No abstract

In this study, the data and pedigree records of the native fowls collected by Fars Native Fowls Breeding Center during 1990-2004 were analyzed. A pedigree file collected on 30855 hens and roosters was used to calculate the inbreeding coefficients and its trend and its effect on production and reproduction traits. The average of inbreeding coefficient for all birds was 0.002% ranging from 0 to 14.8%. In this population, 14% of the birds were inbred with an average inbreeding coefficient of 0.019%. The Inbreeding coefficient was considered as covariate to estimate its effect on economic traits including body weight in 12 weeks (BW12), egg number during 12 weeks (EN), mean egg weight between 28 to 32 weeks (MEW) and Age of Sexual Maturity (ASM). Results showed that inbreeding does not have a significant effect on the traits under study (p > 0.05). Moreover, heritability, genetic and phenotypic correlations between traits was estimated through a multiple traits animal model procedure by restricted maximum likelihood using ASREML software. The estimated heritabilities were 0.53, 0.47, 0.57 and 0.22 for body weight in 12 weeks (BW12), Age of Sexual Maturity (ASM), mean Egg Weight (EW) and Egg Number (EN), respectively. Because of relatively high heritabilities of productive and reproductive traits, it is possible to achieve more genetic gains in these traits using appropriate genetic selection.

The proposed methodology relies on the fuzzy nine-intersection matrix which is a generalization of the crisp four-intersection matrix for topological similarity computing. The similarity computation between 3D fuzzy matrix and 3D crisp nine-intersection matrix enables the decision variables to be derived. Decision variables, which are used for deducing and drawing conclusion, are consisted of semantic parts and quantifiers (type and strength of relations). Since these variables are dependent on the boundary directly, it is essential to present an efficient method for defining 3D fuzzy boundary. So, in this paper, we complete the information about how we can define fuzzy boundaries between two 3D phenomena and present a new procedure for simulation of 3D spatial topology in a deductive geographic information system (GIS). Therefore, a fuzzy knowledge-base system and an inference engine will be shown results for deduction in GIS environment.

Modeling the impact of air pollution is one of the most important approaches for managing damages to the ecosystem. This problem can be solved by sensing and modeling uncertain spatial behaviors, defining topological rules, and using inference and learning capabilities in a spatial reasoning system. Reasoning, which is the main component of such complex systems, requires that proper rules be defined through expert judgments in the knowledge-based part. Use of genetic fuzzy capabilities enables the algorithm to learn and be tuned to proper rules in a flexible manner and increases the preciseness and robustness of operations. The main objective of this paper was to design and evaluate a spatial genetic fuzzy system, with the goal of assessing environmental risks of air pollution due to oil well fires during the Persian Gulf War. Dynamic areas were extracted and monitored through images from NOAA, and the data were stored in an efficient spatial database. Initial spatial knowledge was determined by expert consideration of the application characteristics, and the inference engine was performed with genetic learning (GL) algorithms. Finally, GL (0.7 and 0.03), GL (0.7 and 0.08), GL (0.98 and 0.03), GL (0.98 and 0.08), and Cordon learning methods were evaluated with test and training data related to samples extracted from Landsat thematic mapper satellite images. Results of the implementation showed that GL (0.98, 0.03) was more precise than the other methods for learning and tuning rules in the concerned application.

