Millennials Farmers, Computation Data Analysis and Precision Farming

arshimehboobarshimehboob IndiaPosts: 78 ✭✭
edited March 2019 in Innovations
Innovation today is computation and data analysis. Ag-Tech thrust is to collect quality data, analyze it and provide solutions in “real time” in order to maintain agriculture innovative advantage.

Assuming millennials will drive 75% of the technological change in the farming industry in the coming years, recognising the penchant and dependence on innovative technologies.

Utilising smartphones aggregating and analyzing data, and coming up with effective shortcuts to make tasks more efficient with ingrained millennial instincts to leverage existing or innovating new technology to modernize farming.

Technological Developments for Precision Agriculture

A sustainable environmentally safe and cost effective production system will depend on spatio-temporal information based input management system. Recently, the Government of India launched soil health card programme during February, 2015 to generate soil health cards for 140 million land holdings through testing of 25.3 million soil samples at every three years interval.

The technology would not only help in geofencing / geomapping unit of insurance having homogenous risk profile for the crops, but also issuing advisories to avoid yield loss.

Geographic Information System (GIS) a computerized data storage and retrieval system, which can be used to manage and analyze spatial data relating to crop productivity and agronomic factors. Spatial decision support systems (SDSS) in GIS environment may help growers to solve complex spatial problems and to make a decision concerning to irrigation scheduling, fertilization, use of crop growth regulators and other chemicals.

Recent developments of India in independent positioning system (i.e. IRNSS) and precision navigation (i.e. GAGAN) strengthens GPS (Global Positioning System) enabled variable rate technology (VRT) to provide “on the fly” delivery of field inputs and also drone based VRT.

Limitations:
  • Small farms size, heterogeneity of cropping systems, and land tenure/ownership
    restrictions, high cost of obtaining site-specific data
  • Inadequate climate resilient technologies and frequent occurrence extreme events
    due to climate change
  • Complexity of tools and techniques requiring new skills
  • Perceptions of farmers including resistance to adoption of new techniques and lack
    of awareness of agro-environmental problems
  • Lack of local technical expertise
  • High initial investment
  • Uncertainty on returns from investments to be made on new equipment and
    information management systems, and
  • Knowledge and technological gaps including
  • Inadequate understanding of agronomic factors and their interaction,
  • Lack of understanding of the geostatistics necessary for displaying spatial variability of crops and soils using current mapping software, and
  • Limited ability to integrate information from diverse sources with varying resolutions and intensities.Infrastructure and institutional constraints including market imperfections
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