Year: 2026
Type: article
Abstract: Spatial variation is a major source of error in agricultural field experiments affecting genotype performance prediction. Implementing statistical models that account for spatial effects can improve the prediction of genotype performance. This study evaluated the impact of the P-spline spatial correction method on the estimation of genetic parameters and AIC values in two distinct crops, wheat and cassava, using four models: Block, Block + Spatial, Block + Marker, and Block + Marker + Spatial. Analyses were performed on data from 115 and 68 trials obtained from the T3/WheatCAP and Cassavabase databases, respectively. As assessed using Cullis heritability estimates and AIC values, the results demonstrated that correcting for spatial variation improved analyses of grain yield, test weight, plant height, powdery mildew, stripe rust, and bacterial streak disease in wheat. Similar improvements were observed in cassava for dry matter content, dry yield, and plant height. However, no improvement was observed for cassava mosaic disease or bacterial blight. These results were consistent whether or not marker effects were fitted in the models. This study demonstrates that incorporating spatial correction into statistical analyses substantially improves the precision of variety evaluation. By accounting for field heterogeneity, spatial modeling complements experimental design and enhances the accuracy of treatment comparisons. Therefore, integrating robust experimental designs with appropriate spatial analyses is essential for achieving optimal precision and reliability in field trial evaluations.
Source: PLoS ONE
Authors: Tesfahun Alemu Setotaw, Christine Mwende Nyaga, David James Waring, Jianli Chen, Chiedozie Egesi, Katherine Frels, Lucia Gutierrez, Jinha Jung, Michael Kanaabi, Margaret Krause, R. Esten Mason, Mohsen Mohammadi, Eder Jorge de Oliveira, Eric Olson, Jessica E. Rutkoski, Nicholas Santantonio, Clay Sneller, Mark E. Sorrells, Lukas A. Mueller, Jean-Luc Jannink
Institutions: Cornell University, Boyce Thompson Institute, University of Idaho, National Root Crops Research Institute, International Institute of Tropical Agriculture, International Institute of Tropical Agriculture, University of Nebraska–Lincoln, University of Wisconsin–Madison, Purdue University West Lafayette, National Agricultural Research Institute, National Agricultural Research Organisation, Oregon State University, Colorado State University, Brazilian Agricultural Research Corporation, Embrapa Cassava & Fruits, Michigan State University, University of Illinois Urbana-Champaign, Virginia Tech, The Ohio State University, Agricultural Research Service, Robert W. Holley Center for Agriculture & Health
Language: English
Topic: Genetics and Plant Breeding
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W4411021167