2024 Projects: Yield Stability Zones to Improve Management of Corn
How to Use Yield Stability Maps for Improved Management of Corn?
Zone management within fields can result in much better use of resources and/or more stabilized yields over time. The best indicator to design zones around is yield itself, and yield stability over time (consistency in yields from one year to another). Until recently we did not have a good way to identify such management zones due to lack of consistent equipment (yield monitors), yield data cleaning protocols, and limited number of farmers with multi-year yield records. In 2016 we introduced the concept of "yield stability zones". In this approach, three or more years of yield data for a field are combined into one yield stability map, which contains four yield zones. Fields (or areas within fields) in quadrant 1 (Q1) yield above the farm average and do so consistently across years. The fields (or areas within fields) in Q4 are consistent as well over years, but yield less than the average of the farm. Fields or areas within fields in Q2 and Q3 are much more variable from year to year. If a farmer can identify what keeps production areas in Q3 and Q4 from being higher yielding and what reduces the year to year variability of Q2 areas, there could be options to increase the overall yield of the farm over time. Basically, yield stability zones can help allocate resources better, including nitrogen (N). The release of a data cleaning manual in February of 2018 now allows for standardized cleaning of farmer-collected yield data for corn silage and grain, and with that we can now more easily develop management zones and test what drives yield stability differences and if management needs to be adjusted among management zones.
If you are interested in participating, contact Quirine Ketterings (qmk2@cornell.edu or 607-255-3061). You can also write to: Quirine Ketterings, Nutrient Management Spear Program, Department of Animal Science, Cornell University, 323 Morrison Hall, Ithaca NY 14853.
Goals
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Our goals are to (1) create a multi-agency capacity to obtain and clean yield monitor data from farms (corn grain and corn silage) and to develop yield stability zones for fields with 3 or more years of data; (2) implement N-rich strips (manure or N fertilizer) at planting, for evaluation of N needs for corn for each of the management zones on the farm. The N rich strips with fertilizer and/or manure (farmer driven selection) allows for assessment of crops response to N addition in each of the zones. Here we work with New York farms with yield monitor data to test if extra N (either fertilizer or manure or both) results in a crop response for areas in fields that are classified as Q1, Q2, Q3, or Q4. This will answer the question whether higher yielding areas need more N and/or whether low yield can be increased with N addition. We are developing protocols for integrating spatial and hierarchical Bayesian statistical methods as a standard approach for analyzing and interpreting results from these N rich strip trials.
Funding Sources
This project has been sponsored by grants from the Northern New York Agricultural Development Program (NNYADP), New York Farm Viability Institute, and federal formula funds.
Additional Resources
- Data Sharing Instructions (PDF; August 2, 2017)
- Farm identity is kept confidential.
- Cornell confidentiality statement.
Farmer Impact Stories
Fact Sheets
- Agronomy Factsheet #68: On-Farm Research
- Agronomy Factsheet #69: Adaptive Nutrient Management Process
- Agronomy Factsheet #71: Measuring Corn Silage Yield
- Agronomy Factsheet #77: Nitrogen for Corn; Management Options
- Agronomy Factsheet #78: Adaptive Management of Nitrogen for Corn
- Agronomy Factsheet #84: Crop Vigor Sensing for Variable-Rate Nitrogen
- Agronomy Factsheet #89: Reference Strips for Variable Rate Nitrogen Application
- Agronomy Factsheet #31: Corn Stalk Nitrate Test (CSNT).
- Agronomy Factsheet #63: Fine-Tuning Nitrogen Management for Corn.
- Agronomy Factsheet #72: Taking Corn Stalk Nitrate Test Sample after Corn Silage Harvest.
- Agronomy Factsheet #77: Nitrogen for Corn; Management Options.
- Agronomy Factsheet #78: Adaptive Management of Nitrogen for Corn.
- Agronomy Factsheet #98: Nitrogen Uptake of Corn.
- Agronomy Factsheet #99: Nitrogen Rate Trials in Corn.
- Agronomy Factsheet #103: Multispectral Active and Passive Sensors in Agriculture.
- Agronomy Factsheet #104: Grain Yield Monitor Calibration.
- Agronomy Factsheet #105: Increase Yield Monitor Data Accuracy and Reduce Time Involved in Data Cleaning.
Extension Articles
- Kharel, T., S.N. Swink, C. Youngerman, A. Maresma, K.J. Czymmek, and Q.M. Ketterings (2018). Corn Silage and Grain Yield Monitor Data Cleaning. What’s Cropping Up? 28(2): ..-..
- Ketterings, Q.M., K.J. Czymmek, S.Gami, and M. Reuter (2017). Stalk Nitrate Test Results for New York Corn Fields from 2010 through 2017. What’s Cropping Up? 28(1): ..-..
- Long, E., Q.M. Ketterings, M. Hauser, and W. DeGolyer (2016). Whole Farm Corn and Hay Yield Variability; a Dairy Farm Case Study. What’s Cropping Up? 26(3): 50-52
- Tagarakis, A., I. Cornell, T. Pardoe, J. Cawley, M. Hunter, M. Stanyard, K. Czymmek and Q.M. Ketterings (2016). Proximal sensing for on-the-go variable rate N application in corn. What’s Cropping Up? 26(1): 9-12.
- Czymmek, K.J., A. Tagarakis, and Q.M. Ketterings (2015). Optical sensors for corn silage production – Sensors provide a way to check crop status and evaluate if more N is needed. Eastern DairyBusiness. The Manager. 7(1): 20-21.
Journal Articles
- Tagarakis, A.C., and Q.M. Ketterings (2017). In-season estimation of corn yield potential using proximal sensing. Agronomy Journal. doi: 10.2134/agronj2016.12.0732.
- Tagarakis, A.C., Q.M. Ketterings, S. Lyons, and G. Godwin (2017). Proximal sensing to estimate yield of brown midrib forage sorghum. Agronomy Journal doi: 10.2134/agronj2016.07.0414 .
- Long, E., Q.M. Ketterings, D. Russell, F. Vermeylen, and S.D. DeGloria (2016). Assessment of yield monitoring equipment for dry matter and yield of corn silage and alfalfa/grass. Journal of Precision Agriculture. DOI: 10.1007/s11119-016-9436-y.
- Long, E., and Q.M. Ketterings (2016). Factors of yield resilience under changing weather evidenced by a 14-years record of corn-hay yield in a 1000-cow dairy farm. Agronomy for Sustainable Development. DOI: 10.1007/s13593-016-0349-y.