用籼/籼交重组自交系群体构建的分子遗传图谱及其与籼/粳交群体的分子图谱的比较

为了最终实现对籼稻数量性状基因位点 (QTLs)精确定位 ,用一个包含 1 31个系的籼 /籼交重组自交系群体 (F6∶7)构建了分子遗传连锁图谱。该图谱含由 1 1 3个水稻探针、2 8个小麦探针揭示的 1 6 0个RFLP标记和由 5个PstⅠ /MseⅠ引物组合揭示的 78个AFLP标记。群体的杂合性比率接近期望值 ,表明该群体具有正常的遗传结构。在 6个染色体区域观察到标记的偏分离 ,表明即使在亚种内群体中也可能发生标记的偏分离。本图谱的总长度为 1 4 35 8cM ,相邻标记间的平均距离为 6 38cM。由于采用了一套日本水稻基因组计划 (RGP)的RFLP标记 ,使本图谱能与RGP图谱进行比较。结果表明 ,两个图谱上的共同标记所覆盖图谱总长度几乎相同 ;在水稻 1 2条染色体中的 9条表现完全的连锁保守性。此外 ,水稻的第 1号染色体与小麦的第 3组染色体具有很强共线性。但是 ,两个图谱间也存在明显的差异 ,在 1S、1L、4L和 8L 4个染色体臂上发现 4个小倒位 ;除第 5号和第 6号染色体外的其他染色体上共检测到 1 9个新的位点。籼稻亲本间在染色体臂 2S、7S、1 0L和 1 1S 4个区域的RFLP多态性很低或没有 ,从而导致籼稻图谱在这些区域呈现空白。在这个籼稻图谱中 ,未检测到第 1 1号和 1 2号染色体间的重复性。还就稻属在基因组进化中的染     

数字化地籍测量中定向错误的类型与改正方法

数字化地籍测量中,利用控制点进行定向操作时容易出现错误。如果定向出现问题,将导致该站所测的界址点均出现错误。本文根据不同的错误类型,推导出了不同的数学模型。有些定向错误可以通过数学模型修正,有的错误类型则无法修正,当尽量避免。     

Mapping Ridolfia segetum patches in sunflower crop using remote sensing

Ridolfia segetum is a frequent umbelliferous weed in sunflower crops in the Mediterranean basin. Field and remote sensing research was conducted in 2003 and 2004 over two naturally infested fields to determine the potential of multispectral imagery for discrimination and mapping of R. segetum patches in sunflower crops. The efficiency of the four wavebands blue (B), green (G), red (R) and near‐infrared (NIR), selected vegetation indices and the spectral angle mapper (SAM) classification method were studied using aerial photographs taken in the late vegetative (mid‐May), flowering (mid‐June) and senescence (mid‐July) crop growth stages. Discrimination efficiency of R. segetum patches in sunflower crops is consistently affected by their phenological stages, in this order: flowering > senescence > vegetative. In both fields, R. segetum patches were efficiently discriminated in mid‐June, corresponding to the flowering phase, by using the waveband G, the ratio R/B or SAM with overall accuracies ranging from 85% to 98%. The application of the median‐filtering algorithm to any of the classified images improved the accuracy. Our results suggest that mapping R. segetum weed patches in sunflower to implement site‐specific weed management techniques is feasible with aerial photography when images are taken from 8 to 10 weeks before harvesting.     

遥感与GIS相结合的森林资源信息更新与制图方法研究

目前我国实行的森林经营单位水平上森林资源动态监测主要是通过森林资源规划设计调查 (简称二类调查 )来实现。重点是对森林资源动态、林业经营效果和森林资源监测的综合评价。通常 ,二类调查每 1 0 a复查 1次 ,这种方法所得到的森林资源调查结果可落实到地块 ,也是森林经营单位进行营林生产的重要基础数据 [1 ] 。但是这种常规调查方法也有许多不足之处 ,如 :(1 )复查间隔期长 ,无法及时满足森林经营单位对森林资源变化信息的需求 ;(2 )调查成果多是以报表、文字的形式提交 ,只能建立属性数据库 ,森林资源的空间信息较少通过计算机实现可视…     

ArcView GIS在林业制图方面的应用

应用地理信息软件ArcView GIS在林业制图方面的二次开发,编制出适用的应用程序,操作简单易行,提高了生产效率,为形成规模生产、实现林业制图自动化程度奠定基础。     

