Silicon Improves the Plant Growth and Fruit Quality of Cherry Tomato (Solanum lycopersicum var. cerasiforme) under Nitrogen Imbalance by Modulating Nitrogen Assimilation and Photosynthesis

Abstract

Silicon (Si) is typically considered a nonessential but beneficial element for most plants, and it can alleviate nutrient imbalance stress in crops. However, few studies have investigated the impact of Si application on the growth and fruit quality of cherry tomatoes, leading uncertainty regarding whether Si application can improve cherry tomato yields and quality under N imbalance. In this study, we performed a pot experiment with cherry tomato plants, and used two N fertilizer inputs (high N level, 0.40 g N kg^− 1 soil; low N level, 0.20 g N kg^− 1 soil) with or without Si application, to investigate the influence of Si application on plant growth, photosynthesis, leaf N metabolic enzyme activities, and fruit quality in cherry tomatoes under N imbalance. This study aimed to assess the promotive effects of Si application on the growth and fruit quality of cherry tomatoes under nitrogen (N) imbalance. The results showed that Si application enhanced dry matter accumulation and photosynthesis, regardless of the N conditions. Compared with treatment without Si application, the total dry matter accumulation, net photosynthetic rate, stomatal conductance, and transpiration rate were enhanced by 2.59%, 3.76%, 23.9%, and 17.1% under low N conditions, and by 7.50%, 26.2%, 49.1%, and 26.3% under high N conditions, respectively. Furthermore, Si regulated the activities of leaf N metabolic enzymes, increasing the N content of the plant under low N conditions and decreasing it under high N conditions. Si application improved fruit quality, as the vitamin C content and firmness were increased by 13.2% and 3.57% under low N conditions and by 7.09% and 17.4% under high N conditions, respectively. This study provides evidence regarding Si application as a beneficial strategy for cherry tomato production, highlighting its potential role in optimizing plant responses to varying N levels.