Statistical Modeling of Epistasis and Linkage Decay using Logic Regression

Logic regression has been recognized as a tool that can identify and model non-additive genetic interactions using Boolean logic groups. Logic regression, TASSEL-GLM and SAS-GLM were compared for analytical precision using a previously characterized model system to identify the best genetic model explaining epistatic interaction for vernalization-sensitivity in barley. A genetic model containing two molecular markers identified in vernalization response in barley was selected using logic regression while both TASSEL-GLM and SAS-GLM included spurious associations in their models. The results also suggest the logic regression can be used to identify dominant/recessive relationships between epistatic alleles through its use of conjugate operators

Evaluation of Grape Powdery Mildew Forecasting Programs Grape (Vitis vinifera 'Chardonnay') Powdery Mildew (Uncinula necator)

Three forecasting programs for scheduling fungicide applications were selected for comparison with the standard Oregon phenology based program. The California (Gubler-Thomas, UC-Davis) program used leaf wetness and temperature early in the year to predict ascospore infection periods and only temperature during the summer to predict conidial infection periods. The New York (Gadoury) program was based on rainfall and temperature. The German (Oi Diag) program incorporated relative humidity along with temperature and rainfall. Treatments were arranged in a randomized complete block design in a block of 'Chardonnay' planted in 1985 on a 7 x 10 ft spacing. Vines were trained to a bilateral cordon with spur pruning. Shoot thinning occurred 12-13 May to provide uniform cane density. Each treatment was replicated on 3 sets of 5 vines. Treatments were applied using a handgun sprayer at 300 psi at a rate of 200 gal water/A for applications between 1 May (budbreak) and 13 May (6" growth). Treatments were applied using a hooded boom sprayer at 300 psi at a rate of 200 gal water/A for all applications after 13 May. Approximately 3.5 gal of spray suspension was applied per 15 vines (150 gal water/A) between 1 May and 13 May, 4.5 gal between 21 May and 28 Jul, and 5 gal (200 gal water/A) for the rest of the applications. Treatments were applied as required by the guidelines for each program. However, additional conditions for stopping programs at or just after verasion were incorporated as requested by Oregon growers. The standard program and the water control were applied on 13 May (6" shoots), 21 May (12" shoots), 2 Jun (prebloom, EL growth stage 17), 16 Jun (90% bloom), 1 Jul, 15 Jul (bunch closure), 22 Jul, 5 Aug, and 12 Aug (verasion). No Botrytis control measures, including leaf removal, were applied to test vines. All programs used one of two fimgicides, Thiolux DF at 3 lb/100 gal water or Rally at 2 oz/100 gal water for each application. Trap plants of 'Cabernet Sauvignon' were placed next to nontreated vines for 24 hour periods within the same block of grapes from 8 May to 3 Jul. After 24 hours of exposure, plants were transferred to a greenhouse several miles away for incubation under conditions favorable for powdery mildew development

Development of a grower-conducted inoculum detection assay for management of grape powdery mildew

Management of grape powdery mildew (Erysiphe necator) and other polycyclic diseases often relies on calendar-based pesticide application schedules that assume the presence of inoculum. An inexpensive, loop-mediated isothermal amplification (LAMP) assay was designed to quickly detect airborne inoculum of E. necator to determine when to initiate a fungicide application programme. Field efficacy was tested in 2010 and 2011 in several commercial and research vineyards in the Willamette Valley of Oregon from pre-bud break to v eraison. In each vineyard, three impaction spore traps were placed adjacent to the trunk. One trap was maintained and used by the grower to conduct the LAMP assay (G-LAMP) on-site and the other two traps were used for laboratory-conducted LAMP (L-LAMP) and quantitative PCR assay (qPCR). Using the qPCR as a gold standard, L-LAMP was comparable with qPCR in both years, and G-LAMP was comparable to qPCR in 2011. Latent class analysis indicated that qPCR had a true positive proportion of 98% in 2010 and 89% in 2011 and true negative proportion of 96% in 2010 and 64% in 2011. An average of 3 3 fewer fungicide applications were used when they were initiated based on spore detection relative to the grower standard practice. There were no significant differences in berry or leaf incidence between plots with fungicides initiated at detection or grower standard practice plots, suggesting that growers using LAMP to initiate fungicide applications can use fewer fungicide applications to manage powdery mildew compared to standard practices

The Infection and Impact of Azorhizobium Caulinodans ORS571 on Wheat (Triticum Aestivum L.)

