Performance of AI and IoT driven drip irrigation methods and scheduling approaches on growth and yield of chilli (Capsicum annum L.)

Abstract

A field study was carried out during winter (rabi) seasons of 2022-23 and 2023-24 at Water Technology Centre field, College Farm, College of Agriculture, Rajendranagar, Hyderabad. The experiment was laid out in split plot design with drip irrigation methods as main plots (2) and different irrigation scheduling approaches as subplots (4). The results divulged that between main plots, subsurface drip resulted in higher growth parameters and fruit yield (40.9 and 42.8 t ha-1) in chilli during 2022-23 and 2023-24 respectively. Whereas, among subplots, ET sensor based irrigation triggering resulted in higher growth parameters and fruit yield (42.1 and 44.2 t ha-1) during both the years respectively.