Issues Related to Site-Specific Soil and Crop Management

This article throws light upon the forty-two main issues related to site-specific soil and crop management. Some of the issues are: 1. Site-Specific Use of the Environmental Phosphorus Index Concept 2. Management Zone Concepts 3. Profitability of Site-Specific Farming 4. How to Determine an Accurate Soil Testing Laboratory and Others.

Issues Related to Site-Specific Soil and Crop Management:

1. Site Specific Use of the Environmental Phosphorus Index Concept
2. Management Zone Concepts
3. Profitability of Site-Specific Farming
4. How to Determine an Accurate Soil Testing Laboratory
5. Developing Management Zones to Target Nitrogen Applications
6. Global Positioning System Receivers
7. Variable Rate Equipment—Technology for Weed Control
8. Standardization and Precision Agriculture—’The Promised Land’
9. Yield Monitor Accuracy
10. The Pioneer Split-Planter Comparison Method
11. Earth Model—Calculating Field Size and Distances between Points Using GPS Coordinates
12. Assessing Crop Nitrogen Needs with Chlorophyll Meters
13. Identifying Good Candidates for Precision Phosphorus Management
14. Making Topography Maps
15. Scouting for Weeds
16. Remote Sensing
17. Setting up On-Farm Experiments
18. Simple on Farm Comparisons
19. Area-Wide Management Zones for Insects
20. Estimating the Time of Weed Emergence
21. Variable-Rate Technology (VRT)
22. Potential Applications of Remote Sensing
23. Getting Specific with Site-Specific Nutrient Management
24. Grain Protein Sensing to Identify Nitrogen Management in Wheat
25. Weed Biology and Precision Farming and Others

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Issue # 1. Site-Specific Use of the Environmental Phosphorus Index Concept:

Phosphorus (P) loss to surface water can have negative impacts on the environment. The risk of such loss depends on both source (added fertilizer and manure, soil P) and transport factors (erosion and surface runoff). Fields at risk are those where areas of high P application or soil P coincide with zones of active surface runoff or erosion.

AP index has been developed to rank field vulnerability to P loss so that high risk field may be identified for site specific management. The index provides a framework that can be regionally adapted to prevailing topography, geology, and climatic conditions and requires only readily available data.

Issue # 2. Management Zone Concepts:

Varying the application rates of plant nutrients and other crop inputs across variable fields makes good agronomic sense. For every input some reasonable strategy must be used to guide that application.

Grid soil sampling for phosphorus (P) and potassium (K) has greatly improved the accuracy of fertilizer application, although even greater accuracy can be attained by considering additional site characteristics within sub-regions of fields.

A “management zone” is a sub-region of a field that expresses a relatively homogeneous combination of yield-limiting factors for which a single rate of a specific crop input is appropriate. Spatial information that is most helpful in defining management zones should be quantitative (numerical), densely or continuously sampled, stable over time, and directly related to crop yield.

Issue # 3. Profitability of Site-Specific Farming:

When is site-specific farming (SSF) profitable? What makes it profitable or not? This Guideline looks at both variable rate (VR) input applications and yield mapping. It demonstrates basic budgeting methods to measure average profitability. Profitability results from nine field research studies show that high- value crops give the biggest payoff to VR fertilizer application.

Many yield map benefits come from whole-field improvements such as drainage, land leveling, windbreaks, and fencing. Farmers and agri-businesses should remember that because SSF practices are site- specific, their profitability potential also will be site-specific.

Issue # 4. How to Determine an Accurate Soil Testing Laboratory:

Many people have said that soil testing laboratories are good enough considering the amount of field variability. With the advent of global positioning system (GPS) technology, soil sampling variability is minimized. Now, soil testing laboratories must be more accurate and reproducible to match the improved accuracy and precision achieved with GPS soil sampling.

Issue # 5. Developing Management Zones to Target Nitrogen Applications:

Whether the goal is to determine the level of soil nitrogen (N) or the soil yield potential, management zones for N fertilizer management can be constructed using a variety of tools, including topography, aerial photographs, satellite imagery, soil electrical conductivity sensors, yield maps, and intensive soil survey data.

For the producer starting out, viewing satellite images” and/or aerial photos that are relatively inexpensive to obtain and comparing them with landscape features would be a good place to start. Zones can be constructed and managed for N using a fraction of the number of soil samples required to reveals the same zones through grid sampling.

Zone sampling results in lower sampling costs for variable-rate fertilizer application and allows precision farming to be much more practical for producers of commodity crops. Using these principles, the next step would be to develop computer models to automate the zone development process and eliminate reviewing several maps for each field by the producer in order to decide where to draw zone boundaries.

