Unsupported Browser

Your web browser appears to be outdated. Our website may not look quite right in it.

Please consider updating your browser to enjoy an optimal experience.

Dismiss this message

Blog Image

Smart Farming - plant fertilization and plant protection


Many or all of the products featured here can be from partners who compensate us. This may influence which products we write about and where and how the product appears on a page. However, this does not influencer our evaluations. Our opinions are our own.

This blog is composed of the following topics:

  • Section control
  • Plant fertilization
  • Measures related to partial areas
  • Row cultivation
  • Prognosis crop protection
  • Autonomous vehicles

Section control

→ The section control has already been described in this blog article.

Measures related to partial areas

Zones for application cards

With the variable rate application (VRA) method, the application rates or the cultivation intensity can be set for implements and machines. Target values can be stored on the tractor terminal by means of application cards or application cards. In the field, the work step is now adapted to the target values when the field work is carried out.

The benefit results for a better utilization of the existing yield potential of the soils. Through variable and site-specific measures and the use of operating resources, an increase in yield or yield protection can be achieved. These effects are intensified in the case of very heterogeneous soil properties within the plot. Particularly in view of the tightening of fertilizer requirements, the restrictions on plant protection measures, rising input prices and increasingly stringent environmental regulations, subplot management is becoming increasingly important.

Source: sg.ch

Focus on zones and single plant

Demand for solutions for climate and environmental protection is arising in the areas of plant protection and fertilization, among others. Adaptive processes for image and pattern recognition, such as those already used in plant care, are taking plant cultivation to a new level of precision, focusing on the individual plant rather than arithmetic averages.


Source: sg.ch

Nitrogen sensors that determine the nutrient requirements of each individual plant based on more than 800 measurements per second reduce the need for mineral fertilizers. Using leaf coloration, geodata and soil maps, the fertilizer requirement of each plant can be calculated. This is transmitted to the tractor's on-board computer. In real time, the spreader can then control individually for each individual plant.

Plant protection with plant detection

Source: sg.ch

This sprayer contains computers, cameras, sensors, tanks and nozzles that can spray one type of crop and skip the other: The computer is programmed to recognize a specific crop - and all other plants that do not match the desired crop are treated by a targeted spray of the herbicide. Conversely, a single-plant-specific treatment with fungicides and insecticides can be applied to the crop.

Plant protection - Spotspraying

Source: sg.ch

Spotspraying by color differentiation between the substrate and the plant, for example, when using PPP on a stubble field, leads to a significant reduction in the amount of input. There are also options for retrofitting: Weedseeker or also weed-it. Other suppliers: Agrifac AiCPlus, Garford, Amazone (with Bosch and Xarvio)

Pest control with drone

Source: sg.ch

To control the corn borer without the use of chemicals, eggs of the ichneumon wasp are released in the field with the help of a GPS-controlled drone. The drone flies over the field according to a predefined route and automatically ejects capsules containing ichneumon fly eggs at regular intervals. These white capsules consist mainly of cellulose or corn starch and are naturally degraded. The hatchlings in turn lay their eggs on the pest's eggs, preventing them from hatching.

The following article about drones in agriculture might also be interesting for you:

Drones in agriculture


The documentation of field work is in the interest of every farmer, in order to manage and control the use of means of production, to plan the means of production and to optimize the use. For this purpose, handwritten records are used, but also increasingly the use of software, the so-called electronic field calendar or field index. With the help of software that documents the farmer's work, possible savings become visible, for example in the use of pesticides or through more precise sowing.

Source: sg.ch

© farmdok.com

The law also currently requires farms to keep area-related records. This involves recording which pesticides were applied, how much fertilizer and nutrients were applied, or whether time windows for field cultivation were adhered to.

So that documentation can be done more efficiently and does not still have to be done completely after the work is done in the field and barn, some of the office work can be brought back to the field with the help of technologies available today through smartphones.

Machines record the activity performed and store this data in memory or the cloud.

Applications/apps via smartphones also store the crop yield, for example, or indicate how much fertilizer still needs to be used to achieve an optimum harvest. This allows the farmer to see where he still has work to do and how much fertilizer he still has to apply to which field, for example.

Special knowledge of disease detection

Source: sg.ch

© Mahlein 2016, Plant Disease

Physical and metabolic properties influence the optical properties of plants. The reasons for this are:

  • Changes in pigment balance & water balance
  • Accumulation and degradation of metabolites and toxins
  • Changes in cell and leaf structure

Using hyperspectral cameras, detection of diseases at an early stage is possible before they are visible to the naked eye.
Detection, quantification and identification of plant diseases is possible today, but a transfer of research results into practice is required for this. Also basic methods for disease detection and defense reactions exist but an establishment of suitable platforms and specific sensors and integration into the concept of integrated crop protection is necessary.

