Difference between revisions of "How are productivity maps used?"

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*Monitoring effect of irrigation on crop
 
*Monitoring effect of irrigation on crop
  
'''''//put picture of irrigation issues - credit to Francis '''''  
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| Waterlogging and Drainage issues can be a cause of variability ''(Photo: Francis Yeatman, Aug. 2012)''
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=== Directed sampling  ===
 
=== Directed sampling  ===
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One of the main uses of these maps is to use them as a starting point for field visits, validating on site the different zones, and with information from the farmer and the consultant, characterize the different types of management zones.  
 
One of the main uses of these maps is to use them as a starting point for field visits, validating on site the different zones, and with information from the farmer and the consultant, characterize the different types of management zones.  
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'''''//put figure of grid &amp; directed sampling'''''  
 
'''''//put figure of grid &amp; directed sampling'''''  
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=== Variable Rate prescription  ===
 
=== Variable Rate prescription  ===
  
Specifically related with the use of crop inputs (seed, fertilizes, agrochemicals), it's possible to use productivity maps to generate prescription maps, in order to save inputs in areas with low yield potential and incresase inputs in areas with high potential.  
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Specifically related with the use of crop inputs (seed, fertilizes, agrochemicals), it's possible to use productivity maps to generate prescription maps, in order to save inputs in areas with low yield potential and increase inputs in areas with high potential.  
  
'''''//put figure of productivity map → to seed or =variable rate fertilizer'''''
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=== Recognize the differences - generate the productivity map  ===
 
=== Recognize the differences - generate the productivity map  ===
  
In this step, the productivity map is generated to recognize variability within fields. This entails a 2-step process, where we first analyze regional limiting factors, and then carry out an analysis in each field based on remote sensing, and crop history. This process is analyzed in'''''//put link'''''
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In this step, the productivity map is generated to recognize variability within fields. This entails an analysis in each field based on remote sensing, and crop history, detailed oin [[Productivity_Maps_how_are_they_generated|this article]].
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Optionally, relative differences can be quantified if there is yield data available. By overlapping yield data on productivity zones, and summarizing results, we can determine the average yield by producitivity zone, and eventually group 2 or more zones into one class, to simplify the map and narrow down the focus on issues.
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=== Field visit - Characterize management zones  ===
 
=== Field visit - Characterize management zones  ===
  
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[[Image:Soil_probing.jpg|600px]]<br>
  
 
In this step, Productivity zones are validated in the field, to derive management zones.  
 
In this step, Productivity zones are validated in the field, to derive management zones.  
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<br> '''//put figures of macroambientes / microambientes..'''.  
 
<br> '''//put figures of macroambientes / microambientes..'''.  
  
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== Limitations  ==
 
== Limitations  ==

Revision as of 17:14, 19 September 2012

{{#customtitle:How are Productivity maps used?|How are Productivity maps used?}}

Applications & Benefits

Productivity maps are a reliable tool to understand variability within a field or management unit and support management decisions. By understanding within field variability, there are different  ways that these maps can be used:

Analyze variability and evaluate management alternatives

Understanding the variability within a field is the main application of productivity maps, based on crop history and remote sensing. This allows to evaluate diverse decisions regarding how to address and manage the causes for variability. The following items are examples of the types of decisions that can be taken:

  • Modify the uses of the field and/or management units
  • Select areas for on-farm research
  • Support renting/lease decisions.
  • Selecting soil sampling points
  • Variable rate seed and fertilizer application
  • Selecting sample sites for leaf / plant sampling
  • Selecting moisture probe points
  • Irrigation scheduling
  • Deciding where to dig soil profile pits
  • Drainage system and points
  • Crop rotation strategies
  • Hybrids selection by management zone
  • Monitoring effect of irrigation on crop


Drainage issues.jpg
Waterlogging and Drainage issues can be a cause of variability (Photo: Francis Yeatman, Aug. 2012)


Directed sampling

Productivity maps provide a viable alternative to more data intensive methods, such as grid sampling or on-site surveys, reducing time and costs to diagnose the causes of variability. According to different experiences, the number of sampling points can be reduced from 6 to 1, or 10 to 1, for instance, using methods of grid sampling and directed sampling based on productivity maps.

One of the main uses of these maps is to use them as a starting point for field visits, validating on site the different zones, and with information from the farmer and the consultant, characterize the different types of management zones.


//put figure of grid & directed sampling

Variable Rate prescription

Specifically related with the use of crop inputs (seed, fertilizes, agrochemicals), it's possible to use productivity maps to generate prescription maps, in order to save inputs in areas with low yield potential and increase inputs in areas with high potential.




The decision making process

Productivity maps can guide the manager or consultant, regarding yield differences in their fields. These differences can be validated in the field, management zones delineated, and then take management decisions. The decision making process has three main activities:

Recognize the differences - generate the productivity map

In this step, the productivity map is generated to recognize variability within fields. This entails an analysis in each field based on remote sensing, and crop history, detailed oin this article.

Optionally, relative differences can be quantified if there is yield data available. By overlapping yield data on productivity zones, and summarizing results, we can determine the average yield by producitivity zone, and eventually group 2 or more zones into one class, to simplify the map and narrow down the focus on issues.

 

Yields by zone.jpg



Field visit - Characterize management zones

Soil probing.jpg

In this step, Productivity zones are validated in the field, to derive management zones.

It's recommended to work jointly with the involved parties, such as the farmer, managers, or consultants: visiting the field with a GPS, evaluating differences shown in the productivity maps recognizing causes for variability, and characterizing management zones. One important aspect is that the regional limiting factors can be taken into account for management zones characterization. Directed soil and/or tissue sampling can be carried out to gather additional data and fine tune recommendations. Productivity maps classes can also be grouped to create management zones As a result of this step, management zones are defined, and attributed, which is the basis to evaluate management alternatives. //figure of thomas → productivity maps → management zones


Take management decisions

In this final step, gathered information is analyzed to take management decisions. These can be grouped in two major areas:

  • General decisions, that do not require Variable Rate Technology (VRT).
    This would involve for instance, dividing the fields in broad areas, where different decisions are implemented, such as adopting a crop rotation strategy, hybrid selection, seeding dates, drainage or irrigation management, etc. .
  • Creating Prescription maps for Variable Rate application, optimizing inputs according to the field potential.
    This would include for instance variable rate application of P, N, seed, or micronutrients.


//put figures of macroambientes / microambientes...


Limitations

There are a couple of limitations to consider:

  • Imagery availability on the right dates can be a limiting factor in certain occasions, in most cases the available image banks can provide the historical information needed. This link has additional information on using the right imagery dates //put link
  • Productivity can be evaluated within fields only, and not between fields. The main reason is that in a given farm, fields may have at the same time different types of crops or uses. Thus, NDVIs from different fields cannot be compared. For this reason different images are selected for different fields. As a conclusion, productivity zones maps should only be used to compare variability within fields, but not as a means of comparison between different fields.