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Trend Surface Analysis for Nitrogen Uptake in Soft Red Winter Wheat in a Plant Breeding Variety Evaluation Trial.

Poster Number 2210

Tuesday, November 5, 2013
Tampa Convention Center, East Hall, Third Floor

Kiran Pavuluri1, Carl A. Griffey1 and Wade E. Thomason2, (1)Virginia Tech, Blacksburg, VA
(2)Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, VA
Trend is a linear function of geographic coordinates constructed such that the squared deviations of observation from the trend are minimized. Trend surface analysis (TSA) is a multiple regression using geographic location as the independent variable and the data values as the dependent variable. The objective of TSA is to know the overall trend in nitrogen uptake by a soft red winter wheat (Triticum aestivum L.) variety “Branson” in a variety evaluation trial under moderate nitrogen conditions. The required data was collected from an experiment that was carried out to evaluate regionally established germplasm for nitrogen use efficiency in 2012 at Warsaw, VA, USA. This unreplicated trial contained eight columns and 40 rows of field plots (5 feet * 16 feet) (experimental units). Rows and columns are categorized into five blocks in such a way that each blocks contains eight columns and eight rows. In each block; standard check, “Branson” was planted once in every row and column orthogonally and randomly, to account for experimental variation. Yield and Nitrogen uptake was measured using standard protocols. Columns have not contributed to the total variability of either yield (Prob>|t| =0.7) or N uptake (Prob>|t| =0.9) given that rows are in the model. Similarly, interaction between rows and columns (Prob>|t| =0.15) were found to be statistically insignificant at α= 0.05. Cubic model was found to be the best model for explaining the trend due to higher sequential R2 values and simplicity. The variable, rows explained 66% of total trend variation in N uptake. Experimental site slope could be the reason for the observed trend.
See more from this Division: SSSA Division: Soil Fertility & Plant Nutrition
See more from this Session: Soil Fertility and Plant Nutrition Division and Nutrient Management and Soil and Plant Analysis Division Graduate Student Poster Competition (PhD degree)

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