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Exploring the Power of Imaging in Agriculture: Enhancing Field Management

In modern agriculture, staying ahead of the curve requires innovative approaches and tools. As we strive for more efficient and sustainable practices, agronomists and farmers alike are exploring new technologies to optimize field management. One such tool gaining traction is imaging. In this blog post, we will delve into the potential of imaging in agriculture and how it can complement traditional methods like soil moisture probes and tissue testing. Tim, an experienced agronomist at Netafim, will share his insights on the subject, highlighting the benefits and challenges of integrating imaging into farm operations.

Netafim has been testing imaging in agriculture as a monitoring system for whole fields. This is part of the new Netafim advisory tool that hasn’t been released, but they have learned some valuable information along the way. Soil moisture testing, tissue testing and soil sampling are all excellent management practices that should be part of every grower’s tool bucket. However, these only show points in time in a small area of a field What if there was a tool that showed how the whole field looked, and allowed you to make early interventions on potential problems? Imaging might be the answer.

Netafim used four types of imaging and indexing to monitor different aspects of plant health throughout a growing season. These were

1. NDVI (Normalized Difference Vegetation Index): This image captures biomass and plant health, allowing farmers to monitor changes in crop vigor over time. This allows you to watch trends and monitor for any spots that are not keeping up, or need a little extra help.

2. Modified NDVI: Particularly useful for smaller crops, this image accounts for soil reflectance and enables accurate assessment of crop health.

3. CCCI (Canopy Chlorophyll Content Index): By measuring the darkness of the plant's color, this image provides insights into chlorophyll levels and overall plant health.

4. Red Edge Imagery: This advanced imaging technique combines chlorophyll and NDVI data to assist in precise nitrogen and chlorophyll management.

One of the downfalls of imagery has been the use of color, similar to yield maps. Dark green is good, yellow is medium, red is bad, etc. How do you tell the exact difference between two shades of green? Numbers are much more accurate than gauging color differences. The imaging software used by Netafim is able to assign a number to each color, so you can quantify the differences in a field. There are also high definition and standard definition images. High definition is 1-3M pixels and comes every 1-2 days. Standard definition is every 5-7 days. The cloud cover can also be a concern, but with the high definition option, there are a lot of images to work with and assign trends.

Image of a pivot field with color coded plant health based on imaging scores

Here is an example of an NDVI map. 1.0 is perfect or ideal. The best area of this field is 0.9 (green), while the poorest area of the field is 0.86 (red). This isn’t a lot of variability; this may look like a crop disaster when you first glance at it, but all information is relative, so keep that in mind. This really is a nice field that did a beautiful job of minimizing stress.

Image of a drip irrigated field with color coded plant health based on imaging scores on July 4th

Here is another example of use of imaging: 51 images were gathered from the field from planting April 27th to maturity around September 10th. The season started with good rains and the irrigation system was keeping up nicely in the early part of the season. The map looks relatively nice and green for the entire field. The yellow areas are an ability the tool has to identify areas different than the average. This is done automatically, and allows you to know at a glance which areas you need to pay a little more attention to. You can set these pins wherever you like on the map, and look at the data from that spot. On July 4th, one of the data points read 0.8 on the NDVI scale.

Image of a drip irrigated field with color coded plant health based on imaging scores on August 3rd

One month later, the color of the map is changing slightly but it still looks pretty good. On an analysis of the numbers (on the right hand side), you can see the plant health; it has peaked and is on the downward trend. On August 4th, things tanked and the growers had challenges with water. They used this tool to analyze which part of the field needed water the most, and irrigate that zone. That same data point from earlier was now 0.32 on the NDVI scale; that is a significant decline. Looking at the chlorophyl, or nitrogen management (lower graph), the color of the field is pretty good, but there is a decline happening. This can give you some leeway for proactive management.

Image of a drip irrigated field with color coded plant health based on imaging scores on August 19th

By August 19th, the imaging colors had started showing signs of stress. If we were just going off color, nothing would have been done until now. With the extra numbers gained from field imaging, growers are able to make better proactive decisions to manage their crop health.

The integration of imaging into agricultural practices represents a significant advancement in field management. By combining traditional techniques like soil moisture probes and tissue testing with imaging data, farmers gain a comprehensive understanding of their fields. Tim's insights shed light on the benefits and challenges associated with imaging, underscoring the importance of high-definition imaging for accurate trend analysis. As the agricultural industry continues to embrace new technologies, imaging stands out as a powerful tool that enhances decision-making and maximizes yields while promoting sustainable practices.

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