地方高校精准服务乡村振兴的思路设计

地方高校作为助力地方经济发展的重要力量,是推进乡村振兴战略实施的有力保障。大数据的发展为地方高校精准服务乡村振兴提供了理论和实践指引。从乡村差异出发,挖掘地方高校精准服务乡村振兴的逻辑起点,并以此为基础构建地方高校精准服务乡村振兴的实施路径,将乡村数据资源库、高校资源库作为数据源,通过数据挖掘技术深入发掘各乡村发展需求,并将需求与地方高校进行精准匹配,实现资源合理配置,助力乡村全面发展。     

森林资源二类调查数据处理系统介绍

该系统利用386微机在UCDOS3·0汉字系统的支持下,用FCXbaSe 2.0语言设计而成。     

时序建模及其在农药降解动态模拟中的应用

用数学方法对农药残留量进行预测预报及动态模拟，对于合理使用农药，加强环境保护具有重要意义．作者用时间序列分析的理论与方法，研制农药残留定量预测模型，给出参数估计，提出非平稳时序叠合模型，对农药降解规律进行动态模拟，并以剩余平方和作为优化标准与其他方法进行比较．实例计算结果表明：时序模型预测值与实测值拟合程度优于其他模型，简便实用     

Effects of corn straw or mixed forage diet on rumen fermentation parameters of lactating cows using a wireless data logger

The objective of this study was to evaluate the effect of two different forage types on rumen fermentation parameters and profiles using a wireless data logger. Eight lactating cows were randomly assigned to one of two dietary treatments with a low forage diet with corn straw (CS) or a high forage diet with mixed forage (MF) as the forage source, respectively. Dietary physically effective neutral detergent fiber (peNDF) content was 11.3% greater in CS. Dry matter intake and milk fatty acid content decreased upon CS (P < 0.05). Ruminal pH, temperature and oxidation reduction potential (ORP) were monitored for 14 weeks. The CS group had significantly higher pH but lower temperature and ORP compared to MF (P < 0.01). With the CS diet regime, pH at the time before morning feeding, rumination and post‐ingestion were significantly higher than those in the MF group (P < 0.05). However, times with the ruminal pH below 6.0 and 5.8 were significantly reduced (P < 0.05), whereas ruminal pH below 5.6 tended to be lower (P = 0.07). The results indicated that rumen fermentation parameters were affected by forage types and dietary peNDF content might be predominant in ruminal pH regulation.     

数据库技术在园林植保中的应用现状及趋势

文章阐述了数据库技术在植保领域中的应用和当前的开发现状。介绍了上海市绿化植物有害生物信息查询系统（VPPDIS）的开发情况及其主要功能,并对数据库技术在园林植保中的应用前景进行了探讨。     

基于数据仓库的土壤环境监测综合挖掘模型构架

为解决土壤环境监测全流程优化问题,提出了监测流程综合挖掘方法,采用数据仓库和工作流挖掘技术,构建了一个土壤环境监测综合挖掘模型构架.首先,采用雪花结构建立了数据模型构架,为流程挖掘提供数据底层;然后建立了监测流程综合挖掘模型构架,给出了监测单元挖掘、监测点位挖掘和监测数据挖掘,以及综合挖掘的模型函数和参数,以局部优化和全局优化的思路实现了土壤环境监测全流程优化.研究结果对于提高土壤环境监测效率,拓展LIMS实验室信息管理系统功能,构建土壤环境监测数据仓库和专家系统提供指导.     

应用NOAA/AVHRR遥感资料对阿拉善草地进行动态监测的研究

应用ＮＯＡＡ／ＡＶＨＲＲ遥感资料对阿拉善地区的６个荒漠类草地进行了生长季内的动态监测。结果表明，应用ＮＯＡＡ／ＡＶＨＲＲ遥感资料对阿拉善荒漠进行动态监测是可行的而且是必要的；提出了以“面”取样，“面”与“面”样本区配的建模方式，克服了以往建模方法中样本间“点”对“点”不能很好匹配的缺点。     

卫星遥感图像应用处理新模式的研究

卫星遥感图像增强与处理的研究旨在通过卫星遥感图像的处理,增强图像的显示质量,提高森林资源判读效果。通过应用ERDAS、ENYI遥感软件对TM、SPOT卫星数据的研究,实现资源调查卫片自主生产,降低了成本,提高了工作效率。     

农业信息化多媒体Web数据库构建——以三峡库区为例

三峡库区农业信息化平台的核心是农业信息化多媒体数据库系统的架构。通过对农业信息化平台的需求分析,提出在.NET平台下多媒体数据库的设计思想,阐述了多媒体数据库中主要表的设计和多媒体数据关联。实现了农业信息化平台中表的关联和多媒体Web数据库中数据的查询。     

The impact of truncating data on the predictive ability for single‐step genomic best linear unbiased prediction

Simulated and swine industry data sets were utilized to assess the impact of removing older data on the predictive ability of selection candidate estimated breeding values (EBV) when using single‐step genomic best linear unbiased prediction (ssGBLUP). Simulated data included thirty replicates designed to mimic the structure of swine data sets. For the simulated data, varying amounts of data were truncated based on the number of ancestral generations back from the selection candidates. The swine data sets consisted of phenotypic and genotypic records for three traits across two breeds on animals born from 2003 to 2017. Phenotypes and genotypes were iteratively removed 1 year at a time based on the year an animal was born. For the swine data sets, correlations between corrected phenotypes (Cp) and EBV were used to evaluate the predictive ability on young animals born in 2016–2017. In the simulated data set, keeping data two generations back or greater resulted in no statistical difference (p‐value > 0.05) in the reduction in the true breeding value at generation 15 compared to utilizing all available data. Across swine data sets, removing phenotypes from animals born prior to 2011 resulted in a negligible or a slight numerical increase in the correlation between Cp and EBV. Truncating data is a method to alleviate computational issues without negatively impacting the predictive ability of selection candidate EBV.