Impact of climate change on maize yield in China from 1979 to 2016

Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square(FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results:(1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2(1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2(0.014%).(2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China.(3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.     

基于距离相关系数和KNN回归模型的森林蓄积量估测研究

【目的】探究Landsat8 OLI数据和KNN算法在森林蓄积量估测中的潜力。【方法】以湖南省湘潭县为研究区,采用Landsat8 OLI数据和同时期的二类调查数据,通过距离相关系数筛选特征,分别采用线性回归模型(MLR)、K-近邻模型(KNN)、距离加权KNN模型(DW-KNN)和优化欧式KNN模型(FW-KNN)对森林蓄积量进行估测。使用十折交叉方法进行精度检验,对检验结果进行对比分析。【结果】3种KNN模型的估测结果均高于传统的线性模型,并且在3种KNN模型中,FW-KNN算法效果最好,决定系数达到0.69,为3种模型中最高;3种KNN模型中,本研究优化欧氏距离KNN模型的估测精度最高,其均方根误差为30.3%,相比于传统KNN模型的均方根误差降低了5.1%,相比于DW-KNN模型降低了3.3%。【结论】采用DW-KNN蓄积量估测结果明显优于其他两种模型,说明通过特征与蓄积量的相关性优化样本间的距离是一种可行的KNN优化方法。     

双季鲜食玉米/花生宽幅间作生态高效栽培技术

该文分析了双季鲜食玉米/花生宽幅间作生态高效栽培的意义,阐述了其栽培的技术要点,包括播前准备、播种与覆膜、田间管理、收获与晾晒、秸秆还田与残膜清除等.该技术主要适用于山东省小麦、玉米两熟轮作区及其他相似区域.     

规模化畜牧养殖对生态环境的破坏及防治

近年,畜牧养殖业蓬勃发展,过去的区域化散养已经基本不存在,养殖结构逐渐向集约化、一体化、规模化过渡,养殖规模也逐渐增大。养殖副产品肉、蛋、奶等极大满足了人们的生产生活,养殖中产生的尿液、粪污对生态环境造成极大影响。为促进规模化养殖实现绿色健康发展,该文分析规模化畜牧养殖对生态环境的破坏及防治措施。     

郁金香新品种‘黄玉’

‘黄玉’是从郁金香‘Golden Apeldoorn’的芽变中选育的新品种。株高37 cm，花单生于茎顶，鲜黄色，外轮花瓣外侧黄绿色。生育期75 d，盛花期13 d，花朵品质高，抗寒能力强，是优良的盆栽和园林绿化品种。     

4个甜樱桃品种在德州的引种表现及设施栽培技术

对引入山东德州的4个甜樱桃品种美早、萨米脱、布鲁克斯、拉宾斯进行了日光温室栽培试验,对其性状表现进行了观察。结果表明,4个品种均表现生长良好,适应性强,结果正常,果实品质优良,可以作为德州地区日光温室的栽培品种发展。简述了4个甜樱桃品种在日光温室的栽培技术。     

安徽南陵地区土壤养分丰缺状况研究

以安徽南陵地区土壤大量养分元素为主要研究对象,通过对区内土壤样品的采集与测试,统计分析土壤氮、碱解氮、磷、有效磷、氧化钾、速效钾等的含量特征,并对其分布特征加以研究,最终开展研究区土壤养分地球化学综合等级评价.结果表明,土壤氮和碱解氮在研究区内以丰富为主,且两者相关性较好,相关系数高达0.85,可能与土地利用类型有关;磷及有效磷在区内主要表现为较缺乏-缺乏,两者相关性较差,可能与磷在土壤中的存在形式及人为活动有关;氧化钾在区内分布主要表现为较丰富-中等-较缺乏3种,呈正态分布,孤峰河两侧分布差异明显,速效钾在区内零星分布,特征不明显;区内土壤养分地球化学综合评价结果以三级(中等)土壤为主,占研究区总面积的58.45％.     

New Polyketides from the Antarctic Fungus Pseudogymnoascus sp. HSX2#-11

The species Pseudogymnoascus is known as a psychrophilic pathogenic fungus with a ubiquitous distribution in Antarctica. Meanwhile, the study of its secondary metabolites is infrequent. Systematic research of the metabolites of the fungus Pseudogymnoascus sp. HSX2#-11, guided by the method of molecular networking, led to the isolation of one novel polyketide, pseudophenone A (1), along with six known analogs (2–7). The structure of the new compound was elucidated by extensive spectroscopic investigation and single-crystal X-ray diffraction. Pseudophenone A (1) is a dimer of diphenyl ketone and diphenyl ether, and there is only one analog of 1 to the best of our knowledge. Compounds 1 and 2 exhibited antibacterial activities against a panel of strains. This is the first time to use molecular networking to study the metabolic profiles of Antarctica fungi.     

水霉属菌(Saprolegnia)分离培养技术研究

 对水霉(Saprolegnia)的分离培养技术进行了探索,筛选出大麻籽、油菜籽、红花籽、苍蝇、蚜虫、小麦粒、玉米片、茶叶、葵花仁9种材料作为诱发水霉菌的诱饵。其中油菜籽能防止腐霉菌(Pythium)污染,是初步纯化菌种、排除杂菌的适宜饵料。同时发现控制温度能使水霉在最短时间内分别产生无性或有性繁殖。在水培条件下,25℃左右适合菌丝及无性器官的发育,有性器官却不能产生,而只有在15~17℃条件下才能使水霉很快进入有性生殖阶段;在加入200mg/L链霉素的CMA培养基上促发有性阶段则需要在25℃左右的温度下进行,方能缩短培养时间。