QTL mapping of resistance in lentil (Lens culinaris ssp. culinaris) to ascochyta blight (Ascochyta lentis)

Quantitative trait locus (QTL) analysis of ascochyta blight resistance in lentil was conducted using genomic maps developed from two F₂ populations, viz. ILL5588/ILL7537 and ILL7537/ILL6002. Five QTLs for ascochyta blight resistance were identified by composite interval mapping (CIM) across four linkage groups (LG) in population ILL5588/ILL7537. Three QTLs were identified by CIM in population ILL7537/ILL6002 (two in close proximity on LGI and one on LGII). Two of these coincided with regions identified using multiple interval mapping (MIM) and were shown to be conditioned by dominant and partial dominant gene action. Together, they accounted for approximately 50% of the phenotypic variance of disease severity. Comparison between the two populations revealed a potentially common QTL and several common regions that contained markers significantly associated with resistance. This study demonstrated the transferability of QTLs among populations and identified markers closely linked to the major QTL that may be useful for future marker‐assisted selection for disease resistance.     

New molecular markers linked to qualitative and quantitative powdery mildew and scald resistance genes in barley for dry areas

A partial genetic linkage map was constructed on 71 doubled-haploid lines derived from a cross between the barley lines Tadmor and WI2291 with 181 molecular markers. The segregating population was used to detect markers linked to the gene Mlg conferring resistance to powdery mildew (Erysiphe graminis f. sp. hordei) and to genes for quantitative resistance to scald (Rhynchosporium secalis). The gene Mlg on chromosome 4H was flanked by two AFLP markers at a distance of 2.0 and 2.4 cM, respectively. QTLs for resistance to scald were detected on chromosomes 2H and 3H. This association of molecular markers with qualitative and quantitative disease resistance loci represents a valuable starting-point for marker-assisted selection. This revised version was published online in July 2006 with corrections to the Cover Date.     

Fusarium wilt of chickpea: physiological specialization, genetics of resistance and resistance gene tagging

Chickpea wilt caused by Fusarium oxysporum f. sp. ciceris is one of the major yield limiting factors in chickpea. The disease causes 10–90% yield losses annually in chickpea. Eight physiological races of the pathogen (0, 1A, 1B/C, 2, 3, 4, 5 and 6) are reported so far whereas additional races are suspected from India. The distribution pattern of these races in different parts of the world indicates regional specificity for their occurrence leading to the perception that F. oxysporum f. sp. ciceris evolved independently in different regions. Pathogen isolates also exhibit differences in disease symptoms. Races 0 and 1B/C cause yellowing syndrome whereas 1A, 2, 3, 4, 5 and 6 lead to wilting syndrome. Genetics of resistance to two races (1B/C and 6) is yet to be determined, however, for other races resistance is governed either by monogenes or oligogenes. The individual genes of oligogenic resistance mechanism delay onset of disease symptoms, a phenomenon called as late wilting. Slow wilting, i.e., slow development of disease after onset of disease symptoms also occurs in reaction to pathogen; however, its genetics are not known. Mapping of wilt resistance genes in chickpea is difficult because of minimal polymorphism; however, it has been facilitated to great extent by the development of sequence tagged microsatellite site (STMS) markers that have revealed significant interspecific and intraspecific polymorphism. Markers linked to six genes governing resistance to six races (0, 1A, 2, 3, 4 and 5) of the pathogen have been identified and their position on chickpea linkage maps elucidated. These genes lie in two separate clusters on two different chickpea linkage groups. While the gene for resistance to race 0 is situated on LG 5 of Winter et al. (Theoretical and Applied Genetics 101:1155–1163, 2000) those governing resistance to races 1A, 2, 3, 4 and 5 spanned a region of 8.2 cM on LG 2. The cluster of five resistance genes was further subdivided into two sub clusters of 2.8 cM and 2.0 cM, respectively. Map-based cloning can be used to isolate the six genes mapped so far; however, the region containing these genes needs additional markers to facilitate their isolation. Cloning of wilt resistance genes is desirable to study their evolution, mechanisms of resistance and their exploitation in wilt resistance breeding and wilt management.     

水稻Xa-5基因在水稻和玉米中的比较物理定位

比较基因组分析证明，玉米和水稻基因组间存在广泛的同线性和共线性。对水稻和玉米基因的原位杂交定位可以揭示禾本科植物基因组结构的共同特点和进化规律。用与Xa-5连锁的RG556及RG556筛选出的BAC克隆44B4作探针对水稻广陆矮四号和玉米自交系黄早四进行了原位杂交，在水稻第5号染色体短臂和玉米第8号染色体长臂检出了杂交信     

游离棉纤维长度的计算机测量

文中介绍了一种棉纤维长度测量的新方法,即用CCD捕获游离棉纤维图像,然后依据数字图像处理及模式识别的理论,建立起一个实际可行的算法,来完成对棉纤维多种长度指标的一次性测量。该算法涉及到数字图像的二值分割、补断、修剪、像素跟踪等几个方面,且针对棉纤维图像的特征,进行了优化。     

