Had a producer who purchased a used combine last fall equipped with universal display monitor with no GPS receiver. He purchased and installed new AgGps 162 receiver. He programed the receiver according to dealer specification for the monitor but was never able to get it to work last fall. After checking to make sure the receiver was working and set to recommended specification I still could not get the receiver and monitor to talk to one another, I decided to try different setting. The recommended settings were for port A, RCTM 9600 and NEMA at 4800. After changing the RCTM to 4800 and leaving the NEMA at 4800 we were then able to get a GPS signal to the monitor. He should start cutting wheat any day and we will be able see if these changes will allow us to record yield data.
10 May
Growers use RTK to track floodwater level
A family farm is using RTK elevation readings from the yield monitor on their combine to help them cut wheat ahead of the rising Mississippi River. The river is moving in on about 500 acres of wheat, which is mature but still high moisture and they started cutting at the water’s edge last week. Each day they cut the area covered by a 1′ elevation rise. Everyday the wheat’s moisture drops a little and they get more of their crop out.
23 Mar
Field Boundaries – A management tool
A field boundary defines how precision ag works. While spraying a prescription, a producer sets the sprayer not to spray outside the field boundary. It is used to analyze yield. Having and using accurate field boundaries is essential to determining problems and developing solutions for a field.
With larger equipment becoming standard, producers are combining the traditional smaller fields into larger blocks. These “new” field boundaries need to be used instead of the older boundaries. Keeping the basic information in sync with the actual production practices makes the recordkeeping and analysis much easier and simplier.
For questions and assistance contact Dennis Burns, 318-267-6709 or R.L. Frazier, 318-267-6714.
19 Jan
Normalizing Data Part II
In an earlier post I talked about normalizing as a different way of looking at yield data. Normalized data gives you the advantage of being able to look at field’s performance across multiple years and multiple crops to help identify management zones within a field. Last time we looked at only one year of data with a tradition yield map compared to a normalized map. By normalizing we had a better picture of where yield differences occurred for a single year. This time we will look at the same field over a two year period. In 2009 the field was planted with soybeans behind wheat and followed in 2010 with corn that we looked at earlier.
Traditional Yield Map
Normalized Map
Now let’s look at the same field in 2009 planted to soybeans. Just as a note these were late planted wheat beans. As most of you remember 2009 was extremely dry up until harvest. This crop both benefited and was hurt by the excessive rain in August till harvest in November. This is another good example of why I like to normalize a field and get away from bushels.
Normalized Map
Traditional Yield Map
As we study these maps we see the same yield patterns begin to develop across the field in almost the same locations as in the 2010 corn. You will notice that on the northern edges of the field we had no harvest information. This is because of the heavy rain, this portions of the field was lost to flooding. Again we see the south end of the field out yielded the north end of the field, this is clearer in the normalized map than the traditional yield map. Now let’s create a normalized map for multiple years across multiple crops to see if yield patterns are consistent from year to year with different crops.
Normalized Map Using Multipule Crops and Multipile Years
As you study this map we see that the south end of the field still continues to out yield the north end of the field year after year regardless of the crop. The soil in the south end is a sandy loam and changes to heavy clay in the middle of the field north. There are also problems with getting water to the north end of this field and the dark red area to the north is where a pipeline crossed a few years ago resulting in a change in soil structure.
Knowledge of the field, yield maps and normalized date are tools to identify differences in a field so you can make better management decisions.
19 Jan
Preparing for the upcoming season
Now is the time to get your fields and crops organized for the upcoming season. When it comes to field names/numbers consistency is the key to success. Analyzing yield data or documenting production practices for multiple years make it virtually a requirement. Other information such as crops, variety names, chemicals, fertilizers, equipment, etc. can be entered now in preparation for use. This information can be entered using desktop programs (e.g. APEX, SMS) and copied to the data cards which go in the equipment on the tractors, sprayers, and harvesters. Or you can enter it directly into the equipment if you don’t have one of the desktop programs. Along with these card entries, make a reference notebook with maps that can stay with each tractor, etc.. Time spent now getting data prepared and organized will help keep your field operations moving smoothly with fewer gliches to hinder your data analysis after the tasks are finished.
7 Jan
Preparing for the upcoming season
Now is the time to get your fields and crops organized for the upcoming season. When it comes to field names/numbers consistency is the key to success. Analyzing yield data or documenting production practices for multiple years make it virtually a requirement. Other information such as crops, variety names, chemicals, fertilizers, equipment, etc. can be entered now in preparation for use. This information can be entered using desktop programs (e.g. APEX, SMS) and copied to the data cards which go in the equipment on the tractors, sprayers, and harvesters. Or you can enter it directly into the equipment if you don’t have one of the desktop programs. Along with these card entries, make a reference notebook with maps that can stay with each tractor, etc.. Time spent now getting data prepared and organized will help keep your field operations moving smoothly with fewer gliches to hinder your data analysis after the tasks are finished.
22 Nov
Normalizing Yield Data
Normalizing Yield Data
Well the harvest is over and in Madison Parish we are going to have a fair year, especially with the commodity prices, as they risen here at the end of harvest helping to make up for the shortfalls in production. I have heard many producers say that it sure was nice to be able to gather what you produced this year. For us, this is the first crop complete crop we have harvested in three years. We, like many of you left much of the 2008 and 2009 crops in the field. Much of the conversation around the coffee pot has been how great the weather cooperated with us this year. The best we can come up with is that from the middle of July till mid-November, we have only lost three days of work to the weather. This has allowed us to do much-needed field repairs that we were not able to do the past two falls.
Now on to business, as we began to look over harvest information like load tickets, elevator receipts, yield monitor data and other information about our crop and plan for next year I would like to share a few suggestion and tips for interpreting yield data from a combine or cotton picker. Sometimes we get hung up on looking at yield (bushels or lint/ac). While this is important, it can get in the way when making management decisions. Also in crop rotations like corn, soybeans, cotton and rice the production is very different. To be able to look across multiple years of data, with multiple crops on a given field we need to look the process of normalizing data. This process averages data and gives you a map in percentages not production. To give you a better idea of what I mean the following two pictures hopefully will make it clearer.
Figure 1. Traditional View
Figure 2. Normalized View
These two maps were generated in Farm Works, there are other programs on the market that manage yield data and do normalization of data
As you study traditional view (Fig. 1) you begin to see the dark green to light green to yellow bands across the field. Having knowledge of the field the lighter green on the lower left is the irrigation pipe. Along the north end of the field we begin to see the most visible yield loss. Then as you look in the middle of the field you will see small changes in yield. Most would say there are no real differences across the field that can’t be explained, but when we normalize the yield data from this field we see a different picture. With the normalized view (Fig. 2) it becomes easier to identify differences in production where management zones can be defined.
There are different formulas for calculating normalized yield but in this case we will use the straight average method, the average yield of the field is divided into each yield point or assigned to a pre-determined cell size across the field. By doing this the yield is viewed as a percentage resulting in a better picture of the differences in production. Another advantage of normalizing yield is to compare multiple years of data across multiple crops to identify the strengths and weakness of a field. This will be addressed in future articles.
