Weed Seedbank Evaluating Method to Generate Spatial Distribution Maps

Abstract

The objective of this work was to develop a fast and practical method of weed seedbank evaluation to generate spatially distributed maps for use in site-specific weed management. Soil cores were collected at 0.20 m depth, air-dried, and then submitted to seedling growth in greenhouse. The sampling grid of 20 by 20 m was georeferenced by Global Positioning System, obtaining 73 soil cores with three replicates. During the greenhouse trial, there were two peaks of weed seedling growth: one in 119 days after water irrigation and another after KNO₃ application. Weeds seedbank maps were obtained at different stages of seedling growth. The Pearson correlation was 0.99 for Brachiaria plantaginea seedbank map, 0.95 for Commelina benghalensis, and 0.85 for Cyperus rotudus generated at 119 days compared with 392 days after seedling growth in the greenhouse. The Brachiaria plantaginea seedbank map evaluated at 35 days presented correlation of 0.97 with 392 days. It was concluded that, for site-specific weed seedbank management, the evaluation of seedling growth in greenhouse until the first emergence peak is enough to generate weed seedbank maps.     

土壤重金属监测过程及其质量控制

重点探讨了土壤中典型重金属含量监测过程中样品制备、含水率、预处理等因素对分析结果的影响。实验结果表明,充分风干土壤的含水率在2%～3%左右,200目土壤颗粒度可满足分析精度的要求。硝酸-氢氟酸-高氯酸的多元混酸消解体系可实现对土壤重金属的充分溶解,对标准土壤样品中各元素的回收率可达84%～98%。批次内平行样品以及批次间质控样品各元素的相对标准偏差大都小于10%,符合《土壤环境监测技术规范》的要求,表明该研究建立的系统土壤重金属检测方法结果准确可靠。     

直齿圆柱齿轮精锻技术的研究进展

综述了直齿圆柱齿轮精锻技术的特点和研究现状,并对其前沿问题和发展趋势进行了探讨.     

Prediction Intervals for Estimates of Site Index Based on Ecosystem Type

/ British Columbia has an ecosystem classification system that classifies sites into site series. Foresters commonly measure the productivity of these sites by their site index. In British Columbia, site index is defined as the height of a stand at breast height age 50 and is usually estimated from height-age models. Biogeoclimatic site series/site index relationships are an increasingly popular method of estimating site index in British Columbia for stands where site index cannot be reliably estimated with height-age models. The precision of the predicted site index from these relationships can be evaluated with prediction intervals. This is done for the predicted site index of a single site, a group of sites, or the areally weighted site index of a group of sites. The methodology is also useful in determining the number of sites required to meet a specified precision. These prediction intervals will assist foresters in making sound forest management decisions.KEY WORDS: Biogeoclimatic Ecosystem Classification; Precision; Prediction interval; Site index; Site series     

The potential of remote sensing data for decision makers at the state, local and tribal level: experiences from NASA’s Synergy program

NASA’s Earth Observation System (EOS) satellite data are contributing to the development of policy relevant, remote sensing applications. To promote the use of EOS data for application development, NASA funded the Synergy program in 2000 in partnership with academia, end users, and industry. Three examples of remote sensing applications from the Synergy program are presented here and include agriculture, range management, and water resource management. These examples show that remote sensing products have the potential to be useful to a variety of decision makers and policy makers because of the opportunity to reduce chemicals in the environment, improve crop yields and better manage range lands and water resources. Transitioning from research and development to successful applications must overcome challenges such as the lack of awareness by end users of these technologies, inadequate feedback mechanism between application developers and end users, and unproven cost benefits of remote sensing data. Experience from the Synergy program indicates that these issues could be mitigated by educating and training end users, demonstrating the utility of remote sensing data in improving decision making, and establishing and maintaining a continuous dialogue between developers and end users. Sustainability of remote sensing applications ultimately depends on users continuing reliance on products and benefits from remote sensing data. The Synergy program also demonstrates that remote sensing data sets that are collected primarily for global change research contribute to the development of applications in a variety of disciplines at the regional and local level.     

基于特征和知识的精密注塑模设计和制造系统

采用先进的CAD/CAM技术对传统模具设计制造方法进行改造,是提高模具设计制造质量和效率的关键.此文提出基于特征和知识的才法构造精密注塑模设计和制造系统,并介绍了系统的总体方案和系统包含的各模块功能.这一系统是浙江省科委八五攻关项目“精密注塑模设计和制造(CAD/CAM)技术”的核心.     

带轮毂直齿圆柱齿轮精锻的变形分析

此文对空心坯料精锻带轮毂直齿圆柱齿轮工艺进行了模拟实验,并以座标网格法着重对精锻终了阶段进行了变形分析,获得了金属流动规律,提出了对制订精锻工艺有参数价值的结论。     

高压闷罐与普通敝口容器消解土壤的对比实验研究

土壤（底质）环境样品的消解直接关系到测定结果的好坏，通过对比实验证明，高压闷罐法消解土壤（底质）比普通法具有消解完全，精密度和准确度高，重现性好等优点。     

Using accelerometer,high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.     

Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management

The Lower Rio Grande Valley (LRGV) of south Texas is an agriculturally rich area supporting intensive production of vegetables, fruits, grain sorghum, and cotton. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yields. Intensive agricultural activities in past decades might have caused potential contamination of soil, surface water, and groundwater due to leaching of pesticides in the vadose zone. In an effort to promote precision farming in citrus production, this paper aims at developing an airborne multispectral technique for identifying tree health problems in a citrus grove that can be combined with variable rate technology (VRT) for required pesticide application and environmental modeling for assessment of pollution prevention. An unsupervised linear unmixing method was applied to classify the image for the grove and quantify the symptom severity for appropriate infection control. The PRZM-3 model was used to estimate environmental impacts that contribute to nonpoint source pollution with and without the use of multispectral remote sensing and VRT. Research findings using site-specific environmental assessment clearly indicate that combination of remote sensing and VRT may result in benefit to the environment by reducing the nonpoint source pollution by 92.15%. Overall, this study demonstrates the potential of precision farming for citrus production in the nexus of industrial ecology and agricultural sustainability.