干涉测量土地利用影像分类决策树法森林识别研究

利用ERS－1和ERS－2 SAR串行轨道数据经干涉测量处理生成的干涉测量土地利用影像对森林识别方法进行初步研究。内容包括基于目标识别选择合成干涉测量土地利用影像处理方法、应用斜分类器（OCI）生成分类决策树以及在自主开发的软件中调整分类决策树、对分类结果进行像元级别上的精度检验和误差分析等。结果表明：ERS－1和ERS－2 SAR串行轨道数据经干涉测量处理，利用其强度影像和相干影像可以合成多种干涉测量土地利用影像；其中最小值影像和 标准差影像较之于其它强度影像和变化影像更有利于区分水体和森林；由于OCI生成决策树的算法决定了在分类处理中没有不可分类别的存在，所以在初期选择分类类别时，要尽可能多的覆盖原始影像的数值区间；选择的各类别样本数据要尽可能的“纯”，以减少类别间数值区间的重叠，从而减少误分类情况。     

MapX在空间数据绑定与林业专题图制作中的应用探讨

从空间地图数据与属性数据的关联、专题图的生成各方法，就MapX在林业地理信息系统开发中空间数据绑定与专题图制作中的技术等作了简要探讨。     

DNA分子标记技术在食用菌研究中的应用及进展

根据近年来国内外的文献报道,对DNA分子标记技术在食用菌遗传育种、菌种和菌株鉴定、遗传多样性分析、基因定位和克隆等研究中的应用及进展进行了综述和分析.认为随着分子生物学技术的进一步发展,将有更多、更有效的分子标记在食用菌研究中得以应用,同时随着分子标记技术应用的深入,更高密度、更为实用有效的遗传连锁图谱将被建立,大量重要的功能基因将被定位和克隆,这将为进一步培育高产、优质、抗病、耐贮等食用菌新品种奠定良好的基础.     

Mapping landscapes: Integrating GIS and social science methods to model human-nature relationships in Southern Cameroon

Participatory mapping and GIS are both necessary to model the interactions between humans and their environment. A case study from the forest margin in the Congo Basin demonstrates how data from participatory community mapping and other social science methods can be prepared for quantitative modelling. This approach bridged the gap between spatial modelling data and social decision-making in space by elaborating a geographically consistent social representation of the landscape and giving a geographical base to the connection between land use, its cultural representation, and its social management. This was achieved through an iterative process of GIS cartography, using feedback from village informants and field checking, to transpose the spatial references from participatory mapping sketches into reliable geographic locations. As well as demonstrating the utility of such data for modelling, this work clarified the distribution of land rights among the six main owner-clans spread through the eight hamlets in the watershed. The ‘basin’ of spatial resources and its relation to the rules of land use and natural resource management were defined for each clan. Land-use systems at the forest-agriculture interface in the study area proved to be complex, strongly driven by social rules and influenced by history and settlement strategies. These social and historical aspects established the framework within which communities make current decisions and interventions. The authors thank the people of Akok for their collaboration and hospitality. Village technician Michel Engueng and village contact Adolphe Ze facilitated and assisted this work. Our thanks also to Julie Mbazo’o and Remy Assoumou, both members of the ‘social side’ working group of the FLORES modelling team. Christopher Legg’s contribution to the discussion of this work through his constant reviewing of the CamFlores model is gratefully recognized. Finally, thanks to the whole CIFOR-ACM team for numerous scientific and methodological inputs. The Italian Foreign Ministry funded the work of Valentina Robiglio (APO-GIS specialist) through an APO contract with IITA. The European Union (Tropical Forestry budget line DG VIII) contributed to the CIFOR’s research program on the ‘Adaptive Collaborative Management of Forests’ (ACM) in Africa, and to the Alternative to Slash and Burn (ASB) program in Cameroon on ‘Environmental Services and Rural Livelihoods’ through the World Agroforestry Centre.     

An overview of animal science research 1945–2011 through science mapping analysis

The conceptual structure of the field of Animal Science (AS) research is examined by means of a longitudinal science mapping analysis. The whole of the AS research field is analysed, revealing its conceptual evolution. To this end, an automatic approach to detecting and visualizing hidden themes or topics and their evolution across a consecutive span of years was applied to AS publications of the JCR category ‘Agriculture, Dairy & Animal Science’ during the period 1945–2011. This automatic approach was based on a coword analysis and combines performance analysis and science mapping. To observe the conceptual evolution of AS, six consecutive periods were defined: 1945–1969, 1970–1979, 1980–1989, 1990–1999, 2000–2005 and 2006–2011. Research in AS was identified as having focused on ten main thematic areas: ANIMAL‐FEEDING, SMALL‐RUMINANTS, ANIMAL‐REPRODUCTION, DAIRY‐PRODUCTION, MEAT‐QUALITY, SWINE‐PRODUCTION, GENETICS‐AND‐ANIMAL‐BREEDING, POULTRY, ANIMAL‐WELFARE and GROWTH‐FACTORS‐AND‐FATTY‐ACIDS. The results show how genomic studies gain in weight and integrate with other thematic areas. The whole of AS research has become oriented towards an overall framework in which animal welfare, sustainable management and human health play a major role. All this would affect the future structure and management of livestock farming.