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The effect of different nitrogen (N) treatments on the nutrient contents of tomato (Lycopersicon esculentum Mill., cv. ‘Tayfun F1’) under different boron (B) concentrations were investigated in greenhouse conditions with four replications. Four different levels of B (0, 5, 10 and 20 mg kg⁻¹) and three levels of N (100, 200, 300 mg kg⁻¹) were used in this research. The results showed that tomato plant growth was negatively affected with increasing B concentrations and symptoms of boron toxicity were observed. The tomato leaf nutrient concentrations were increased in all plants with B and N treatments and 20 mg kg⁻¹ B and 300 mg kg⁻¹ N treatments were determined to be more effective compared to the others. 20 mg kg⁻¹ B and 100 mg kg⁻¹ N treatment caused the highest micro element concentrations of tomato leaf. This could be interpreted as N application having a dilution effect to be able to maintain development under conditions of toxicity of B. The plants growth under boron toxicity conditions showed increased vegetation with increasing N applications which was attributed to the dilution effect.
Agricultural wastes have increased with the intensive production in recent years. These wastes that affect the physical, chemical and biological properties of soils should be composted and added to soil. In this study, composts were consisted of different agricultural wastes such as greenhouse wastes-GPW, used cocopeat wastes-UCW, spent mushroom composts-SMC and at different ratios. Used cocopeat wastes were especially chosen in this experiment because it was not preferred in compost mixtures up to the present. Five different compost mixtures were added to the soil and their effects on growth and nutrient contents of lettuce plants were determined. The experiment was carried out during two successive seasons (autumn and spring). The results showed that plant growth and yield were found higher in the compost applications than in control. Generally the highest values were obtained from M1 application (80% GPW + 10% UCW + 10% SMC) for many parameters.
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