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Colorado State University FROM THE GROUND UP Agronomy News January 2001 Volume 21 Issue 1 |
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| Zoning In On Precision Ag | New technologies help growers pinpoint management zones to
improve the bottom line. by Raj Khosla |
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| Pest Management Uses New Tools | Global Information Systems data are critical for diagnosing
and tracking infestations. by Howard Schwartz |
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| Corn Insect Management | Site specific management techniques help growers
pinpoint zones needing treatment. by Frank Peairs |
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| Precision Irrigation | Researchers focus on ways to improve irrigation efficiency.
by Harold Duke |
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| Fertilizer Application By Management Zones | Soil color, landscape position, and past management experience
are keys to developing management zones for fertilizer application. by Kim Fleming, Dwayne Westfall, and D.W. Wiens |
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| Meet | Raj Khosla | ||||||||||||||||||||||||
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OTHER RECENT ISSUES:
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Zoning In On Precision Ag |
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New technologies help growers pinpoint management zones to improve the bottom line. |
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Precision farming is an art and science of utilizing advanced technologies to enhance grain yields in an economic and environmentally sensible manner. Our goal is to maximize ag-input use efficiency, or in other
words maximize net dollar return per acre from the fields, increase grain
yields, protect environment, and enhance farm profitability. We have been practicing crop production for centuries. And during this time period we all have realized that when we harvest our crops year after year, the grain yields harvested from different areas of a field are not uniform (Figure 1). For example, you have a 160-acre cornfield or a quarter section center pivot cornfield, there are areas within the same field that produces different levels of grain yield. The grain yield variability in one field can range from to 300 bushels/acre. Well we all have observed that for a long time. The question is, what can we do about it? Is there something we can do to enhance our production and bottom line? In the past, we did not have the technology to quantify these differences in grain yield. Thanks to precision farming technology we can now locate, measure and record such areas in the field that produce below or above the average grain yield of the whole field (Figures 2 & 3). Not only that but precision farming provides us the tools and the opportunity to manage the grain yield variability that exist in our fields.
Concept of Management Zones
I think the concept of management zone is easy to understand. If we look at the fingers of our hand, they all belong to the same hand, but their sizes are different. The three management zones can exist in the same field, but their production potentials are different (see Figure 5.) No matter how much water and nutrients we may add, the grain yield in each region is limited to the productivity potential of that zone. You can estimate the maximum yield potential of each zone through years of farming experience and yield monitoring. Going back to the “fingers of our hand example” above, no matter how much we may stretch our fingers they are not going to increase in size. I am not suggesting that there is no further potential for our crop yields to increase, I am suggesting that the three management zones “Low, Medium, and High” are based on the productivity potential of the soil. The question then becomes: Should we be applying the same amount of nutrients across the field? For example, if
It is quite logical that we do not need to apply the same amount of nutrients across the field when we know that the nutrient needs are different for different areas of the field. If your inputs are based on the highest yield goal, you know you are over applying in Zone 2 & 3. If you target your input application based on the average yield goal, you know you are under-applying for Zone 1 and over-applying in Zone 3. Managing nutrients within zones It is a general feeling among folks I have talked to that if they apply more inputs (water and nutrients) to low yield management zones they will be able to bring the grain yield level up to the level of the most productive management zone.
The point I am trying to make is that different
areas of the field have different productivity levels, and merely applying
more inputs to low productivity areas are not going to translate into
more grain yields. Instead we may lose or leach that extra water and nutrients
out of the soil below the root zone and increase the potential for leaching
of nutrients to ground water slowly over time. Instead of applying the
same amount over the field, the nutrients should be tailored to fit the
potential of the management zone, just as you would tailor a coat to fit
the size of the person’s body.
The key to managing variability that exists in our farm fields is to optimize the application of our agricultural inputs to different regions or “management zones” of the field based on their inherent productivity potential.
For more information, please feel free to contact me at
970-491-1920, or by e-mail at Raj.Khosla@colostate.edu. |
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Pest Management Uses New Tools |
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Global Information Systems data are critical for diagnosing and tracking infestations. |
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Since 1997, Colorado State University plant pathology personnel have utilized GPS/GIS technology to describe more than 1000 vegetable production fields (bean, onion, potato) and foliar disease outbreaks in eastern Colorado (26,000 km2), with emphasis upon bean rust (Uromyces appendiculatus), onion purple blotch (Alternaria porri), and potato late blight (Phytophthora infestans) and early blight (Alternaria solani). Annual pest surveys were conducted periodically throughout major crop production regions to verify field reports provided to CSU by cooperators and record cropping patterns and priority disease sightings including some soil-borne problems such as Fusarium Wilt (Yellows) of bean, onion and sugar beet.
