Morphological characterization of cactus pear (Opuntia ficus-indica) accessions from the collection held at Agadir, Morocco

Meriem Nefzaoui, Mario Andrade Lira Junior, Mohamed Boughlala, Sripada M. Udupa, Mounir Louhaichi. (30/3/2017). Morphological characterization of cactus pear (Opuntia ficus-indica) accessions from the collection held at Agadir, Morocco. Coquimbo, Chile.

Abstract

The North Africa region falls under arid and semi-arid climate and it is considered as a hot spot for climate change. To face feed shortage, increase income of the rural poor and to mitigate the effect of climate change, around 1 million ha of cactus crop has been planted in Tunisia, Algeria and Morocco. Aware of the importance of germplasm, in-situ collections are being initiated in the region where promising accessions have been introduced from many countries. The objective of this contribution was to assess the genetic diversity of 20 cactus pear accessions from the in-situ collection located in the INRA Morocco research station of Agadir using morphological characterization based on FAO-Cactusnet descriptor. The data were subjected to Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC) using XLSTAT 2015 package. The results showed that the accessions can be discriminated by the morphological descriptors. Many of these morphological descriptors are significantly correlated as the number of cladodes and the number of fruits (r=0.73), the number of cladodes and the plant diameter (r=0.73), the length of the cladode and the plant height (r=0.7), the length of the spine and the number of areoles (r=0.67). The cladode shape and the number of spines and areoles are the recommended descriptors, and are capable to discriminate accessions with a suitable accuracy. Other descriptors do not seem to influence the morphological characterization as the cladode thickness, the number of spine, the plant height and the cladode shape index. Therefore, Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC) are good tools to segregate accessions using a reduced number of morphological descriptors. Another important finding is that the number of morphological descriptors may be reduced without potential risk of reducing the accuracy of the phenotypic characterization.