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Abstract
Sour skin of onion (Allium cepa L.), caused by the soil-borne bacterium Burkholderia cepacia, (ex Burkholder 1950) Yabuuchi et al. 1993, is a devastating disease of onion and is responsible for post-harvest losses annually. Current management strategies are to avoid contaminated fields and adjust planting dates to avoid high temperatures during harvest. In addition, harvesting onions at optimum maturity, field-curing a minimum of 48 h, sorting and grading to remove infected onions and storing onions under proper conditions are also used to manage sour skin. However, these strategies have not adequately reduced losses when conditions are favorable for disease. Other strategies, such as chemical control and resistance, are not viable options for controlling sour skin. Furthermore, infected onions may go undetected during the sorting and grading process. Such bulbs have the potential of infecting healthy onions in storage. Innovative and integrated management practices aimed at preventing disease in the field and improving early detection are needed to effectively manage sour skin of onion. This research evaluated management practices focused on prevention of sour skin in the field by rotating or double-cropping with crops that had a negative impact on B. cepacia populations in vitro. Under controlled conditions in the laboratory, populations of B. cepacia declined in the soil as a result of direct contact with root exudates of pearl millet (Pennisetum glaucum (L.) R. Brown). Initially, double-cropping onion with pearl millet reduced sour skin incidence and severity in field trials. However, by the fourth year of continuous double-cropping of onion with pearl millet, the beneficial effects of reducing sour skin were virtually non-existent. Since the crops used in the rotation and double-cropping treatments deplete different soil nutrients, the role that mineral nutrition plays on plant disease development also was investigated. In 2012 and 2014, field-grown onion bulbs and soils were evaluated for mineral composition. Data were analyzed with stepwise and maximum R2 improvement regression using sour skin (incidence or severity) as the dependent variable. In 2012, a tissue model (P=0.0002; adj. R2=0.51) was developed that included ratios of copper: iron, zinc: iron and sulfur: aluminum as well as manganese and nitrogen as independent variables. Likewise, a soil model (P = 0.00006 adj. R2 = 0.57) that included the ratios of zinc: iron, iron: manganese and manganese: zinc as well as copper and potassium as independent variables were also developed to predict sour skin severity. Due to a total crop loss in 2013, onions purchased from grocery stores were inoculated, incubated, graded for disease severity, and used for mineral analysis. The grocery store model (P=0.00001; adj. R2=0.43) also contained a ratio of copper: iron, and the minerals aluminum, potassium, nitrogen, and sulfur as independent variables, all of which were components of the models developed in 2012. In 2014, a tissue model (P=0.00002; adj. R2=0.34) based on natural infections in the field contained the ratios of copper: iron, sodium: iron, manganese: zinc, and the elements calcium, manganese, and nitrogen as the independent variables. The elements copper, iron, manganese, and zinc consistently occurred in nine different sour skin models developed over a 3 year period. These elements are cofactors of three superoxide dismutases (SODs) in plants that play a key role in reactive oxygen species (ROS) detoxification and systemic acquired resistance (SAR). Preliminary results suggest that the effects these elements have on sour skin is by ultimately affecting SODs and the SAR pathway. In addition to field studies, investigations on early disease detection were conducted to improve current sorting and grading processes. Improvements are needed for the onion industry to eliminate onions with internal infections from going in to storage or entering the marketplace. Targeting the detection of volatile organic compounds (VOCs) using zNose technology was evaluated. When numbers of infected onions ranged from 10-50% and the volume of the container was < 2 L, an increase in the level of VOCs could be detected, but qualitative differences could not be discerned due to the inability of zNose technology to distinguish closely related compounds. In addition, when the level of infected onions was decreased to 1% and the storage area was increased to 11,000 L, neither increased levels of VOCs nor a distinct profile could be detected. However, VOCs such as dipropyldisulfide and propyl-1-propenyldisulfide, unique to onions with sour skin, were identified using GCMS. These compounds could be used as targets for early disease detection.