由地铁隧道工程引起地表横向沉降的预测分析

应用Peck法、Logan-Poulous法、随机介质理论等方法对由地铁隧道工程引起的地表横向沉降进行预测,并对上述方法的实质加以研究。用STS沉降预测系统对实测数据进行分析和计算,并通过实测曲线和预测曲线的比对分析,验证上述方法的预测精确性。     

临安山核桃产量的Lasso-灰色预测模型研究

为实现对山核桃(Carya cathayensis Sarg)产量的精确预测,分析了气候因素和种植规模对山核桃产量的影响,建立了Lasso回归和灰色预测组合模型,并以临安山核桃为例进行实证研究。结果表明,与Lasso-BP,Lasso-RBF以及Lasso-GRNN这3种模型的预测效果相比,Lasso-GM模型预测精度较高,平均相对误差达到6.99%,能够较好地掌握山核桃产量的变化规律。同时,预测结果也显示,到2024年临安山核桃产量处于稳步增长的态势。     

光系列葡萄品种在福州地区的引种表现

为丰富福建葡萄品种资源结构,2014年起国家葡萄产业技术体系福州综合试验站引进河北省农林科学院昌黎果树研究所选育的‘春光’、‘蜜光’、‘宝光’、‘峰光’等4份优良鲜食葡萄品种,对其植物学特性、物候期、果实性状、生长结果习性及抗病性等进行观察,总结其在福建的综合表现。结果表明：4个欧美杂交葡萄品种较现有主栽品种巨峰具有坐果稳定、着色成熟一致、果肉硬脆耐储等优势,适宜在福建地区推广种植。     

覆膜种植年限柠檬园蜘蛛群落的影响*

【目的】覆膜种植作为一种重要的农作物栽培方式,在农业生产实践中被广泛应用。蜘蛛在生态系统中扮演着捕食者和指示生物等重要角色,了解覆膜种植年限对柠檬园蜘蛛群落的影响,对柠檬的科学种植和蜘蛛群落多样性保护及在生物防治中的应用具有积极意义。【方法】通过陷阱法和网扫法对覆膜种植年限0a(柠檬园I)、2a(柠檬园II)及4a(柠檬园III)的3种类型柠檬园蜘蛛群落进行调查。【结果】柠檬园I采集蜘蛛13科21种300头;柠檬园II采集蜘蛛9科17种159头;柠檬园III采集蜘蛛12科15种104头。蜘蛛多度和物种丰富度均随着覆膜年限的增加而降低。柠檬园I的蜘蛛群落结构与柠檬园II和III的不相似。【结论】覆膜种植对柠檬园蜘蛛群落多样性产生了消极影响,柠檬园蜘蛛群落多样性水平随着覆膜种植年限的增加而降低。     

Genomic Prediction of Arsenic Tolerance and Grain Yield in Rice: Contribution of Trait-Specific Markers and Multi-Environment Models

Many rice-growing areas are affected by high concentrations of arsenic(As). Rice varieties that prevent As uptake and/or accumulation can mitigate As threats to human health. Genomic selection is known to facilitate rapid selection of superior genotypes for complex traits. We explored the predictive ability(PA) of genomic prediction with single-environment models, accounting or not for trait-specific markers, multi-environment models, and multi-trait and multi-environment models, using the genotypic(1600 K SNPs) and phenotypic(grain As content, grain yield and days to flowering) data of the Bengal and Assam Aus Panel. Under the base-line single-environment model, PA of up to 0.707 and 0.654 was obtained for grain yield and grain As content, respectively; the three prediction methods(Bayesian Lasso, genomic best linear unbiased prediction and reproducing kernel Hilbert spaces) were considered to perform similarly, and marker selection based on linkage disequilibrium allowed to reduce the number of SNP to 17 K, without negative effect on PA of genomic predictions. Single-environment models giving distinct weight to trait-specific markers in the genomic relationship matrix outperformed the base-line models up to 32%. Multi-environment models, accounting for genotype × environment interactions, and multi-trait and multi-environment models outperformed the base-line models by up to 47% and 61%, respectively. Among the multi-trait and multi-environment models, the Bayesian multi-output regressor stacking function obtained the highest predictive ability(0.831 for grain As) with much higher efficiency for computing time. These findings pave the way for breeding for As-tolerance in the progenies of biparental crosses involving members of the Bengal and Assam Aus Panel. Genomic prediction can also be applied to breeding for other complex traits under multiple environments.     

