摘要：Eighteen clones of Eucalyptus tereticornis （Sm.） were evaluated for three years by adopting randomized block design for various growth parameters at Hoshiarpur, Punjab, India and compared with two checks. Significant variations were recorded for height, diameter at breast height （DBH） and clear bole height （CBH）. The broad sense heritability was low to moderate for both height and CBH. The genetic gain for height and CBH increased substantially pe se with the increase in age of trees. The average genetic gain for thres years was recorded maximum for height （159.60%） followed by DBH （110.97%） and CBH （70.34%）. Clone 17 attained maximum DBH over other genotypes for second and third year followed by clones 14 and 11. Clone 5 showed an upward trend for DBH and maintained its superiority for CBH as the age of the tree increased. Similarly, clone 11 changed its ranking from 9th to 8th to 3rd for DBH and from 9th to 4th to 2nd for CBH, respectively for the age of one, two and three years. Nonetheless, clones 6 and 10 per- formed poorly for all the characters studied. Clones 17, 14 and 5 were found to be the most promising clones for commercial deployment.

摘要：In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition （HFT） to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.