In this paper we calculate Sainfoin quality parameters of nineteen populations by means of NIRs method. Based on the obtained results, different populations have significant effects on forage quality. We found a negative and significant correlation between water soluble carbohydrates, total ash, crude fiber and Neutral Detergent Fiber. This implies that digestibility can improve Sainfoin forage quality. Principal component analysis is a cluster analysis complementary and hence for all populations principal component analysis were done. The first and the second main components justify 71.310 % of the total variance. The first component has a high positive correlation with the traits NDF, CF and ASH and high negative correlation with the trait WSC. The second component has a high positive correlation with DDM and so with CP. Therefore, the selection based on these two components will have a positive impact in improvement of the traits. The populations based on the cluster analysis method are divided into two main groups. The scattering plot obtained from principal analysis of components verifies the results of the cluster analysis and partially could distinguish the populations. The calculations show with different combinations of the traits, it is possible to improve the quality of Sainfoin.
