During the past century wheat breeders have produced a large number of genetically improved wheat lines and varieties. This activity has led to widespread adoption of improved varieties, a steady increase in average wheat yields during the past 4–5 decades and major contributions to food security and poverty reduction. The rate of generation and adoption of improved varieties, and therefore the time lag from varietal release to widespread use, varies across regions. The remarkable success of wheat improvement hinges on the decisions of millions of farmers to adopt, or replace older wheat varieties with superior material. The present paper summarizes studies on the determinants of adoption. Because adoption is a necessary but not sufficient condition for economic impact, the present paper synthesizes key assessments of impact from different farming systems in developing countries.

RESUMOMatas de galeria possuem grande diversidade genética e desempenham importantes funções ecológicas, como a proteção das nascentes, controle da erosão e funcionam como filtros retendo poluentes. A serapilheira, que pode ser usada como um indicativo de produtividade ecológica é amplamente coletada por meio de coletores que são distribuídos aleatoriamente em um ecossistema florestal. No entanto, a distribuição da vegetação pode apresentar dependência espacial, logo, a produtividade da serapilheira pode ser mapeada utilizando técnicas geoestatísticas o que permite a delimitação de zonas de manejo. Portanto, o objetivo deste estudo foi avaliar a eficiência de métodos geoestatísticos na delimitação de zonas de manejo da produtividade de serapilheira em uma área de mata de galeria. O estudo foi realizado na mata de galeria do córrego Lava-pés (3 ha) em Ipameri -GO, utilizando-se 60 coletores (cada um com 0,33 m² de área e suspensos a 0,65 m do solo) instalados em uma malha regular georreferenciada de 32 x 32 m. A serapilheira foi coletada mensalmente de dezembro de 2011 a novembro de 2012. Todas as amostras foram separadas manualmente nas frações: folhas (FF), ramos (FR -galhos e cascas), e estruturas reprodutivas (FER -flores, frutos e sementes) e foram expressas em kg ha -1 . Realizou-se a análise estatística descritiva e geoestatística dos dados. A produtividade de serapilheira para a FF e o total apresentou forte dependência espacial. A FR e a FER apresentaram efeito pepita puro. O mapa dos valores de serapilheira total obtido pelo método de interpolação Krigagem indicaram áreas de produtividade variando de 900 a 10.900 Kg ha -1 ano, evidenciando alta variabilidade na área. Foi possível por meio da técnica de interpolação krigagem delimitar zonas de manejo da produtividade de serapilheira na mata de galeria estudada, o que permitiu o manejo florestal específico da serapilheira. Palavras-chave: ecossistemas florestais; krigagem; dependência espacial. ABSTRACTThe gallery forests have great genetic diversity and important ecological functions, such as protecting the headwaters, controlling erosion, and functioning as buffer zones and filtering chemicals. Litterfall, which can be used as an indicator of ecological productivity, is widely collected using litter traps that are randomly distributed in a forest plot. However, vegetation distribution may present spatial dependence,

We evaluated the effect of initial spacing on the distribution of Eucalyptus grandis x Eucalyptus urophylla tree diameters in a Nelder wheel design. The study area was in west-central Brazil. A Nelder wheel design with three repetitions was used. This design provides 432 planting spots per plot/repetition. Planting density varied from 0.50 m² to 41.25 m². The diameter at breast height was measured for all plants every four months until 36 months of age, totaling eight measurements. The description of the diameter distribution was developed by fitting probability density functions for each spacing and age. The quality of fit was evaluated using the root mean square error percentage, Pearson’s correlation coefficient, and the Kolmogorov-Smirnov test (α < 0.05). The spacings up to 1.17 m² must be harvested in less than two years, since it is noted that in the third year the increment in diameter is static and the mortality rate increases. The spacing highly affects the diameter structure of the population, impelling the forester to consider different uses for the wood. For wood requiring larger diameters, spacing above 8.69 m² per tree is recommended

Considering the importance of optimizing forest production, plant spacing is one of the most relevant silvicultural practices, as it holds ecological, silvicultural, and economic implications to the final product. Therefore, this study set out to assess the influence of spacing on the initial growth and production variables of hybrid clones of Eucalyptus urophylla S. T. Blake x Eucalyptus grandis W. Hill ex Maiden planted in a Nelder (fan-shaped) design. Plant densities ranged from 0.50 m² to 41.25 m² in area-per-plant. Variables such as total height, diameter, and volume were observed at 16, 24, and 36 months. A descriptive statistical analysis, Pearson’s correlation coefficient, and cluster analysis of averages were used to evaluate the effect of spacing on the variables in question. Different spacings were found to exert significant influences on growth in height, diameter, and volume.

The objective of this study was to evaluate, with the use of artificial neural networks, the influence of some environmental variables in litterfall. The study was conducted on the gallery forest along ‘Lava-pés’ stream in Goiás State, Brazil where the experimental site (3 ha) was structured in a grid of 60 litterfall traps, with 0.33 m2 each and held 0.65 m above the soil, georeferenced and spaced at intervals of 32 x 32 m. Litterfall was monthly collected from December 2011 to November 2012. All litterfall samples were manually separated into three fractions: leaves (LE), branch bark (BB), and reproductive parts (RP). Relevance of climate , temporal, spatial and phytosociological variables in litterfall deposition were evaluated, through sensitivity analysis provided by the artificial neural network with the best performance. According to the statistical analysis, all variables were significant in the phenomenon, while the variable time (months of the year) was the most important for litterfall in the evaluated area. Artificial neural networks are shown as a powerful tool for litterfall analysis.