Big Data and Climate Smart Agriculture - Status and Implications for Agricultural Research and Innovation in India

被引:17
|
作者
Rao, N. H. [1 ]
机构
[1] Univ Hyderabad, Ctr Earth & Space Studies, Hyderabad, India
来源
关键词
D O I
10.16943/ptinsa/2018/49342
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Climate change will increase the vulnerability of agricultural production systems, unless scientists and farmers reorient their present approaches toward making them climate smart or climate resilient. The integration of recent developments in big data analytics and climate change science with agriculture can greatly accelerate agricultural research and innovation for climate smart agriculture (CSA). CSA refers to an integrated set of technologies and practices that simultaneously improve farm productivity and incomes, increase adaptive capacity to climate change effects, and reduce green house gas emissions from farming. It is a multi-stage, multi-objective, data-driven, and knowledge based approach to agriculture, with the farm as the most fundamental unit for both strategic and tactical decisions. This paper explores how big data analytics can accelerate research and innovation for CSA. Three levels at which big data can enhance farmer field level insights and actionable knowledge for the practice of CSA are identified: (i) developing a predictive capability to factor climate change effects to scales relevant to farming practice, (ii) speeding up plant breeding for higher productivity and climate resilience, and (iii) delivery of customized and prescriptive real-time farm knowledge for higher productivity, climate change adaptation and mitigation. The state-of-art on big data based approaches at each of the three levels is assessed. The paper also identifies the research and institutional challenges, and the way forward for leveraging big data in research and innovation aimed at climate smart agriculture in India.
引用
收藏
页码:625 / 640
页数:16
相关论文
共 50 条
  • [21] Climate-smart agriculture for sustainable agricultural sectors: The case of Mooifontein
    Mathews, Jennifer A.
    Kruger, Leandri
    Wentink, Gideon J.
    [J]. JAMBA-JOURNAL OF DISASTER RISK STUDIES, 2018, 10
  • [22] Climate-Smart Agriculture and Non-Agricultural Livelihood Transformation
    Hellin, Jon
    Fisher, Eleanor
    [J]. CLIMATE, 2019, 7 (04):
  • [23] Adaptation Implications of Climate-Smart Agriculture in Rural Pakistan
    Shahzad, Muhammad Faisal
    Abdulai, Awudu
    Issahaku, Gazali
    [J]. SUSTAINABILITY, 2021, 13 (21)
  • [24] Design of smart agriculture based on big data and Internet of things
    Li, Chunling
    Niu, Ben
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2020, 16 (05):
  • [25] Big Data Driven Smart Agriculture: Pathway for Sustainable Development
    Sarker, Md Nazirul Islam
    Wu, Min
    Chanthamith, Bouasone
    Yusufzada, Shaheen
    Li, Dan
    Zhang, Jie
    [J]. 2019 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND BIG DATA (ICAIBD 2019), 2019, : 60 - 65
  • [26] Agricultural biotechnology research in India: Status and policies
    Sharma, M
    Charak, KS
    Ramanaiah, TV
    [J]. CURRENT SCIENCE, 2003, 84 (03): : 297 - 302
  • [27] TECHNOLOGY AND ECOLOGY - IMPLICATIONS FOR INNOVATION RESEARCH IN PEASANT AGRICULTURE
    ASHBY, JA
    [J]. RURAL SOCIOLOGY, 1982, 47 (02) : 234 - 250
  • [28] Data-Driven Agricultural Innovation Technology for Digital Agriculture
    Kim, Wan-Soo
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (20):
  • [29] The research on application of agricultural big data agricultural economic management
    Zhao, Yuxuan
    [J]. AGRONOMY JOURNAL, 2023, 115 (01) : 59 - 70
  • [30] Environment and Big Data: Role in Smart Cities of India
    Dwevedi, Rajneesh
    Krishna, Vinoy
    Kumar, Aniket
    [J]. RESOURCES-BASEL, 2018, 7 (04):