جستجوی مقالات مرتبط با کلیدواژه « تجزیه pcoa » در نشریات گروه « کشاورزی »

Given the growing rate of population and its consequences, such as hungrier people and more demand for food, the Food and Agricultural Organization (FAO) has introduced potato (Solanum tubersum L.) as a food security plant. Thus, the need for expanding potato production is globally felt to manage the increase in food demands and food security (4, 10). The interaction between the genotype and the environment creates complexity in yield prediction and is a challenge for plant production and breeding programs. This study was conducted to achieve a stable high-yielding genotype that is adaptive to climatic conditions of potato-producing regions in Iran.

A total of 20 potato hybrides along with five commercial varieties (Savalan, Agria, Caesar, Luta and Satina) were evaluated in a randomized complete block design with three replicates in the agricultural research stations of five locations (Ardabil, Hamadan, Isfahan, Karaj, and Razavi Khorasan) in Iran, for two years (2016 and 2017). Each of the hybrids and control cultivars were planted in two rows with six meters long. The rows with inter row spacing of 75 cm and plant spacing of 25 cm was taken. The genotype yields were measured after the harvest. Combined analysis of variances was done and comparison of means was done by LSD at one percent probability level. The principal coordinate analysis was used to analyze yield stability.

The results of combined analysis of variance indicated that the effect of genotype, year, location and year – location, location – genotype, year – genotype and year - location – genotype interactions were significant at 1% level of probability. Therefore, the analysis of genotype - environment interaction was performed using multivariate analysis of principal coordinates. Compared to the grand mean, 10 environments under study were divided into two groups including three environments with higher performance than the total average and seven environments with lower performance than the total average. The most stable genotypes based on the MST (Minimum Spanning Tree) and distance from the center of plots were hybrids 1, 8 and Savalan cultivar in low cycles and hybrid 5 was identified in high cycles.

The hybrids 1 (35.57 ton/ha), 8 (35.05 ton/ha) and Savalan cultivar (33.52 ton/ha) which could be recommended for environments with the yield lower than the average mean of all studied environments. Also, hybrid 5 (41.21 ton/ha) was identified for environments with higher performance than the total average.

 The objective of this study was to assess the genetic diversity of some commercial apple cultivars in Khorasan Razavi province using 40 RAPD primers. DNA was collected from fresh leaves of apple samples studied and extracted based on dellaporta method. In order to investigate polymorphism, the PCR analysis was performed for each primer and the marker indices were calculated. The genetic similarity and distance were evaluated using Jaccard coefficient by UPGMA method and PcoA analysis by NTSYS-PC ver 2.2, respectively. The genetic structure analysis was performed using STRUCTURE software ver 2.3.   The percentage of polymorphic bands was different from 37.5% for OPJ13 marker to 100% for OPA7 markers. The highest and lowest PIC parameter was related to OPA4 (0.48) and OPM6 (0.2), respectively. With respect to cluster analysis, the samples were grouped into two main clusters and five subgroups. The highest similarity was between Golab Esfahan-Golomkani, Margenduft-Low Red Roem Beauty and Alimori Khorasan Dalago, while the lowest similarity was between Golab Esfahan-Fuji Rossa and Golab Esfahan-Low Red Roem Beauty cultivars. The classification based on PcoA analysis was different with UPGMA. In addition, the obtained result of Bayesian analysis showed lack of admixture of the apple cultivars studied.   According to the results of RAPD analysis, this marker can be used for recognition of polymorphic regions, assessment of genetic distance and management of apple genotypes and cultivars.