Issue # 6. Global Positioning System Receivers:

The global positioning system (GPS) and GPS receivers provide the means to determine position at locations anywhere on earth. Developed by the U.S. Department of Defense (DOD) and used for many civilian purposes, from fishing to flying, GPS has also made precision farming a reality.

A typical configuration for on-farm agricultural applications includes a GPS receiver and antenna, a differential correction receiver and antenna, and cables to interface differentially-corrected (DGPS) data from the receiver to other electronic equipment such as a yield monitor or a variable rate controller.

Accurate, automated position tracking with GPS receivers allow farmers and agricultural service providers to record geo-referenced data and to apply variable rates of inputs to smaller areas within larger fields.

Issue # 7. Variable Rate Equipment—Technology for Weed Control:

Sprayer controllers have been developed by agricultural equipment vendors to minimize variation of applied rates of chemicals within fields. The control systems that allow these devices to compensate for changes in vehicle speeds now also provide the potential to apply variable rates of pesticides according to pre-planned maps. The types of sprayer systems and controllers are capable of variable rate control.

Issue # 8. Standardization and Precision Agriculture—’The Promised Land’:

Progress toward increased use of electronic systems for precision farming applications will be enhanced by the introduction of standards for electronic communications on agricultural equipment and translation of spatial data formats. The standard 1939 will provide a uniform approach to communications on tractors and implements.

Issue # 9. Yield Monitor Accuracy:

Laboratory tests showed that the accuracy of the yield sensor was affected by sudden grain flow changes. The yield sensor had a quick response to flow variations; however, it did not provide consistent readings when grain flow variations were abrupt. In field tests, the yield monitor showed yield trends quite reasonably.

The yield monitor accuracy was higher at a constant combine ground speed compared to varying speeds based on weights from individual strips. Yield monitor calibration plays a key role in obtaining the best possible accuracy from the yield monitor.

Issue # 10. The Pioneer Split-Planter Comparison Method:

The Pioneer Split-Planter Comparison Method is a simple, low-cost technique for making treatment evaluations using a global positioning system (GPS) equipped yield monitor in whole fields. Comparisons can be made between two hybrids, varieties, or agronomic treatments applied in alternating strips throughout a field.

Pooling results from similar comparisons made at multiple locations is much preferred to relying on single-location results. The ability to bring a yield difference map into a geographic information system (GIS) and overlay it with other spatial data layers will greatly increase the value of the map as a crop management tool.

Issue # 11. Earth Model—Calculating Field Size and Distances between Points Using GPS Coordinates:

An ever-increasing number of farmers have global positioning system (GPS) receivers on their combines. When not harvesting, GPS receivers are useful for more than locating one’s favorite spot. The distance between two sampling points and the area of a field can be found using GPS coordinates and knowledge of the Earth Terrestrial Coordinate System.

The objective of this guideline is to provide a method those farmers and agricultural practitioners can use to calculate distances between points and to calculate the size of a field using Excel, a commonly available spreadsheet.

Issue # 12. Assessing Crop Nitrogen Needs with Chlorophyll Meters:

One of the most difficult challenges facing farmers is to determine the appropriate fertilizer nitrogen (N) application rate. Irrespective of sources, most N in soil is eventually transformed to the nitrate (NO₃) form. To minimize NO₃ leaching, cropping systems and management practices must minimize excess NO₃ in the soil and the potential for percolation below the root zone.

The problem is basically one of synchronizing soil N availability (from all N sources) with crop N needs. This task is complicated because it is difficult to accurately predict climatic variables that influence crop growth, soil microbial activity, and NO₃ leaching.

Issue # 13. Identifying Good Candidates for Precision Phosphorus Management:

i. In fields with high soil test P variability, precision management of P produced the greatest levels of profitability when the composite soil test P level was in the high to very high soil test P categories.

ii. Average soil P test level and prior field histories can be used as a decision aid to reduce economic risks associated with adopting precision farming techniques.

iii. Appropriate P response models and yield goals must be used to accurately assess potential profitability associated with precisions P management.

Issue # 14. Making Topography Maps:

A code-phase differentially corrected global positioning system (DGPS) can be used for grid sampling by applying variable rate fertilizers, and monitoring yield. After a while it can be seen that soil nutrient, pH, and yield information on topography maps is superimposing and thereby, improving the ability to identify management zones.

