National Security and Geo Politics

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.

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Most economically dependent on agriculture, 2018
Source: WorldInFigures and The World Bank
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Agriculture, forestry, and fishing, value added (current US$), 2017, 2018, 2019
Source: The World Bank

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.



Rural Employment

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.

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World Employment in agriculture (% of total employment) and employment in services (% of total employment)
Source: The World Bank Employment in agriculture and The World Bank Employment in Services

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Credit To Agriculture

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. .



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Commodity Markets
Source: The World Bank

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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.

Food Security

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. .



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Commodity Markets
Source: The World Bank

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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.

Infrastructure & Digital Data Intelligence

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. .



png
Commodity Markets
Source: The World Bank

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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.

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More on Democratization of Artificial Intelligence for creating a sustainable food future, please check our published thought leadership paper: png
More on the role of combinatorial mathematical optimization and Heuristics, please check our published thought leadership paper: png