Today, farming is barely sustainable without implementing modern farm technologies. With the rapid development of precision technology based on sensors, farmers can achieve successful crop production. Digital information regarding weather, soil conditions, and crop health has the potential to help modern farmers optimize their yields and achieve a high level of farm productivity. As a result, farming is becoming modernized and is increasingly becoming completely based on data.
The most important tools in modern agriculture management are sensors. These range from sensors for soil condition analysis to sensors for real-time application of nitrogen, growth regulators and water. Sensors help farmers quickly and easily determine various soil and crop factors crucial for farming.
In striving to manage successful farm production, care should be taken in regards to crop characteristics too. Using crop sensing technology, the farmer is able to improve crop conditions by measuring plant water potential, yield quality, stage of development (ripeness), nutrient levels, pest and disease infections, and various morphology factors such as biomass, leaf area, and distribution of plants and organs.
Crop sensing technology works using one of three principles of measurement:
- Mechanical
- Acoustic
- Optical
Mechanical Crop Sensor
Mechanical sensors operate based on a plant contact. According to the measured parameter, they can be classified into:
- Sensors which measure crop water potential, i.e. the relative changes in the leaf’s turgor pressure. The leaf is placed between two magnets which measure the difference between plant turgor and magnetic pressure. Low plant turgor will increase magnetic pressure, thus indicating that the plant lacks sufficient water, making, irrigation necessary. Such sensors can measure changes in leaf turgor pressure in real time.
- Sensors for crop biomass density measuring; in which the sensor has a pendulum system which passes over the crop under a certain angle, thus detecting differences within the crop. In measuring the crop biomass, the sensor serves to be beneficial, as it regulates nitrogen applications over specific areas as well as ensures optimum plant protection.
Acoustic Crop Sensor
Acoustic sensors have a miscellaneous appliance in farm management. Some of the target appliances are:
- Soil cultivation; to detect the rows of plants from the soil
- Weeding; to detect the plants from the weeds
- Herbicide application; to detect the plants from the weeds
- Fruit harvesting; to find the fruit inside the tree canopy
- Grain and forage harvesting; to detect the harvested area, thus avoiding overlapping.
These sensors detect the plant geometric structure by emitting an ultrasonic wave signal to the plant. The sensor emits the signal as a repeated sweep under a certain frequency (usually 50-100 kHz). As a result of the application of ultrasonic energy to the plant, several echoes occur. Each echo contains information about the geometric structure of the plant, i.e. the structure of the foliage. This information can be captured by extracting features from the echo signal into geometric features related to the foliage structure (size, shape, orientation, and overall positioning of the leaves).
Additionally, the leaf structure greatly influences the amount of reflected ultrasonic sound. In general, the more leaves on a plant and the larger the leaves, the greater the percentage of ultrasonic sound that will be reflected by the sensor.
Optical Crop Sensor
There is a very wide range of optical sensors used in farming which measure the agricultural crop reflectance. These sensors can be classified according to the platform. These include:
- Satellites – use cameras to collect images from great distances
- Aerial (airplanes, UAV) – use cameras to collect images from long distances
- Ground-based – collect reflectance data from short distances and can store it in a text file
The ground sensors can also be classified as active or passive based on the light source. Active sensors have their own source of light. This source can be a wide range light or a specific wavelength. Oppositely, passive sensors require an external source of light, such as the sun and are not able to work at night. They may also indicate different, inaccurate readings when there are clouds or shadows. Passive sensors need to be positioned at an exact distance from the plant in order to be able to capture the crop reflectance. Another limiting factor is the dew presence which can change the reflectance in both visible and near-infrared. In other words, it increases the reflectance but affects the visible light.
Optical crop sensors evaluate various crop conditions by using specific wavelengths, from monochromatic to multi-spectral (<10 wave bands) and hyperspectral (>10 wave bands). By shining light of specific wavelengths at crop leaves, sensors are able to measure the type and intensity of the light wavelengths reflected from the leaves back to the sensors.
Different color light waves can be used to measure different crop conditions.
Measuring crop reflectance, optical sensors are used to evaluate crop conditions related to nitrogen. They can estimate crop parameters like LAI (Leaf Area Index), leaf chlorophyll content, soil cover, dry matter, water content, yield, nitrogen content, and many others.
An optical sensor, connected to a GPS, is able to use geographical coordinates to create maps from reflectance measurements. This map can help identify the parts of the field that are experiencing more stress, thus saving the use of inputs.
The Era of Data Farming Has Already Begun
Farming based on sensors is a daily activity that is growing increasingly important to more and more farmers. Having the possibility to precisely monitor in-field variability and make decisions based on data will completely transform farm management.
Precision farming allows farmers fast and easy determination of various soil and crop factors crucial for farming. Because of this, crop sensing technology is one of the fastest growing segments in precision farming. This cost-effective method may greatly improve crop yields, while at the same time saving the inputs and environment.
In the era of digital farm technologies and data-driven decisions, every farmer has the opportunity to make farming more efficient and easier than ever.
Text sources: Yara || Carnegie Mellon School of Computer Science || INTECH
Image sources: Yara || Landwirtschaft || sachsen.de || CLAAS Group || Farm Equipment || ATB
