Performing Department
(N/A)
Non Technical Summary
Southern blight, caused by Athelia rolfsii, is a significant yield limiting pathogen in warmproduction areas circumglobally. The overarching goal of this project is to improve southernblight management in annual crops by developing a risk forecasting tool that can be used bygrowers to optimize integrated management strategies. This will be achieved by 1) determininggrowth thresholds for A. rolfsii in a laboratory setting, 2) developing a model to predict the riskof southern blight in tomato and potato, 3) and implementation of the model for integratedmanagement of southern blight in annual rotations. This work will be accomplished throughlaboratory, computational, and field-based research in collaboration with growers and farmadvisors in the Sacramento and Central Valleys. The primary AFRI priority area addressed byimproving southern blight management in annual cropping systems is plant health productionand products. Additionally, the project is relevant to agriculture systems and technology throughthe development of a mobile application and web platform to assist farmers with themanagement decision making. Furthermore, project objectives will impact agriculture economicsand environmental aspects of AFRI priority areas through cost matrices of management practicesand optimized sprays based on disease risks. In order to better predict the onset of southernblight and to improve management, we propose to develop a model, based on fungal biology andweather conditions, to predict southern blight risk. Additionally, we plan to assess diseaseamelioration and cost effectiveness when integrating strategic crop rotations with model-basedfungicide regimens.
Animal Health Component
50%
Research Effort Categories
Basic
20%
Applied
50%
Developmental
30%
Goals / Objectives
The overarching goal of this project is to improve southern blight management in annual crops by developing a risk forecasting tool that can be used by growers to optimize integrated management strategies.Objective 1- Determine growth thresholds for A. rolfsii in a laboratory setting: Towards this objective, I will (1a) conduct growth assays of sclerotia at varied temperatures from multiple crops and locations; and (1b) assess the effect of high temperatures on A. rolfsii growth.Objective 2- Develop a model to predict the risk for southern blight in tomato and potato: Towards this objective, I will (2a) use data on weather and soil conditions and disease development in order to build a predictive model for southern blightdevelopment; and (2b) I will validate the model at research sites and in grower fields.Objective 3: Implement the model for integrated management of southern blight in annual rotations: In order for the model to be used as a management tool by growers, I will (3a) evaluate whether sprays applied based on model recommendations can reduce disease, sclerotia accumulation, and costs compared with calendar sprays; and (3b) develop a web platform and/or mobile app that can be used by growers as a tool for management decisions.
Project Methods
Objective 1- Determine growth thresholds for A. rolfsii in a laboratory setting: Towards this objective, I will (1a) conduct growth assays of sclerotia at varied temperatures from multiple crops and locations; and (1b) assess the effect of high temperatures on A. rolfsii growth.(1a) Characterize temperature response curves for sclerotia germination across crops and locations.Approach: Currently, the Swett Lab has 20 isolates that have been maintained in pure culture including isolates from the northern (Sutter and Yolo) to mid (Solano, Contra Costa, San Joaquin) Central Valley from diverse annual crops. I will germinate sclerotia exposed to temperature gradients in the laboratory, on sterile soil in petri dishes, and evaluate germination over time. I will also collect sclerotia-infested field soil and evaluate response to this same gradient using the methanol method. These data will be used to compute upper and lower air temperature thresholds as described in Clarkson et al. 2007. The number of sclerotia germinating in each replicate will be converted to a percentage, and mean values will be plotted against time. Data will be analyzed using a simple accumulated thermal time response, to determine whether A. rolfsii sclerotia exhibit a temperature accumulation response.(1b) Evaluate the effect of high temperatures on A. rolfsii germination and growth.Approach: Additional assays will expose sclerotia to temperatures at a finer temperature gradient between 95 and 104°F and will evaluate the ability for pre-germinated sclerotia to continue to grow at high temperatures in order to characterize conditions and outcomes of suppression. I will assess the growth area of A. rolfsii isolates using the imaging software, Image J. The combined data from 1a and 1b will be used to determine temperature thresholds.Objective 2- Develop a model to predict the risk for southern blight in tomato and potato: Towards this objective, I will (2a) use data on weather and soil conditions and disease development in order to build a predictive model for southern blight development; and (2b) I will validate the model at research sites and in grower fields.