Effects of Real-time Location-specific Drip Irrigation Scheduling on Water Use, Plant Growth, Nutrient Accumulation, and Yield of Florida Fresh-market Tomato

Abstract

Florida is the largest fresh-market tomato (Solanum lycopersicum L.)–producing state in the United States. Although vegetable production requires frequent water supply throughout the crop production cycle to produce maximum yield and ensure high-quality produce, overirrigation can reduce crop yield and increase negative environmental consequences. This study was conducted to evaluate and compare irrigation schedules by a real-time and location-specific evapotranspiration (ET)-based SmartIrrigation Vegetable App (SI) with a historic ET-based schedule (HI). A field study was conducted on drip-irrigated, fresh-market tomato during the Fall of 2015 and Spring of 2016 on a Florida sandy soil. The two scheduling methods (SI and HI) were evaluated for irrigation water application, plant biomass accumulation, nutrient uptake and partitioning, and yield in open-field tomato production. Treatments included 100% HI (T1); 66% SI (T2); 100% SI (T3); and 150% SI (T4). Treatments were arranged in a randomized complete block design with four replicates per treatment during the two production seasons. In both seasons, depth of irrigation water applied increased in the order of T2 < T3 < T1 < T4. Total water savings was greater for T3 schedule compared with T1 schedule at 22% and 16% for fall and spring seasons, respectively. No differences were observed among treatments for tomato biomass accumulation at all sampling periods during both seasons. However, T3 resulted in significantly greater total marketable yield compared with other treatments in both seasons. The impact of irrigation application rate was greater in fruit and leaf nitrogen accumulation compared with that of stem and root biomass. Based on the plant performance and water savings, this study concludes that under a sandy soil condition, a real-time location-specific irrigation scheduler improves irrigation scheduling accuracy in relation to actual crop water requirement in open-field tomato production.