Big data analytics is a new way of thinking and transforming all sectors. The emerging technologies in IoT and AI have made it possible for us to tap into the value of big data analytics. It is one of the marvels of human innovation but artificial intelligence (AI) offers tough competition for us. The days of speculating rain and sunshine may soon fade with artificial intelligence’s capability to predict the right conditions with precision to an extent. This has led to a new era in farming – the era of precision agriculture and smart agriculture.
AI comprises one of the basic aspects of precision agriculture (PA) promoted even by the government and the private sector to boost productivity, crop yield and in turn, farmers’ income.
AI-based sowing advisories lead to 30% higher yields as Microsoft, in collaboration with ICRISAT, developed an AI Sowing App powered by Microsoft Cortana Intelligence Suite including Machine Learning and Power BI. The app sends sowing advisories to participating farmers on the optimal date to sow without them installing any sensors in their fields or any additional cost; all they need is a phone capable of receiving text messages.
Precision agriculture is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. It is one of many modern farming practices that make production more efficient.
One example of a precision agriculture practice is to evaluate the natural soil variability of a field. If the soil in one area holds water better, crops can be planted more densely, and irrigation can be spared.
Advanced data analytics is helping in predicting short term weather conditions and its effects which goes a long way in ensuring the right yields are sourced in anticipation. Weather patterns are at times unpredictable, data analytics through the right planning will contribute to the planting and harvesting seasons and in turn, benefit the country.
According to the 2018 report on the state of food security and nutrition in the world by the Food and Agriculture Organization of the United States (FAO), hunger is on the rise with nearly 821 million people facing chronic food deprivation in 2017 from around 804 million in 2016. Therefore, there is a need to invest in data analytics systems that help in leveraging the technological advances in the field of agriculture.
In Kenya agriculture contributes 35% of the gross domestic product (GDP) and constitutes 40% of the export earnings. In line with the government’s Big 4 development agenda, agriculture aims to attain 100% food and nutritional security for all Kenyans by 2022. The descriptive analytics from the government data shows that in the past 6 years, horticulture and livestock farming has improved in various counties.
With the emergence of digital tools that aim to deliver efficiencies in agriculture, the country has seen breakthroughs through data analytics, as agriculture data is turned to real gold – an invaluable resource for planning and decision-making. The smart farming initiatives have enabled farmers to collected big data which are now used to improve yield and reduce the cost of production. The diagnostic analytics provided on farmer’s phones has helped data-driven farmers to achieve improved yield. The farmers have been able to choose the right seed variety.
The descriptive and predictive analytics of the weather data lead to the introduction of the hybrid maize seeds. The farmers can use these analytics to predict their yield and hence secure the financial farming resources. The data collected give insights into the levels of food production and will be keen on noting food shortages in time to increase food production.
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