Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods

The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.     

基于电子经纬仪及PDA自动量测的电子角规测树原理、功能及精度研究

针对常规角规测树较为粗放的现状,为了满足精准林业的需要,实现单木和林分精准测量,该文以电子经纬仪和掌上电脑为硬件,经PDA编程开发,形成电子角规测树系统,充分发挥了电子经纬仪精密的测角功能和PDA强大的数据处理和存贮功能.利用电子角规可获得树木树干的胸径、树高、任意处直径和材积,树冠部分的表面积和体积,林分的胸高断面积、林分平均高、平均株数、蓄积量和生长量等数据.经过分析,电子角规测树精度为1/7 000,而比特利希角规测树精度总误差达1/32,电子角规的测树精度比普通角规高出200倍以上,其速度也较快.     

烤烟施肥数学模型及推荐施肥专家系统研究

通过分析衡阳烟区烤烟3414肥效试验数据,获得了衡阳烤烟精准施肥的相关技术参数,筛选出了植烟土壤有效养分校正系数估算的最佳数学模型;并依据斯坦福施肥量计算公式W=(U-Ns)/R,结合烟叶目标产量、植烟土壤速效养分测试值及实际施肥纯量等指标,建立了N、P、K施肥用量(Y)同烟叶产量(X_1)和烟田土壤养分含量(X_2)的二元一次回归数学模型;将最适施肥的数学模型及计算过程置入Excel软件和安卓智能手机APP中,构建了烟草推荐施肥专家系统。该系统能简单方便地指导烟户因地制宜地精准施肥,同时通俗易懂、可行性高,适合基层技术人员及农户使用。     

要正确对待西部种草

西部种草需要正确对待几个问题：良种不是绝对的，与环境协调发展的就是好草种；种草的效益不是单方面的，不是追求单方面的效益；人工草地是现代农业的必要组分，同时不要忽视天然草原；种草不要忽视灌木，清除灌木要慎重；种草要有必要农业投入，应该用好地种草；要以发展动物生产和饲料工业为重点，完善草地农业系统；管理是草业的命脉，应尽早达到草业生产数字化。     

Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate?

This paper reviews the literature concerning the spatial distribution of weeds; highlighting the limitations of our current sampling and analytical methodologies, and suggesting how these inadequacies can be addressed. Most research studies have used discrete sampling, i.e. weeds are counted within a quadrat, on a grid basis. Few have mapped weeds at a whole-field scale, either with a resolution appropriate to spraying operations or key ecological processes. Statistical analyses used to describe the data can be divided into two main types, spatially implicit (also at the scale of the sampling unit) or spatially explicit, in which the location of individuals is included in the analyses. Spatially implicit methods can be strongly affected by quadrat size and mean density and are of doubtful benefit. More attention is required to address sampling resolution issues for spatially explicit methods. Our understanding of the formation and dynamics of spatial pattern, as well as predicting the consequences of site-specific management, can be improved with models. Unfortunately, most models consider only newly expanding patches and appear incapable of predicting spatial distributions when an area has been fully invaded. More detailed biological information is required if models are to become more realistic and informative. We also need to ensure that we understand the spatial processes in the context of the whole field environment, to optimize the success of site-specific weed management in the longer term.     

农业机器人轨迹优化自动控制研究——基于BP神经网络与计算力矩

以农业机器人精密轨迹优化自动控制为目标,在优化算法中引入BP神经网络与计算力矩法结合的自动控制器,旨在减少作业过程中的运动误差,提高其工作效率。首先,建立农业机器人数学模型,分析其运动学和动力学原理;然后,设计了农业机器人运动控制系统,引入BP神经网络对不确定动力学因素进行判断,并提出解决该因素的自适应学习法;最后,对该系统运用Mat Lab进行了仿真。试验表明:以BP神经网络与计算力矩法结合的自动控制器可以有效优化机器人运动路径,提高机器人整体作业效率,系统运行稳定、可靠性强,且对外部环境的干扰因素具有较强的自适应学习能力。     

智能变量施肥技术初步试验研究

结合承担的精确农业变量施肥技术研究项目，提出了智能变量施肥技术体系和实现方法。利用美国MAPINFO公司MapInfo Proression 6．0地理系信息系统，采用MapBasic语言编程，建立了施肥地理信息与决策系统；利用89C52单片机实现智能变量施肥机控制系统。试验表明。研制的智能变量施肥机能够实现精确农业信息控制自动变量施肥作业，为精确农业的进一步试验研究提供技术依据。     

GIS在农业水土领域的应用与研究进展

介绍了近年来国内外GIS在农业灌溉管理、精确农业和农业区划、土壤利用和土壤侵蚀方面的研究和应用情况，并对GIS在该领域的研究进行归纳和总结，此外探讨了GIS在当前农业领域应用的主要发展方向。     

基于姿态实时监测的多路精准排肥播种控制系统研究

针对现有精准排肥播种控制系统缺少对机具姿态进行监测判别的现状,在现有精准排肥播种控制系统架构基础上,增加了机具作业姿态实时监测模块,使系统可以根据机具的实时前进速度和作业姿态自动控制排肥量和播种量,减少人员对系统的操作。该系统主要由车载控制终端、PID控制器、多路集成比例阀、光电转速测试码盘、机具姿态解析模块、机具位置与速度解析模块、液压马达等组成,其中机具姿态解析模块采用MPU6050芯片实时测量下拉杆与机架的俯仰角,应用STM32F103MCU芯片实时获取MPU6050芯片的输出数据,并反馈到车载控制终端,封装后的机具姿态解析模块安装在拖拉机三点悬挂的下拉杆中部,对下拉杆与水平面的夹角数据进行实时记录和反馈,判别机具的作业姿态是否处于工作状态。将该控制系统安装在小麦基肥精准分层施肥播种机上,在北京市昌平区小汤山国家精准农业研究示范基地,对该控制系统进行静态标定和动态试验,以检测可靠性和稳定性。静态标定试验结果显示,马达转速与系统的排肥排种量存在一元线性关系,此时浅层肥料、深层肥料和种子的单圈排量分别为16.97、29.31、11.2g;姿态标定结果表明,设置临界角为5.3°时,系统的机具姿态提示信息正确,能够满足姿态监测的要求;动态试验表明,机具工作状态下,浅层肥料、深层肥料和种子排量变异系数分别为3.5%、3.8%和3%,3路的排量偏差都控制在5%以内,机具抬升状态下,排肥排种轴处于静止状态,说明该系统的运行过程总体比较稳定,能够满足小麦基肥分层施肥播种机具的精量排肥排种的作业要求,同时能够减少人为操作流程。