The food and agriculture sectors are extensive, interconnected, diverse, and complex.
Designated as critical infrastructure and primarily owned and operated by private sector and non‑Federal entities,
food and agriculture systems and supply chains are vulnerable to disruption and damage from domestic and global threats.
One underlying theme that is vital is the cybersecurity that impacts all other major influencers.
Cyber security is the minimum requirement to make food production and data systems function at their full potential and
at their full optimal level as food cyber security is the national security. Most people don’t pick up a mango in the
produce aisle of a grocery and think to themselves, "How might the situation of the smallholder farmers that produced this
fruit halfway across the world contribute to U.S. national security?" But the next time you notice your fruit has a sticker
that says “Product of Ecuador,” remember that the world’s smallholder farmers - most of whom live off-grid, in rural areas
in emerging markets - produce around a third of the world’s food and are an integral part of global food security.
This means they are an integral part of national security and the environment that allows your business to keep running as usual.
Investing in improving and protecting the productivity of smallholder farmers will help stabilize an incredibly uncertain future.
The purpose of the Machine Learning and Artificial Intelligence algorithms developed ensure sustainability to small farmers
that ensure overall security to the world.
More on Food Security is National Security, please refer the White House Briefing -
National Security Memorandum on Strengthening the Security and Resilience of United States
Food and Agriculture.
and Food Safety Modernization Act (FSMA) -
The FDA Food Safety Modernization Act (FSMA) is transforming the nation’s food safety system by shifting the focus from responding to foodborne illness to preventing it.
Agriculture is one of the largest worldwide employers and is one of the biggest industries; in 2018, agriculture contributed to 3.272 percentage (Source: The World Bank ) of the global gross domestic product (GDP) and, in some developing countries, it can account for more than 25% of the (GDP).
Globally, Food and Agriculture business form a $5 trillion industry that is growing, with the largest agricultural output being from China ($978.5 billion 2018, $1020.11 billion 2019), India ($431.37 billion 2018, $478.72 billion 2019), the Unites States of America ($189.744 billion 2018, $196.51 billion 2019), Indonesia ($133.5 billion 2018, $142.26 billion 2019), and Nigeria ($84.2 billion 2018, $98.16 billion 2019) (The World Bank - Agriculture, forestry, and fishing, value added (current US$)).
The countries that developed with Agriculture include: China, India, the United States of America, the Republic of Indonesia, Brazil, Liberia, and Somalia. Countries with the highest dependencies of their GDP depend on the agriculture include: Sierra Leone, Guinea-Bissau, Chad, Niger, Mali, Libera, Kenya, Sudan, Ethiopia, and Central Africa Republic. It is no wonder that the agriculture employees around 65% of adults worldwide and many are small scale farmers.
In summary, agriculture is economic and industrial backbone of a nation and the small farmers are the major workfoce that make it possible. The economic growth of a country is directly dependent upon the way it treats its Small Farmers and taking care of small farmers is in the direct vested interest of the country.
Explanations of the importance of the agricultural sector in the economy as economic growth progresses have benefitted greatly from the dual sector theory of Arthur Lewis. The modern service or industrial sector utilizes the surplus labor in the agricultural or primary sector as its source of growth, along with capital generated by the investment of savings, to expand its production and thus the gross output of the economy. As the Services or industrial (modern) sector expands in importance, there is a concomitant reduction in the percentage contribution to gross output by the agricultural sector. This growth process thus generally requires the movement of labor from rural areas to the urban areas with a decline of the rural population as a percentage of the national population. Paradoxically, the rural population and percentage of agriculture employment to total employment play an important role in the growth of agriculture. It is general knowledge that agriculture does not just contribute food and fiber to the economy, but also labor, capital, and foreign exchange, which all go toward economic development. if agriculture fails to develop at a suitable pace, this could prove to be a critical constraint to the growth of the industrial sector as well as other sectors of the economy.
Many of the agricultural datasets (for instance, the World Bank, Food And Agriculture Organization of the United Nations, the United States Department of Agriculture, and other agricultural research institutions) are derived from census and Survey Data Sources. The inclusion of Internet of Things (IoT) enabled data sources is a major game changer and helps to develop a closed loop back system with near teal-time or real-time information insights. Hanumayamma Dairy IoT Sensors provide such advantage to small farmers across the world. Dissecting the interplay of macro level economics, commodity prices, demand factors, environmental factors, transportation & storage factors, and weather patterns is complex. Enabling the small-scale farmer with this information on a constant basis would provide a better planning tool, information services, and enable small scale farmer to join information & Information Communication Technologies (ICT). Application of advanced data science techniques, Natural Language Processing, and Econometric models to deliver easily digestible form would bring big data revolution to small scale farmer. .
