Horticulture is increasingly driven by data, and it constantly uses new digital technologies, such as cloud computing, Internet of Things, machine learning, and robotics, writes Cor Verdouw with Mprise Agriware.
At Greentech in Amsterdam, this is very clear. 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 are a sensor network of digital insect traps (Trap-Eye), an autonomous cultivation system for indoor farming (Gronos), and a software tool to calculate CO2 foodprints (HortiFoodPrint calculator). Several digital solutions were also highlighted in 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 growth systems (Blue Radix, ioCrops, Koidra) , and many more.
Remote growth of Digital Twins
These technological advances have drastically changed horticultural production. Instead of experienced growers personally monitoring plant conditions (‘management by walking around’), planting 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 linked to the real greenhouse and continuously updated.
A Digital Twin can be enhanced with smart algorithms, and machines or robots can be connected. Thus, growers will receive alerts through the Digital Twin in case of (anticipated) problems, and they can check the condition of the greenhouse from behind their desk or smartphone through a digital view of the plants or machines which is involved. They can also use Digital Twin to digitally simulate the effects of interventions in advance, then take the best action remotely and then check if the problem has 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 (almost) 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 the plants in 3D. But all Digital Twins have five characteristics::
- Timeliness: a Digital Twin represents its physical twin in (almost) real-time, changes in the physical object are (immediately) identified and synchronized, and vice versa;
- Integrity: the reliability and security of a Digital Twin must be unquestionable, allowing blind trust in Digital Twins for decision-making;
- Integration: a Digital Twin combines different types of data from the physical object and ensures its unambiguous representation;
Intelligence: Digital Twins not only display object data but also use algorithms for describing, analyzing, and predicting the behavior of physical counterparts; - Complexity: Digital Twins can mirror different physical objects at different levels of granularity, from horticulture to the genetics of individual plants to a company or value chain.
The Digital Twins of horticulture now focus on gardening
Although the term Digital Twin seems like a new buzzword, I consider it a continuous development of smart, data-driven horticulture. In practice, Digital Twins already exist, although they are generally not yet referred to as such. A literature review by one of my students at Wageningen University showed that most are still relatively ‘basic’ Digital Twins focusing on remote monitoring and control. However, more ‘advanced’ Digital Twins, such as those for (near) real-time predictions, are emerging.
Another conclusion of the study is that the Digital Twins of horticulture today mainly focus on the management of greenhouse cultivation in relation to climate, energy, and lighting. There is little research on Digital Twins for individual plants, although that level of detail is important for breeding, e.g. Completely absent from the review are Digital Twins for business processes and the performance of horticultural companies in general.
Integrated Digital Twins for business and cultivation
However, Digital Twins are not an end in themselves, but a means to improve business results. For the future, I, therefore, imagine a layered Digital Twin that unites the company, cultivation, and even individual plants. The point of departure is the management cockpit with actual and expected business performance, such as lead times, product quality, wastage, cost price, and delivery reliability.
These indicators combine different data from different sources, including ERP systems, greenhouse or field automation, and external data. Smart algorithms allow the simulation of expected performance, for example, through demand forecasts based on artificial intelligence. One can drill down into details for specific business processes, locations, types, production lots, etc.
For the planting process, you zoom in, for example, the Digital Twin in a greenhouse, where the expected yield is lower than planned. In this digital greenhouse, the grower checks the climate and other growing conditions for the plots concerned. They can also look at the physiological characteristics of the plant (for example, stress) and even the genetic profile of the Digital Twin of a reference plant in these lots.
Various Digital Twins support this analysis with smart decision support tools. These tools advise a grower on the steps to take, for example, the use of 8,000 additional predatory mites against spider mites in compartments A and B of greenhouse Z. After the grower’s consent, the Digital Twin commands a drone to release the exact number of predatory mites in the right places.
By the way, Greenhouse Digital Twin will autonomously manage most of the cultivation operations based on predefined rules. This allows growers to focus on exceptions and the business side of gardening.
There are no ‘layered’ Digital Twins without integrated business software
The virtualization of horticulture with Digital Twins now seems to be gaining momentum and has a significant impact on productivity, efficiency, quality, and sustainability. In my opinion, the successful Autonomous Greenhouse Challenge is very good. In this event, participating groups control the cultivation of their compartment completely remotely based on sensor data and smart algorithms.
The net profit of this year’s winner (lettuce) was almost 30% higher than the reference group of experienced growers. In fact, last year (cherry tomatoes), all teams performed better, and the winner’s net income more than doubled!
Digital Twins can also gain the knowledge of experienced horticultural experts, thus contributing to solving the shortage of green personnel. Additionally, Digital Twins is a great tool for setting up, scaling, and managing international production sites.
I expect that Digital Twins will become more embedded in business management in the near future. As a result, they often consist of several interconnected levels from the company to the plant. However, this is only possible if the underlying data is good.
For a ‘layered’ Digital Twin from farm to plant, this not only means cultivation and plant data but also business data and external data. A well-integrated business management system, which smoothly cooperates with the automation of the greenhouse and the field, is therefore, an important condition.
