Device for monitoring the condition of seedlings

To be honest, when you hear “device for monitoring the condition of seedlings,” the first thing that comes to mind is another expensive toy with a bunch of sensors that will fail in field conditions in a week. But over the past three seasons, I had to reconsider this skepticism, especially after working with systems from Shandong Linyao Intelligent Agriculture Technology LLC. Their approach toseedling monitoringturned out to be not about beautiful graphs, but about how to notice in time the difference in the development of the root system in sandy and loamy areas.

Why standard solutions don't work in the early stages

In 2022, they tried to install multispectral cameras on drones - it would seem ideal for assessing density. But in reality, the results were just colored spots: the system confused the difference between a healthy sprout and one that was just beginning to turn yellow from a lack of zinc. I had to admit that we cannot do without ground-based sensors that monitor the microclimate in the subsoil layer.

Colleagues from Shandong Linyao LLC were just then showing their system, whereseedling condition monitoringwas based on a combination of humidity, soil temperature and electrical conductivity. Not the most revolutionary solution, but they added an amendment for soil type - that very little thing that is usually missed in ready-made kits.

I noticed an interesting nuance: their sensors are not installed on a standard grid, but with an emphasis on risk zones - where there is water in the spring or where last year’s vegetation creates shade. This is the kind of practicality that you won't find in instructions.

What does the workflow look like in the field?

This season, their system was tested on winter wheat in the Stavropol region. The first thing that caught my eye was that the humidity sensors are placed not at the standard 20 cm, but at two levels: 5 cm to monitor the crust after rains and 15 cm to assess the availability of water for the roots. It would seem obvious, but most manufacturers do not think about it.

The most valuable thing about themdevice for monitoring the condition of seedlings- not the readings themselves, but the interpretation algorithm. For example, if the nighttime soil temperature at a depth of 5 cm falls below +3°C with high humidity, the system marks the area as a risk of damping off. You usually notice such things only when it’s too late.

The downside is that you still need to physically check the calibration every 10-12 days. Especially after rainstorms, when clay particles clog the sensors. But this is a common problem with all soil sensors, not only them.

What technical specifications are silent about

Not a single passport says that wireless sensors begin to fail when the seedlings grow above 15 cm - apparently due to the shielding of the signal by the stems. I had to add repeaters on my own, although the system was initially positioned as completely autonomous.

Another point: most systemsseedling monitoringwind load is not taken into account. Young shoots in strong winds create microvibrations that distort the readings of pressure sensors. We had to install windbreaks - a simple solution, but it is not mentioned anywhere.

By the way, on the website https://www.lyzhihuinongye.ru there is a section with cases where a similar case with corn in the Voronezh region is described. But there they solved the problem through software filtering - I wonder if it will work in our conditions.

Integration with other systems - where are the pitfalls?

We tried to connect their system to our old weather station. It turned out that data transfer protocols are compatible only on paper. I had to tinker with the converters for almost a month - time that could have been spent on calibration.

Here it is worth paying tribute to the technical support of Shandong Linyao LLC - they sent their engineer, who wrote a patch for the software in three days. But the fact itself shows: even with gooddevice for monitoring the condition of seedlingscannot be expected to be easily integrated into existing infrastructure.

Now we are testing their new development - sensors with autonomous power supply from solar panels. So far they last two weeks without recharging, but how they will perform in cloudy weather is a question.

What really affects the accuracy of readings?

I noticed a pattern: the largest discrepancies between the system forecast and the actual state of seedlings occur during transition periods - early spring and late autumn. Apparently, the angle of incidence of sunlight on the optical sensors affects it.

Another factor that is often overlooked is the biological activity of the soil. After adding organic matter, the electrical conductivity readings fluctuate so much that the system detects a 'developmental anomaly'. You have to manually make adjustments - the automation can’t handle it yet.

This is where the approach of Shandong Linyao Intelligent Agriculture Technology LLC has proven useful - they provide not just equipment, but a methodology for adaptation to a specific farm. Their specialists first studied our fields for a week, and only then proposed a scheme for placing sensors.

Development prospects - what to expect in the coming seasons

Judging by what is currently being tested in their laboratories, systems will soon appear that can distinguish weed species at early stages based on spectral characteristics. This could reduce herbicide use by 20-30% - a dream for any agronomist.

But for nowseedling condition monitoringremains a tool for making tactical decisions rather than strategic ones. The system can show where the problems are, but will not tell you what to do if the seedlings lag behind in development due to a complex of factors.

Interestingly, in their last demonstration they showed a prototype that analyzes the symbiotic relationship between roots and fungi. If this is brought to fruition, it will be a breakthrough - but for now the technology is crude, like most innovations in precision agriculture.