What is Precision
Agriculture?

Precision Agriculture through Soil Mapping and Crop Sensors

Where do you go when your car is not as fast as you want or working the way it should? You have someone take a look at the moving parts. Soil is the engine of the agricultural machine, a power source, or at times, a disability to the rest of the moving parts. As demands rise, soil composition does what it always has, it fluctuates frenetically. Although we have conquered medical anomalies, forged dialogue between inanimate machinery, and mastered hydroponics, there is one mountain we cannot move—we cannot change the weather. Because we cannot control the weather, we cannot control the soil, along with other factors inherent to soil composition (salinity, pH, textures, organic matter, etc.).

Farmers have always scouted samples manually, and shipped them off to a third-party for analysis. Not only is this process skewed, considering it paints a very one-dimensional picture, but it also takes too long to process. Defining land by one or two soil samples is like defining the world by the perspective of one or two human beings—soil is highly complex and a dynamic facet of the environment, impossibly captured in a single sample.

Digital soil mapping a component of precision agriculture, and defined as a geographical representation of soil composition through extensive data collection. In other words, we are recreating the soil digitally through the use of sensors placed throughout the viable land. In collecting real-time analytics on soil attributes, farmers can better understand what additives will induce optimal growing conditions. These sensors inhabit a wide spectrum, meaning there is a significant gap between the functionality of the simplest sensor and the most sophisticated one, levels dictated by the IT intelligence driving the actual mechanism. Sensor software has the ability to funnel data from the device to the database, self-adjusting variables according to the analytics.

Crop sensors are essentially accomplishing the same as soil sensors, but instead collect data related to crop lifecycle. Here we are trying to be more precise with our allocation of additives and resources—giving the crops or livestock just enough sustenance to maintain homeostasis. In monitoring conditions in real-time, farmers reduce waste and reap greater harvests, as their lifecycle becomes more predictable and less prone to unexpected loss. Yes, crop and soil analytics give way to profound changes on a micro level, but also compound to form a storyline growers can access for the next harvest. So as the macro form over time, agriculture becomes increasingly precise, especially since sensors create a continuous data flow—starting with a grainy image of the operation that focuses as we add layers. Sensors leverage qualitative and qualitative relationships to refine agricultural processes, bringing environmental variables from dirt to database.

Generally, these are the sensors growers are toying with:

• > Electromagnetic

• > Optical

• > Mechnical

• > Electrochemical

• > Airflow

• > Acoustic

What Does UAV Mean?

Unmanned aerial vehicle. Basically, a drone. UAVs seemed outlandish not too long ago, mostly because of the high price tag and futuristic exterior. However, as UAVs have become affordable to smaller operations, we have unearthed a plethora of practical applications within the agricultural realm, more specifically, within the precision agriculture model. UAVs complement sensors through 3-D mapping capabilities. Through high-resolution, aerial mapping, growers can apply their real-time analytics to a digitalized replica of their land, engineering seed patterns by conjoining the two forces.

UAVs can be used not only as a data collection device, but also as machinery. Growers can utilize UAV technology to spread seed pods over the fields they manage through a network of sensors. The seed pods contain all the necessary nutrients for the preliminary stages of life, alleviating the stress and manpower required to distribute those additives manually. The same UAVs can be programmed to preform aerial spraying—a fertilizer technique that maximizes crop absorption and prevents excessive ground absorption.

Drones can be engineered with sensors as well, calculating thermal conditions to deliver heat maps that bring visuals to soil mapping sensors. As the technologies collaborate, growers are rewarded with a comprehensive health assessment of their current field conditions, as well as a prediction of how they may look in a few hours, days, and months. The UAV flies overhead, emitting visible and near-infrared light to record green light and NIR light levels within the field. All of this is done through an interconnected, automation system operated and monitored remotely, which bring us to our final topic, remote monitoring.

So What's Up With Remote Monitoring?

In today's IT landscape, there is one word we keep hearing (besides big data), interoperability. We want our systems to be able to forge their own conversations and support cross-channel relationships. Inevitably collaboration yields more comprehensive results. Precision agriculture is no exception. In order to manage their land remotely, the UAVs must coexist with the crop sensors, and the crop sensors should carry an amiable back-and-forth with the soil mapping sensors. By nurturing inoperability, growers can wave goodbye to archaic farming practices, getting out of the heat to understand their land in a more robust way remotely.

Remote monitoring is the hallmark of a successful precision agricultural system. No longer are growers indebted to weather patterns or manual scouting. By implementing these technologies, they will confidently answer the dreaded what, why, when, and where with no trepidation. Precision agriculture is planting with purpose, recreating your farm digitally to know it inside and out, and remaining environmentally conscious as a secondary benefit. Although we have historically paired hard, manual labor with the agricultural industry, it is time to loosen up. IT software solutions give way to an enlightened era, where the farmer retires the Farmer's Almanac for unmanned aerial vehicles seeding the land and sensors that tell you when the seeds need to be nurtured. By bringing dirt to databases, we finally push pass the supply and demand tipping point.