Issue # 15. Scouting for Weeds:

The concept behind scouting for weeds is to provide accurate and timely information needed to make intelligent, cost effective decisions. Moreover, scouting is a key component in the design of effective weed management strategies that help to manage risks by providing information needed to optimize the correct timing of herbicides and accurately monitor weed management successes and failures.

Adaptive sampling strategies (rather than fixed strategies such as grid sampling) are flexible and build on previous information and experience. Adaptive approaches also result in more dynamic data gathering systems that can be used to determine if the current weed management system is or is not meeting goals. However, there is no single scouting strategy that is best in all situations.

Issue # 16. Remote Sensing:

Photographic vs. Non-Photographic Systems. The intention of site-specific management is to optimize grower inputs on areas much smaller than the entire field. These areas may be as small as a few square meters in size. To manage a field on such a scale, data would have to be collected on a similar or smaller scale.

To collect the data by hand would be very time consuming, labour intensive, and destructive. This is the role remote sensing systems can play in site-specific management.

Issue # 17. Setting up On-Farm Experiments:

The ability to perform on-farm experiments has been greatly improved with the advent of yield monitoring and differentially-corrected global positioning system (DGPS) equipment. However, care should be exercised &hen planning a particular experiment to remove sources of variation that might confound the interpretation of the data.

In addition, the use of yield monitor data may require more observations or larger loads to adequately capture the random variation in the field.

Issue # 18. Simple on Farm Comparisons:

Many farmers are continuously conducted experiment with new farming approaches to optimize profitability. The selection of a method for conducting the experiment and making comparisons is critical to minimize incorrect interpretation of experimental results.

It is not necessary to implement complicated experimental or statistical methods to determine if a change in management will improve production. The purpose of this guideline is to provide a framework for conducting simple on-farm experiments. These techniques can be used for any comparisons where two factors are required to be compared with statistical precision.

Issue # 19. Area-Wide Management Zones for Insects:

Through this management, the incidence of insects can be reduced substantially and provide economic and social sustainability. Farmers working together to manage a problem can overcome many of the difficulties that might be encountered. A proactive and futuristic approach to pest management can yield many unexpected benefits related to total farm management.

Issue # 20. Estimating the Time of Weed Emergence:

The basis for timing of many weed control operations is seedling emergence. However, weeds rarely, if ever, emerge in a synchronous and uniform flush.

Instead, they emerge in “fits and starts”, depending upon weather, soil, and management conditions. Recently developed computer software permits site-specific prediction of weed emergence, early seedling growth using on-farm weather data and also forecasting forthcoming emergence. The software is sensitive to tillage system and soil type.

Issue # 21. Variable-Rate Technology (VRT):

Developing accurate variable-rate technology (VRT) fertilizer application maps is critical in implementing precision farming management. Intensive grid soil sampling may be used to develop application maps.

However, the cost and labour intensity associated with intensive grid sampling suggests other approaches may be more feasible. Management zone technology may provide a more economical method of developing VRT application maps.

Issue # 22. Potential Applications of Remote Sensing:

Since the development of remote sensing nearly 60 years ago, there have been many applications for agriculture. Some have proved effective, while others have not succeeded in assisting farmers with problem solving. Profit margins for individual farmers are typically slim; therefore, farmers are likely to take seriously any technology advances that will help increase those margins.

So far the use of remote sensing data has proven most economical for the high value crops where the risks are greater per acre.

Issue # 23. Getting Specific with Site-Specific Nutrient Management:

Over simplification of site-specific nutrient management can lead to reduced profits and production. Currently, site-specific nutrient management typically involves applying a definite set of recommendations of different areas in a field, based upon a few factors, such as soil test levels and yield goals.

However, if these recommendations do not consider other site-specific factors that influence response to fertilizer application, substantial opportunities to increase profits and production may be lost. Proper evaluation of these yield-limiting factors and appropriate management changes based on readily available information could make site-specific nutrient management more profitable.

Issue # 24. Grain Protein Sensing to Identify Nitrogen Management in Wheat:

Protein concentration in grain is greatly influenced by the level of nitrogen (N) fertility. However, there is significant spatial variation in N fertility in a field. Conventional uniform application ignores this variability and leads to over-fertilization in some areas and under-fertilization in others.

Therefore, the question arises as to whether grain protein can be optimized on site- specific bases by accounting for spatial variability of N fertility within individual field.

Issue # 25. Weed Biology and Precision Farming:

Weeds, and methods used to control weeds, can have negative economic and environmental impacts. With precision agriculture, growers can take advantage of the patchy nature of weeds by targeting management efforts only where they are needed instead of wasting expensive and potentially hazardous inputs where weeds are not present.

