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How Can Floriculture Artificial Intelligence (AI) Help SmallHolder Cut Flower Farmers

Floriculture-Artificial-Intelligence

Who Are Small Scale Cut Flower Farmers

The floriculture industry is one of the fastest growing sub-sectors of the horticultural industry in the Kenyan economy.

The cut flower industry is dominated by large-scale sophisticated outfits, growing mainly flowers in greenhouse. Smallholder contribution to the total earning from the sector has been declining steady, from an estimated 13.5% share of total value of exports to an estimated 5.1% in recent years.

The floriculture industry in Kenya has approximately 5000 producers ranging from smallholder farmers (less than 0.4-1.6 ha) to medium scale operations (4-10 ha) and large commercial operations (20- more than 100).

Fifty medium to large scale operations contribute or produce 75% of total exports fresh cut flowers and another 10-15% of exports are produced by several dozen small- to medium-scale operations. The remaining 5-13% of exports was produced by 3,000 – 4,000 smallholder farmers.

Smallholders have actively participated in flower agriculture, which has contributed significantly to the development of rural economies.

Contract farming between agribusiness firms and smallholders, the so-called ‘core–satellite’ model, is prevalent in floriculture but can artificial intelligence (AI) solve contextual constraints in fresh cut flowers farming?

Intelligent Floriculture

Fresh cut flowers farming is the next frontier for using artificial intelligence (AI) to efficiently solve complex problems especially by smallholder farmers.

One way to use these tools for smallholder farmers is to create probabilistic models for seasonal forecasting. If done properly, we can look six months in advance and provide farmers with simple information: what crop varieties will be suitable for the season, when they should plant, and how they can optimize their farm management based on weather patterns during the season.

But there are many variables that must be considered simultaneously, including soil nutrients, seed bed preparation, germination rate, irrigation, cultivation, minerals, microorganisms, pests, and disease.

AI For Small Holder Cut Flower Farmers

  • Crop Predictive Analytics – Machine learning models are being developed to track and predict various environmental impacts on crop yield such as Climate, Pest Control, Yield Simulation and Demand/ Supply Insights.
  • Controlled pesticide usage and Organic Farming – With our data models and deep learning algorithms we help farmers to keep a check on the weed which helps them in being responsible while spraying chemicals. We encourage farmers to reduce the usage of the fertilizers on entire field. Small-scale organic farming and Ecological farming – high yield with little to use pesticides and chemical fertilisers
  • Traceability and Sustainability – The ability of modern supply chains for fresh produce to provide traceability is becoming the norm. Our systems provides relatively straightforward capability to trace back from the florist market to the small holder cut flowers farmer.
  • Alternative credit systems powered by Blockchain – We help farmers access capital with transaction based lending systems to farmers in our platform

Conclusion

Kenya is the third largest exporter of cut flowers in the world, accounting for 38 per cent of all sales in the European Union. More than 500,000 smallholder farmers in the country depend on the trade according to the Kenya Flower Council. The main production areas are around Lake Naivasha, Mt. Kenya, Nairobi, Thika, Kiambu, Athi River, Kitale, Nakuru, Kericho, Nyandarua, Trans Nzoia, Uasin Gishu and Eastern Kenya.

Artificial Technology is expected to improve sustainable farming by helping farmers to forecast weather conditions.

AI apps will help small-holder farmers maximise crop output despite unpredictable weather conditions by providing risk forecasts and crop advice for a 3-4km radius of a farm and will also allow information sharing – including via SMS for farmers without access to the Internet or a smartphone.

Engaging smallholders for productive agriculture remains a great challenge, whereas small farms are still recognized as important for rural development.

Contract farming has been considered beneficial to smallholders in general, because such arrangements could facilitate the transfer of technology and provide access to markets to smallholders

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