RESUMEN
Because of the rapid development of transgenic maize, the potential effect of transgene flow on seed purity has become a major concern in public and scientific communities. Setting a proper isolation distance in field experiments and seed production is a possible solution to meet seed-quality standards and ensure adventitious contamination of products is below a specific threshold. By using a Gaussian plume model as basis and data recorded by meteorological stations as input, we have established a simple regionally applicable maize gene-flow model for prediction of the maximum threshold distances (MTD) at which gene-flow frequency is equal to or lower than a threshold value of 1 or 0.1 % (MTD1%, MTD0.1%). After optimization of the model variables, simulated outcrossing rate was a good fit to data obtained from field experiments (y = 1.156x, R (2) = 0.8913, n = 30, P < P 0.01). In the process of model calibration, it was found that only 15.82 % of the total amount of the pollen released by each plant participated in the dispersal process. The variable "a" for genetic pollen competitiveness between donor and recipient was introduced into our model, for the "Zinuo18" and "Su608" used, "a" was 17.47. Finally, the model was successfully used in the spring maize-growing region of Northeast China. The range of MTD1% and MTD0.1% in this region varied from 10 m to 49 m and from 17 m to 125 m, respectively.
Asunto(s)
Agricultura/métodos , Flujo Génico/genética , Modelos Genéticos , Plantas Modificadas Genéticamente/genética , Semillas/genética , Zea mays/genética , China , Genética de Población , Polen/genética , Análisis de Regresión , Dispersión de Semillas/genéticaRESUMEN
We designed Adaptive Neuromorphic Architecture (ANA) that self-adjusts its inherent parameters (for instance, the resonant frequency) naturally following the stimuli frequency. Such an architecture is required for brain-like engineered systems because some parameters of the stimuli (for instance, the stimuli frequency) are not known in advance. Such adaptivity comes from a circuit element with memory, namely mem-inductor or mem-capacitor (memristor's sisters), which is history-dependent in its behavior. As a hardware model of biological systems, ANA can be used to adaptively reproduce the observed biological phenomena in amoebae.
Asunto(s)
Modelos Neurológicos , Redes Neurales de la Computación , Neuronas/fisiología , Neurociencias/instrumentación , Animales , Encéfalo/citología , HumanosRESUMEN
We aimed to establish a rice gene flow model based on (i) the Gaussian plume model, (ii) data from a three-location x 3-yr field experiment on transgene flow to common rice cultivars (Oryza sativa), male sterile (ms) lines (O. sativa) and common wild rice (Oryza rufipogon), and (iii) 32-yr historical meteorological data collected from 38 meteorological stations in southern China during the rice flowering period. The concept of the gene flow coefficient (GFC) is proposed; that is, the ratio of the transgene flow frequency (G%) obtained from field experiments to the aggregated pollen dispersal frequency (P%) calculated based on the pollen dispersal model. The maximum distances of gene flow (MDGF) to traditional rice cultivars, ms lines, and common wild rice at a threshold value of either 1.0 or 0.1% were determined. The MDGF and its spatial distribution in southern China show that the gene flow pattern is significantly affected by the monsoon climate, the topography, and the outcrossing ability of recipients. We believe that the information provided in this study will be useful for the risk assessment of transgenic rice in other rice-growing regions.