‫س‬ ‫دسیبفز:‬ ‫بسیخ‬ 21 / 8 / 96 ‫دزیشؽ:‬ ‫سبسیخ‬ 26 / 4 / 97 ‫چکیذُ‬ ‫پصٍّص‬ ‫ّذف‬ ‫حاضر‬ ، ‫از‬ ‫استفادُ‬ ‫با‬ ‫لپتیي‬ ‫شى‬ ‫ضکلی‬ ‫چٌذ‬ ‫هطالعِ‬ ‫تکٌیک‬ PCR-SSCP ‫آهیختِ‬ ٍ ‫بختیاری‬ ‫لری‬ ‫ًصاد‬ ‫گَسفٌذ‬ ‫در‬ ‫بختیاری‬ ‫لری‬ -‫صفات‬ ‫با‬ ‫شًَتیپی‬ ‫الگَّای‬ ‫ارتباط‬ ‫بررسی‬ ٍ ‫افطاری‬ ‫ر‬ ‫گَس‬ ‫در‬ ‫ضذ‬ ‫بختیاری‬ ‫لری‬ ‫فٌذاى‬ ‫بَد‬ . ‫از‬ 58 ‫ًصاد‬ ‫گَسفٌذ‬ ‫راض‬ ‫بختیاری‬ ‫لری‬ ‫ًر‬ ٍ ‫هادُ‬ ٍ ‫ضْرکرد‬ ‫ضَلی‬ ‫ایستگاُ‬ ‫در‬ ‫هَخَد‬ 42 ‫بختیاری‬ ‫لری‬ ‫آهیختِ‬ ‫ًصاد‬ ‫گَسفٌذ‬ ‫راض‬ -‫افطاری‬ ‫از‬ ‫رٍستاّای‬ ‫آهذ.‬ ‫عول‬ ‫بِ‬ ‫خًَگیری‬ ‫ضْرکرد‬ ‫استخراج‬ DNA ‫گرفت‬ ‫صَرت‬ ‫سیٌاشى‬ ‫ضرکت‬ ‫کیت‬ ‫با‬ . ‫کویت‬ ٍ ‫کیفیت‬ ‫تعییي‬ DNA ‫آگا‬ ‫شل‬ ‫با‬ ٍ ‫رز‬ ‫قطعِ‬ ‫تکثیر‬ ‫ضذ.‬ ‫اًدام‬ ‫اسپکترٍفتَهتری‬ 275 ‫اگسٍى‬ ‫بازی‬ ‫خفت‬ 3 ‫صَرت‬ ‫پلیوراز‬ ‫ای‬ ‫زًدیرُ‬ ‫ٍاکٌص‬ ‫از‬ ‫استفادُ‬ ‫با‬ ‫لپتیي‬ ‫شى‬ ‫ای‬ ‫رضتِ‬ ‫تک‬ ‫فضایی‬ ‫چٌذضکلی‬ ‫گرفت.‬ SSCP ‫هحصَالت‬ PCR ‫بذست‬ ‫ًقرُ‬ ‫ًیترات‬ ‫آهیسی‬ ‫رًگ‬ ٍ ‫آهیذ‬ ‫اکریل‬ ‫پلی‬ ‫شل‬ ‫از‬ ‫استفادُ‬ ‫با‬ ‫گَسفٌذا‬ ‫برای‬ ‫باًذی‬ ‫الگَی‬ ‫ّطت‬ ‫آهذ.‬ ‫ػبسی‬ ‫طجیؼی‬ ‫ٔٙبثغ‬ ٚ ‫وـبٚسصی‬ ‫ػّْٛ‬ ‫دا٘ـٍبٜ‬ ‫دأی‬ ‫سِٛیذار‬ ‫دظٚٞـٟبی‬ ‫ثخشیبسی‬ ‫ِشی‬ ‫٘ظاد‬ ‫ٌٛػفٙذاٖ‬ ‫دس‬ ‫سؿذ‬ ‫كفبر‬ ‫ثشخی‬ ‫ثب‬ ‫آٖ‬ ‫اسسجبط‬ ٚ ‫ِذشیٗ‬ ‫طٖ‬ ‫ؿىّی‬ ‫چٙذ‬ ‫ثشسػی‬ . AbstractThe purpose of this study was evaluation of leptin gene polymorphism by PCR-SSCP and its relationship with some growth traits in Lori Bakhtiari and crossbred of Lori Bakhtiari-Afshari sheep. Blood samples were collected from sheep (male and female) of Lori-Bakhtiari in Shahr-e-Kord Sholi station and sheep (male and female) of Lori Bakhtiari-Afshari crossbreed from villages of Shahr-e-Kord. DNA was extracted, using extraction kit of Sinnagen co. Evaluation of quality and quantity of DNA was performed using agarose gel electrophoresis and spectrophotometry. Polymerase chain reaction (PCR) was conducted to amplify bp fragment of exon of leptin gene. Then single strand conformation polymorphism (SSCP) of PCR products was performed and genotypic patterns were obtained using acrylamid gel and silver staining. For leptin gene in Lori bakhtiari sheep, band patterns including L to L and for crossbreeds sheep, band patterns including L to L were obtained. There was a high polymorphism in exon of the leptin gene in both breeds. Also results of means comparison showed that the leptin gene was significantly associated with weight at and months.