shuffled complex evolution method. The estimated monthly lake evaporation rate is consistent with the evaporation rate estimated by the energy budget Bowen ratio method based on in situ data from 2004 to 2005. Moreover, the calculated time series of daily lake levels agrees well with those of measured lake levels during 1983 to 1999. Thus, the model is useful for evaluating the lake water budget. Numerical analysis reveals seasonal and annual variation characteristics in the water budget components. Precipitation, inflow from the catchment area, and river water supply are generally high during the rainy season from June to July with substantial annual variation. Lake evaporation is greatest in October and least in April, but the annual variation is relatively small. Agricultural water use is relatively high from April to September. There are no marked seasonal changes in leakage and drinking water use. The lake level is generally highest in September and lowest in March, which is characterized by seasonal changes in water budget components. The model was also applied to 17-year simulations under hypothetical hydrologic conditions to examine the effect of water use and agricultural water management on the lake level. Results indicate that river water supply, provided under the agricultural water management system, effectively compensates for the decrease in lake water resulting from agricultural water use.     

Combined use of optical and radar satellite data for the detection of tillage and irrigation operations: Case study in Central Morocco

The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season.The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations.The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.