The demand for efficient, sustainable, healthy and locally produced food is growing strongly driven by various pull and push factors:
In order for flowers and plants to grow properly, an optimal environment is required, consisting of different parameters such as temperature, humidity, light intensity, certain levels of minerals, etc. A greenhouse is a complex system with different components, such as crop, climate and irrigation strategies. Within this system, sensors measure different plant characteristics with optical and imaging techniques. Horticulture is therefore a data-rich environment in which people try to achieve an “optimal production cycle” with many repetitive tasks. It is therefore an extremely fertile ground to exploit new digital technology and utilize the generated data to meet the changing demand.
Combining in-depth knowledge of cultivation recipes in the “minds” of horticulturalists with the possibilities of data, robotics and AI offers the opportunity to substantially increase the efficiency and quality of food production. The following successive steps can be taken with the use of digital technology in greenhouse horticulture:
1. Describe and diagnose with dashboards – creating key insights through dashboards that continuously display a comprehensive overview of business performance. With this descriptive and diagnostic analysis, decision-makers can better see what is happening and why and coordinate actions to be taken accordingly
2. Yield forecast – the combination of an accurate forecast of food production and customer demand through the use of data and AI results in optimization of revenue, planning, asset allocation and business strategy
3. Automation of production through robotics – industrial robotics is deployed on internal processes where a lot of data has to be processed and/or where repetitive tasks are involved to make production more efficient and more precise, to guarantee the quality of the product or to reduce the dependence on physical labour
4. The greenhouse operates autonomously through a combination of robotics and AI – bringing together an accurate yield prediction model with robotics in a digital platform driven by AI and machine learning will result in (semi) autonomous greenhouses in which the requested products are efficiently produced and sold for the optimal price
For a successful transformation it is essential to make a make-or-buy choice per element of the (digital) operating model and to determine what the correct speed of the implementation should be. Based on these two axes, four choices are distinguished:
1. collaborative innovation
2. business transformation
3. M&A/ strategic partnerships
Because an important part of the knowledge about digital technology is lacking within the agricultural sector, technology companies are trying to take a position. In addition, private equity companies see opportunities to realize an international growth strategy with Dutch companies as a platform for growth. These developments result in an increase in M&A transactions. For example, JBR recently supervised the purchase of a minority interest in Certhon by the Japanese robotics specialist DENSO with the aim of jointly realizing step 3.
If you want to know more about the possible steps you can take with example cases, please read the full article here.
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