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The influence of water field capacity and fertilizer combinations on tomato under intelligent drip in greenhouse
Abstract
Tomato production is significant as the demand is increasing in time to meet food security and human nutrition as well. The purpose of the study was to investigate the effect of water and fertilizer application in greenhouse tomato growth index, yield and quality using an intelligent drip system to achieve improved yield by minimizing the fertigation. A randomized block design was used in ten treatments including control (CK-W4N4,K4) consisting four level (W1-65%, W2-75%, W3-85%, W4-100%) each of water field capacity and four-level Urea-Potash (N1,K1-245,490, N2,K2-350,700, N3,K3-455,910, N4,K4-80,100 kg ha-1) combinations. Data obtained were analyzed by a general linear model and developed a regression model for yield. The results showed, the highest tomato yield was 103.16 t ha-1 in T8-W3N2K1 significantly influenced by the treatment, which is found 2% greater compared to the CK (100.92 t ha-1). The highest leaf area index (5.21) was obtained with T7-W3N1K3 produced improved yield. The highest fruit weight (288.77 g fruit-1) and fruit diameter (85.33 mm) obtained with T2-W1N2K2 had no significant influence on tomato yield. The model delivered a paramount prediction (r2 = 0.82) of tomato yield. In conclusion, results showed the intelligent drip system could be used to minimize inputs to improve tomato production.
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