by Andreas Neuman
Published on April 20, 2016
Remote sensing is one of the considerable advances in farming of the past 20 years. Lately, the arrival of drones allows technology that was prohibitively expensive to be affordable for most farmers, and with a precision previously unachievable even by the most costly options. This new accuracy allows growers to rapidly analyze specific plants instead of only large areas, thus making it useful not only for big landowners but also to small producers. But once you have your imagery in hands, what are the next steps?
When using a vigor map, it is important to understand that high vigor is not always optimal and stress is not always bad. Viticulturists and winemakers need for instance to do BRIX measurements in the zones that have previously been identified by the use of the Normalized Difference Vegetation Index (NDVI) or other vegetation indices such as the Normalized Difference Red Edge Index (NDRE) or the Soil-adjusted Vegetation Index (SAVI) imagery. A vine with more stress often has fruit with more desirable characteristics for the winemaker than healthier grapes do. For most growers, what is more, important than identifying individual stressed plants is that variance in the field is first identified and then the causes of the variance are understood. Growers must also determine at what scale variance becomes significant. For example, growers of grapes destined for premium wine may very well determine that using an NDVI scale with 10 or 20 classifications so that they can treat individual plants is the correct scale to operate with. However, growers of grapes destined for table wines may wish to use a simpler NDVI scale with four classifications based upon average NDVI values in one, two or three-meter zones.
As discussed above, when designing field surveys based upon NDVI imagery the goal is to ground truth the findings on the same scale that the NDVI was produced. Growers (and in many cases their consultants as well) who use NDVI imagery will design a ground truthing plan that efficiently ensures that a representative sample is taken for each classification so that they can accurately extrapolate that information and apply it throughout zones with similar NDVI readings. They also help to determine what is causing the variance in the field and a cultivation plan can be put in place to create a more homogenous crop.
While it is its backbone, precision agriculture goes far beyond remote sensing imagery. Viticulturists and other fruit growers use ground sensors (FDR sensors), weather stations, spectrometers, BRIX readings in addition to soil analysis, visual observations, among other current and historical datasets.
To avoid misconception, here is a short list of what is possible with remote sensing and NDVI imagery and what is not (yet):
- Remote sensing imagery tells you at a fraction of the cost (both in terms of time and money) of doing field inspections where the problems and zones of interest are.
- A vigor map and soil moisture data from ground sensors allows growers to detect a lack of water (usually identified as stress of an area of relatively lower vigor plants) or excessive irrigation, provoking excessive vegetation growth or on the opposite, rotten roots.
- An NDVI map allows growers to map where individual plants or sections are stressed, but targeted manual inspections performed by workers in the field are still needed to determine the exact causes.
- Mathematical models are being developed to diagnose specific risks such as exact disease, pest, virus, or bacteria and even to monitor the chemical composition of crops. Terroir matters and it may take a season or two of ground truthing NDVI imagery to perfect a model, so the sooner a grower starts incorporating modern precision agriculture tools the sooner they can benefit from algorithms tailored for their fields.
- NDVI imagery ground-truthed by standard assessments (BRIX, acidity, polyphenols analysis, etc.) allows growers to clearly delineate sub-zones based upon variance in a vineyard for selective harvest.
- The stress caused by nutrient deficiency will be detected in NDVI imagery and can be ground proofed by soil and/or plant sampling to perform variable-rate nutrition plan.
Join Our Newsletter
Discover Precision Agriculture and Biocontrol news and tips, learn about your fellow UAV-IQ users, and stay up to date with what’s happening at UAV-IQ.
Some predators and parasitoids have proven to be very efficient at controlling mealybugs.
99% of the US’s grape is produced in California because of its favorable conditions, but the nice weather and moderate winter in the Golden State is particularly attractive to mealybugs.
Another powerful way in which savvy vineyard managers and winemakers are unlocking remote sensing’s potential value: selective harvest.
FOLLOW US ON