Economic Viability and Capital Payback of IoT-Automated Drip Irrigation Coupled with Biostimulant Application in Tomato
Jagarlamudi Nethra *
Vignan Institute of Agriculture and Technology (VIAT), School of Agriculture and Food Technology, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Vadlamudi, Guntur 522213, Andhra Pradesh, India.
M. Chandra Surya Rao
Vignan Institute of Agriculture and Technology (VIAT), School of Agriculture and Food Technology, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Vadlamudi, Guntur 522213, Andhra Pradesh, India.
V. Vijaya Bhaskar
College of Horticulture, Chinalatarapi, Dr. Y.S.R. Horticultural University, Venkataramannagudem 534101, West Godavari District, Andhra Pradesh, India.
U. Shiva Kumar
College of Horticulture, Parvathipuram, Dr. Y.S.R. Horticultural University, Venkataramannagudem 534101, West Godavari District, Andhra Pradesh, India.
U. Pandu
Vignan Institute of Agriculture and Technology (VIAT), School of Agriculture and Food Technology, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Vadlamudi, Guntur 522213, Andhra Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
Background & Aims: Commercial tomato production in semi-arid regions requires irrigation strategies that conserve water without undermining farm returns. This study evaluated the financial performance of Internet of Things (IoT)-automated drip irrigation combined with foliar biostimulants, using both annualised agricultural costing and seasonal cash-flow accounting.
Methods: A split-plot experiment with three replications was conducted over the 2024–25 and 2025–26 late Rabi seasons in Andhra Pradesh, India. Conventional calendar-based drip irrigation was compared with sensor-controlled irrigation triggered at 25% and 50% depletion of available soil moisture. Four foliar treatments comprised a water-spray control, seaweed extract, humic and fulvic acids, and amino acids with peptides. Capital payback, monetary water productivity and sensitivity to price and yield changes were assessed.
Results: Initial capital expenditure was ₹ 1,71,884 ha⁻¹ for conventional drip infrastructure and ₹ 4,69,484 ha⁻¹ for the IoT-automated installation. Under CACP costing, automated drip at 25% DASM with foliar amino acids (I2B4) recorded the highest pooled net returns (₹ 6,54,493 ha⁻¹) and benefit-cost ratio (2.53), yielding ₹ 11,14,801 ha⁻¹ in net returns (B:C 3.60) in Year 2. Under cash-flow accounting, complete capital recovery occurred in 1.18 crop seasons (14.2 calendar months) for the total IoT setup and 1.24 crop seasons (14.9 calendar months) for the incremental automation retrofit. Scheduling irrigation at 25% DASM saved 17.12% applied water (88.71 mm) and lifted gross economic water productivity from ₹ 57.48 to ₹ 279.79 m⁻³. Sensitivity modelling confirmed farm solvency (B:C 1.76) even under concurrent -20% market price and -20% yield reductions.
Conclusion: Sensor-automated drip irrigation scheduled at 25% DASM combined with foliar amino acid application delivered maximum net farm earnings, amortised capital equipment within two seasons and conserved substantial irrigation water. Extending operational state micro-irrigation subsidies (APMIP G.O.Rt.No.1004) to include sensor hardware shortens chronological payback to 1.12 seasons, establishing clear financial justification for commercial smallholder adoption.
Keywords: Benefit-cost ratio, biostimulants, CACP cost concepts, capital payback period, cash-flow accounting, IoT automation, precision drip irrigation, tomato, water productivity