A simulação da biomassa de aveia por elementos climáticos, nitrogênio e regulador de crescimento / The simulation of the oat biomass by climatic elements, nitrogen and growth regulator

A produção de biomassa de aveia voltada à elaboração de silagem de qualidade é dependente de elementos climáticos e nitrogênio sem ocorrência de acamamento. O objetivo do presente estudo é a definição da dose ideal do regulador de crescimento que possibilite, no máximo, 5% de acamamento de plantas de aveia, bem como a identificação das variáveis potenciais para composição do modelo de regressão linear múltipla com simulação da produtividade de biomassa à elaboração de silagem nas condições de uso do regulador, em reduzida, alta e muito alta fertilização com nitrogênio. O estudo foi conduzido em 2013, 2014 e 2015, em delineamento de blocos ao acaso, com quatro repetições em esquema fatorial 4x3, para doses de regulador (0, 200, 400 e 600mL ha-1) e doses de nitrogênio (30, 90 e 150kg ha-1), respectivamente. A dose de 495mL ha-1 de regulador se mostra eficiente na redução do acamamento de plantas de aveia em condição de reduzida, alta e muito alta fertilização com nitrogênio. A soma térmica, a precipitação, a radiação, a dose de regulador e o nitrogênio qualificam a composição do modelo de regressão linear múltipla, tornando eficiente a simulação da produtividade de biomassa da aveia para silagem ao longo do ciclo.(AU)

The production of oat biomass focused on the development of quality silage is dependent on climatic elements and nitrogen without lodging occurrence. The objective of the study is to define the optimal dose of growth regulator that allows a maximum of 5% oat plant lodging and identify potential variables for composition of multiple linear regression model with productivity simulation of biomass to the preparation of silage in the conditions of low, high and very high fertilization with nitrogen. The study was conducted in 2013, 2014, and 2015 in the randomized block design with four replications in a factorial 4x3, for regulator doses (0, 200, 400 and 600ml ha-1) and nitrogen doses (30, 90 and 150kg ha-1), respectively. The dose of 495mL ha-1 regulator is efficient in reducing the oat plant lodging in condition reduced, high, and very high fertilization with nitrogen. Thermal time, precipitation, radiation, regulator dose and nitrogen dose qualify the composition of the multiple linear regression model, making efficient the biomass oat productivity simulation for silage over the cycle.(AU)

Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases.

Sugarcane (Saccharum spp.) is a clonally propagated outcrossing polyploid crop of great importance in tropical agriculture. Up to now, all sugarcane genetic maps had been developed using either full-sib progenies derived from interspecific crosses or from selfing, both approaches not directly adopted in conventional breeding. We have developed a single integrated genetic map using a population derived from a cross between two pre-commercial cultivars ('SP80-180' x 'SP80-4966') using a novel approach based on the simultaneous maximum-likelihood estimation of linkage and linkage phases method specially designed for outcrossing species. From a total of 1,118 single-dose markers (RFLP, SSR and AFLP) identified, 39% derived from a testcross configuration between the parents segregating in a 1:1 fashion, while 61% segregated 3:1, representing heterozygous markers in both parents with the same genotypes. The markers segregating 3:1 were used to establish linkage between the testcross markers. The final map comprised of 357 linked markers, including 57 RFLPs, 64 SSRs and 236 AFLPs that were assigned to 131 co-segregation groups, considering a LOD score of 5, and a recombination fraction of 37.5 cM with map distances estimated by Kosambi function. The co-segregation groups represented a total map length of 2,602.4 cM, with a marker density of 7.3 cM. When the same data were analyzed using JoinMap software, only 217 linked markers were assigned to 98 co-segregation groups, spanning 1,340 cM, with a marker density of 6.2 cM. The maximum-likelihood approach reduced the number of unlinked markers to 761 (68.0%), compared to 901 (80.5%) using JoinMap. All the co-segregation groups obtained using JoinMap were present in the map constructed based on the maximum-likelihood method. Differences on the marker order within the co-segregation groups were observed between the two maps. Based on RFLP and SSR markers, 42 of the 131 co-segregation groups were assembled into 12 putative homology groups. Overall, the simultaneous maximum-likelihood estimation of linkage and linkage phases was more efficient than the method used by JoinMap to generate an integrated genetic map of sugarcane.