The GIS records and GPS receiver allow specialists to return to last year’s field problems with no hesitation or confusion. Since 1997, we have utilized GPS/GIS technology to improve our pest survey efficiency and verify the successful overwintering of bean rust, onion purple blotch, and potato early blight. This information on pest biology and sightings was then related to environmental events obtained on a daily basis from a network of remote electronic weather monitoring stations maintained by CSU, USDA/ARS, and NCWCD (Northern Colorado Water Conservancy District) personnel throughout Colorado. These data are incorporated within disease models to help pest management specialists improve the timing and accuracy of disease forecasts in relation to local weather forecasts for the next 7 - 10 days, and enhance the effectiveness of integrated pest management strategies which will be implemented by crop consultants and growers in the affected region. Timely pest alerts on outbreaks and management of bean rust, late blight and early blight of potato, and purple blotch of onion have been distributed weekly via newsletter (CSU Pest Alert), educational satellite (Data Transmission Network), and Internet (VegNet @ http://www.CSUag.com) to regional growers, scouts and IPM personnel throughout the growing season from May to September. The impact of this program has been widespread as timely IPM information and alerts helped growers and commodity groups prevent widespread and devastating outbreaks and multi-million dollar losses from these types of foliar pathogens. Future research and adaptation of GPS/GIS technology for pest management programs at Colorado State University will continue to backstop our growers and supportive commodity groups such as dry beans, onions and potatoes, and various research and extension programs including Colorado Integrated Pest Management and the USDA/ARS that are also involved with sugar beets. A recent article by M. R. Nelson et al. (“Applications of Geographic Information Systems and Geostatistics in Plant Disease Epidemiology and Management”, Phytopathology 83:308-319, 1999) provided some interesting insights from their GPS/GIS and pest management experiences in Arizona that are very applicable to Colorado and the surrounding region: Research is needed on cost/benefit analyses of GIS applications in agriculture. The current most successful applications of this technology involve teamwork; that includes ann experienced field person, an experienced computer user with some background in statistics, and a patient data entry person. Larger farms, younger farmers, and better-funded extension programs are more likely to apply these tools. It will illustrate the association of environmental factors, landscape features, and cropping patterns with the recurrence of disease or other problems. This technology will aid practitioners in the design of disease management in IPM programs, particularly on a regional scale. |
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Corn Insect Management |
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Site specific management techniques help growers pinpoint zones needing treatment. |
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| Arthropod pests are rarely distributed uniformly throughout
a corn crop or a corn producing region. For example, Banks grass mites are
more common along the edges and in drought-stressed portions of corn fields.
European corn borer adults tend to select earlier-planted fields during
the first generation flight and later-planted fields during the second generation
flight. Within a field, larger plants will be preferred during the first
flight and less mature plants during the second. Western corn rootworm larvae
are generally more abundant in those parts of the fields with heavier soils
and higher organic matter levels.
Management of corn insect and mite pests is generally accomplished by (1) estimating the average population density or amount of damage of an infestation in a given field; (2) comparing this estimate to an economic threshold; and (3) application of an approved insecticide or miticide to the entire field if the economic threshold is exceeded (see the Western High Plains Integrated Pest Management Guide for Colorado, Western Nebraska, Montana and Wyoming for economic thresholds and registered pesticide products). Given that pest distributions are variable within a field and that treatment decisions are made on a whole-field basis, it is likely that some portions of the field will not be infested or damaged at a level above the economic threshold. Site-specific scouting and application methods would allow producers to avoid the unnecessary expense of treating these areas. Sampling for corn insects generally involves counting insects, usually eggs or larvae, or damaged plants on a set number of plants at each of several locations per field. These counts can then be converted to percent infested or damaged plants or to insects or damage per plant for economic threshold comparisons. The amount of effort involved will depend on pest species and plant growth stage, but treatment decisions are usually based on information gathered in one hour or less per week per field. Determining the treatment need for small field subsections using this approach would be exceedingly expensive. Two possible, more cost-effective, alternatives are (1) more efficient scouting methods or
We now have an efficient method of sampling the adult stage of these two important corn pests. However, corn is damaged by the larval stage of these insects. The relationship between pheromone trap catches and egg-laying or larval activity is not well known under our growing conditions. We currently are trying to measure this relationship. If there is a close relationship, then pheromone trapping could be a viable tool for site-specific corn pest management decisions.
