安徽省农业气象灾害时间分布特征与灰色关联分析

为了探寻安徽省农业气象灾害的分布特点以及各种气象灾害对粮食生产的影响,本研究基于安徽省1992—2012年有关气象灾害数据,对4种主要气象灾害(旱灾、水灾、风雹灾、霜冻灾)的分布特征进行统计分析,并采用灰色关联分析研究其对安徽省粮食单产的影响。结果表明:1992—2012年,安徽省气象灾害具有发生频率高、波动大的特点,但整体上呈下降趋势。旱灾和水灾是发生面积较大的气象灾害,且常在时间上交织、空间上并存。灰色关联分析表明,4种气象灾害对粮食产量影响顺序:风雹灾水灾旱灾霜冻灾,说明风雹灾是影响粮食产量最主要的气象灾害,其次是水灾、旱灾,霜冻灾影响较小。本研究可为安徽省防灾减灾措施的制定提供决策依据。     

12份燕麦品种在阿鲁科尔沁旗地区的生产性能研究

【目的】筛选适宜内蒙阿鲁科尔沁旗地区种植的燕麦品种。【方法】对12份燕麦(Avena sativa)品种的生育期、草产量、茎叶比、营养特性等进行测定和分析,并运用灰色关联度分析法对各品种的生产性能进行综合评价。【结果】12份供试燕麦品种均能在阿鲁科尔沁旗地区完成整个生育期,表现出较好的适应性,生育期为83～94 d,其中枪手的生育期最短(83 d),爱沃的生育期最长(94 d)。贝勒二代和牧王的株高均达到100 cm以上。枪手、贝勒二代和牧王的干草产量较高,分别为9.99,8.69和8.59 t/hm~2。贝勒二代的茎叶比最低(1.12),适口性最好;美达的茎叶比最高(3.19)。爱沃和贝勒二代的粗蛋白含量(质量分数)较高,分别为12.20%和11.90%;太阳神、贝勒二代和领袖的中性洗涤纤维及酸性洗涤纤维含量较低,领袖和贝勒二代的相对饲喂价值较高。灰色关联度分析表明,综合评价排在前2位的燕麦品种为贝勒二代和牧王,其加权关联度分别为0.838 2和0.799 1。【结论】燕麦品种贝勒二代和牧王综合表现最好,适宜在阿鲁科尔沁旗地区推广种植。     

土壤有机碳时空变化研究进展与展望

土壤有机碳不但是土壤肥力形成、粮食生产和土壤健康的基础,而且在全球碳平衡中起着关键的作用,因此,明晰土壤有机碳时空变化规律对于保障土壤健康和粮食安全、发挥土壤生态系统服务功能和应对气候变化等均具有重要意义。本文首先介绍了土壤有机碳时空变化的主要驱动因素和估算方法,随后分析了全球及国家等相对较大尺度上土壤有机碳时空变化研究的主要进展,最后从土壤有机碳模型结构改进、驱动数据分辨率提升、不确定性量化评估等方面综合分析了未来土壤有机碳时空变化研究需亟待解决的重要科学问题。     

射流泵装置性能预测方法

提出了一种射流泵装置性能预测方法,并进行了试验验证.以射流泵试验所得射流泵的流量比与压力比曲线,以及离心泵的流量扬程曲线作为预测初始条件,通过射流泵装置2种吸上高度4.5和9.0 m的性能试验,比较各流量比时装置工况点试验值与预测值精度,发现数值解法整体误差较小,能更好地反映射流泵扬程随流量比变化的情况,但与试验值相比仍存在误差且个别工况点误差较大,需进一步修正.引入预测值与试验值的比值作为修正系数,通过Plackett-Burman试验设计,从吸上高度、面积比、喷嘴直径、流量比、喉嘴距、喉管长径比、泵转速等因子中筛选出对射流泵扬程影响效应显著的面积比及流量比作为修正公式的关键参数,利用遗传算法和公式自动搜索拟合,得到射流泵扬程的计算公式,且相关系数超过0.99.通过射流泵装置在吸上高度为3.5和8.0 m的试验结果比较,表明具有较高的可信度.     

Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

基于“3S”技术的辽宁省某尾矿库扩容工程生态影响预测与评价

以辽宁省某尾矿库为例,基于GIS技术,利用2010年的TM遥感影像及地形图,预测该尾矿库扩容后的生态影响。分析结果显示:尾矿库扩容工程对生态的影响主要体现在土地利用、植被、生态景观和地形地貌的变化4个方面。     

Bioinformatics Analysis of Bone Morphogenetic Protein 4 (BMP4) of Sheep

The assay was aimed to explore the biological characteristics of bone morphogenetic protein 4 (BMP4) of sheep,NCBI,DNAMAN DNAStar,TMHMM Server v.2.0,PsortⅡ,SignalP various bioinformatical softwares were used to speculate the physical and chemical properties,hydrophobic property,phosphorylation site,conservative structure domain,protein secondary structure of BMP4 protein.Also,the three-dimensional structure was forecasted with the SWISS-MODEL Workspace software.The results indicated that the BMP4 of sheep had high homologies with the BMP4 of various species.The encoded protein was a hydrophilic protein which was unstable.There was no transmembrane regions and it was likely to be located in the nucleus.What was more,there was signal peptide and eighteen phosphorylation sites.Through the forecast of functional domains,the protein had two functional domains,including the transforming growth factor-beta (TGF-beta) superfamily and TGF-beta propeptide superfamily.The result was consistent with the function of BMP4 gene family,it also demonstrated that BMP4 was a growth factor and it had the function of signal transduction.The amino acid homology between the predicted 3D structure of protein and template 3bmp.1.A was 88.29%.The bioinformatics analysis of BMP4 gene could provide reference for the further study in practice.     

基于贡献度随机森林模型的公司债信用风险实证分析

运用贡献度随机森林方法（CRF）方法探讨公司债财务指标比率与其违约率的关系.运用连续属性离散化方法（OB）进行财务指标最优降维；运用WOE变换进行模型变量约简.研究表明，CRF模型的分类性能显著优于其他模型，测试集评估总体正确率达90.47%，AUC统计量、AR比率及K-S值分别提升了2.6%、7.6%、4.38%，变量贡献度量化了各财务指标对违约率影响，为诠释随机森林预测机制提供了依据.     

基于Lasso和BP神经网络的组合预测及其应用——以居民消费支出预测为例

在变量选择的基础上，构建基于Lasso方法和BP神经网络的预测模型，并对我国城乡居民的消费支出进行预测，结果显示：基于Lasso方法和BP神经网络的组合预测精度要明显高于BP神经网络、Lasso方法的预测精度；在2014~2020年，我国农村居民消费增长率有所提升，城镇居民消费增长率减缓，城乡居民消费增长率之间的差距呈下降趋势，但短期内城乡居民消费差距依然难以缓和。     

花生黄曲霉生长预测模型的研究

通过对分离自花生的黄曲霉LYYSS03-3在不同温度(15-35℃)、不同相对湿度(水活度分别为0.5,0.7,0.9)下的菌落生长特性进行检测,采用Boltzmann和Logistic 模型对黄曲霉的生长曲线进行拟合,结果表明,在适宜温湿度阶段,花生黄曲霉的生长曲线更适合用Boltzmann模型拟合.