Optimization of Water Use Efficiency of Hydroponic Maize Fodder Production System under Different Microclimatic Conditions

Aims: Hydroponic method of producing fodder is an advanced technique which helps to achieve very high-water use efficiency (WUE). The main objective of the study was to optimize WUE by controlling the system and reducing the stress on the crops to give higher yield. Study Design: The experiment employed a statistical design known as Completely Randomized Design Place and duration of the study: The experiment was carried out in the Precision Farming Development Centre (PFDC) building, Kelappaji College of Agricultural Engineering and Technology (KCAET), Tavanur during May and June 2021. Methodology: Three different water application methods namely, mist (I1), micro sprinkler (I2), fogger (I3) was selected. Artificial light source of LED red (L1), LED blue (L2), LED red + blue (L3) and sunlight (L4) were considered for the study. Statistical analysis was conducted to understand the significance of different treatments used in the experiment in optimizing yield and WUE of the system. Results: Highest yield was observed in treatment involving fogger irrigation and LED red + blue (2.11 kg/tray) with highest WUE (515.43 kg/m3) compared to other treatments. Seed to fodder ratio obtained was 1:6. Chemical analysis showed higher percentage of crude protein (13.56%) and crude fibre (12.59%) in this treatment. Higher growth of green fodder under artificial light source can be attributed to the continuous supply of energy compared to highly varying sunlight and also the uniform distribution of water by fogger irrigation which maintained favourable condition for fodder growth. Conclusion: Results clearly indicated that growing green fodder with artificial light source (LED red + blue) and water supply with fogger can be recommended to farmers for achieving better growth of green fodder for domestic animals

Improving Yield of Tomatoes Grown in Greenhouses Using IoT Based Nutrient Management System

Aims: This paper discuss, a study conducted to evaluate the developed automated IoT based fertigation control system for greenhouse for tomato (Solanum lycopersicum L.) crop. Study Design: Different nutrient and irrigation water levels were used to evaluate developed system using three replications in a factorial randomized block design (RBD). Methodology: An automated fertigation scheduling system was implemented in a greenhouse with soil moisture sensors at three depths (15, 30, and 45 cm) within the tomato root zone. R2, RMSE, NSE and MAE values were used to establish the correlation between sensor values and actual soil moisture. Tomato crop biometric parameters were collected and analyzed to evaluate the system's performance. Results: The results indicated strong correlation between sensor and observed soil moisture with R2 (0.8642 to 0.9528), RMSE (1.0786 to 1.8328), NSE (0.8438 to 0.9463), and MAE (0.9729 to 1.7043) values. Highest plant height (255 cm), girth (2.29 cm), number of leaves (21), number of flowers (23.1), fruit length (8.05 cm), fruit weight (110 g), yield/plant (2.75 kg), yield (68.77 t/ha) and sugar (5.1°Brix) were observed with drip irrigation at the rate of 100% ETc and 100% recommended dose of fertilizer (RDF), while minimum values of these parameters were noted in the control treatment. Conclusion: Using sensor-based drip irrigation at 100% ETc and 100% RDF led to a 62.92% increase in tomato yield and water saving of 14.84% compared to the control treatment. For tomato crop, the system required 2.27 l/plant/day water at 100% ETc. The developed automated fertigation system found suitable for greenhouse vegetable crops with the use of sensor based drip irrigation at 100% ETc and 100% RDF