NASA's Transiting Exoplanet Survey Satellite (TESS) has been conducting high-precision photometric observations for over seven years, covering more than 95% of the sky. By the end of Cycle 8, over 90% of this coverage will include observations from multiple sectors. The upcoming ESA PLAnetary Transits and Oscillations of Stars (PLATO; Rauer et al. 2025) mission, scheduled for launch by the end of 2026, aims to detect terrestrial planets in the habitable zones of bright, Sun-like stars. PLATO will observe stars in the Southern Hemisphere (LOPS2) for a minimum of two years, overlapping with TESS's continuous viewing zone. By the time of PLATO's launch, TESS will have accumulated four years of data on this region, offering a unique opportunity to measure and catalogue stellar rotation periods in advance of the mission. TESS light curves, with 27-day observations per sector, contain intra- and inter-sector gaps occurring approximately every 14 days (due to downlink operations) and every 27 days (at sector boundaries). While suitable for detecting short rotation periods (Prot < 14 days), these gaps hinder the measurement of longer periods (Prot > 14 days). Variations in flux normalization across sectors further complicate the construction of long-baseline light curves for measuring rotation. To address this, we applied the PyTADaCS-R stitching module, which uses a Bayesian approach to stitch sector-normalized light curves. Using star-privateer (Breton et al. 2021, 2024) and a random forest classifier to identify stars exhibiting rotational signatures, we analyzed 32,000 stars in the PLATO LOPS2 field and identified reliable rotation periods for 9,000 stars.