Mapping QTLs for aluminum tolerance in maize

Aluminum toxicity is one of the major constraints for plant development in acid soils, limiting food production in many countries. Cultivars genetically adapted to acid soils may offer an environmental compatible solution, providing a sustainable agriculture system. The aim of this work was to identify genomic regions associated with Al tolerance in maize, and to quantify the genetic effects on the phenotypic variation. A population of 168 F-3:4 families derived from a cross between two contrasting maize inbred lines for Al tolerance was evaluated using the NSRL and RSRL parameters in nutrient solution containing toxic level of aluminum. Variance analyses indicated that the NSRL was the most reliable phenotypic index to measure Al tolerance in the population, being used for further QTL mapping analysis. RFLP and SSR markers were selected for bulked segregant analysis, and additional SSR markers, flanking the polymorphisms of interest, were chosen in order to saturate the putative target regions. Seven linkage groups were constructed using 17 RFLP and 34 SSR markers. Five QTLs were mapped on chromosomes 2, 6 and 8, explaining 60% of the phenotypic variation. QTL(4) and marker umc043 were located on chromosomes 8 and 5, close to genes encoding for enzymes involved in the organic acids synthesis pathways, a widely proposed mechanism for Al tolerance in plants. QTL(2) was mapped in the same region as Alm2, also associated with Al tolerance in maize. In addition, dominant and additive effects were important in the control of this trait in maize.

Semi-automatic modeling of buildings from digital surface models

Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.

Orientação semi-automática de uma sequência de pares de imagens frontais por fototriangulação a partir de fotocoordenadas extraídas pelo SIFT

Pós-graduação em Ciências Cartográficas - FCT