Based on our previous study, cereal crop wheat (Triticum aestivum L.) could be infected by rhizobia Azorhizobium caulinodans ORS571, and form para-nodules with the induction of 2.4-dichlorophenoxyacetic acid, a common plant growth regulator. To enhance this infection and the potential agricultural application, we compared six different infection methods (Direct seed dip; Seed germination dip; Pruned-root dip; Foliar spray; Circum-soil dip; Seed dip and circum-soil dip) for achieving the high efficient infection of A. caulinodans into wheat plants by employing a green fluorescent protein (gfp)-labeled Azorhizobium caulinodans strain ORS571. With proper methods, copious rhizobia could enter the interior and promote the growth of wheat to the hilt. Circum-soil dip was proved to be the most efficient method, seed germination dip and pruned-root dip is the last recommended to infect wheat, seed germination dip and seed dip and circum-soil dip showed better effects on plant growth, pruned-root dip did not show too much effect on plant growth. This study laid the foundation for understanding the interaction between rhizobia and cereal crops and the growth-promoting function of rhizobia

Sensitivity of Disease Management Decision Aids to Temperature Input Errors Associated with Sampling Interval and Out-of-Canopy Sensor Placement

Many plant disease epidemic models, and the disease management decision aids developed from them, are created based on temperature or other weather conditions measured in or above the crop canopy at intervals of 15 or 30 min. Disease management decision aids, however, commonly are implemented based on hourly weather measurements made from sensors sited at a standard placement of 1.5 m above the ground or are estimated from off-site weather measurements. We investigated temperature measurement errors introduced when sampling interval was increased from 15 to 60 min, and when actual in-canopy conditions were represented by temperature measurements collected by standard-placement sensors (1.5 m above the ground, outside the canopy) in each of three crops (grass seed, grape, and hops) and assessed the impact of these errors on outcomes of decision aids for grass stem rust as well as grape and hops powdery mildews. Decreasing time resolution from 15 to 60 min resulted in statistically significant underestimates of daily maximum temperatures and overestimates of daily minimum temperatures that averaged 0.2 to 0.4 degrees C. Sensor location (in-canopy versus standard-placement) also had a statistically significant effect on measured temperature, and this effect was significantly less in grape or hops than in the grass seed crop. Effects of these temperature errors on performance of disease management decision aids were affected by magnitude of the errors as well as the type of decision aid. The grape and hops powdery mildew decision aids used rule-based indices, and the relatively small (+/- 0.8 degrees C) differences in temperature observed between in-canopy and standard placement sensors in these crops resulted in differences in rule outcomes when actual in-canopy temperatures were near a threshold for declaring that a rule had been met. However, there were only minor differences in the management decision (i.e., fungicide application interval). The decision aid for grass stem rust was a simulation model, for which temperature recording errors associated with location of the weather station resulted in incremental (not threshold) effects on the model of pathogen growth and plant infection probability. Simple algorithms were devised to correct the recorded temperatures or the computed infection probability to produce outcomes similar to those resulting from in-canopy temperature measurements. This study illustrates an example of evaluating (and, if necessary, correcting) temperature measurement errors from weather station sensors not located within the crop canopy, and provides an estimate of uncertainty in temperature measurements associated with location and sampling interval of weather station sensors.Keywords: Stem rust, Forecast, Ryegrass seed crops, Potato late blight, Model, Susceptibility, Perennial ryegrass, Washington, Information, RotKeywords: Stem rust, Forecast, Ryegrass seed crops, Potato late blight, Model, Susceptibility, Perennial ryegrass, Washington, Information, Ro