阻隔法防治草履蚧研究

通过对草履蚧[Drosicha corpulenta (kuwana)]进行胶环，毒环，绑扎塑料裙和毒绳等阻隔试验，结果表明，应用废机油加羊羊脂（5:1)进行涂环阻隔防治，效果最好，其粘性持续时间达到80－120d，利用“阻隔法”防治草履介的防治最佳时期应设在草履蚧卵开始孵化至上树前的1月上旬－2月上旬。     

杀螟·噻嗪酮乳油防治松褐天牛的研究

To control Monochamus alternatus and its amount of population is one of the effective ways on controlling Bursaphelechus xylophilus.The Japanese black pine which were badly harmed by M.alternatus were sprayed with the ditution from diluting fenitrothion · buprofezen 50%EC with water to 100 times, 200 times and 300 times. In this trial, the treatment is divided into two groups: one is of the different concentration but the same object (trees in the forest), the other is of the same concentration but different environmental condition (trees in the forest and felling trees indoor). Each treatment repeated five times. In the meantime, the check is not treated. After twice trial, the result indicated that the mortality rate of M. alternatus is 71.33%, 52.31% and 37.82% in the condition that trees in the forest were sprayed with the 100 times, 200 times and 300 times fenitrothion·buprofezen, and 69 69% in the condition that the felling trees indoor were spraded with 100 times fenitrothion·buprofezen, but the mortality rate of the check is only 8.92%. By this trial, it was also found that the dead adults of M.alternatus laid in the entrance of emergance hole, so enhancing the somatic character of fenitrothion · buprofezen can enhance the injury ratio of larva and pupae of M.alternatus.     

柳杉长卷蛾(Homona issikii Yasuda)的重要天敌短角宽扁蚜蝇(Xanthandrus talamaoi(Meigen))

在对四川洪雅林场柳杉长卷蛾危害调查中，发现一种柳杉长卷蛾（Homona issikii Yasuda)的捕食性天敌－短角宽扁蚜蝇（Xanthandrus talamaoi(Meigen)）（食蚜蝇科Syrphidae)。该蝇在幼虫阶段取食卷蛾幼虫，捕食量日均约0.56-0.65头，蝇虫比例随害虫虫口密度增加，在林间诸种天敌中居优势地位，对抑制柳杉长卷蛾的危害具有重要作用。     

The application of rough sets-neural network theory to mine ventilation system evaluation

To solve the instability problem of established sample in the neural network evaluation method for mine ventilation system, a comprehensive evaluation of the ventilation system is carried out based on rough sets and BP neural networks. Taking the ventilation system of a mine as an example, the classification quality of raw data samples are tested by using rough set data analysis system. Then, based on artificial neural network theory, a rough sets-neural network evaluation model of a mine ventilation system is established and a new rough sets-neural network evaluation method of mine ventilation system is formed. The results show that, after the model validation of data and application, its theoretical evaluation results are in line with the actual situation, and the network total error is less than 0.004. It shows that the comprehensive evaluation method based on rough sets-neural networks has a good effect in evaluating mine ventilation system in practical application.     

葡萄利用结果枝副梢二次结果栽培试验

摘要：在桂林葡萄产区开展利用结果枝副梢促花二次结果的栽培试验，总结在新梢生长期喷多效唑（或矮壮素）、对新梢重度修剪促进冬芽提早萌发是整齐促放葡萄二茬果的关键技术，观测了二茬果果品品质和效益，提出了生产二茬果注意的技术问题。     

棉花黄萎病抗性鉴定新方法——无底塑钵菌液浇根法

通过一系列的试验 ,笔者发展了一种快速鉴定棉花品种抗黄萎病性能的新方法—无底塑钵菌液浇根法 ,此法比传统的纸钵撕底醺根法更简便 ,发病较轻 ,能准确客观地反映品种的抗性     

四川旱耕地生产、生态问题及水土流失综合治理研究

四川地域辽阔 ,地貌以山地和高原为主 ,农耕地分布范围广 ,旱耕地比重大 ,水土流失和与之相关的旱、洪灾害等生产、生态问题突出 ,既导致农作物产量低而不稳 ,又给长江中下游带来安全隐患 ,因此 ,四川在实施西部大开发战略中 ,除实施天然林保护工程外 ,旱耕地 ,特别是旱坡耕地 (2°～ 2 5°)的水土流失综合治理 ,既具有极其重要的战略位置 ,也是四川农业持续发展不能忽视的重大问题     

西安市雨水资源化及其利用的探索

随着城市化的发展 ,城市地表水严重污染 ,地下水超量开采 ,开发利用雨水资源已成为西安市解决水资源问题的最佳途径。雨水是宝贵资源 ,可通过多种方式实现雨水资源化 ,充分利用雨水资源以补给城市水源 ,涵养地下水 ,调节城市生态环境 ,防治雨洪灾害。对西安市区域内雨水下渗和贮存、实现雨水资源化及其利用等方面做了探索 ,并根据实际情况对西安市雨水资源化的必要性、可能性及可持续性进行了分析。     

四川自然土壤和旱耕地土壤可蚀性特征研究

应用美国通用土壤流失方程 (USLE)和土壤侵蚀预报模型 (WEPP)中的土壤可蚀性K值 ,对四川各类自然土壤和旱耕地土壤可蚀性特征进行了研究。结果表明 :土壤可蚀性K值与土壤理化性质直接相关 ,自然土壤和旱耕地土壤可蚀性K值在 0 2 68～ 0 3 44之间 ,紫色土的分布面积和K值较大 ,是易遭受侵蚀的土壤。应采取增施有机肥、实行坡改梯等措施 ,加强对耕地、高可蚀性土壤侵蚀的综合防治     

Combination of GPS monitoring and ANN prediction for slope deformation

Based on the evolution pattern of slope deformation and failure, stability status of a slope is evaluated through analyzing the data of GPS monitoring. A neural network model of slope displacement time is developed based on the GPS monitoring data. It can be used to forecast slope deformation trends. A neural network displacement prediction model of slope deformation is proposed with Matlab ANN toolbox. Upon a case study, the ANN prediction results based on GPS monitoring data are analyzed.