Regardless of their size, once the treatment need has been determined for field subsections we then need the technology to treat some subsections and leave others untreated. There is substantial concern about the accelerated development of insecticide and miticide resistance by the use of reduced rates. Therefore, site-specific management will likely involve either treatment with a full rate or no treatment.
Site-specific management of corn insects has the potential to make corn production more efficient through more targeted insecticide and miticide applications. Improvements in pest sampling methods and application technology will be necessary to realize this potential. |
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| Precision Irrigation | |
| Researchers focus on ways to improve irrigation efficiency. |
by Harold Duke
Agricultural Engineer USDA-Agricultural Research Service |
| Irrigation is by far the biggest consumer of water in Colorado, and irrigated
agriculture has been identified as a potential non-point source of pollutants
to our State’s water supplies. Virtually every irrigator is aware of this
potential problem, and most are keen to do the best job they can to maintain
quality as well as quantity of our water supplies. USDA-ARS in Fort Collins
has worked with farmers for many years to provide best irrigation management
practices to minimize the adverse impact of irrigated agriculture on public
waters. To us, precision irrigation means two things: precision with respect
to area and precision with respect to time. Because crop nutrients, such
as nitrogen (and many pesticides) are very readily dissolved in water, thus
move through the soil if excess water moves through the soil, precision
irrigation in either context means less opportunity for contaminating our
water supply because more ag chemicals are kept in or on the soil where
they belong.
The time aspect of precision irrigation is called “irrigation scheduling,” and many farmers as well as farm advisors are aware of this terminology. Irrigation scheduling can mean using field devices, such as gypsum blocks or expensive instruments to measure when the soil can hold more water, or it can mean computation of how much water is required by the crop at its current stage and by weather conditions, to meet crop needs in the near future. Either approach can provide guidance as to when to irrigate and how much water to apply, and may provide the opportunity to reduce irrigation application significantly — thus reducing costs of pumping, nitrogen fertilizer, and other chemicals, as well as protecting water quality. Today, the Colorado Climate Center (CCC) at Colorado State University CSU, in cooperation with CSU Cooperative Extension, CSU Ag Experiment Station, USDA, and several commodity groups, maintains a network of 36 weather stations across the state. These stations report their weather to CCC daily, and these data are used to compute the water used by a variety of crops. The weather data as well as crop water use (evapotranspiration or ET) are posted on the Internet. In years past, the concept of irrigation scheduling has been promoted on the basis that we can calculate the ET quite accurately if we know the appropriate weather data from the past few days, and that we can determine how much irrigation water is applied if we assume that the irrigation system applies the same amount of water everywhere in the field. The concept of precision farming now allows us to take a different approach to the concept of precision irrigation — one of applying just the right amount of water needed in each area of the field. Seldom do we have enough information to say that the crop in one square foot of a field requires more water than that in another area. However, we do know how differences in soils affect how much of the water applied is held for later crop use. We also know that irrigation does not result in the same amount of water being stored in the soil in one part of the field as in another. With gravity irrigation systems, changes in slope, soil type, tillage, wheel traffic, irrigation stream, set time, and distance from the head ditch all effect the amount of water stored in the soil. Even with center pivots, irrigation is not the same from one point of the field to another, but depends on topography, sprinkler package, and end gun operation. What is appropriate irrigation management and the outcome of that management, also depends on the climate. For example, in the eastern US, where irrigation may account for 6 to 8 inches of water annually to supplement rain, it may be feasible to irrigate sandy spots only, hoping that heavier soils will hold enough water to last until a rain in the near future refills the soil profile. In these cases, we may well find that some soils have a lower ability to produce a crop, and that precision farming