(2a) Identify biologically relevant variables for the prediction of southern blight in a statistical model using weather and soil data. Approach: Field sites will be located in both regions with long histories of southern blight and regions with new outbreaks of southern blight. Field trials will be established with collaborators in a mixture of grower and University of California research sites in Kern County and Yolo County. Replicated potato field trials will have plots treated with fungicides (formulation based on results of fungicide efficacy trials conducted by the Swett Lab in 2019) and untreated plots in order to assess the impact of fungicides on southern blight risk with calendar-based sprays (Obj. 3). Plot level sensors will be implemented in order to measure biologically relevant parameters including soil temperature, EC and moisture from the first 12 cm of soil (the depth from which sclerotia can germinate), ambient air temperature, soil moisture via a volumetric water content reflectometer probe, and wind speed.Additionally, temperature thresholds calculated from laboratory and field experiments, can be used to create a variable for the length of time, in hours, when temperatures were within this optimal temperature interval for sclerotia germination. Sclerotia loads will be monitored at the beginning and end of the growing season by sampling soil and comparing initial versus final sclerotia numbers using the methanol method. Additionally, we will scout fields for stem and tuber rot developmentwithin research plots on a fortnightly basis starting after the first week with a high of 85°C in tomatoes and potatoes.Disease incidence and severity will be used to calculate a classical disease index, and yield will be collected at the end of the season. Southern blight will be assessed on a diseased, cull potato weight per yield basis in order to understand the yield impact of southern blight in affected potato fields.(2b) Validate the predictive ability of the model at research sites and in grower's fields. Approach: For validation in annual cropping systems collection of sclerotia before and at the end of the growing season will occur in addition to scouting at 10-20 tomato grower fields, in a zig-zag pattern. Scouting will occur through fruit set and growth to assess disease with the potential to impact yield. Since southern blight symptoms in potato occur after burn down in potato fields, and it is not possible to destructively harvest in grower's fields, validation for potatoes will occur using the same plots used for model development, by partitioning the data into a "test set" that can be used for validation after model development, and data will be collected from rotation trials (described in the next objective), as it is optimal to validate trials over large areas and outside of locations where the model was developed. Test data will only be used for validation in order to avoid over-fitting of the model. To test the hypothesis that predictive modeling can enable fungicide application prior to full canopy closure, I will also collect canopy density data using NDVI.Objective 3: Implement the model for integrated management of southern blight in annual rotations: In order for the model to be used as a management tool by growers, I will (3a) evaluate whether sprays applied based on model recommendations can reduce disease, sclerotia accumulation, and costs compared with calendar sprays; and (3b) develop a web platform and mobile app that can be used by growers as a tool for management decisions.(3a) Trials will evaluate the effect of rotation and sprays based on model recommendations to reduce disease, inoculum, and result in cost savings. Approach: In the summer of 2020, sweet potato, potato, tomato, and onions will be planted and soil will be sampled for the presence of sclerotia in the beginning and end of the field season. As previously mentioned, potato plots will be sampled for disease symptoms for model development. Each rotation will have eight treated and untreated, replicated plots (using a fungicide labeled for the cropping system). In 2021, potatoes will be grown on all plots, with half (four) of the plots per rotation and spray regimen, receiving calendar based sprays in 2020, at burndown, and the other four per rotation and spray regimen receiving model based sprays, based on sensors.Applications of fungicides using model risk assessments will be made based on predicted moderate and high conditions in the three days after risk prediction, using Daily Risk Values (DRVs). Daily index values (DIVs) for parameters base on daily means of environmental parameters that are found to be important based on the model can be multiplied by each other in order to determine a DRV. Additionally, I will calculate the costs involved with spraying based on model predictions versus calendar sprays, relative to yield losses in the treatments in order to determine whether a cost savings is incurred by model-based sprays.(3b) Disseminate the risk of developing southern blight as predicted by the model, using a mobile application and web platform, for growers to make management decisions. Approach: Risk can be described on a per field basis using GPS coordinates via a webpage. The webpagewill be created in collaboration with an intern in 2023. Additionally, growers will be able to opt for email or text alerts based on when the model calculates a "high" risk level based on previously determined thresholds.