Location: Peanut and Small Grains Research Unit
Project Number: 3070-30400-001-001-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 5, 2025
End Date: Sep 30, 2027
Objective:
The cooperator will address the following objectives: (1) Assess effects on sorghum grain yield of whorl worm infestation in sorghum fields; (2) Determine the effects of chinch bug feeding on sorghum plant growth of lines and varieties of grain sorghum under greenhouse conditions; and (3) Develop and test a smart phone App to implement economically effective sequential sampling for sorghum headworm in grain sorghum for the Southern and Central Plains states of Texas, Oklahoma and Kansas.
Approach:
For objective 1, plots will be established in sorghum fields within which response and predictor variables pertaining to injury and grain yield will be measured. A 50 x 50 m plot will be established in each field. Within the plot 2 x 2 m subplots and will be established and sampled once each week for whorl worm plant injury by selecting and examining six sorghum plants from within each subplot. Sorghum plant growth stage, the percentage of leaf area destroyed by whorl worm and the presence of injury to the developing grain head or growing point within the whorl will be measured. When grain heads have matured grain heads will be harvested in each subplot, individually threshed and seeds weighed and counted.
For objective 2, first a laboratory rearing method will be established for chinchbug, then a combination of choice and no-choice experiments will be used to evaluate sorghum entries for resistance to chinchbug feeding. All experiments for this study will be conducted in a greenhouse.
For objective 3, an iOS App for implementing HW sequential sampling methodology previously developed by NC Elliott and collaborators and previously published in peer reviewed journals will be constructed in collaboration with the Oklahoma State University and its App Center. The App will have capability to determine the economic threshold for HW from an estimate of the number of sorghum heads per acre, sorghum grain value, and control cost; and will also account for the size category of HW in the field (medium, large, or mixed). Users will input the number of HW per head for sorghum plants sampled, and the app will calculate sampling results on the fly and generate a ‘treat/no-treat’ decision when the upper or lower sequential sampling stop line is crossed. The App will be constructed and tested. Methods for validating sequential sampling methods will involve comparing decisions derived from sequential sampling with the App to actual mean numbers of HW per head derived from large (ca. 72 head) samples from fields. When this process is repeated across numerous fields error rates will be compared with expected error rates, and if not acceptable, they will be reformulated to achieve correct rates. We will test whether the sequential sampling method as it is implemented in the iOS App correctly classifies HW population intensity as above or below the economic threshold, and that error rates are as specified in the sequential sampling methodology and its implementation in the App. We estimate that sampling approximately 50 sorghum fields in this manner will provide enough information for accurate validation. If bias exists it will be corrected in developing a revised sequential sampling technique. If revision to methodology and/or the App is required, it will be accomplished, and testing will be repeated. There are no contingencies that we expect to hamper success of this research because the sequential sampling technique has been developed and tested. Furthermore, we have previously developed Apps for implementing sequential sampling techniques for other insect pests of small grains. Therefore, developing, testing, and refining the apps should be achieved.