Multivariate Analysis Of Potato Genotypes For Genetic Diversity

Sustainable production of food crops relies on germplasm improvement and genetic diversity that helps to identify appropriate parents, which is very important step in breeding of genotypes having high yield potential for future use. This study was conducted to investigate the extent of genetic diversity using multivariate technique on the basis of qualitative and quantitative traits. An experiment was comprised of 74 exotic genotypes and started at National Agriculture Research Center Islamabad, Pakistan during autumn 2017-2018 and 2018-2019. Data was recorded on qualitative and quantitative traits by following standard procedures and Biplot analysis was used to calculate the significance among the studied quantitative traits to exhibit the strength of relationship between traits. Results showed significant diversity in qualitative traits and quantitative traits. Red, yellowish, brown, light yellow, light brown color tubers were produced. Alike, genotypes produced yellow, cream and white flesh color tubers. Genotypes had oval, round, oblong, elliptic and reform with medium, small and large size tubers. Alike, brown, light brown, dark red and yellow eyes color was noted. In case of quantitative traits, genotypes had high variance regarding plant height, leaf area and number of tubers per lane. Genotypes had very high genetic variance for weight of tuber per plant and weight of tuber per lane while low variance was recorded for germination, number of stem per plant and number of eyes per tuber. Significant positive correlation was observed between number of tubers per plant (TPP) with number of eyes on tubers (r = 0.241) and number of tubers per lane (TPL) (r = 0.349). But negative correlation was noted between number of tubers per plant (TPP) with plant height (r = - 246), leaf area (−0.529) and germination (r = −0.283). Plant height was found significantly positive correlated with leaf area (r= 0.456), germination percentage (r = 0.255) and weight of tubers per plant (r = 0.307). Leaf area (LA) showed positive significant correlation with number of tubers per plant (r = 0.466) and weight of tubers per plant (r = 0.263)., yield and harvest index (r = 0.798, 0.755, 0.255). Weight of tubers per lane (WTL) showed positive correlation with weight of tubers per plant (r = 0.387). Regarding the interrelation between the traits and genotypes, the first two principal component axes (PC1, 24.83% and PC2, 23.46%) accounted for about 48.29% of the total variability reflecting the complexity of the variation between the plotted traits of genotypes.


INTRODUCTION
The availability of diverse genetic germplasm ensures success in development of new high yielded cultivars (Buckler, 2009). Genetic diversity and suitable germplasm are very important factor in agricultural crops. Genetic diversity helps to identify appropriate parents, which is very important step in breeding of genotypes having high yield potential for future use.
A comprehensive knowledge about variability in genetic material is necessary for the improvement of suitable traits (Kahrizi, Maniee, Mohammadi, & Cheghamirza.., 2010).
Knowing and understanding the accessible diverse genetic germplasm is of the most important for successful exploitation and estimation of germplasm (Zubair, Ajmal, Anwar, & Haqqani, 2007). The genetic diversity is helpful to identify different parental combinations to produce progenies having maximum genetic variability for further selection (Mohammadi & Prasanna, 2003) and one can take genes of our choice from diverse germplasm (Habtamu, 2013). Genetic relationships between pure or inbred lines is also important for scheduling crosses, selection of lines to particular heterotic groups and for precise recognition regarding plant varietal protection (Franco et al., 2001). Genetic diversity also assists to identify such groups possessing similar genetic background and their utilization as a genetic resource (Thompson, Nelson, & Vodkin, 1998).
Multivariate analysis is an important and very popular method for estimation of genetic variability (Malik et al., 2014) and to determine pattern of dissimilarities and their genetic relationship between germplasm collections (Ajmal et al., 2013). Multivariate analyses have been used in various countries (Babić, Pajić, Prodanović, Babić, & Filipović, 2010) for different food crops like wheat (Ajmal et al., 2013), maize (Azad, Biswas, Alam, & Alam, 2012;Lee, Herrman, Lingenfelser, & Jackson, 2005) and sorghum (Ali et al., 2011). To select genetically distance parents, various genetic diversity researches have been initiated between crop species on the basis of quantitative and qualitative traits (Hailegiorgis, Mesfin, & Genet, 2011). To harness friable genetic variation in breeding material, it is worthwhile to trace the total variation into its components. The present research was initiated realizing the significance and need for such a comparative study in potato particularly to investigate the level of genetic diversity by employing multivariate technique on the basis of qualitative and quantitative characters to sort out superior genotypes and to adopt a suitable breeding program for variety development in country. Keeping this in view, the present study was carried out to evaluate their genetic diversity.

Materials and Methods
The experiment was evaluated at Plant Genetic Resource Institute (PGRI), National Agriculture Research Centre (NARC) Islamabad, Pakistan during November 2017-2018 to 2018-2019. In this experiment, 76 exotic genotypes (Table 1) were imported from International Potato Centre, Peru. The experiment was sown in a RCBD (Randomized Complete Block Design) with plant to plant and row to row distance of 25cm and 65 cm, respectively. The recommended dose of fertilizers i.e. nitrogen 250 kg/ha, phosphorus 125 kg/ha and potassium 125 kg ha -1 was applied. All the phosphorus, potassium and half dose of nitrogen were applied at the time of sowing while remaining was used at 1st and 2 nd earthing up. Crop was visited regularly during growing season. Irrigation and plant protection measures were carried out when required.
Observations for qualitative traits such as tuber shape, tuber size tuber color, tuber flesh color, tuber skin, eye color of tuber and tuber eyes depth were taken. Similarly, quantitative traits such sprouting percentage, plant height, number of stem, leaf area, number of tubers/plant, number of tuber/row, weight of tuber/plant, weight of tuber/row and number of eyes/tuber were recorded by following standard procedures.

Observations
Following observations were recorded during experimental trials.
For tuber shape, tuber size tuber color, tuber flesh color, tuber skin, eye color of tuber and tuber eyes depth, tubers of 5 plants of each genotype were taken and observed visually.

Sprouting percentage
It was calculated by following formula For plant height, 5 plants of each genotype were selected randomly and their height was measured from base to top with the help of a meter rod and then averaged.

Number of stem/plant
For number of stem/plant, 5 plants of each genotype were selected randomly and their number od stem was noted.

Number of tubers per plant and number of tubers per row
To count the number of tuber per plant, 5 plants from each genotype selected randomly and their tubers were counted and then averaged. At harvesting, all the potatoes of each genotype in their respective rows were counted.

Tubers weight per plant and tubers weight per row (g)
For tuber weight, 5 plants of each genotype were selected randomly and their tubers weight was noted with the help of digital electrical balance and then averaged. At harvesting, all the potatoes of each genotype in their respective rows were weighted individually.

Number of eyes
For number of eyes, tubers of 5 plants of each genotype were observed carefully after harvesting and their eyes were noted and then averaged.

Leaf area (cm 2 )
For leaf area, leaves of 5 plants of each genotype were harvested, their leaves were separated and leaf area was noted with help of leaf area meter.

Data analysis
For basic statistics, data were analyzed in Microsoft Office Excel 2010. To establish phenotypic similarity and dissimilarity, a Biplot analysis was carried out. Pearson's correlation coefficient was also calculated and the significance was noted among the studied quantitative attributes to disclose the strength of relationship using XLSTAT 2012.

Qualitative traits
Results showed that genotypes have diversity in qualitative traits (Figures 1-3

Quantitative traits
Seventy six potato genotypes (