Optimization of tomato water productivity under deficit sub-surface drip irrigation and mulching systems

Abstract

The greatest challenge in the agriculture is to produce more food with low quantity of water. The challenge facing tomato farmers in Njoro Sub - County is the unfavourable conditions for tomato growth which includes very low rainfall during the seasonal dry periods. However, there is limited information on optimum water management practices, or deficit irrigation that would increase tomato crop yield and additionally improve the tomato quality when drip irrigation is used. The objective of this study was to evaluate the effect of deficit sub – surface drip irrigation and mulching systems on water productivity of tomato (Lycopersicon esculentum mill) crop in Njoro Sub - County. The study was carried out on experimental plots measuring 4 m2 in a shade at Egerton University. Factorial experimental design was used in this study where the treatments were three water levels (100 % ETC, 80% ETC and 60 % ETC) and four grass mulch densities (0, 0.5, 1.0 and 1.5 kg/m2 ) replicated three times. Drip laterals for the drip irrigation system were laid at a depth of 5.0 cm below the ground surface. An estimated water depth was applied to the respective experimental plots based on the various irrigation levels as guided by the four tomato crop growth stages. The agronomic parameters and yield were monitored on weekly basis over a period of 135 days. The results of tomato crop water productivity under the interactive effect of deficit sub – surface drip irrigation and grass mulch densities was highest at 60 % ETC and 1.0 kg/m2 of grass mulch and lowest at 100 % ETC and 1.5 kg/m2. Aquacrop model was used to estimate the tomato water requirements, water productivity, yield and biomass under deficit irrigation and mulching. The findings for the Aquacrop model showed a fair correlation between the actual and simulated yield, biomass and water productivity as determined by the Nash and Sutcliffe efficiency (NSE), Root Mean Square Error (RMSE) and Coefficient of determination (R2). The findings show application rates for farmers that will enable them to produce more tomato yields with little water. This has the potential to enhance farmer’s income from tomatoes thus leading to increased income by improving the agri-business of the small scale farmers in Njoro Sub - County.