畜禽数量性状基因座位的精细定位

数量性状基因座位(QTL)的精细定位是实施QTL克隆及标记辅助选择(MAS)的重要基础。然而就目前畜禽QTL定位的结果来看,除了通过候选基因法识别的少数基因外,大多数QTL定位的精度仍无法满足实际应用的要求。为进一步提高QTL定位的精度,缩小QTL定位的置信区间,人们相继提出并发展了一系列新的QTL定位方法。本文在分析畜禽QTL定位的基本方法及影响畜禽QTL定位精度的主要因素基础上,对提高QTL定位精确性的策略和方法进行了相应的探讨。     

A method for mapping the distribution of willow at a catchment scale using bi-seasonal SPOT5 imagery

This study showed that seasonal imagery acquired at specific stages of phenology can be used to improve the mapping accuracy of invasive willow at a catchment scale. SPOT5 XI (10 m) satellite imagery was acquired for early autumn and winter to represent the phenological stages of leaf cover and leaf fall respectively. Four classification regimes were evaluated using single‐ and bi‐seasonal composite imagery to determine the most accurate method. Significant spectral noise was found in willow populations, especially in the winter image, due to the effects of undergrowth exposure, shadowing, topography and boundary‐mixed pixels. Two noise reduction techniques were applied to the bi‐seasonal composite image to improve the classification results. The noise‐reduced bi‐seasonal composite image was classified using the spectral angle mapper (SAM) algorithm before importation into a geographical information system. Aerial photography was used to reduce the errors of commission associated with misclassification of pastures. The class accuracy achieved for willow using the method described in this study was 77.5% (Kappa =0.87). The high cost of eradicating willow means that managers must establish priorities for control; this technique can provide a powerful tool for prioritizing control programmes and for monitoring results at a catchment scale.     

一个新的乘法性质的证明

本文用环的理论证明了关于２个自然数相乘的一个新的性质，并将这一性质进行了推广。     

基于特征筛选算法的数字土壤制图研究

平缓地带数字土壤制图中，环境协变量的选择是提高制图精度的关键。已有研究证明遥感影像可作为推理制图的辅助因子，而如何确定环境因子推理制图时各自的权重已成为现阶段研究的重点。选取湖北省麻城市乘马岗镇为研究区，采用3种特征筛选方法进行有效环境变量筛选，探索参与平原-丘陵混合区域制图的因子并确定其重要性，依据选择的相对稳定的指标，进一步探索提高土壤类型制图准确性的途径。根据141个野外独立样点的检验结果表明：在推理制图中，遥感因子在平原区域的重要性程度高于丘陵区域，且遥感因子中归一化植被指数(NDVI)和均值(Mean)较为稳定；基于递归特征算法的按地形推理制图精度最高为75.89%，分别高于ReliefF算法和基于Tree的特征筛选算法13.48%和4.97%；此外3种特征筛选算法制图结果中，按地形因子分区制图的精度均高于整体区域制图。因此，遥感因子作为辅助手段参与推理过程可有效提高制图精度。本研究采用的特征挖掘与机器学习算法对提升土壤制图精度具有一定的理论意义。     

有限个渐进非扩张非自映射的带有误差的Ishikawa迭代的收敛性

介绍了有限个渐进非扩张非自映射的带有误差的Ishikawa迭代, 并且证明了在一致凸Banach空间中这种带有误差的Ishikawa迭代在一个新的条件下的强收敛性.     

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.     

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。     

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.