Abstract:
Ridge Gourd (Luffa acutangula), a widely cultivated vegetable crop belongs to Family
Cucurbitaceae. There are some local varieties such as “Niyan Watakolu” and “Hean Watakolu”
which are low in diversity. Germplasms are hard to find to continue the breeding programs. The
recognition of superior genotypes that have improved characteristics is essential for sustainable
production and the market demand. Therefore, a comprehensive study is required to evaluate the
genetic diversity of ridge gourd. The aim is to investigate genetic variability within Luffa
populations to identify genetic potential associated with yield, quality traits, and phenotypic
characterization. This study was conducted at Plant Breeding Division, Horticultural Crop
Research and Development Institute in Yala season 2023. The superior plant varieties RG152,
RG007, RG003, KSP9298, Amaya, Roshani, Ajax which selected based on the mean performance
of yield and quality related traits from F2 population and self-pollination was done to obtain F3
population seeds. The parents and origin of F1 population is unknown. Vegetative data, pod data,
inflorescence data and seed data were collected under the guidance of both Luffa descriptor from
International Plant Genetic Resource Institute (IPGRI) and the Luffa catalogue from Plant Genetic
Resource Center (PGRC). The research revealed the variation in characters like leaf length, width,
internode length, peduncle length, fruit length, weight, mature fruit length, width was distinct
among the cultivated species. Data were analyzed using Minitab 17 software, and cluster analysis
was conducted to identify similar groups of accessions with a 70% similarity. Varieties were
grouped into clusters such as cluster one - Ajax, RG152; cluster two - KSP9298, Ajax, Amaya;
cluster three - RG003, RG007, Ajax, Roshani; cluster four - RG003, cluster five - Ajax, Roshani;
cluster six - Roshani based on qualitative and quantitative data accordingly. In conclusion, this
study found that descriptors used for morphological characterization effectively distinguished
differences between accessions. Cluster analysis also identified common parents among the
accessions were proven by the similarity index between the clusters. Future studies should use
Principal Component Analysis to select quality traits in luffa, discern distinct characteristics and
develop future populations (e.g., F4, F5, F6) for obtaining inbred lines.