Hanumayamma Analytics platform analyzes the credit to Agriculture from over 120 countries on the amount of loans provided by the private/commercial banking sector to producers in agriculture, forestry and fisheries, including household producers, cooperatives, and agro-businesses. Predicting commodity prices is a challenge and includes data science & econometrics overlay with macroeconomic factors, governmental regulations, subsidies, import/export, production, and demand356 [8]. The application of econometric analysis, advanced statistics techniques, and machine learning and artificial intelligence techniques provide understanding of price transmission, correlation, and causality.
Many of the agricultural datasets (for instance, the World Bank, Food And Agriculture Organization of the United Nations, the United States Department of Agriculture, and other agricultural research institutions) are derived from census and Survey Data Sources. The inclusion of Internet of Things (IoT) enabled data sources is a major game changer and helps to develop a closed loop back system with near teal-time or real-time information insights. Hanumayamma Dairy IoT Sensors provide such advantage to small farmers across the world. Dissecting the interplay of macro level economics, commodity prices, demand factors, environmental factors, transportation & storage factors, and weather patterns is complex. Enabling the small-scale farmer with this information on a constant basis would provide a better planning tool, information services, and enable small scale farmer to join information & Information Communication Technologies (ICT). Application of advanced data science techniques, Natural Language Processing, and Econometric models to deliver easily digestible form would bring big data revolution to small scale farmer. .
Hanumayamma Analytics platform analyzes the credit to Agriculture from over 120 countries on the amount of loans provided by the private/commercial banking sector to producers in agriculture, forestry and fisheries, including household producers, cooperatives, and agro-businesses. Predicting commodity prices is a challenge and includes data science & econometrics overlay with macroeconomic factors, governmental regulations, subsidies, import/export, production, and demand. The application of econometric analysis, advanced statistics techniques, and machine learning and artificial intelligence techniques provide understanding of price transmission, correlation, and causality.
The World is at a critical juncture.In 2020, nearly one in three people did not have access to adequate food - between 720 and 811 million people faced hunger. Compared with 2019 , 46 million more people in Africa, almost 57 million more in Asia, and about 14 million more in Latin America and the Caribbean were affected by hunger. Based on forecasts of global population growth, current deficit to feed people around the world, and increased demand for greener fuel & biodiesel, food security will remain an important economic development issue over the next several decades. As food-versus-fuel tension becomes more intense , the day will come when more agricultural products will be used for energy than food. Adding to the conundrum, the COVID-19 pandemic has changed the face of the earth in terms of supply chain, resource availability, and human labor and has exposed our vulnerabilities in food security to an even greater extent. In essence, humanity is at a critical juncture and what this unprecedented movement in our lives has thrusted upon us -- the practitioners of the agriculture and technologists of the world -- is to innovate and become more productive to address the multi-pronged food security challenges.
Many of the agricultural datasets (for instance, the World Bank, Food And Agriculture Organization of the United Nations, the United States Department of Agriculture, and other agricultural research institutions) are derived from census and Survey Data Sources. The inclusion of Internet of Things (IoT) enabled data sources is a major game changer and helps to develop a closed loop back system with near teal-time or real-time information insights. Hanumayamma Dairy IoT Sensors provide such advantage to small farmers across the world. Dissecting the interplay of macro level economics, commodity prices, demand factors, environmental factors, transportation & storage factors, and weather patterns is complex. Enabling the small-scale farmer with this information on a constant basis would provide a better planning tool, information services, and enable small scale farmer to join information & Information Communication Technologies (ICT). Application of advanced data science techniques, Natural Language Processing, and Econometric models to deliver easily digestible form would bring big data revolution to small scale farmer. .
Hanumayamma Analytics platform analyzes the credit to Agriculture from over 120 countries on the amount of loans provided by the private/commercial banking sector to producers in agriculture, forestry and fisheries, including household producers, cooperatives, and agro-businesses. Predicting commodity prices is a challenge and includes data science & econometrics overlay with macroeconomic factors, governmental regulations, subsidies, import/export, production, and demand356 [8]. The application of econometric analysis, advanced statistics techniques, and machine learning and artificial intelligence techniques provide understanding of price transmission, correlation, and causality.
