The present scenario witnesses an exponential growth in the research field pertaining to text mining and automatic text summarization is a relevant topic. Varied methods in this regard have been developed for English and other European languages, but Odia language maintains a nascent status. The complexity and the highly inflective property of the language restrict the existing models for being directly applied on it. This paper proposes effective extractive single document automatic summarizer for Odia text document. Both statistical and clustering methods are applied and their evaluation metric F scores are compared. The present work is the need of the existing scenario. The experimental documents belong to news domain. The proposed algorithms meticulously deal with the complexity of the language and solve the problem of summarization to an appreciable extent.