Submitted to: United States Japan Natural Resources Protein Panel
Publication Type: Proceedings
Publication Acceptance Date: 9/15/2007
Publication Date: 10/1/2007
Citation: Pinson, S.R., Osborn, G.S., Thomas, A.E., Mcclung, A.M. 2007. Resistance to rice grain fissuring: Improving breeding selection techniques and identifying physical, chemical, and genetic factors underlying fissure resistance. United States Japan Natural Resources Protein Panel 36:227-231.
Technical Abstract: Kernel fissuring is one of the leading causes of reduced milling yield. Any reduction in fissuring results in direct increases in yield and profit for both producers and millers. Breeders are anxious to incorporate fissure resistance into new varieties, but success has been hampered by a lack of appropriate early-generation evaluation techniques. At the initiation of this series of studies, little was yet known about varietal differences in fissure resistance. We knew that the variety ‘Cypress’ was more fissure resistant than most U.S. varieties, and it was widely considered that the most definitive method for detecting fissure resistance was to harvest sequentially drier grain samples from each field plot and analyze them for loss of milling quality over time or over sequentially lower harvest moistures. While this sequential-harvest method was effective at identifying Cypress as fissure resistant, it is too labor intensive and requires too large a plot size and seed supply to be used as a breeding selection tool. Our research objectives were to a) test a grain-attribute model already used by agricultural engineers for predicting fissuring rates under various post-harvest conditions for its ability to also model observed varietal differences for field fissuring, b) focus on key grain attributes identified by the model to identify a method that required less labor, cost, and seed for identifying fissure resistance (FR) among numerous genotypic lines, and c) use that improved evaluation method to map QTL underlying rice FR. We first used the sequential-harvest method to identify varieties exhibiting small as well as large differences in FR to create a “measuring stick” with which to test the grain attribute model and various FR evaluation techniques. Using four varieties within the “measuring stick”, FR predictions obtained with the post-harvest grain-attribute model were found to fit with field observations. The model revealed that grain shape differences small enough to not impact market class were found capable of causing statistically significant differences in FR. It was also determined that Cypress’ FR was predominantly due to low hull diffusivity keeping moisture away from the kernel, while the FR exhibited by the variety ‘Saber’ was attributed instead to endosperm characteristics. Laboratory exposure of paddy rice to controlled levels of humidity was found to be a suitable small-sample method for detecting Cypress-type hull-related FR, and has since been used to identify FR-QTLs within several rice gene-mapping populations. As the model predicted, many FR-QTL appear to be related to grain shape, but some FR-QTL appear shape-independent.