NDVI is the best parameter for yield prediction at the peak vegetative stage of potato (Solanum tuberosum L.)

Abstract

Accurate yield prediction and optimization are critical for sustainable potato production, particularly in resource-limited regions affected by climatic variability. This study evaluates the normalized difference vegetation index (NDVI) values obtained during the peak vegetative stage to optimize tuber yield prediction in potato (Solanum tuberosum L.) under subtropical conditions. Field experiments were conducted over two years in Kharagpur, India, using a strip-plot design. Soil management treatments included mulched and non-mulched plots, while water management treatments comprised conventional furrow irrigation (C), drip irrigation at field capacity (D-FC), 90 ​% field capacity (D-90 ​%FC), and 80 ​% field capacity (D-80 ​%FC). Key parameters, including NDVI, biomass, soil moisture, and tuber yield, were measured and analyzed using correlation, principal component analysis (PCA), and quadratic regression models. NDVI emerged as a critical predictor of tuber yield, showing strong positive correlations with biomass and yield traits. Drip irrigation (D-FC) significantly improved tuber yield compared to conventional furrow irrigation, with the highest yield recorded at 26.22 ​t ​ha⁻¹, followed by D-90 ​%FC at 21.69 ​t ​ha⁻¹, while conventional irrigation yielded 22.37 ​t ​ha⁻¹. Additionally, mulching (+M) enhanced yields across all drip irrigation treatments. Treatments like D-90 ​%FC and D-90 ​%FC-M showed the highest associations with NDVI, biomass, and yield. A quadratic regression model (R² ​= ​0.95) accurately captured the relationship between NDVI and tuber yield, with model validation (R² ​= ​0.97) confirming its reliability across seasons. This study highlights the potential of NDVI-based monitoring for real-time yield prediction and precision irrigation in potato production. The findings suggest that integrating NDVI-based monitoring with advanced irrigation practices can enhance resource efficiency and promote sustainable agriculture.