Influence of Sensor Based Drip Irrigation and Nitrogen Management on Soil Parameters of Mulberry Garden
Arun Kumar, M. *
Department of Sericulture, College of Agriculture, UAS, GKVK, Bengaluru - 560 065, India.
Chandrashekar, S.
Department of Sericulture, College of Agriculture, UAS, GKVK, Bengaluru - 560 065, India.
Seenappa, C.
Department of Agronomy, College of Agriculture, UAS, GKVK, Bengaluru - 560 065, India.
Ramya, V. S.
Regional Sericultural Research Station, Central Silk Board, Anantapur, Andhra Pradesh-515 001, India.
Thimmegowda, M. N.
Department of Agrometeorology, College of Agriculture, UAS, GKVK, Bengaluru - 560 065, India.
*Author to whom correspondence should be addressed.
Abstract
Aim: India, the world’s second largest silk producer (40.44%), still faces sericulture expansion challenges due to limited land and freshwater availability for mulberry. Although drip irrigation is widely practiced, the systems themselves cannot determine when or how much to irrigate, which often leads to under- or over-irrigation by the farmer. A field experiment was conducted to study the effect of sensor based drip irrigation and nitrogen management on soil nutrient parameters of mulberry garden.
Study Design: There were nine treatment combinations comprising of three different drip irrigation and nitrogen management methods, replicated three times and laid out in strip plot design.
Place and Duration of Study: The field experiment was conducted during 2022-2023 at Department of Sericulture, University of Agricultural Sciences, GKVK, Bangalore.
Methodology: In conventional drip irrigation, the irrigation was scheduled based on irrigation water/cumulative pan evaporation (IW/CPE) approach whereas in Yellow SMI (YSMI) based drip irrigation, the irrigation was scheduled based on soil moisture sensor and in soil moisture sensor based drip Irrigation, irrigation was scheduled using soil moisture depletion approach. The soil properties were analyzed before and after the experiment by following standard procedures. Data generated were subjected to ANOVA using O.P stat software.
Results: The results showed that sensor based drip irrigation (16.22 ha cm) can save 12.32% of water when compared to conventional drip irrigation (18.50 ha cm) in mulberry. The significantly higher available nitrogen (270.37 kg ha-1), phosphorous (49.78 kg ha-1) and potassium (170.98 kg ha-1) were recorded in sensor based drip irrigation @ 50% DASM applied plots whereas significantly higher calcium (5.87 c. mol/kg) and magnesium (1.91 c. mol/kg) content were recorded in sensor based drip irrigation @ 50% DASM and conventional drip irrigation @ 0.8 CPE plots respectively. The micronutrients such as iron and manganese significantly increased with respect to 100% RDN application.
Conclusion: Sensor based drip irrigation at 50% DASM with NDVI based nano urea application has shown better results on soil primary and secondary nutrient status and also water productivity of mulberry. This proposed system not only reduces labour on irrigation but also eradicates the difficulties faced by the farmers due to delay in onset of monsoon.
Keywords: Sensor based irrigation, IoT, mulberry, precision farming, NDVI and Soil analysis