基于CLIMEX和ArcGIS的灰茶尺蠖在中国的潜在适生区预测

基于中国820个气象站点数据、灰茶尺蠖已知地理分布资料和生物学数据,结合CLIMEX模型与ArcGIS软件模拟预测灰茶尺蠖在中国目前及未来的潜在分布范围,评估灰茶尺蠖的潜在分布范围及气候变暖对其分布的潜在影响。结果表明,灰茶尺蠖在中国目前的适生区主要分布在3°51′N~40°6′N,适生区面积占全国总面积的34.27%。中国大部分省份的气候条件均适合灰茶尺蠖种群生长。随着气候的变化,灰茶尺蠖在中国的潜在适生区面积总体增幅不大,但其组成变化较大。至2050年,预测灰茶尺蠖高度适生区面积占比达最大（22.23%）。相比各种能源之间的平衡情景（A1B）,较高能源需求情景（A2）下灰茶尺蠖在陕甘宁地区向内陆扩张更快。灰茶尺蠖在中国适生区分布广泛,应加强灰茶尺蠖预测预报,趁早采取防控措施,以保障茶叶优质安全生产。     

Screening of Human CYP1A2 and CYP3A4 Inhibitors from Seaweed In Silico and In Vitro

Phenolic compounds and carotenoids are potential inhibitors of cytochrome P450s. Sixteen known compounds, phenolic compounds and carotenoids from seaweed were examined for potential inhibitory capacity against CYP1A2 and CYP3A4 in silico and in vitro. Morin, quercetin, and fucoxanthin inhibited the enzyme activity of CYP1A2 and CYP3A4 in a dose-dependent manner. The IC₅₀ values of morin, quercetin, and fucoxanthin were 41.8, 22.5, and 30.3 μM for CYP1A2 and 86.6, 16.1, and 24.4 μM for CYP3A4, respectively. Siphonaxanthin and hesperidin did not show any significant effect on CYP1A2, but they slightly inhibited CYP3A4 activity at high concentrations. In silico modeling of CYP’s binding site revealed that the potential inhibitors bound in the cavity located above the distal surface of the heme prosthetic group through the 2a or 2f channel of CYPs. This study presents an approach for quickly predicting CYP inhibitory activity and shows the potential interactions of compounds and CYPs through in silico modeling.     

Hybrid breeding for biomass yield in winter triticale: II. Combining ability and hybrid prediction

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single-cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid-parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate-to-low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid-parent values as emphasized by our simulation study, but can be expected to shift to GCA-based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.     

运用植被指数时序特征对落叶松人工林分类

为探究植被指数时序特征是否有利于落叶松人工林提取,以孟家岗林场为研究试验区域,根据落叶松人工林季相和物候特征,利用Landsat8OLI影像数据提取研究区内5种植被的归一化植被指数(I NDV)、差值植被指数(I DV)、比值植被指数(I RV)、增强型植被指数(I EV),构建相应的植被指数时序特征。采用最大似然和随机森林两种方法对单一时相影像和加入植被指数时序特征的影像进行对比试验。结果表明:影像中加入植被指数时序特征后,最大似然算法的分类总体精度为89.53%,Kappa系数为0.87,比单一时序特征的影像分类精度提高了13.35%;随机森林算法的森林类型分类总体精度为93.22%,Kappa系数为0.92,比单一时序特征的影像分类精度提高了19.8%。因此,加入植被指数时序特征后能得到更高的落叶松人工林提取精度。     

基于最大熵（MaxEnt）模型对西北地区2种红砂属植物潜在适宜区预测分析

基于黄花红砂与五柱红砂的现有分布数据,利用地理信息系统（ArcGIS）技术与最大熵（MaxEnt）模型软件,对2种红砂属植物在3个时期的潜在适宜分布区进行模拟。结果表明:1）五柱红砂的潜在适宜分布区主要在青海地区、新疆南疆地区以及甘肃部分地区;黄花红砂的潜在适宜分布区主要集中在宁夏地区、内蒙古地区、甘肃地区以及新疆与青海部分地区。2种红砂属植物在3个时期的潜在适宜分布区有所增加。黄花红砂的潜在适宜区朝着东北方向移动,五柱红砂的潜在适宜区出现收缩现象。2种红砂属的低适宜区相比较高适宜区与较适宜区变化较大。2）黄花红砂与五柱红砂通过MaxEnt模型运算出的AUC值均>0.9,表明MaxEnt模型预测精度很高。可以用于2种红砂属植物的潜在适宜分布区的预测。3）控制黄花红砂潜在分布的关键环境变量为最湿月降水量、最暖季度降水量和最湿季度降水量,影响五柱红砂潜在分布的关键环境变量为海拔、等温性和温度季节性变化。上述研究结果对2种红砂属植物资源保护利用与未来分布趋势提供了重要的指导意义。