Digital Copy of the Greenhouse: Digital-Twins in Horticulture

Digital Twin: It can be simple, like a map of a greenhouse showing real-time info, or more detailed, like a virtual tour where you can look at 3D models of plants.

Horticulture is increasingly data-driven and it is ever-more using innovative digital technologies, such as cloud computing, Internet of Things, machine learning and robotics.

At the Greentech in Amsterdam, this was very evident. For example, all but one of the nominated innovations were digital, data solutions. Berry,a harvesting robot for strawberries, won the concept award. Other nominees were a sensor network of digital insect traps (Trap-Eye), an autonomous cultivation system for indoor farming (Gronos),and a software tool to calculate CO2 footprints (HortiFootPrint calculator).Many digital solutions were also being promoted at the booths. A small selection: greenhouse drones (PATS, Corvus),tomato harvesting robots (the winner of the Robot Challenge GRoW, en EGA Matic),sensors for measuring plant stress (Vivent) and leaf temperature (Sigrow), sensing systems for digital phenotyping (Hiphen),yield predictions based on computer vision (YieldComputer, ecoation), autonomous growing systems (Blue Radix, ioCrops, Koidra), and much more.

Remote growing with Digital Twins

These technological developments are radically changing horticultural production.

Instead of experienced growers personally monitoring the condition of the crop ('management by walking around'), cultivation decisions can be based on real-time data and intelligent algorithms.

Growers can monitor and control operations remotely, enabled by so-called Digital Twins. Such a virtual twin is a digital copy of, for example, a greenhouse that is linked to the real greenhouse and continuously updated..

A Digital Twin can be enriched with smart algorithms and machines or robots can be connected. Thus, growers receive alerts via the Digital Twin if there are (expected) problems and they can check the situation in the greenhouse from behind their desk or smartphone by digitally viewing the plants or machines involved. They can also use the Digital Twin to digitally simulate the effects of interventions in advance, then take the best action remotely and afterwards check whether the problem has actually been solved.

What are Digital Twins?

The term Digital Twin was introduced by NASA in 2012 for ‘mirroring’ the exact state of a real space vehicle during a mission. So in essence a Digital Twin is a virtual, digital representation of a physical object, linked to it in (near) real-time. This representation can be basic, for example, an overview of a greenhouse with live data. It can also be a realistic environment, where, for example, you can virtually walk through the greenhouse and inspect 3D plants. But all Digital Twins have these five characteristics::

1. Timeliness: a Digital Twin represents its physical twin in (near) real-time, changes of the physical object are (immediately) identified and synchronized and vice versa;
2. Fidelity: the reliability and security of a Digital Twin must be unquestionable, allowing to blindly trust Digital Twins for decision making;
3. Integration: a Digital Twin integrates different types of data from the physical object and ensures its unambiguous representation;
4. Intelligence: Digital Twins do not only reflect object data but also use algorithms for describing, analysing and predicting the behaviour of the physical counterpart;
5. Complexity: Digital Twins can mirror various physical objects at different levels of granularity, ranging in horticulture from the genetics of individual plants to a company or value chain.

Although the term Digital Twin seems to be a new buzzword, I consider it to be a continued development of smart, data-driven horticulture. In practice, Digital Twins already exist, although they are often not yet called such. A literature review by one of my students at Wageningen University shows that most are still relatively 'basic' Digital Twins that focus on remote monitoring and control. However, more 'advanced' Digital Twins, such as for (near) real-time predictions, are emerging.

Another conclusion of the study is that Digital Twins in horticulture now mainly focus on cultivation management in the greenhouse with respect to climate, energy and lighting. There is still little research on Digital Twins for individual plants, although that level of detail is important for breeding, for instance. Completely absent in the review were Digital Twins for the business processes and the performance of horticultural companies as a whole.

Business data is key

Digital Twins serve as a means to enhance business outcomes, rather than being an end goal. I foresee a layered Digital Twin for the future, encompassing company, cultivation, and individual plants. A management dashboard will display real-time and projected business performance indicators, integrating data from ERP systems, greenhouse/field automation, and external sources. AI-powered algorithms will simulate performance and allow in-depth analysis of specific processes, locations, varieties, and production lots.

For cultivation, you can zoom into a Digital Twin of a greenhouse with lower-than-planned yields. Here, growers can assess climate conditions, cultivation variables, plant physiology (e.g., stress), and genetic profiles of reference plants. Various Digital Twins offer decision support tools, recommending actions like releasing 8,000 predatory mites in specific areas via drone after grower approval.

By the way, the Greenhouse Digital Twin will autonomously manage most of the cultivation operations, based on predetermined norms. This allows growers to focus on exceptions and the business side of cultivation.

'Layered' Digital Twins demands integrated business software

The virtualization of horticulture with Digital Twins now seems to be gaining momentum and will have a major impact on productivity, efficiency, quality, and sustainability.

In my opinion, the successful Autonomous Greenhouse Challenge is very exemplary. In this event, the participating teams control the cultivation in their compartment fully remotely based on sensor data and smart algorithms.

The winner (lettuce) had a 30% higher net profit than experienced growers this year. Last year (cherry tomatoes), all teams performed much better, with the winner's net profit more than doubling. Digital Twins can capture horticultural experts' knowledge and help address the shortage of green personnel. They are a promising tool for international production site management. Expect Digital Twins to play a bigger role in business management, with interconnected levels from company to plant. However, this requires reliable data integration, including cultivation, plant, business, and external data, and a well-integrated business management system.