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Exploring Multi-Year Soybean Yield Trial Data In South Dakota Environments, Jixiang Wu, Jianli Qi, Jonathan Kleinjan
Exploring Multi-Year Soybean Yield Trial Data In South Dakota Environments, Jixiang Wu, Jianli Qi, Jonathan Kleinjan
Conference on Applied Statistics in Agriculture
Crop performance test (CPT) is a common practice to evaluate yield performance and adaptability of each cultivar. In this study, we combined 16 years of soybean CPT data, which included six representative locations, three major maturity groups, and over 1000 cultivars, to determine some patterns associated with yield production. As expected, the repeatability for these cultivars in trial over years was very low. Thus, the data processing in this study was focused on descriptive statistics regarding time, location, and seed supplier and several linear model analyses. The results will be presented during the conference.
Response Of Soybean Yield And Yield Components To Phosphorus Fertilization In South Dakota, Adams Kusi Appiah, Rebecca Helget, Yi Xu, Jixiang Wu
Response Of Soybean Yield And Yield Components To Phosphorus Fertilization In South Dakota, Adams Kusi Appiah, Rebecca Helget, Yi Xu, Jixiang Wu
Conference on Applied Statistics in Agriculture
Increased demand for soybean [Glycine max (L.) Merrill] production for industrial, human, and animal consumption has provided many incentives for farmers and producers to increase their production. In many soils used for soybean production, phosphorus (P) becomes a major limiting factor to soybean growth and grain production. A field experiment was conducted in five locations across Eastern South Dakota in 2013 to study the response of soybean yield and yield components to phosphorus fertilizer applications. The experiment was laid out in a randomized complete block (RCB) design with four replications. The treatments consisted of five P levels 0, 20, 40, …
Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota, Kaushal Raj Chaudhary, Jixiang Wu
Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota, Kaushal Raj Chaudhary, Jixiang Wu
Conference on Applied Statistics in Agriculture
Genotype-environment interaction has always been an important and challenging issue for plant breeders in developing desirable varieties. Determination of genotype and environment is common in breeding program as it helps to find out the genotypes that have wide or specific adaptability across various environmental conditions. In this study, fifteen varieties of soybean were evaluated for stability of grain yield (ton/ha), protein content (%), and oil content (%) at six different locations of Eastern South Dakota in 2011. Mixed linear model and Additive main effects and multiplicative interactions (AMMI) were applied to detect genotype-by-environment (G*E) interactions and stability of each variety …
Functional Divergence Of Duplicated Genes In The Soybean Genome, Paul L. Auer, R. W. Doerge
Functional Divergence Of Duplicated Genes In The Soybean Genome, Paul L. Auer, R. W. Doerge
Conference on Applied Statistics in Agriculture
The soybean genome has undergone many different evolutionary changes that are observable with modern technologies. Of particular interest to scientists and plant breeders is the fact that the soybean genome exhibits features of genome duplication from millions of years ago. Genes that were copied during the duplication event have since diverged functionally. Identifying functionally divergent duplicate genes may provide insight into the evolution of soybean. To investigate functional divergence, transcripts from seven different tissue samples of pooled soybean messenger RNA were sequenced using the Solexa next-generation sequencer and analyzed for gene expression. We tested differential expression of duplicated genes within …
A Combined Analysis Of Experiments When Treatments Differ Among Experiments, Paul N. Hinz, Mario R. Pareja
A Combined Analysis Of Experiments When Treatments Differ Among Experiments, Paul N. Hinz, Mario R. Pareja
Conference on Applied Statistics in Agriculture
The advantages of repeating experiments in several locations and years are discussed and standard methods of analysis are reviewed. The methods assume that the same treatments are used in each experiment. This paper discusses a method used for a combined analysis when the treatments represent levels of a quantitative factor but differ among experiments. The method makes use of multiple regression analysis in which a continuous variable represents treatment levels, classification variables represent experiments, and products of the continuous and classification variables represent differences among experiments. The method is illustrated on data from a series of experiments designed to study …