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.
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.