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Agricultural Input Use Efficiency and Climate Change: Ways to Improve the Environment and Food Security

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Input Use Efficiency for Food and Environmental Security

Abstract

Crop yields and input use efficiency are highly affected by prevailing climatic conditions. Increase in climatic aberrations in the recent past has increased year-to-year variations in crop productivity over different regions of the globe. Crops yield is the maximum under specific set of climatic conditions, referred to as cardinal/optimum limits as under optimum conditions, there is highest growth, yield, and efficiency of utilization of resources. However, increased variations in the recent years are leading to deterioration of soil and environmental health. As a result, input use efficiency is declining, endangering sustainability of agriculture and natural resources and threatening food security. Climate change triggered increase in frequency and intensity of extreme weather events, resulting in significant yield losses every year along with deterioration of natural resources. Climate projections are further indicating about intense warming scenarios if appropriate measures are not taken to contain the emissions from various sectors. Unfavorable weather conditions significantly reduce heat, water, radiation as well as nutrient use efficiency of crops. Under such conditions, adoption of mitigation and adaptation strategies is essentially required to sustain crop productivity and natural resource base. Various agronomic management strategies such as adjustment of sowing time, irrigation management, fertilizer management, etc., need to be adopted in different crops for improved resilience to climate. Identification and development of stress tolerant genetic resource base are required to develop varieties able to resist different types of stresses. Various microclimatic modifications such as mulch applications, row orientation, row spacing, etc., should be explored to create optimum crop microclimate. Timely available and accurate weather forecasts and agro-advisory services can also play significant role in decreasing the harmful effects of extreme weather conditions. Crop simulation modeling is another strategy that can be used successfully to study crop responses to various stresses, which can also help in decision-making and research reorientation in view of climate change. The emerging techniques of remote sensing should also be applied in the field of agriculture to monitor and predict crop responses to various stresses and to find out viable solutions at regional level. Multidisciplinary approach involving exhaustive research efforts is the need of the hour for sustaining agricultural productivity as well as improving input use efficiency and environmental health under changing climatic scenarios.

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Abbreviations

AET:

Actual evapotranspiration

ASW:

Available soil water

AwiFS:

Advanced wide field sensor

B2A :

Different climate change scenarios

CERES:

Crop

CWP:

Crop water productivity

DSSAT:

Decision support system for agrotechnology transfer

ET:

Evapotranspiration

f:

Fractional PAR interception

FACE:

Free air CO2 enrichment

FAO:

Food and Agriculture Organization

FYM:

Farmyard manure

GHGs:

Greenhouse gases

GI:

Green index

GIS:

Geographic Information System

gLAI:

ground measured leaf area index

GPS:

Global positioning system

HI:

Harvest Index

HUE:

Heat use efficiency

IGP:

Indo-gangetic plains

IMD:

India Meteorological Department

IPCC:

Inter-governmental Panel on Climate Change

IRSS:

Indian Remote Sensing Satellite

ITSGB:

Irrigation at tillering, stem elongation, booting and grain filling stages

IW/CPE:

Irrigation water/cumulative pan evaporation

k:

Canopy extinction coefficient

Ky:

Yield response factor

LAI:

Leaf area index

LSD:

Least square difference

NCP:

North China Plain

NDMI:

Normalized difference matter index

NDVI:

Normalized difference vegetation index

NDWI:

Normalized difference water index

NOAA:

National Oceanic and Atmospheric Administration

NUE:

Nitrogen use efficiency

PAR:

Photosynthetically active radiation

PET:

Potential evapotranspiration

PSO:

Particle swarm optimization

RMSE:

Root mean square error

RRMSE:

Relative root mean square error

RUE:

Radiation use efficiency

RUEGY:

Radiation use efficiency for grain yield

RVI:

Ratio vegetation index

SAVI:

Soil-adjusted vegetation index

SDD:

Stress degree days

SNP:

Sodium Nitroprusside

SSP:

Shared socioeconomic pathway

Tc – Ta:

Canopy minus air temperature

Tc:

Canopy temperature

TFs:

Transcription factors

TSMC:

Tarafeni south main canal

WPET:

Water productivity based on evapotranspiration

WUE:

Water use efficiency

WUEDM:

Water use efficiency for dry matter

WUEY:

Water use efficiency for yield

WUEYRS :

Remote sensing generated yield-based water use efficiency

YRS:

Remote sensing based yield

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Authors and Affiliations

  1. Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana, Punjab, India

    P. K. Kingra

  2. Agricultural Meteorology Division, India Meteorological Department, Office of the Climate Research and Services, Pune, Maharashtra, India

    A. K. Misra

Authors
  1. P. K. Kingra
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  2. A. K. Misra
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Correspondence to P. K. Kingra .

Editor information

Editors and Affiliations

  1. Regional Research Station, Punjab Agricultural University, Ludhiana, Punjab, India

    Rajan Bhatt

  2. Department of Agronomy, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India

    Ram Swaroop Meena

  3. Soil Science Division, Bangladesh Wheat and Maize Research Institute, Dinajpur, Bangladesh

    Akbar Hossain

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© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kingra, P.K., Misra, A.K. (2021). Agricultural Input Use Efficiency and Climate Change: Ways to Improve the Environment and Food Security. In: Bhatt, R., Meena, R.S., Hossain, A. (eds) Input Use Efficiency for Food and Environmental Security. Springer, Singapore. https://doi.org/10.1007/978-981-16-5199-1_2

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