Proposed Method for Statistical Analysis of On-Farm Single Strip Treatment Trials
| Autor: | Karl Czymmek, Joseph Guinness, Tulsi P. Kharel, Quirine M. Ketterings, Ángel Maresma, Jason Cho, Jan van Aardt |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
precision agriculture
Covariance function Agriculture Generalized least squares Stability (probability) Least squares on-farm experimentation Statistical power remote sensing Data point Standard error Statistics Agronomy and Crop Science statistical design zone-based management Independence (probability theory) spatio-temporal analysis Mathematics |
| Zdroj: | Agronomy Volume 11 Issue 10 Agronomy, Vol 11, Iss 2042, p 2042 (2021) |
| ISSN: | 2073-4395 |
| DOI: | 10.3390/agronomy11102042 |
| Popis: | On-farm experimentation (OFE) allows farmers to improve crop management over time. The randomized complete blocks design (RCBD) with field-length strips as individual plots is commonly used, but it requires advanced planning and has limited statistical power when only three to four replications are implemented. Harvester-mounted yield monitor systems generate high resolution data (1-s intervals), allowing for development of more meaningful, easily implementable OFE designs. Here we explored statistical frameworks to quantify the effect of a single treatment strip using georeferenced yield monitor data and yield stability-based management zones. Nitrogen-rich single treatment strips per field were implemented in 2018 and 2019 on three fields each on two farms in central New York. Least squares and generalized least squares approaches were evaluated for estimating treatment effects (assuming independence) versus spatial covariance for estimating standard errors. The analysis showed that estimates of treatment effects using the generalized least squares approach are unstable due to over-emphasis on certain data points, while assuming independence leads to underestimation of standard errors. We concluded that the least squares approach should be used to estimate treatment effects, while spatial covariance should be assumed when estimating standard errors for evaluation of zone-based treatment effects using the single-strip spatial evaluation approach. |
| Databáze: | OpenAIRE |
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