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United States Department of Agriculture

Agricultural Research Service

Research Project: PREDICTING INTERACTIVE EFFECTS OF CO2, TEMPERATURE, AND OTHER ENVIRONMENTAL FACTORS ON AGRICULTUAL PRODUCTIVITIY

Location: Plant Physiology and Genetics Research

Title: A Conceptual Model for Describing Processes of Crop Improvement in Database Structures

Authors
item Delacy, Ian - UOFQUEENSLAND, AUS
item Fox, P - ACIAR, CANBERRA, AUS
item Mclaren, Graham - CRIL, IRRI, MANILA, PHIL
item Trethowan, Richard - UOFSYNDEY, ISS, AUS
item White, Jeffrey

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 15, 2009
Publication Date: November 1, 2009
Citation: Delacy, I.H., Fox, P.N., Mclaren, G., Trethowan, R., White, J.W. (2009). A Conceptual Model for Describing Processes of Crop Improvement in Database Structures. Crop Science, 49:2100-2112.

Interpretive Summary: Plant breeding is key to increasing productivity and profitability of agriculture. Using a complex process of crossing, growing out new generations of plants, and selecting the best materials, breeders improve the productivity of crops and enhance the economic or nutritional value of the harvested products. However, rising costs and the need to deal with an increasing range of breeding objectives mean that breeders must manage their data as efficiently as possible. Furthermore, good data management is essential in managing legal restrictions on use of specific crop varieties, genes or even breeding methods. The International Crop Information System (ICIS) was developed to provide breeders and other researchers with a flexible data management system. The Genealogical Management System (GMS) of ICIS was designed to capture data describing any conceivable method that a plant breeder might use. The GMS recognizes three classes of methods used in breeding new varieties. Generative methods are those such as crossing or inducing mutations that are used to increase variation. Derivative methods usually involve selection, and maintenance methods are used to conserve the genetic makeup of a group of plants, such as in multiplications of seed stocks. Unlike systems that only track pedigrees, the model accommodates the complete selection history as well as novel methods for generating variability. Application of the model is illustrated with four crops; rice, wheat, maize, and potato. The International Rice Information System, a version of ICIS for rice breeders, currently holds about 2.6 million unique identifiers (for germplasm accessions, crosses, populations, and lines) and requires about 900 megabytes of storage space, which can easily be managed on a desktop personal computer. The ICIS GMS model thus appears suitable for widespread use in managing data on crop improvement. Use of ICIS should enhance the efficiency and security of plant breeding, ultimately benefitting producers and consumers through new crop varieties.

Technical Abstract: Rising research costs, broadening research goals, intellectual property rights, and other concerns have increased the need for robust approaches to manage data from crop improvement. In developing the International Crop Information System (ICIS), a flexible data model was developed to allow any conceivable plant breeding process to be recorded unambiguously in a relational database. This paper describes this model, which underlies the Genealogical Management System (GMS) of ICIS. The model recognizes three classes of methods by which genetic material is advanced. Generative methods are those such as crossing or mutagenesis that are used to increase variation. Derivative methods usually involve selection, and maintenance methods are used to conserve the genetic makeup of germplasm, such as in multiplications of seed stocks. Unlike systems that only track pedigrees, the model accommodates the complete selection history as well as novel methods for generating variability. Application of the model is illustrated with self-pollinating, outcrossing, and clonally propagated species. The ICIS GMS has been implemented for diverse species including rice (Oryza sativa L.), wheat (Triticum aestivum L.), maize (Zea mays L.), potato (Solanum tuberosum L.), common bean (Phaseolus vulgaris L.), and the novel oil crop lesquerella (Lesquerella fendleri). The International Rice Information System, an implementation of ICIS, currently holds about 2.6 million unique germplasm identifiers (for germplasm accessions, crosses, populations, and lines) and requires about 900 megabytes of storage space, which can easily be managed on a desktop personal computer. The ICIS GMS model thus appears suitable for widespread use in managing data on crop improvement.

Last Modified: 8/22/2014
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