By Denise Attaway
The humble huckleberry may never rival the soybean in the number of acres planted, but there’s no reason it and other specialty crops can’t have the same technological benefits as row crops do — such as big data.
The competitiveness and sustainability of the $36 billion specialty crop industry in the United States is threatened by declining land availability, labor shortages, pests, diseases, increasing costs, supply shortages and climate. To help the industry overcome these challenges and ensure an adequate food supply, two Clemson agriculture researchers have joined colleagues for a research initiative focused on expanding existing resources by providing easier access to big data.
Ksenija Gasic, horticulture professor, peach breeder and geneticist in the Clemson Plant and Environmental Department, and Trevor Rife, assistant professor of phenomics and crop improvement at the Pee Dee Research and Education Center, are leading the Clemson team. Rife’s group will work on improving the Field Book mobile app for field data collection and developing new tools that can be used to increase the speed at which specialty crops are improved. Gasic’s group will use those tools to collect data and to train breeders and allied scientists in using the tools and databases.
“Specialty crop data are being generated at exponential rates and these data are stored in a variety of locations,” Gasic said. “The challenge for plant breeders and scientists is to ensure adequate storage, access and timely utilization of this big data.”
OBJECTIVES AND OUTREACH
The project aims to meet the demand for accessible big data resources by expanding 25 databases for rosaceae, citrus, vaccinium and pulse crops. The Rosaceae family includes pome fruit trees (such as apple, pear and quince), stone fruit trees (such as peach, apricot, almond, plum, sweet and tart cherry) and some berries (such as strawberry, red and black raspberry). Citrus crops include oranges, lemons, limes, tangerines and grapefruits. Vaccinium plants include bilberries, blueberries, cranberries and huckleberries. Pulse crops include beans, lentils and peas.
By developing the necessary infrastructure to collect, organize and combine data from genomics, genetics and breeding, project members will be able to rapidly integrate this data into their research to generate and select new plant varieties with improved genetics, like disease resistance or cold tolerance. Development of these tools will be enhanced with input from project scientists as they receive the training needed to adopt these field data collection apps and crop-specific databases.
Data collected from this project will be uploaded to the Breeding Information Management System (BIMS) and will include details about the performance of different crop accessions in different environmental conditions. Clemson field data will be collected from the peach germplasm at the Musser Fruit Research Center. Using standardized tools to capture and store research data ensures that it can be easily processed, analyzed and retrieved for future projects.
“Scientists must be able to easily access all of the data for further analyses and utilization in translational research and routine breeding decisions,” Rife said.
Outreach and training to help ensure scientists and breeders know about and understand how to use the database tools also will be provided. This will involve delivering on-site and online training by experts on proper use of the BIMS, the Field Book app and other tools.
Information will be disseminated via social media, newsletters, tutorials, grower meetings, conference presentations and publications. Lessons learned and successes gained from this project will be used to encourage other specialty crop breeders and scientists to adopt similar database systems for their research.
Dorrie Main, professor of bioinformatics at Washington State University, is the lead researcher on this project. In addition to Gasic, Rife and Main, other researchers for this study are located at the University of Florida, Auburn University, the U.S. Department of Agriculture (USDA) Agricultural Research Service, the Cedar Lake Research Group and the University of Queensland. This research is supported by an almost $5.2 million grant from the USDA’s National Institute of Food and Agriculture.
Digital agriculture, or the use of new and advanced technologies to improve food production, is helping people in agriculture make informed decisions more quickly. Digital applications and platforms potentially can change the way knowledge is processed, communicated, accessed and used.
The use of these technologies generates large amounts of data, known as big data.
Gasic said benefits provided by this project will include the following:
- Support the acceleration and more efficient production of new cultivars for 25 specialty tree fruit, nut, berry and pulse crops
- Enable breeders to manage and analyze their data for making enhanced decisions
- Allow for more efficient development of new cultivars that require less labor to harvest, are more resistant to pests and diseases and are more resilient to climate change
Artificial intelligence will allow for driven performance prediction of selections. In addition, this project serves as a model of cyber-collaboration, efficient resource utilization and database sustainability. Other benefits include:
- Optimizing a return on investment of federally funded research data by making it available for reuse through incorporation in the databases and data modeling programs
- Providing researchers with advanced resources to identify and exploit genetic variants underlying key traits in target crops
- Providing support for conversion of valuable legacy specialty crop databases or efficient creation of new databases for orphan specialty crops with emerging database needs
Denise Attaway is a writer/editor for the College of Agriculture, Forestry and Life Sciences at Clemson University.