Assessing long term impact of nutrient management and rainfall variability on the agroecological resilience of maize (Zea mays)- wheat (Triticum aestivum) system in NW India

P SHEORAN; SHER SINGH; S S BAWA; V SARDANA; ASHWANI KUMAR; RAJKUMAR; B BHUSHAN; G S DHERI

doi:10.56093/ijas.v86i1.55246

Authors

P SHEORAN ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
SHER SINGH ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
S S BAWA ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
V SARDANA ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
ASHWANI KUMAR ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
RAJKUMAR ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
B BHUSHAN ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001
G S DHERI ICAR-Central Soil Salinity Research Institute, Karnal, Haryana 132 001

https://doi.org/10.56093/ijas.v86i1.55246

Keywords:

Maize-wheat, Nitrogen, Prediction model, Rainfall, Sustainability

Abstract

A long-term (2000-2010) field experiment was carried out in the lower Shiwalik foothills of Punjab to study the carry over effect of organic manures and fertilizers on the productivity of maize (Zea mays L.)- wheat (Triticum aestivum L.) cropping system for efficient N management and resource use under rainfed conditions and to develop predictive models describing relationship between yields and seasonal rainfall. N management strategies involving combined application of 15 kg N/ha either through compost or leucaena loppings along with 20 kg N/ha through inorganic fertilizer for maize-wheat cropping sequence utilized growth resources most efficiently and maintained stable yield performance culminating in significantly higher system productivity, better resource use efficiencies and sustainable yield index, suggesting partial N substitution through compost or locally available plant material. The regression models developed to predict the effects of N sources on crop yields using monthly rainfall would be of interest to estimate the yield at a given level of rainfall with the likely fluctuation (as error) particularly under rainfed conditions.

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