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Exploring AI and Machine Learning in Weed Seed Cultivation

Artificial Intelligence has been on an upward trajectory since its introduction. An increasing number of people are looking into different ways to integrate the various systems into their lines of work. With each waking day, AI is included in other sectors, and people are trying to learn how it works.

What about the cannabis industry? Like many other fields, researchers have been keen to pinpoint how AI and machine learning systems can improve the production and sale of marijuana. What are some of these ways, and how do they change the cultivation processes of weed?

Benefits of Using High-Quality Weed Seeds

In cannabis cultivation, one of the most important aspects is finding high-quality seeds. Growers frequent seed banks to buy cannabis seeds usually stock various weed products. Their main goal is to purchase viable propagation materials that will give them high yields and healthy plants.

There are proven benefits of utilizing healthy propagation materials instead of low-quality ones. These benefits can be seen in the short term as well as the long time. The probability of getting a poor yield with low-quality seeds is high.

The most prominent benefit of using high-quality marijuana seeds is with getting a high germination rate. High-quality propagation materials undergo processes to ensure the end product is highly viable from a reputable brand with sufficient treatment have a high germination rate.

Another practical benefit is that the seeds grow into plants resistant to pests and diseases. Most small-scale growers use propagation materials from their previous harvests. Though this strategy is cost-saving, it risks future growth from having a lower genetic profile. The reduction in quality over time increases the susceptibility of the plants to pests and diseases. Farmers can avoid this by using new seeds with each growing season.

The other issue with high-quality propagation ovules has to do with their potency. As weed plants mature and produce seeds, the potency level changes. The potency of cannabis plants largely depends on the plant ovules, the environmental conditions, and the parent stock. An effective way to produce highly potent crops is by ensuring the planting materials are of the highest quality.

Lastly, using viable seed materials ensures high yields and fast growth in marijuana plants. For instance, F1 marijuana seeds grow more vigorously than traditional ones. Besides growing faster and more healthily, it is more likely to get higher yields from high-quality seeds.

How AI is Driving Changes in the Marijuana Industry

AI is taking the world by storm, and its integration in several fields is all the evidence we need. For the past couple of years, researchers have been investigating the various methods they could utilize AI in different parts of the marijuana industry. Some systems currently optimize propagation, pest management, harvesting times, etc.

The goal of integrating AI in cannabis production is to get better yields and easier growth that will ultimately lead to high profits. According to MJ Biz Daily, AI solutions address several processes. The most notable are weed-growing methods, day-to-day labour, tracking growth rates, yield forecasting, inventory management, and profitability management.

The basis of these systems is that they utilize digital sensor technology. They work by noting and controlling the plants’ lighting, temperature, irrigation, CO2 levels, and airflow needs. With machine learning technology, the systems note when the lightning needs changing, when the plants require more water and other crop requirements.

Some companies mount sensors on robots or drones that circle the fields detecting any plant needs. With the information entered into their systems, they can note any changes or deficiencies with the plants. AI and machine learning in cannabis seed cultivation enable growers to manage their crops with little human labour.

Some systems target pest and disease detection and treatment. They analyse the conditions of the marijuana plants and advise on viable treatment options for any pests and diseases. The opportunities that these machine learning systems offer farmers are wide.

Regarding technology in the cannabis sector, several companies are looking into the different ways growers can benefit from the same. A good example is a company from South Africa known as AgriSmart Engineering. According to their CEO, they focus on three critical aspects of digitization of the growth process. These critical areas are the hydroponic recirculation process, LED lighting, data management, and automation.


Different AI and Machine Learning Systems for Cannabis Cultivation

Considering AI systems have been in development for years, it is not a shock that there are already well-developed ones. In the agricultural sector alone, machine learning systems cater to each stage of the plant’s growth. The following are some of the companies we feel would have positive impacts on AI-promoted cannabis growth.


As far as the head of SpexAI is concerned, there are numerous AI-related systems in processing. Their main focus at the moment is a smart camera called Hugin. Hugin gets attached to a robot that goes around the grows at night. Its camera uses spectral imaging to capture plants and build 3D models.

Once the information gets processed, the system utilizes machine learning to detect cannabinoids, pests, and diseases. The 3D models result from 1000 data points, allowing researchers to optimize and see any changes within the plant. Besides capturing the plant’s data, the system also analyzes the environmental conditions and offers advice on improving the crops’ management.


Currently, Koidra does not have an AI system for cannabis growth. It has models for tomato growth and other leafy vegetables. According to its CEO, Kenneth Tran, it would be easy to use its current systems to control the environmental conditions needed for marijuana growth.

Their system has its basis in developing a 3D greenhouse model of the actual greenhouse. The system works on both the crop model and the greenhouse climate model. These models mean that the digital twin (virtual greenhouse) system has information on the plants’ nature and condition and the greenhouse’s environmental condition.

Furthermore, the system can offer insight into how to control better the changing ecological situation to optimize plant growth. Ideally, the digital twin would alert the farmer if there is a need to increase or decrease energy, irrigation, manage pests, and any other problem.

AI AgTech

AI AgTech, a San Mateo company, is analysing the probability of implementing AI and machine learning in their plant propagation. Their need comes from the fact that the CEO, Justine Clune, noted a problem with their cultivation process. The height of the crisis was that it was increasingly hard for human laborers to detect the growth of female and male plants.

A single employee had to walk around 10 hectares of marijuana plants, observing each to determine the sex. Clune hypothetically thought of a drone AI-powered system that would make the rounds and decrease the need for a lot of labor. In his research on the matter, he did find some issues with finding a high-level drone.

The end product was a machine learning-incorporated drone that works much like humans. With the information on detecting plant sex, the drone’s sensor could do the work of 10-20 people on the ground in a single day.

Takeaway on AI and Machine Learning in Marijuana Seeds Cultivation

Most people are still fairly new to the AI buzz. There are a lot of questions on how machine learning systems can benefit farmers. Farmers can learn of some functioning systems already in use with the available resources.

Despite the growing benefits of the same, there are some issues that cannabis farmers need to know about. For instance, integrating machine learning on a small scale is very costly. The maintenance of the systems and the process it takes to integrate them may incur losses for small-scale farmers. Though the integration cost for larger fields is still high, the returns from the same may outweigh the initial costs.

Another key issue is finding a quality system tailored for marijuana production. The best way to do this is to conduct a lot of research and liaise with well-known researchers in the field.


AI and machine learning are quickly becoming the reality of these modern times. The benefits of these systems are long and wide for people in different sectors. Within the agricultural industry and weed growth, to be specific, researchers are using sensors and machine learning to monitor plants. The creation of 3D models ensures that farmers can monitor and detect problems with normal plant growth. With additional research, these machine-learning systems could offer much-needed agricultural support for small-scale and large-scale marijuana growers.

Denys Svirepchuk wrote this article. His interest in the marijuana field pushes him to research various ways farmers and users alike can benefit from new technologies. In writing this piece, enough research and collaboration were of the utmost priority to offer much-needed accurate information to people.


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