Data Science – the defender of the last resort

Across the world, small farmers are facing unprecedented challenges – a fact that can be witnessed through increasing rural poverty rates and the rapid decline of small farmers in the national US and other places. The numbers speak for themselves: In Europe, agriculture is the major employment provider with about 10.5 million agricultural holdings in 2016. Despite this, farm numbers, ironically, have been in steep decline for many years. Most of the EU’s farms are small in nature; two thirds were less than 5 hectares in size in 2016. These small farms play an important role in reducing the risk of rural poverty, by providing additional income and food. Like Europe, agriculture and animal husbandry are the major sources of income for the people in Asia. Agriculture is important for all countries of Asia and the Pacific, with more than 2.2 billion people relying190 on agriculture for their livelihood. Small and marginal farmers hold 86% of the agricultural landholding in India191.
Agriculture is by far the single most important economic activity in Africa193. It provides employment for about two-thirds of the continent’s working population and for each country contributes an average of 30 to 60 percent of gross domestic product and about 30 percent of the value of exports. While Africa holds more than 60% of the worlds arable land194, the continent’s share in global agricultural production remains low.
Agriculture is largest employer in the Latin America and Caribbean (LAC) region. In 2018, 14.1% of total labor force in the LAC region was employed in agriculture. Countries. The LAC region experiences high incidence of poverty and extreme poverty in rural areas (48.6% and 22.5%, respectively) since 2017 and widening gap between rural and urban poor with high undernourished people in the region (39.3 million).

Artificial Intelligence play an important role in improving productivity of small farmers across the world and improve standard of living. Through Data Science and Machine Learning Techniques, a small increase in productivity improves financial wellbeing of small farmers and reduce the widen gap & rural poverty. Importantly, Artificial Intelligence is the defender of the last resort in protecting small farmers from the onslaught on their survival - increasing "industrialization" of agriculture by large industrial houses and the application of automation at the expense of economic stability & sustainability of small farmers. Put it simply, the competitive market landscape is no longer plane and equal. In the "David and Goliath” fight, the small farmers need the capabilities of advanced machine learning and data science that can help them to prepare onslaught of “industrialization”.

 
 

 
 

Try Our Fertilizier Price Predict

Fertilizer Price Predict Model is based on the World Bank Pink Sheet Data. Please note that the Machine Learning model developed considers the variance of Fertilizer Price depend on the demand for Commodities. For instance, more demand of Commodities for example Rice or Wheat exert pressure on production side. This indeed increases the consumption of Fertilizers. Second, on the Supply side, in order to make Fertilizer one of the important component is Crude Oil or Natural Gas (depend on the manufacture technique). By inputting both demand and supply side, we can at least provide Small Farmer on the trend of Fertilizer prices.

As per the World Bank pink sheet data, the following are common Fertilizers used:

  • DAP (diammonium phosphate)
  • Phosphate rock
  • Potassium chloride
  • TSP (triple superphosphate)
  • Urea


Urea is the top fertilizer used across the world with consumption around 113,122.89 tonnes per year.

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Commodity Markets
Source: The World Bank

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Try our Milk Price Predict Model

You can access our current Milk & Agricultural Commodities Machine Learning Model through the button below; Our Open AI model is built on top of USDA and FAO Datasets. The model features the following commodities:
  • Corn - Corn stalks are a cost effective means of ration for lactating cows, or those ready to produce milk; acknowledging this, it is important for producers to exercise caution when using corn stalks as ration and not add them at excessive inclusion rates.
  • Wheat – Traditionally, the milling of wheat produces flour for both human and animal consumption. Wheat becomes an attractive feed ingredient for the cattle, swine, and poultry industries when the price gap between corn and wheat shrinks. Both Hard Winter Wheat, which is generally high in protein, and Soft Winter Wheat-- usually lower in common protein -- serve well as dairy feed.
  • Soybeans - Incorporating soybeans and their byproducts in the rations for dairy cattle is a fairly common practice. Soybeans are an excellent source of essential amino acids and they fit into any type of forage-based ration. Soybeans, when properly heat treated, can provide additional rumen undegradable protein (RUP) and fat; soybeans that have not been heated serve as a source of degradable and soluble protein.
  • Sorghum – Sorghum contains more crude protein than corn. Thus, sorghum grain is both interchangeable with corn in the diets of lactating dairy cattle, or can serve as a replacement for corn altogether. Although research has shown sorghum grain to be comparable to corn in lactating dairy cow diets, the market often values sorghum less than corn.
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Basic Commodities to Milk Price
Source: The USDA and FAO

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Try Our GDP Predict Model based on 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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Heuristics & Advanced Modeling

A heuristic is a method drawn from experience, expertise – a trait many small farmers master, or an educated guess – citizen data scientists that farmers are, that aims at providing or contributing to providing a practical solution to a problem that is usually very difficult to solve (NP-Hard), and consequently an optimal or good, feasible solution is too complicated to obtain. For example, fertilizer use to improve organic & green agriculture or finding veterinarian to dairy farmer to improve clinical access that is acute in developing countries.
Heuristic methods can be used to speed up the process of finding a good, feasible solution by providing farmers with a shortcut to expensive and practical problems. This speed-up process is usually carried out via search algorithms where we traverse a tree representing the space of possible solutions. The application of certain problem-specific heuristics can significantly reduce the tree search.
Heuristic methods possess some information about the proximity of every state to the goal state, which allows them to explore the most promising paths first. Heuristics underlie the whole field of Artificial Intelligence and the computer simulation of thinking, as they may be used in situations where there are no known algorithms. Out Fertilizer pricing module applies heuristics to better mix and price point for the benefit of small farmers.

 
 
 
 

Predictive Analytics & Budget Speech Cohort Mining

A heuristic is a method drawn from experience, expertise – a trait many small farmers master, or an educated guess – citizen data scientists that farmers are, that aims at providing or contributing to providing a practical solution to a problem that is usually very difficult to solve (NP-Hard), and consequently an optimal or good, feasible solution is too complicated to obtain. For example, fertilizer use to improve organic & green agriculture or finding veterinarian to dairy farmer to improve clinical access that is acute in developing countries.
Heuristic methods can be used to speed up the process of finding a good, feasible solution by providing farmers with a shortcut to expensive and practical problems. This speed-up process is usually carried out via search algorithms where we traverse a tree representing the space of possible solutions. The application of certain problem-specific heuristics can significantly reduce the tree search.
Heuristic methods possess some information about the proximity of every state to the goal state, which allows them to explore the most promising paths first. Heuristics underlie the whole field of Artificial Intelligence and the computer simulation of thinking, as they may be used in situations where there are no known algorithms. Out Fertilizer pricing module applies heuristics to better mix and price point for the benefit of small farmers.

 
 
 
 

 
 
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