不同裂荚特性箭筈豌豆裂荚力数字化评价

以美国种质资源库(NPGS)提供的541份箭筈豌豆(Vicia sativa)种质为基础,经过连续3年裂荚率评价,共筛选出高、中、低裂荚种质33份。以这33份箭筈豌豆种质作为本研究的试验材料,利用艾德堡HP-50数显推拉力计结合裂荚率对箭筈豌豆荚果水平放置时的裂荚机械力和垂直放置时的裂荚机械力进行分析,为选育箭筈豌豆抗裂荚种质提供精确、快速的评价方法。结果显示,1)箭筈豌豆高裂荚种质荚果裂荚机械力极显著低于低裂荚种质荚果裂荚机械力(P0.01)。2)箭筈豌豆荚果水平放置时的裂荚机械力极显著低于垂直放置时的裂荚机械力(P0.01)。3)箭筈豌豆荚果在水平放置下裂荚机械力大于9.286N的为低裂荚种质,裂荚机械力小于2.163N的为高裂荚种质。研究表明,利用推拉力计测试水平放置的箭筈豌豆荚果裂荚机械力可准确反映箭筈豌豆不同种质的裂荚特性,并为箭筈豌豆裂荚特性的标准化测定提供了重要的参考依据。     

农业院校图书馆印刷型外文期刊利用状况的统计分析

在电子期刊蓬勃发展并日益得到读者青睐的新时代,馆藏印刷型外文期刊的利用率降低;更由于各高校图书馆的经费与存储空间有限,导致外文印刷型期刊在采购和收藏上存在很大的困难。通过对东北农业大学图书馆五年来读者阅览和复印外刊的变化统计,显示出印刷型外刊在广大的农业院校读者群中还有其存在的意义和作用,为各高校图书馆采购和收藏外刊提供可靠的数据依据。     

高校图书馆大流通环境下的读者教育与管理探析

大流通运行模式已在高校图书馆普遍运用，其优势非常明显，但存在的问题也比较突出。通过对大流通的内涵、特征及其在大流通环境下存在的问题进行分析，指出了产生问题的主要原因，提出了图书馆加强读者教育与管理的思路。     

中国图书馆电子资源联盟采购的实践与思考

[目的/意义]梳理国内图书馆电子资源联盟采购现状,剖析存在问题,提出改进建议。[方法/过程]结合不同类图书馆采购联盟的发展背景、用户需求及客观现实条件,阐述不同类图书馆联盟采购的发展概况,深入分析组织管理架构、采购流程及经费分摊方式等,总结特色亮点,剖析存在的短板或问题。借鉴国内外图书馆联盟采购典型案例和相关研究成果,结合国内图书馆在经费及平台方面的客观实际,分别从6方面提出对策与建议。[结果/结论]建立并完善相关运作机制;优化价格模式、拓展筹资渠道;综合内容、使用和服务等多维数据建立电子资源评价指标体系;深度整合联盟内部资源,构建统一信息交流平台建设;提高法律意识,捍卫长期保存与永久使用权;重视多方合作、灵活组建不同类型联盟、增强竞争实力等,是有效提升图书馆联盟采购效益的良策。     

新媒体时代公共图书馆创新服务研究——以重庆图书馆为例

随着新媒体时代的到来,人们接受信息的途径也有了全新的变化。新媒体给公共图书馆带来了机遇和挑战,公共图书馆面对种种挑战,积极创新服务,增强服务能力,提高服务水平和质量。     

高校图书馆人才危机及其对策

随着信息技术的发展和人们信息需求水平的提高,高校图书馆的人才危机也发生了变化,主要体现为高校图书馆馆员有限的能力与读者日益提高的信息需求水平的矛盾。这是由于高校图书馆馆员偏低的学历层次、不合理的学科结构以及较低的工作积极性所造成的。对此,提出了诸如建立有效的交流机制、激励机制、人员流动机制以及提升馆员学历层次等办法及建议,来缓和这一矛盾。     

高职数字图书馆个性化信息推荐服务研究

介绍了高职数字图书馆个性化信息服务的含义、服务模式、服务方式、重要性及存在的问题,提出了高职数字图书馆开展个性化信息服务的措施。     

Simulating farming practices within a region using a stochastic bio-decisional model: Application to irrigated maize in south-western France

Agricultural is a major contributor to environmental resource management problems. Modelling the distribution of agricultural land use to evaluate current situations or scenarios is an important issue for policy-makers and natural resource managers. A promising approach is the use of bio-decisional models based on decision rules. However, at the regional scale, the large number of farmers makes it difficult to identify decision rules, and the diversity of farmers' decisions is rarely considered. To this end, we developed SIMITKO, a spatialised and stochastic bio-decisional model, able to simulate the spatial and temporal variability in farming practices. We focused on the choice of varietal earliness and sowing practices of maize (Zea mays L.) in the Baïse sector (south-western France). Model development was based on statistical analyses of surveys of farmers’ practices to identify their current strategies, the best variables to describe the practices and the probabilities associated with the values of the variables for each strategy. We tested SIMITKO by simulating the dynamics of areas sown with maize. Comparing model predictions of practices to observed data showed generally good predictions of sowing dynamics but less satisfactory predictions of varietal earliness choices. Possible improvements are suggested.     

高等农业院校素质教育评价体系的构建

构建素质教育评价体系对高校改革发展具有重要作用。调查显示,农业院校学生迫切需要强化素质教育。农业院校素质教育评价体系的构建与实施应从自身实际出发,针对学生实际,构建科学合理的知识结构,突出学生的综合发展测评。同时,注意助推学校的改革发展,准确合理定位学校的层次、类型、功能和特色,使学校育人目标和社会人才需求目标一致,学校发展目标和师生发展目标相和谐。     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).