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Identifying Soil and Terrain Attributes that Predict Changes in Local Ideal Seeding Rate for Soybean [Glycine Max (L.) Merr.]

Matcham, Emma Grace
http://rave.ohiolink.edu/etdc/view?acc_num=osu1554475109598299

Abstract Details

2019, Master of Science, Ohio State University, Horticulture and Crop Science.
Soybean agronomic optimum seeding rate (AOSR) varies from less than 200,000 seeds ha-1 to over 400,000 seeds ha-1 based on yield potential and environmental factors, and planting at or near the AOSR helps farmers maximize yield. Understanding where AOSR is likely to be high or low is useful for soybean farmers utilizing variable rate seeding. An AOSR representing an area smaller than a whole field is referred to as local ideal seeding rate (LISR). The objective of this on-farm study was to identify soil and terrain attributes that were most predictive of differences in LISR. Randomized, replicated seeding rate strip trials were established at 4 fields in 2017 and 3 fields in 2018. Yield data taken from yield monitors were used to estimate LISR 33 to 68 times per field. Soil physical and chemical properties were measured across the field using 0.2 hectare grid samples. In order to estimate soil fertility at the same scale as LISR, geographically weighted regression and random forest interpolation methods were compared. Geographically weighted regression (GWR) had lower root mean square error and better identified low-phosphorous areas of the field, so GWR was used to interpolate all soil properties. Terrain attributes calculated from 0.76 m digital elevation models were also summarized to this scale. Random forest analysis was performed to identify which soil and terrain attributes were most important for predicting LISR within each site-year. Terrain attributes were generally more important than soil properties at all site-years. Univariate linear models were used to relate the most important soil and terrain attributes to LISR. Valley depth was an important variable for model stability in multiple sites and had a strong univariate relationship with LISR across 7 site-years. Moving from the lowest valley to the highest ridge was associated with an LISR increase of 76,000 seeds ha-1. Aspect and relative slope position also had large univariate impacts on LISR. While terrain attributes are less familiar to most farmers compared to soil fertility or yield maps, they may be appealing to farmers interested in VRS because they relate to both yield and LISR, are free to obtain, and remain stable over time. High quality soil maps made using grid soil samples and interpolation likely have more utility for variable rate fertilizer or lime application than variable rate seeding, since in instances where soil fertility was a good predict of LISR there would also likely be a yield increase if fertilizer or lime were applied to portions of the field.
Laura Lindsey (Advisor)
John Fulton (Committee Member)
Elizabeth Hawkins (Committee Member)
Pierce Paul (Committee Member)
Sakthi Subburayalu (Committee Member)
106 p.
Agronomy; Soil Sciences
agronomy; soybean; soil sampling; interpolation

Recommended Citations

Citations

  • Matcham, E. G. (2019). Identifying Soil and Terrain Attributes that Predict Changes in Local Ideal Seeding Rate for Soybean [Glycine Max (L.) Merr.] [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554475109598299

    APA Style (7th edition)

  • Matcham, Emma. Identifying Soil and Terrain Attributes that Predict Changes in Local Ideal Seeding Rate for Soybean [Glycine Max (L.) Merr.]. 2019. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1554475109598299.

    MLA Style (8th edition)

  • Matcham, Emma. "Identifying Soil and Terrain Attributes that Predict Changes in Local Ideal Seeding Rate for Soybean [Glycine Max (L.) Merr.]." Master's thesis, Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554475109598299

    Chicago Manual of Style (17th edition)

osu1554475109598299
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This open access ETD is published by The Ohio State University and OhioLINK.