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Plant Science Today (PST)

Research Articles

Vol. 12 No. sp4 (2025): Recent Advances in Agriculture by Young Minds - III

Agrometeorological assessment of Bt -Cotton yield with varietal interactions response under varying growing environments under semi-arid region of Hisar

DOI
https://doi.org/10.14719/pst.11387
Submitted
21 August 2025
Published
31-12-2025

Abstract

The present investigation was conducted during Kharif 2023 and 2024 at University Research Farm, CCS HAU, Hisar, Haryana, India to evaluate the influence of weather variability on Bt cotton yield across different growing environments. The study spanned 21 to 44 Standard Meteorological Weeks (SMWs), encompassing key weather parameters such as rainfall, temperature, humidity, wind speed, evaporation and sunshine hours. Four Bt cotton varieties were sown on 3 different dates with 3 replications of each to assess their phenological response and yield performance. Agrometeorological indices as Growing degree days (GDD), Heliothermal Units (HTU) and Photothermal Units (PTU) were computed to quantified thermal utilized by Bt cotton through life cycle completion. Results revealed variation of seed cotton yield under different growing environment. Maximum value of yield attributes (like No. of sympodial branches/ plant, No. of bolls/plant and Avg. boll weight/boll (g) and yield (yield/plant and yield/ha) was observed in crop sown earlier on 3rd week of May with maximum accumulation of thermal units (GDD, HTU and PTU). From present study it was concluded that variety V₄: ACH 177 performed best under prevalent weather conditions. For late sown crop 3rd week of May is suitable further delay in sowing leads to yield reduction. Future research should focus on developing user-oriented agrometeorological advisory systems that provide farmers with timely, location-specific guidance on optimum sowing dates and suitable Bt cotton varieties for prevailing weather conditions. Such initiatives would support sustainable Bt cotton production and enhance resilience to increasing climatic variability and uncertainty in semi-arid regions.

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