Row cultivation

A satellite-guided steering system with a correction signal is recommended as a basis for cultivation close to the crop. This enables to perform straight or parallel crop rows and repeatable measures on the crop rows. The absolute and relative accuracy enables the very small distance to the crop during the vegetation period.

Source: sg.ch

© garford.com

In order to make a precise hoeing should be done already with the sowing of the row crops with GNSS, so that for the following treatments the georeferenced plant position is known. At this point, the exchange of field and line data between the different machines also becomes massively important.

In recent years, there have been many new developments in the field of chipping equipment. A distinction should be made between the following processing variants:

  • Hoeing equipment (e.g. coulter hoe, roller hoe, bow hoe, separating hoe, disc hoe brush, row tiller) that can work very close to the plant but not between the plants within the row by means of camera control.
  • Hoeing equipment for weed control in the plant row (e.g. finger hoe, torsion hoe, roller harrow).
  • Hoeing equipment referred to as hoeing robots, which are equipped with camera and, depending on the type, other sensor technology for plant discrimination and can also destroy weeds between plants within the row using special hoeing shares.
  • Autonomous hoeing robots with their own drive and GPS control, which can already distinguish weeds from crops mostly by camera and sensors. They are not yet widespread in our country 

A good overview and description of mechanical weed control is summarized in DLG Leaflet 449.

The travel speeds are usually still quite low at 2 to 4 km/h. The advantage of this equipment is that it enables mechanical weed control in intensive crops and drastically reduces the use of chemical agents. Also, the fertilizer can be applied precisely where the plant needs it for growth and thus the total fertilizer consumption is reduced.

Robocrop InRow Weeder

Source: sg.ch

© garford.com

Hydraulically or electrically driven hoeing tools with a sickle-shaped disc profile work about 1 - 2 cm deep within the row. Hoeing blade moves in an arc rotating around the crop. 

Manufacturer: Garford Farm Machinery Ltd, England

Distribution CH: NOVAXI, France

Rimeco Germany GmbH, Germany


Source: sg.ch

© kress-landtechnik.eu

The hoeing unit consists of two hydraulically or electrically driven tool carriers, each with a flat coulter at the end. Tools move between the crops from both sides.

Manufacturer: F. Poulsen Engineering ApS. Denmark

CH-Distribution: K.U.L.T. Kress Umweltschonende Landtechnik GmbH; Germany


Source: sg.ch

Each hoeing element is equipped with an infrared light barrier for plant detection. Each element has two hydraulically moving arms with interacting tines.

Manufacturer: Ferrari Costruzioni Meccaniche, Italy


IC Weeder

Source: sg.ch

The chipper with a PTO-driven compressor and sickle-shaped knives as working tools works pneumatically in the row and mechanically between the rows.

Manufacturer: Machinefabriek Steketee B.V., Netherlands
CH-distributor: Möri Kartoffel- und Gemüsebautechnik, CH-3270 Aarberg

Prognosis crop protection

The aim of forecasting models is to reduce chemical crop protection to the absolutely necessary level. The producer should therefore have a range of relevant information at his disposal to enable a sustainable and effective use of plant protection products. This involves monitoring the various influences of pests, diseases, phenological development, etc. on quality and yield. The maturity of these systems is still quite early and thus subject to a certain dynamic and requires continuous monitoring and further development. Thus, new scientific findings and improvements from trials and practice are constantly flowing into product development.

A prognosis model represents the risk of a disease or pest infestation as a function of weather and other influencing factors and provides the farmer with a decision-making aid with regard to optimized crop protection. The said forecast model is ultimately programming and algorithms as a result of various information services:

Source: sg.ch

Autonomous vehicles

As the degree of automation increases, small autonomous field robots in particular are gaining in importance. Corresponding activities have already been taking place worldwide at various universities since the end of the 1990s. The advantages of autonomous agricultural robots are their low weight, the fact that they can work largely independently of the day, and the fact that they can simultaneously carry out additional work, such as crop sampling.

Differentiation can be made in the scope of functions and orientation of the plant treatment, whether mechanical, chemical or by current pulses. Another feature is the optical plant recognition, data processing and by means of approaches through the so-called artificial intelligence (hereinafter AI) to set off a specific selective treatment.

However, there are still no official and legal requirements that allow machines to run autonomously and freely in the field. Currently, the machines still have to be monitored by humans.

Start-ups are particularly active in this area. In general, many companies are in the prototype phase or "teaching" the systems to the different crops and weeds. In the coming years, they will be found more and more in practice.
The currently most well-known field robots are listed below:

  • Ecorobotix (CH)
  • Farmdroid FD 20 (DNK)
  • Bonirob (DE)
  • Anatis (FR)
  • OZ (FR)
  • Dino (FR)
  • Robotti (DNK)
  • Xaver (DE)
  • Fenntec (DE)
  • Etarob (DE)
  • Thorvald (NOR)
  • Weedy (DE)
  • Dick, Tom, Harry (UK)
  • Ted (FR)
  • Bakus (FR)
  • VineScout (FR)