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Automatic drip irrigation scheduling effects on yield and water productivity of banana

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Title Automatic drip irrigation scheduling effects on yield and water productivity of banana
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Creator P.PanigrahiS.RaychaudhuriA.K.ThakurA.K.NayakP.SahuS.K.Ambast
 
Subject Automatic drip irrigation Water saving Banana Fruit yield Fruit quality
 
Description Journal article
Water scarcity is one of the major factors affecting the productivity of banana. Drip irrigation (DI) has been found as a water saving technique in banana cultivation. Further, sensor-based automated DI which has been considered as a smart and real time water application technique might increase the water savings and enhance yield of banana. With this hypothesis, a field experiment was conducted to study the performance of automated DI in banana (cv. Grand Naine) at Bhubaneswar, India during 2016–2017. Five automated DI schedules: (i) soil water sensor-based irrigation (I1) and timer based irrigation (ii) at 1 h interval 3 times daily at 80% crop evapotranspiration (ETc) (I2), (iii) at 2 h interval 2 times daily at 80% ETc (I3), (iv) at 1 h interval 3 times daily at 60% ETc (I4) and (v) at 2 h interval 2 times daily at 60% ETc (I5) were compared with manually operated DI at 100% ETc (I6) in the crop. The highest vegetative growth of plants (plant height, canopy diameter, stem girth) was observed with manually operated DI. However, sensor-based DI produced 15% higher fruit yield with 20% water saving, resulting in 40% higher water productivity (yield per unit quantity of water) compared with manually operated DI (water used, 820 mm; yield, 60.5 t ha−1; water productivity, 6.2 kg m−3) in the crop. The fruit qualities (total soluble solids and acidity) of sensor-based irrigated plants were superior to manually irrigated plants. The volumetric soil water content under manual DI was marginally higher (11–15%) than that under sensor-based DI (21.2–24.8%). The soil available nutrients (N, P and K) and leaf nutrients content of the plants followed the similar trend of soil water content under different treatments. The yield forecasting based on leaf-N, leaf-K, leaf water content and radiation interception using ‘Principal component analysis’ performed well with reasonably accuracy (R2 = 0.82). Overall, these results reveal that soil water sensor-based automated DI is a productive and water saving technique which may be adopted in banana cultivation in eastern India and anywhere else with similar agro-climates of the study site.
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Date 2021-07-20T04:47:33Z
2021-07-20T04:47:33Z
2019-01-01
 
Type Article
 
Identifier Not Available
0304-4238
http://krishi.icar.gov.in/jspui/handle/123456789/48973
 
Language English
 
Relation Not Available;
 
Publisher Elsevier