best dictates that inputs be reduced in those areas that have lower production potential. Thus, a system with the ability to put different amounts of water in different areas may be worthwhile. In Colorado, where corn requires 24 to 27 inches of well-timed water to produce at its potential, rainfall is not as large a factor (typically providing 7 to 10 inches during the growing season). In this case, we have the potential to control the total water picture much better than irrigators in areas with more rainfall. Where water is the controlling factor of production, and particularly where nutrients can be applied with the water, there is little reason to believe that one soil has a lower potential production than another soil. We see evidence in the fact that many of the very sandy soils, considered not irrigable prior to center pivots, produce as much or more than the “good” or heavier soils of the major river valleys. We believe that precision irrigation implies that we need to design the irrigation system to apply water as uniformly as practical, then to operate the system to apply just the amount of water the crop needs. We are presently conducting studies on the same center pivot irrigated fields as our colleagues at Colorado State, and I will use information from those studies to illustrate the importance of uniformity. In the past, irrigation engineers believed that a system capable of applying water with a “coefficient of uniformity” (CU) equal to 80 was a good system. However, we now know that we pay dearly in terms of water required, and consequently in terms of both energy and lost chemicals, if we have an irrigation system with low uniformity and we try to keep most of the field “well irrigated.” Figure 1. shows how much water we must pump, as a percentage of what the crop requires, for different values of uniformity if we keep 85-90% of the field “well irrigated”. Thus, if we increase uniformity from 85 (132%) to 95 (108%) we can reduce the total water required by 24%! There are several reasons that uniformity of a center pivot may not be up to par — nozzles worn from pumping sand, improper nozzles installed (either poor design, or nozzles not installed where they were intended), large changes in elevation on systems without pressure regulators (or regulators that no longer work). One of the big factors in nonuniformity of irrigation is use of an end gun. When the field is planted to near the limit of end gun reach, it is obvious from plant growth that water is not applied uniformly. Less obvious is the variation of water application along the pipeline as pressure changes when the end gun turns on or off. The range of total seasonal irrigation application over one of our study fields (CU = 86) in 1999 is shown in Figure 2. As a result of topographic changes, incorrect nozzle sizing along the pipeline, turning the end gun on and off, and stopping the system when it rained, then moving back to the pivot road before starting the next irrigation, the water application is less than uniform, even on this “well designed” system. Less than half the field receives within 5% of the average irrigation application, and significant areas receive either a deficit or a surplus exceeding 10 percent. Overall, if the irrigator manages to keep 85-90% of the field well watered, he will need to pump 28 percent more water than the crop requires. The concept of precision timing is equally important, as studies in several areas show that the average irrigation is frequently on the order of 30 percent more than the crop actually needs. Our current work is concentrated on determining the effect of this “imprecise irrigation,” combined with fertigation, soil differences, and estimated leaching, on the availability of nitrogen fertilizer to the crop, and ultimately on crop yield. |
Click here to view a Word file containing Figure
1. Click here to view a Wordperfect file containing Figure 2.
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| Fertilizer Application By Management Zone | |
| Soil color, landscape position, and past management experience are keys to developing management zones for fertilizer application. |
by Kim Fleming and Dwayne
Westfall Dept. Soil and Crop Sciences Colorado State University D. W. Wiens CenTrak L.L.C. |
| Developing accurate variable rate technology (VRT) fertilizer application
maps is critical in implementing precision farming technology. Intensive
grid soil sampling has traditionally been used to develop application maps.
However, the cost and labor associated with grid sampling has led us to
conclude that another approach, such as production level management zones
may be more feasible. A production level management zone is a region of
a field that has similar yield limiting factors. Therefore, a specific rate
of fertilizer, or other input, may be appropriate for this management zone.
