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NIR Sensors

In this video, Dennis Schrijver from John Deere explains what Near-Infrared Spectroscopy (NIR) sensors are and how they work.
NIR sensors measure nutrient profiles in the crops and manure. NIR stands for near-infrared spectrometry. This works a bit similar as what you do with your human eye. It’s sending a light window to a surface or to a crop, and now we are not measuring in a wavelength of the human eye, but in a wavelength of near-infrared. Based on this profile, it is possible to predict what’s in a product for nutrients or constituents. We have three different applications for you to apply the sensor. One is on our self-propelled forage harvester. In this graphic, you can measure different constituents like protein, starch, and sugar.
And you can do the same measurements in these crops in your own office to measure what you already having in your silo, already have on your farm. And based on that, you can make decisions for your cow feeding or what to put in your BioGrass plant. And the last application we have is that you can mount on a slurry tanker. So you can measure the nutrients within manure. Practise in the past was to apply it as a flat rate and based on volume. We can now apply based on, for example, the amount of nitrogen. So you’re not applying too much nitrogen or too less nitrogen, based on the location in your field.
Benefits of using NIR sensors in agriculture is that we can real-time measure what we are harvesting or applying manure. This can help to improve yields, save input costs, and also to help save the environment. We see different trends in the world. We see a world population growing. We need more and more food. But the other side we see the environmental impact of agriculture. And an [INAUDIBLE] sensor like this NIR sensor, can more specifically apply nutrients where it is exactly needed. So we’re going to be more efficient and not waste our inputs and pollute the environment. That’s where this NIR technology and also precision can help for the future agriculture.

In this video, Dennis Schrijver from John Deere explains what Near-Infrared Spectroscopy (NIR) sensors are and how they work.

The HarvestLab 3000 can be used on a slurry tanker, on a self-propelled forage harvester or as a stationary laboratory for feed analysis. This makes it possible to use the John Deere NIR system year-round and results in quick amortization. Valuable knowledge is gained from the real-time sensor data and the location specific documentation of the Sensor. This makes it possible to make decisions based on facts to create accurate application maps for the next field work and to better control and even reduce operating costs, for example, when it comes to silage and feed. The data gained makes it possible to use organic fertilizers, such as mineral fertilizer, or to identify a suitable variety of plant. When harvesting silage, the Sensor helps to determine the optimum harvest time and the exact dry matter yield. Lengths of cut precisely matched to the dry matter of the harvested crop for optimum compaction and ensiling and precise knowledge of the ingredients form the reliable basis for high-quality silages. As a stationary laboratory on cattle farms, the NIR system provides information about the ingredients of each ration in order to adapt the feed to be economical and tailored to the respective animal.

The HarvestLab 3000 uses near-infrared spectroscopy (NIR) to determine the various content substances of pig and cattle liquid manure, biogas digestate, fresh harvested crops or silage. The heart of the system is the highly sensitive sensor, which measures near-infrared light reflected off of the harvested crop and provides more than 4,000 measuring points per second. The system has already been officially certified by the German Agricultural Society (DLG) for its excellent accuracy in determining the dry matter content of corn silage and the content substances in pig and cattle liquid manure and in liquid digestate.

Figure 1: Functional Principle and System of the Sensor

Figure 1: Functional Principle and System of the Sensor (Click to expand)

Figure 2: Dry Mass Yield Map and Protein Yield Map

Figure 2: Dry Mass Yield Map and Protein Yield Map (Click to expand)

Figure 3: Images to illustrate applied amount of nitrogen; manure; and second nitrogen application with isobus implement

Figure 3: Dry Mass Yield Map and Protein Yield Map (Click to expand)

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