Big Data Agriculture

Farmers tend to be loyal to specific dealers and input brands. Given that complexity of input decision making. Given the annual nature of growing seasons and the rate of change in production biotechnologies, data aggregation across a large number of farms is critical to developing improved crop forecasting models and production recommendations. Individual farm-level longitudinal data would not generate sufficiently large data samples to estimate useful models. This is especially true given the geo-climatic-specific nature of farms, since soil characteristics and climate both vary regionally and are key determinants of crop production and farm input choice. The attributes of large individual farming operations or a group of farms in a particular region – may add variation to the estimation sample that allows for more precise estimates of key parameters.

Huetz mobile will be responsible for database management of the farmer upon un-disclosure agreement with the other stakeholders with an economic interest, such as the tenant, landowner, cooperative, owner of the precision agriculture system hardware. The data privacy principles contractual consent documents, including disclosures of how data will be used and the third parties with whom data will be shared.  Our services includes are:

  • Adding precision to agriculture: Knowing when and what to plant; being demand-driven; sharing what farmers are growing and how much; measuring changes in practices and their relative benefit(s);
  • Enabling frequent feedback : Via 2-way feedback loops for better decision- making, service delivery and programming; understanding farmer demands; for influencing extension info delivery; for localized and tailored services;
  • Increasing cost-effectiveness and time savings: Proven reductions in cost; leveraging tools across projects; linking systems to reporting mechanisms ;
  • Increasing reach: Greater farmer reach globally and engagement; that is, difficult to achieve through analog processes and using crowdsourcing platform;
  • Agricultural Transformation: The process by which an agrifood system transforms over time from subsistence-oriented and farm-centered to more commercialized, productive, and off-farm centred.

Technological developments in combination with shifts in power relationships   and   new   business   models   can   cause disruption   in agri-food   supply   chains. Technologies are distinguished into following:

  1. Expected high impact on  agri-food value  chain:  Internet  of Things  (IoT),  Robotization, Artificial Intelligence (AI) and Big Data;
  2. Expected medium   impact   on  agri-food  value   chain:   Blockchain,  Global  Navigation;
  • Satellite System (GNSS) and Virtual Reality (high longer-term impact);
  1. Expected low-impact on agri-food value chain:  Broadband networks, Information  and Communication  Technology (ICT) and platforms for e-business.

Value Co-creation

  1. Technology advancement includes  integration  of  technologies  in  systems  to  enhance traceability.  Often  IoT,  Big  Data  and  Artificial Intelligence (AI)  are  used   in  combination,  as  well  as  AI  and robotization. Drones are often combined with satellites and Big Data;
  2. Some applications of technologies target reduction of risks in agricultural production, such as detecting crop diseases early on in production. For instance, use of drones to create detailed soil maps for damage control, benefit the whole value chain. Some technologies target  risks associated  with emissions and climate change, which impact  the  society more broadly, including consumers and citizens;
  • Other applications of technologies primarily target efficiency in production, such as use of water and energy throughout the value chains. Efficiency impacts the  environment  and climate positively, as well as productivity; and
  1. Besides impacting vertical integration, digital technologies impact horizontal integration in the food chain, which tends to favour large food suppliers.
  • Agriculture Value Chain Development
    Innovation is increasingly important for the competitiveness of farming and agri-food sectors. The full range of product and process development opportunities can be offered to smaller processors and farm businesses. Targeted investment in equipment, management processes and training. Innovation initiatives focusing on individual farms or on the agri-food chain (particularly for quality products), thereby, achieving a multiplier effect in various agriculture value chain development in the following sectors;
  1. Agro Crops Production – Cereals;
  2. Agro Production – Fat and Oil Seeds;
  • Agro Crops Production – Fiber;
  1. Agro Crops Production – Fruits, Pastures, Grasses and Legumes;
  2. Agro Crops Production – Grain Legumes;
  3. Agro Crops Production – Root and Tubers;
  • Agro Crops Production – Vegetables Crops;
  • Agro Crops Production – Tree Crops;
  1. Livestock’s Farms – Fisheries, large and small animals;
  2. Seed Farms – Organic farming of seed;
  • Post-Harvest and Allied Processing;
  • Storage management and Air cargo export; and
  • Agriculture aviation.

merging Business Environment

  1. Enlarging the context of business: stakeholder value and  social responsibility;
  2. Networking in innovation ecosystem;
  • Formal and informal ties, local collaboration;
  1. Global collaboration with best partners;
  2. Forming local and global partner;
  3. Adopting an distributed model of innovation;
  • Open innovation;
  • Using innovation democracy as an asset; and
  1. Users and customers as innovator for value co-creation.