Device for monitoring the condition of seedlings main country of the buyer

When you hear about devices for monitoring seedlings, the first thing that comes to mind is beautiful graphs on the screen and “smart” ones. forecasts. But in reality, especially when working with buyers from the CIS countries, you are often faced with the fact that expectations are too high. Everyone wants a universal solution that will immediately solve all problems with the harvest, but they forget that technology is just a tool. The main country of the buyer dictates its own conditions: in some places resistance to dust is critical, in others to humidity, and in other regions there simply is no stable Internet for data transfer. Let's talk about these pitfalls.

Why is seedling monitoring not just “plant and forget”?

Let me start with an example: last season we supplied a batch of sensors for Kazakhstan. The customer complained that the data on wheat seedlings was “floating”. It turned out that the problem was not in the devices, but in the fact that they were installed without calibration for the local soil - loam with a high salt content. The device showed humidity, but did not take into account electrical conductivity, so discrepancies were obtained. I had to adjust it on the spot and add correction factors. Conclusion: even expensive monitoring is useless if you do not take into account the agrochemicals of a particular field.

By the way, many people still confuse monitoring the condition of seedlings with conventional weather stations. Yes, the latter measure temperature and precipitation, but do not record critical parameters such as the density of seedlings or the uniformity of distribution over the area. To do this, we need multispectral cameras or hyperspectral sensors - those that can “see”? not only the visible spectrum. UShandong Linyao Intelligent Agriculture Technology Co.,LtdThere are interesting developments in this regard: they combine data from drones and ground sensors, but more on that later.

Another point is timing. Monitoring of seedlings is most valuable in the first 2–3 weeks after sowing, when the root system is being formed. If you miss this period, it will be difficult to correct anything later. I have seen cases where farmers bought equipment, but only started using it in the tillering phase. Result? There is data, but it is no longer possible to influence the yield.

Equipment: What Really Works in the Field

If we talk about hardware, then it is important to separate laboratory and field solutions. For example, optical scanners work great in greenhouses, but in open ground their accuracy decreases due to dust and light fluctuations. For steppe regions, where the main buyer is often agricultural holdings from Russia or Ukraine, resistive sensors are more reliable, although they require regular maintenance.

Here is a specific case: last year we tested a monitoring system based on IoT modules in the Rostov region. The problem was not the technology itself, but the data transmission - cellular networks in the fields are unstable. We had to supplement the system with repeaters, which increased the cost of the project by 15%. But now we take this experience into account when assembling supplies. By the way, onhttps://www.lyzhihuinongye.ruThere are technical specifications where such nuances are spelled out honestly - for example, requirements for LoRaWAN coverage area.

We should also mention the calibration. Most manufacturers supply devices with factory settings, but they are designed for average conditions. In reality, each region makes adjustments. For example, to monitor corn seedlings in the Krasnodar Territory, we additionally adjusted sensitivity thresholds for high insolation - without this, the sensors were overloaded during the midday hours.

Integration with irrigation systems: where the risks lie

Bundledevice for monitoring the condition of seedlingsand automatic watering - this is logical, but not always simple. Let's take a project for vineyards in Moldova: they used soil moisture sensors that were supposed to control drip irrigation. In theory - ideal. In practice, it turned out that seedling data arrived with a delay of 2–3 hours due to the features of the software. During this time, the young shoots have already experienced water stress.

We corrected the situation by switching to edge computing - when part of the data analysis occurs directly in the controller, without sending it to the cloud. This reduced the delay to a few minutes. Similar solutions are now being actively developedShandong Linyao Intelligent Agriculture Technology Co.,Ltdin their smart park projects. Their approach is minimal dependence on external servers, which is often critical for rural areas.

By the way, it is a mistake to think that automation always saves water. Without proper interpretation of monitoring data, you can get the opposite effect. One of our early projects in the Volga region showed that when automatically watering based only on soil moisture data, the excess water consumption reached 20% because the phase of seedling development was not taken into account. Now we always recommend linking algorithms to the phenology of the culture.

Software: Why the interface is everything

The most advanced instrument is of no use if the farmer does not understand what the graphs show. I remember how in the Kostanay region an agronomist complained that the platform from a European manufacturer “draws NDVI indices, but does not tell what to do with these numbers?” We had to develop simplified report templates with color indication: green - everything is normal, yellow - you need to check, red - urgent action should be taken.

It is important to note here thatbuyer's main countryoften determines software requirements. Complex platforms are suitable for large holdings with IT departments, and mobile applications with basic alerts are suitable for small farms. On the websitelyzhihuinongye.ruI see that they took this into account - they offer both a web interface for agricultural managers and a simple option for tractor drivers.

A separate pain point is compatibility with existing systems. In 2022, there was a case when purchased monitoring equipment did not interface with the local GIS platform in Belarus. I had to write a custom API gateway, which took three weeks. Now we always clarify in advance which systems will be integrated with.

Prospects: where is seedling monitoring headed?

Nowadays they are increasingly talking about predictive analytics - when the system not only records the condition of seedlings, but also predicts risks. For example, by combining soil temperature and moisture data, it is possible to predict the development of fungal diseases 5-7 days before visible symptoms appear. But there is a catch: for accurate forecasts, you need historical data on a specific field, which not everyone has.

I wonder whatShandong Linyao Intelligent Agriculture Technology Co.,Ltdin its projects it relies on modularity. Instead of monolithic systems, there is a set of sensors and controllers that can be gradually expanded. This makes sense, especially for farms with a limited budget: start with monitoring basic parameters, then add spectral analysis, then irrigation automation.

Personally, I believe that the future lies in hybrid systems, where data from drones is supplemented by ground sensors. The quadcopter gives an overall picture of the field, and stationary sensors monitor the dynamics at key points. We are already testing this approach in a project to monitor soybean seedlings in the Altai Territory - so far the results are encouraging, although we had to tinker with data synchronization.

In the end I will say this:device for monitoring the condition of seedlings- This is not a magic wand, but a complex instrument. Its effectiveness depends 70% on how well it is integrated into specific conditions. And if the manufacturer, howShandong Lingyao, understands this and offers adaptive solutions - which means he knows what he is doing. The main thing is not to chase fashionable functions, but to choose what really works in your fields.