大菱鲆健康苗种高产培育技术

介绍了在大菱鲆苗种培育过程中,添加微藻、有益复合菌、弧菌疫苗,在稳定的水环境中培育健康苗种,取得较高的成活率。     

黄土高原健康生命研究

黄土高原,孕育了中华民族和延续五千年的灿烂文化。但随着历史车轮的向前辗转,黄土高原上出现了生态危机,并且越来越严重。本文运用生态伦理学的有关理论,根据黄土高原的基本特征和所面临的危机,提出了黄土高原健康生命的概念,以及建立黄土高原健康生命的目的,并尝试建立起黄土高原健康生命的指标体系。最后在此基础上探讨了维持黄土高原健康生命的途径。旨在通过此类研究唤起人们对黄土高原的重新认识,唤醒人类对黄土高原的尊重,我们要视黄土高原为一生命体,与之和谐相处,做到可持续发展。     

奶牛常用饲料中毒的预防与治疗

随着牛肉制品和乳制品需求量的增多,我国养牛业规模也在逐渐增大,反刍动物饲料市场快速发展,从每年全国饲料质量安全监测结果来看,国内饲料产品总体合格率超90%。但个别散养户在奶牛养殖过程中,为降低成本,会给奶牛饲喂农业生产中的副产品,若加工或饲喂方法不当,会引起奶牛中毒,威胁乳制品安全。从其生产中常用的农副产品来看,主要包括玉米、马铃薯、棉籽饼、白菜、萝卜和地瓜等,但是采摘时节不对、贮存条件不合理、饲喂前未进行检查等,奶牛会因食用变质饲料而损害瘤胃和整个机体健康。由于这种饲料源性中毒往往引发急性症状,若养殖人员经验不丰富或日常护理不当,会造成奶牛死亡,严重影响养殖效益。鉴于此,本文对奶牛常用饲料的中毒症状、治疗方法和预防措施进行概述,以期提高奶牛饲料安全性,促进我国奶牛养殖业健康发展。     

大学生品行实践学分评定的实践探索与理论思考

设立学生品行实践学分,是思想政治理论课教学改革深化的必然结果和必要举措,是社会主义大学培养合格人才的要求,是马克思主义理论教育的需要,是大学生全面健康发展的重要保证。品行实践学分评定工作的具体开展要有利于促进学习,改进学风;有利于发挥引导作用,切实育人;有利于各方形成合力,共同育人;有利于以人为本,科学发展。     

长沙市城市森林健康调控试验及初步结果

以长沙市王陵公园为试验点,开展城市森林健康调控试验,采用害虫综合调控方法,运用生物天敌调控、生物药剂控制、物理防治等方法对该公园内的主要森林害虫,如马尾松毛虫,白蚁科、金龟子科、夜蛾科、天蛾科等的害虫,降低了虫口密度,保持了林分内的生态平衡,为城市森林健康的维护提供了新的综合途径。     

植物健壮素对辣椒农艺性状的影响

[目的]为辣椒的长季节优质栽培提供理论依据。[方法]采用不同浓度植物健壮素（稀释500、750、1 000倍）对辣椒进行不同间隔时间（4、7、10 d）的处理,以清水处理为对照,研究不同处理对辣椒生长势、结果性、果实商品性和产量的影响。[结果]植物健壮素稀释1 000倍,间隔用药时间为7 d的处理可提高辣椒株高10.5%、茎粗8.5%和开展度10.2%,同时可提高辣椒的结果率（＋17%）,使辣椒商品率达95.0%,产量达17 976.0 kg/hm2,比对照高18.9%。[结论]植物健壮素对辣椒的最佳使用浓度为稀释1 000倍,最佳间隔用药时间为7 d。     

健康家兔肠道中乳酸菌的分离鉴定

本试验选用MRS、MRS+10%家兔硬粪浸出液和MRS+10%泡菜汁3种选择培养基,对健康家兔肠道的乳酸菌群分别进行需氧和厌氧培养,根据可培养细菌菌落特征、染色特性、显微镜形态观测,共分离出7株乳酸菌株,其中需氧菌2株,厌氧菌5株。结合生化试验初步鉴定,需氧菌株分别为乳酸乳球菌和短乳杆菌,厌氧菌株分别为嗜酸乳杆菌,嗜粪乳杆菌,肠乳杆菌,乳酸乳杆菌和弯曲乳杆菌。本实验为弄清健康家兔肠道的有益菌群,以便下一步制作更易于在畜禽的肠道中定植存活的复合动物微生态制剂做准备。     

中兽医药技术是猪只康养最佳供给体系

在我国养猪业面临产品安全和环境污染两大瓶颈的情势下,如何使所生产的猪肉食用卫生,所排粪污环境安全,纯天然、无污染、广效低毒、绿色环保的中兽医药学为破解这两大瓶颈提供了技术支撑。充分发挥我国传统的中兽医药技术的特色和优势,构建以中兽医药为主体的猪只康养技术供给体系,旨在集生产管理"适其天性"、所喂药料"无污染"、治疗药物"纯天然"、预防措施治"未病"、治疗方法"和谐调节"和四季保健"药饲同源"于一体的技术供给体系,从源头上破解这两大难题,从而实现猪只康养,环境安全,猪肉安康,凸显出中兽医药是猪只康养的最佳供给体系。     

Optimum Planting System for Energy Saving and Healthy Demanded

It is proved that planting is effective to improve environment both indoor and outdoor resulted from the functions of plants to clean air and save energy. So the contradiction between saving energy and comfort,healthy demanded by people can be solved by planting. The planting have being emphasized and expanded during recent years,but in the planting plan,just the function of beautifying the environment is concerned and the function of ecological and saving energy are neglected. The analysis on the ooptimum system of planting is to make the planting system as an organic composition in the effectiveness structure and space layout of the city. Based on the study on equivalent relation of different effects on environment, the optimum system of planting structure will be determined in order to achieve the integrated effects of planting on environment.     

Prediction of pine mistletoe infection using remote sensing imaging: A comparison of the artificial neural network model and logistic regression model

In this study, the prediction of pine mistletoe distribution in Scots pine ecosystems was explored using remote sensing variables to compare the multilayer perceptron (MLP) artificial neural network (ANN) and logistic regression (LR) model performances. For this purpose, 109 sample plots were distinguished in pure Scots pine forests (natural) in the Eastern Black Sea Region of Turkey. Distinguishing mistletoe-infected stands (69) and uninfected stands (40) was performed with field observations. The variables acquired from Landsat 8 (Level 1) images were used as independent variables for independent-sample t-test, MLP ANN and LR models. Remote sensing variables indicated that mistletoe-infected stands were in drier areas with a lower vegetation-leaf area index. Based on the performance results of both models, the sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV) and accuracy of the MLP ANN model were superior to those of the LR model. The prediction percentages (SEN, SPE, PPV and NPV) of mistletoe-infected stands were better than the prediction percentages of uninfected stands. The prediction accuracies of LR and MLP ANN models were 74.3% and 89.6%, respectively. However, all remote sensing variables were included in the prediction equation of the MLP ANN model, while the thermal infrared 1 (TIRS1) variable was included in the LR model. In the MLP ANN model, the TIRS1 variable also had the highest normalized importance (100%). The area under the curve (AUC) value for identifying the mistletoe-infected stands of Scots pine forests used by the MLP ANN model (0.892 ± 0.034) was higher than in the LR model (0.838 ± 0.039), explaining the more accurate predictions obtained from the MLP ANN model. The MLP ANN model showed much better performance than the LR model. The results of this study are expected to make important contributions to the identification of potential mistletoe-infected areas.