A high-resolution map of the rice blast resistance gene Pi15 constructed by sequence-ready markers

The gene Pi15 for resistance of rice to Magnaporthe grisea was previously mapped to a ≈0.7-cM region on chromosome 9. To further define the chromosomal region of the Pi15 locus, a contig spanning the locus was constructed, in silico , through bioinformatics analysis using a reference sequence of the cultivar 'Nipponbare'. One simple sequence repeat marker adopted from the International Rice Microsatellite Initiative and six candidate resistance gene (CRG) markers, developed from gene annotation of the reference sequence of the contig, were used for linkage analysis in a mapping population consisting of 504 extremely susceptible F₂ plants. The Pi15 locus was delimited to a ≈0.5-cM region flanked by the markers CRG5 and CRG2 and co-segregated with the markers BAPi15₇₈₂, CRG3 and CRG4, which was physically converted to a 44-kb interval.     

Genetic mapping of AFLP markers in Japanese bunching onion (<Emphasis Type="Italic">Allium fistulosum</Emphasis>)

Summary The first genetic linkage map of Japanese bunching onion (Allium fistulosum) based primarily on AFLP markers was constructed using reciprocally backcrossed progenies. They were 120 plants each of (P₁)BC₁ and (P₂)BC₁ populations derived from a cross between single plants of two inbred lines: D1s-15s-22 (P₁) and J1s-14s-20 (P₂). Based on the (P₂)BC₁ population, a linkage map of P₁ was constructed. It comprises 164 markers – 149 amplified fragment length polymorphisms (AFLPs), 2 cleaved amplified polymorphic sequences (CAPSs), and 12 simple sequence repeats (SSRs) from Japanese bunching onion, and 1 SSR from bulb onion (A. cepa) – on 15 linkage groups covering 947 centiMorgans (cM). The linkage map of P₂ was constructed with the (P₁)BC₁ population and composed of 120 loci – 105 AFLPs, 1 CAPS, and 13 SSRs developed from Japanese bunching onion and 1 SSR from bulb onion – on 14 linkage groups covering 775 cM. Both maps were not saturated but were considered to cover the majority of the genome. Nine linkage groups in P₂ map were connected with their counterparts in P₁ map using co-dominant anchor markers, 13 SSRs and 1 CAPS.     

基于显著和模糊检测的浅景深作物病害图像分割

大多数现有的基于图像的作物病害诊断方法往往对输入图像的质量具有很高的要求,例如要求背景简单、大景深等等。因此这些方法的预处理过程中需要去除复杂背景,然而这个预处理较难获得理想的结果。此外,当作物病斑面积较小时,会使得获取的图像景深较浅,也导致了这些方法难以抽取精确的病斑区域。为了解决上述问题,该文提出一种利用目标检测来分割病斑图像的方法。首先,该方法对抽取的结构特征和颜色特征进行整合并对特征空间进行量化,从而得到作物病害图像的显著区域。该方法不需要进行去除复杂背景的预处理过程即可得到病斑区域的图像;同时,为了处理浅景深的病害图像,引入了模糊检测方法用以进一步过滤背景和模糊区域的图像。试验中利用多种黄瓜和水稻病害的图片,将该方法与阈值法、图切割法进行了对比,结果表明该方法在效率不明显降低时,其分割效果明显优于阈值法;在分割效果差异不大时,其运行效率明显高于图切割方法;同时,该方法能够对浅景深的作物病害图像的病斑区域进行有效的分割。     

基于分幅房产图的土地利用现状信息提取

以《房产测量规范》（GB/T17986.1-2000）标准绘制的分幅房产图为土地调查底图,依《土地利用现状分类》（GB/T21010-2007）标准对房产图上的土地利用现状信息进行提取。详细探讨从分幅房产图上的商业金融业用地、市政用地、公共建筑用地、交通等用地中提取地类信息的归并情况,指出从分幅房产图上提取土地利用现状信息存在的问题为：概念范围界定不统一、相同地类名称不相同、表示信息侧重点不同和精度差异等。为共享资源,节约社会成本,建议统一地类划定标准,多种地图一体化综合测绘等。     

基于AOS的扩展C-V模型及背景填充耦合的单板节子缺陷识别

分析木材单板节子缺陷图像的特点,提出一种基于AOS的扩展C-V模型及背景填充耦合的单板节子缺陷识别算法。首先,对Chan-Vese提出的基于Mumford-Shah模型的水平集图像分割算法进行改进,使分割速度得到提高;其次,用AOS算法改进原模型的差分格式,使得差分格式无条件稳定;最后,结合背景填充技术,使得到的新图像缩减了目标与背景间的特征差别。通过对比试验,表明该分割方法能够快速识别单板单个节子缺陷,充分说明该耦合方法比Chan-Vese方法及其改进方法有更好的分割效果。通过用多水平集作为初始轮廓演化曲线,结果表明该方法也可快速实现对单板多节子缺陷图像的识别,实现对单板节子图像的多目标分割。