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Agri 3.0 – Data Science in Agriculture

    Home Insights Agri 3.0 – Data Science in Agriculture
    data science agriculture
    Insights, Agriculture | 0 comment | 30 December, 2021 | 0

     Matogen Applied Insights’ (MAI) has successfully completed a wide range of innovative data science projects in the agriculture sector.

    What is Agri 3.0?

    An interesting outcome of the COVID-19 pandemic and the resultant lockdown in South Africa is that it brought into relief the notion of “essential services”. Suddenly, it was emphasised in staggered form which activities and enterprises were absolutely critical for human survival. Health services, transport and communication were highlighted, while societal extras like entertainment and leisure were quickly shut down to curb the spread of infections. Panic buying at supermarkets was an expression of people’s fear that the supply of food, the most essential of essentials, would be disrupted. However, to everyone’s great relief, the agricultural sector (as well as the other links in the food supply chain) kept chugging along more or less as usual. Nevertheless, this scenario served as a stark reminder of the importance of the agricultural sector.

    Agriculture 3.0 is the term given to describe the “Third Agricultural Revolution”, i.e.  data science in agriculture, also known as “digital farming”. It is characterised by the large-scale use of data to drive food production to levels that far outperform the two previous agricultural revolutions: mechanisation and genetic modification, respectively. Data produced by customised farming software products, weather stations, satellite imagery, leaf and soil samples, as well as irrigation systems, is measured and analysed to optimise yield, efficiency and profitability.

    Data science in agriculture

    To date, Matogen Applied Insights (MAI) has collaborated on a variety data science projects within the agriculture sector. These range from building customised systems, data wrangling and analysis, the construction of predictive models to computer vision. This innovative company comprises a team of highly skilled individuals from diverse backgrounds. It leverages international best practice from the fields of statistics and machine learning in synergy with clients’ domain expertise to examine trends and impart data-driven insights. This empowers clients to make better decisions towards more efficient farming practices, saving time and money, as well as limiting wastage. 

    Undertakings within the farming industry include systems such as dashboards, bots and electronic alerts for weather risk and crop protection spraying conditions, as well as plant disease image recognition. In addition, the analysis of agricultural data allowed for the identification of trends with regard to growth phases, nutrient deficiencies and irrigation. However, it is within the realm of predictive analytics that MAI’s unique approach and cooperative capabilities position it favourably to contribute towards the Third Agricultural Revolution. Completed forecasting projects range from the prediction of crop disease risk and plant nutrient deficiency, as well as optimal harvest date and irrigation practices. 

    Remarkably, MAI has already produced cutting-edge revelations that could potentially transform data-driven decision-making within farming as the Third Agricultural Revolution progresses.

    agriculture, data science, machine learning

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