Weeds are patchy because weed spread, survival, and reproduction are variable within a field and over time.

Issue # 26. Interpreting Remote Sensing Data:

Can remote sensing fulfill its 30-year-old promise for enhancing profitability in agriculture? The answer is still not clear-cut for everyone, but a combination of past experience and technological improvements is now making it profitable to incorporate remote sensing into many farms. This guideline explores some of the basic analysis options for agricultural applications of remote sensing data.

Issue # 27. Strategic Approach to Site-Specific Systems:

Site-specific management must be approached logically and systematically. Like any major change, it is easier to break the process into manageable action steps that ultimately build to a complete management system.

A strategy is offered in contrast to a generalized recipe of tools and practices. A successful strategy considers farmer goals and characteristics of the individual farm, .farmer, and fields before decisions about tools and practices are made.

Issue # 28. Geographic Information Systems (GIS) in Site-Specific Systems:

The collection and management of data from site-specific crop and soil management systems soon overwhelm the standard farm record system. Geographic information systems (GIS) provide a systematic approach to managing the large amounts of data accumulated, along with the tools necessary for analysis and interpretation.

Issue # 29. Yield Monitors—Basic Steps to Ensure System Accuracy and Performance:

According to today’s yield monitor manufacturers, most users should obtain accuracy within +/-3 per cent, if the system is properly installed, maintained and calibrated. Items that operators must be conscious of and attend to for good results can be summarized as follows: Proper calibration of the mass-flow sensor using multiple loads acquired according to the manufacturer’s recommendations. Inspection of the system sensors, particularly those affected by crop conditions, during the harvest. Verification and, if necessary, calibration of the ground speed sensor.

Verification and calibration of moisture and temperature sensors. Correct entry of the operating information such as crop type, field and header width for each field into the system console. Proper use of the software to extract and process the yield data.

New technology often requires time and experience to ensure all things are operating at peak performance. The items discussed here are lessons learned with field experience.

Issue # 30. Trouble Shooting Yield Monitor Systems:

In spite of extensive calibration, yield monitors can still have problems recording the data. When yield monitors stop working, trouble-shooting to solve the problem can be difficult, especially when the time to harvest the crop is at hand. The objective of this guideline paper is to provide information for trouble-shooting yield monitors.

Issue # 31. Site-Specific Soil Compaction Mapping Using a Digital Penetrometer:

Soil compaction is generally defined as an increase of the natural density of soil at a particular depth. A density increase translates into less pore space, less plant available water, slower water transport, and a decrease in the root’s ability to penetrate the compacted zone as it seeks out water and nutrients.

Similarly, the increase in density due to compaction can serve to retard or divert the flow of water, resulting in ponding or excessive runoff. These factors may limit yield and inhibit effective site management for many crops compaction can be measured with penetro meters. Recent advances in digital penetrometer systems can provide users with a simple way to map soil characteristics over large areas in the field.

Issue # 32. Soil Information Required for Site Specific Management:

Country soil surveys contain a compendium of information about soil and climatic conditions within a region. The soil surveys are available from local Natural Resources Conservation Service (NRCS) offices. Boundaries of the different soils are usually drawn on an aerial photograph.

Interactions between soil and climatic conditions influence land productivity and weed, disease, and nutrient spatial and temporal variability. By understanding these interactions, our ability to manage risk, increase productivity, and protect the environment can be improved. There is no single strategy for incorporating soils information into the decision process.

Issue # 33. Variable-Rate Nitrogen Management for Crop Production:

Adoption of variable-rate nitrogen (N) management by farmers especially in India is low, despite the potential economic and environmental benefits of this practice. A major obstacle is that recommended N fertilizer rates based on targeted yield are often poorly correlated with actual economically optimum N rates.

Nitrogen response patterns are often field-and-season-specific and can vary widely within the same field, further complicating adoption. Side-by-side comparisons of uniform and variable rate N management have revealed no consistent advantages for either strategy in yields achieved, profitability, whole-field N usage, or N-use efficiency by plants.

Issue # 34. Estimating Yield Losses from Unevenly Spaced Planting:

Agronomists and corn growers have long assumed that evenly spaced stands of com have a greater yield potential than unevenly spaced stands. The uniformity of spacing between plants can easily be determined by using a commonly used statistic, standard deviation SD. This statistic is available within most spreadsheets. By measuring the SD of plant uniformity, yield loss due to non-uniform plant spacing can be estimated.

