Canory Reflectance Sensors [Farmer]

Introduction

Remote Sensing is the ability to measure the properties of an object or region without the need of physical contact with the object itself (Lillesand and Keifer, 1994). In most remote sensing applications, electromagnetic radiation (EMR) is used to ‘sense’ a certain attribute of the object or area of interest.^[1]

By combining more than one bands of the recorded remote sensing data, we can create vegetation indices and use them to estimate crop status. Depending on the visible and near-infrared reflectance, the produced vegetation indices give us an indication on the amount of chlorophyll present in the plants, and therefore, information on their vigor and growth. With this information we can estimate if and how much stress the plants are under and adjust fertilization and irrigation accordingly. Healthy vegetation has high reflectance in the near-infrared spectrum. Before chlorophyll starts to break down in stressed plants, whatever is causing the stress has already started to affect the cellular structure of the leaves. This affects the plant reflectance in the near infrared, even before the loss of chlorophyll changes the reflectance in the visible region. With remote sensing we can see the changes in the near infrared (which are not visible to our eyes) before the chlorotic symptoms appear, and this way we can have an early warning that the plants are under stress.^[2]

The information on crop vigor and stress can be used for Variable Rate applications, either with a real time system or a prescription map. Real time sensors adjust the application rate as the application machinery crosses the field, while in the prescription maps a map is uploaded on the application platform (i.e. fertilizer spreader) and adjusts the rate according to the maps values using a positioning system to identify its location in the field.

Related Smart Farming Technology Products

Trimble GreenSeeker^[3]

The GreenSeeker system uses optical sensors to measure and quantify the variability of the crop. It then creates a targeted prescription to treat the crop variability.

Figure 1. The Greenseeker canopy reflectance sensor

Figure 2. Greenseeker sensors mounted in a tractor to apply Variable Rate Fertilization

TopCon CropSpec^[4]

CropSpec sensors measure plant reflectance to determine chlorophyll content, which correlates to nitrogen concentration in the leaf. CropSpec units mount on the cabin roof out of harm’s way, providing the largest sensor footprint in the industry, attaining more accuracy in application.

Crop Circle ACS-430^[5]

The Crop Circle ACS-430 active crop canopy sensor provides classic vegetative index data as well as basic reflectance information from plant canopies and soil. Unlike passive radiometric light sensors, the Crop Circle ACS-430 is not limited by ambient lighting conditions— measurements can be made day or night due to its unique, light source technology.

For on-the-go applications, the Crop Circle ACS-430 sensor can be mounted to virtually any type of vehicle to remotely sense and/or map plant or crop canopy biomass while driving through a field.

Figure 3. The Crop Circle ACS-430 active crop canopy sensor

RapidSCAN CS-45 Handheld Crop Sensor^[6]

The RapidSCAN CS-45 represents the latest advancement in active crop canopy sensing solutions. The RapidSCAN CS-45 is a completely self-contained active crop canopy sensor that integrates a data logger, graphical display, GPS, crop sensor and power source into one, small compact instrument.

The sensor is unaffected by ambient illumination allowing it to take accurate biomass measurements day or night due to its internal polychromatic light source. The sensor is capable of collecting data from vegetation at sensor-to-canopy distances ranging from 0.3 meters to over 3 meters.

Figure 4. RapidSCAN CS-45 Handheld Crop Sensor

Skye Instruments SpectroSense 2^[7]

SpectroSense 2 is a reflectance sensor that uses its own sensors to make corrections os its data reading with sunlight sensors mounted near the canopy sensors, taking into consideration both reflected and incident sunlight for each data sampling.