Calculating Difference Between Target Rx and As-Applied Maps

In precision agriculture, one of the common challenges is ensuring the application of seeds, fertilizers, or crop protection agents as per the prescribed rate (Target Rx).

Variations between the target prescription and what is actually applied on the field (As-Applied) could lead to inefficient use of resources and impact crop performance.

By leveraging GeoPard’s powerful analytics, you can calculate and visualize the differences between your Target Rx and As-Applied maps.

This difference analysis can serve as an important tool to quickly identify issues with equipment, application timing, or the actual application itself.

Let’s take a deeper look into this:

• Visualizing Differences: GeoPard’s platform allows you to generate a “difference map”, overlaying your Target Rx and As-Applied data. This visual representation of variance provides a quick and intuitive way to spot areas where the actual application didn’t match the target.
• Identifying Problems: By comparing the difference map against your original Rx and As-Applied maps, you can pinpoint specific areas or trends that might indicate equipment malfunction, sub-optimal application timing, or issues with the applied product itself.
• Improving Efficiency: This analysis can help you optimize resource usage by addressing the identified issues, thus aligning your As-Applied rates closer to your Target Rx for future applications.
• Enhancing Crop Performance: By ensuring that your field receives the right amount of inputs at the right time, you can boost crop health and potentially increase yield.

Remember, precision agriculture is all about making more informed and accurate decisions. By integrating this feature into your regular farm management practices, you can ensure you’re getting the most out of your inputs and drive your farm towards greater productivity and profitability.

Application prefix contains the operations related to the applied application some of them are:

1. Application Applied Rate – original applied map from the machinery (how was the product applied)

2. Application Target Rate – original target from the machinery (how has the product to be applied)

3. Application Accuracy Clusterization – clusterization of the results: 0 – no data (machine did not visit these spots), 1 – applied below the target and not in the acceptable range (+-5% from the target)t, 2 – applied in the acceptable range ( +-5% from target), 3 – applied above the target and not in the acceptable range (+-5% from the target)

4. Application Rate Difference – difference between applied and target rates in absolute numbers (l/ha units)

Seeding prefix contains the operations related to the seeding some of them are:

1. Seeding Applied Rate – original applied from the planter (how many seeds were seeded)

2. Seeding Target Rate – original target from the planter (how many seeds have to be seeded)

3. Seeding Accuracy Clusterization – same clusterization rules, BUT the acceptable range is +-1% from the target

4. Seeding Accuracy Clusterization Zoomed – same as Seeding Accuracy Clusterization but zoomed to show same area as Seeding Target Rate and Seeding Applied Rate

5. Seeding Rate Difference – the difference between applied and target rates in absolute numbers (seeds/ha units)

What is target prescription (Target Rx) in agriculture?

In agriculture, the target prescription refers to the recommended or desired set of practices or inputs prescribed for optimal crop growth, health, and yield. It serves as a guideline or plan for farmers to follow in order to achieve specific agricultural objectives.

The target prescription takes into account various factors such as crop type, growth stage, soil conditions, climate, pest and disease pressures, and nutrient requirements.

It provides instructions on the application of fertilizers, pesticides, irrigation, crop rotation, seed selection, planting density, and other essential agricultural practices.

The purpose of a target prescription is to provide farmers with scientifically backed recommendations based on research, agronomic knowledge, and local conditions. It aims to optimize resource utilization, minimize crop losses, and enhance overall agricultural productivity.

Target prescriptions are often developed by agricultural experts, agronomists, agricultural extension services, or research institutions.

They may be specific to different crops, regions, or even individual fields, taking into account the unique characteristics and challenges of each farming context.

Farmers use target prescriptions as a reference point to guide their decision-making and management practices.

By following the recommended guidelines, farmers aim to maximize crop health, yield, and quality while minimizing the negative impact on the environment.

It is important to note that target prescriptions should be flexible and adaptable to account for variations in local conditions and the need for sustainable farming practices.

Farmers may need to make adjustments based on real-time observations, on-farm experiences, and continuous monitoring to ensure the best possible outcomes for their specific agricultural operations.

What is applied on the field (As-Applied)?

As-applied agriculture encompasses the process of accurately and precisely applying inputs, such as fertilizers, pesticides, and irrigation, to crops based on real-time data and site-specific conditions.

It involves the integration of various technologies, including GPS (Global Positioning System), GIS (Geographic Information System), sensors, and variable rate application equipment.

What is Variations between them?

In agriculture, variations between the target prescription and the actual application on the field refer to the differences or deviations between the recommended or desired agricultural practices and the real-world implementation.

These variations can manifest in various aspects, including the use of fertilizers, pesticides, irrigation, cultivation techniques, and more.

Factors Influencing Variations

Several factors contribute to variations between the target prescription and actual field application in agriculture:

• Environmental Factors: Agricultural practices are influenced by dynamic environmental conditions, including soil composition, climate patterns, and water availability. Variations may arise due to unexpected changes in these factors, affecting the feasibility and effectiveness of prescribed practices.
• Human Factors: The knowledge, skills, and expertise of farmers play a crucial role in implementing prescribed practices accurately. Variations can occur when farmers encounter challenges in understanding or interpreting the prescribed instructions, leading to deviations during the application.
• Technological Limitations: Agricultural technology, while advanced, may not always be accessible or affordable to all farmers. Variations can arise when farmers do not have access to the latest equipment, precision farming tools, or real-time data, impacting the accuracy of field applications.
• Timing and Logistics: Agriculture is time-sensitive, with specific windows for planting, harvesting, and applying agrochemicals. Variations may occur if farmers face logistical constraints, such as delays in procuring inputs or adverse weather conditions that disrupt the timely application of prescribed practices.

結論

Variations between the target prescription and actual field application in agriculture present challenges that need to be addressed for sustainable and efficient farming practices. Understanding the factors contributing to these variations and their impact on agricultural outcomes is crucial.