Issue # 35. Soil Samples for N and P Fertilizer Recommendations:

Soil fertilizer recommendations in modern crop production rely on laboratory analysis of representative soil samples. Regardless of where the samples are collected (grid points, management zones, or whole fields) the accuracy and precision of the fertilizer recommendation can be improved by considering the factors that influence nutrient variability in the design of the sampling protocol.

The objectives of this guide are to discuss how management influences nutrient variability and to provide insight into how to design soil sampling protocols that provide good fertilizer recommendations.

Issue # 36. A ‘Cookbook’ Approach for Determining the ‘Point of Maximum Economic Return’:

Many agronomists and producers have been conducting on-farm experiments that are designed to determine the impact of different fertilizer rates or plant populations on crop yields. These data are usually analyzed by plotting the input (fertilizer or population rate) vs. output (yield).

The point of maximum yield may be picked directly off the plot. To make the results of these experiments more useful, the point of maximum economic return should be calculated.

Issue # 37. Selection of Satellite Remote Sensing Product for Precision Farming:

From large number of satellite remote sensing products, it is difficult to select the appropriate one because each satellite has different revisit times, delivery schedules, ordering requirements, pixel resolutions, sensors, and costs. Some satellites collect on a regular schedule (Landsat), while other satellites (IKONOS, Quick Bird, and SPOT) need advance programming (tasking).

To obtain high resolution satellite information promptly from Quick Bird or SPOT, either High Priority or Rush Tasking may need to be purchased. The purpose of this Guideline is to provide direction on how to select an appropriate satellite-based remote sensing product.

Issue # 38. Determining the “Best” Approach to Identify Nutrient Management Zones:

Productivity zones, yield stability maps, and management zone maps based on elevation, electrical conductivity, yields, and remote sensing may be developed using a variety of different approaches.

Producers frequently ask: Which method for identifying zone boundaries is best? The answer to this question depends on the criteria used to evaluate the zone boundaries. At least three different criteria for assessing management zone boundaries are used.

These criteria are:

i. The ability to group areas with similar soil test results into the same zone;

ii. The ability to group areas with yields into the same zone; and

iii. The ability to improve fertilizer recommendations.

However, if the goal was to minimize nitrogen (N) and phosphorus (P) recommendation errors, then this was accomplished by using multiple years of yield monitor data to develop landscape specific yield goals, sampling old homesteads separately from the rest of the field, and grid-cell soil sampling to fine-tune N and P recommendations.

Similar analysis can be conducted in your field if you have multiple years of yield data and an understanding of soil nutrient variability.

Issue # 39. Using Remote Sensing to Develop Weed Management Zones in Soybeans:

Crop scouting should provide accurate, timely and cost effective information about diseases, insects, nutrient deficiencies, and weeds in production fields. Approaches for weed scouting include examining edges of fields or driving across fields.

Remote sensing can be used to guide ground-scouting activities and identify the extent of weed patches. Ground-truthed remote sensing information can be used to develop effective weed management strategies and monitor weed management successes and failures.

Issue # 40. Characterizing Soil Variability Using On-the-Go Sensing Technology:

One of the major objectives of precision agriculture technologies is the site-specific management of agricultural inputs to increase profitability of crop production, improve product quality, and protect the environment. Information about the variability of different soil attributes within a field is essential to the decision-making process.

The inability to obtain soil characteristics rapidly and inexpensively remains one of the biggest limitations of precision agriculture. The major benefit of on-the-go sensing has been the ability to quantify the heterogeneity (non- uniformity) of soil within a field and to adjust other data collection and field management strategies accordingly.

Issue # 41. Developing Productivity Zones from Multiple Years of Yield Monitor Data:

Yield is the ultimate integrator of landscape and climatic variability and therefore should provide useful information for identifying management zones. However, due to year-to-year climatic variation, identifying useful management zones based on a single year’s yield map is difficult.

Increasing the number of years used to define zones may be solution to this problem. ‘Mean yield’ maps created from multiple years of data may be used to determine yield goals and fertilizer recommendations, while standard deviation maps may be used to identify areas requiring corrective management.

Issue # 42. Global Navigation Satellite System (GNSS) Based Auto-Guidance in Agriculture:

Auto-guidance, also called auto-steer, of tractors and self-propelled agricultural machines that is based on a global navigation satellite system (GNSS) represents one currently available technology that can provide significant benefits for crop production in diverse growing environments.

There is an ongoing effort to define and quantify performance of auto-guidance systems so that users of this technology could better select the most suitable option for a given farm operation.

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