The question is how do we identify these different production level management zones in a field? We have known that soil color in bare soil photographs can be used to identify different soil organic matter (SOM) levels. We also know that topography affects production with higher yield generally being obtained in lower positions in the landscape, with lower yields on eroded side slopes and hills. One of the best estimates of yield differences in a field is obtained from the producer. Producers know which areas of a field produce good yield and which areas are low in production. It is logical that nutrient needs are different among these areas. Based on these relationships, we have developed a research and extension program to determine if management zone technology could be used to develop accurate VRT application maps based on aerial photographs showing soil color, landscape position, and past management experience. Aerial photographs were taken and used as an initial template in developing production level management zones. In this procedure, a gray scale image of a bare soil photograph was enhanced using Adobe Photoshop® to contrast color differences. The farmer drew vector lines using commercially available software (Agri Trak Professional®) to establish the individual management zones (high, medium, and low productivity areas) based on soil color, topography and his/her management experience with the field (figure 1). Management zone maps were developed for two center pivot irrigated corn fields in northeast Colorado. The fields were sampled using a 1.4 acre grid. Samples were analyzed for nitrate, organic matter, phosphorus, potassium, zinc, pH, and texture. Electrical conductivity and yield were also mapped on both fields. Evaluation Using the soil and yield data we have begun to evaluate if the farmer-developed management zones represent areas of high, medium and low productivity and have the potential for developing Variable Rate Application maps. We found that soil nutrients and grain yield followed the trends indicated by management zones. Levels of soil organic matter, potassium and grain yield were significantly different in all management zones. Soil texture data show similar trends. Clay and silt levels were significantly higher in high productivity zone, intermediate in the medium zones, and lowest in the low productivity zones. Sand followed the opposite trend. These soils are sandy and higher productivity in areas of lower sand and higher clay levels would be expected due to the higher water holding and cation exchange capacity of the more clayey soils. Electrical conductivity values also followed trends indicated by the management zones and were significantly different across all management zones. In these soils, texture probably has the greatest influence on conductivity values with clay having the highest conductivity values and sand the lowest. Results from field No. 2 indicated that the soil and crop parameters were significantly different across the management zones, however, they did not always follow trends indicated by the zones. This indicates that our method of delineating management zones is consistent . However, the zones need to be ground truthed to classify them into various productivity levels. Electrical conductivity data collection appears to be a cost-effective alternative to soil sampling to ground truth management zones. Practical implications Grid soil sampling to the intensity required to generate accurate Variable Rate Application maps may not be feasible because of the time and expense required. Management zone technology may be a more economical method of developing Variable Rate Application maps. |
Click here to view a Wordperfect file containing Figure 1. |
| meet | ![]() |
| Raj Khosla
Dr. Khosla is an Assistant Professor and Extension Specialist in the Department of Soil & Crop Sciences at Colorado State University. He is responsible for Research, Extension and Teaching Program in the area of Precision Farming and Irrigated Cropping Systems. He teaches an undergraduate course “GIS in Agriculture” every fall semester in the department of Soil & Crop Sciences and Bio-Ag Resources and Chemical Engineering. Dr. Khosla’s current area of research and extension is focused on evaluating various techniques of delineating “in-field production level management zones”. He uses GPS and GIS technologies to manage spatial variability of soils by precise crop input management in an environmentally sensible manner. His work also includes evaluating remote sensing techniques to quantify crop stress conditions for nitrogen in irrigated corn, ground truthing with tissue samples and chlorophyll meter measurement, and making site-specific N-recommendations. The overall goal of Dr. Khosla’s research and technology transfer efforts are to enhance farm profitability while enhancing environmental protection by developing precision agriculture strategies that are compatible with farming practices in irrigated western Great Plains region. Dr. Khosla has traveled extensively around the world including, Asia,
Europe, North and Central America. In his spare time he likes reading,
playing tennis, and traveling.
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| websites |
| Global Positioning Systems
http://www.aero.org/publications/GPSPRIMER/index.html
http://www.trimble.com/gps/index.htm
Geographic Information Systems http://www.gisdatadepot.com/
http://www.esri.com/
Precision Agriculture http://www.precisionfarming.com/
http://www.pioneer.com/usa/technology/precision.htm
http://www.veristech.com/applications.htm
http://terraserver.com/
http://www.deere.com/deerecom/Farmers+and+Ranchers/harvestlink.htm
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| agronomy news
is a monthly publication of Cooperative Extension, Department of Soil & Crop Sciences, Colorado State University, Fort Collins, Colorado. Web Site: http://www.colostate.edu/Depts/SoilCrop/extens.html The information in this newsletter is not copyrighted and may be distributed freely. Please give the original author the appropriate credit for their work. Jessica Davis and Troy Bauder
Direct questions and comments to:
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Extension staff members are: Troy Bauder, Water Quality Mark Brick, Bean Production Betsy Buffington, Pesticides Jessica Davis, Soils Kirk Iversen, Soils Jerry Johnson, Variety Testing Raj Khosla, Precision Farming Sandra McDonald, Pesticides Clark Oman, Minor Crop Pesticides James Self, Soil, Water & Plant Testing Gil Waibel, Colorado Seed Growers Reagan Waskom, Water Quality |