A distinguishing feature of the music repertoire of the Syrian tradition is the system of classifying melodies into eight tunes, called 'oktoe\={c}hos'. It inspired many traditions, such as Greek and Indian liturgical music. In oktoe\={c}hos tradition, liturgical hymns are sung in eight modes or eight colours (known as eight 'niram', regionally). In this paper, the automatic oktoe\={c}hos genre classification is addressed using musical texture features (MTF), i-vectors and Mel-spectrograms through stacked bidirectional and unidirectional long-short term memory (SBU-LSTM) and GRU (SB-GRU) architectures. The performance of the proposed approaches is evaluated using a newly created corpus of liturgical music in Malayalam. SBU-LSTM and SB-GRU frameworks report average classification accuracy of 88.19\% and 87.50\%, with a significant margin over other frameworks. The experiments demonstrate the potential of stacked architectures in learning temporal information from MTF for the proposed task.