College of Agriculture, Forestry and Life Sciences; Public Service and Agriculture

Clemson researchers help provide easier access to specialty crop big data


Musser Fruit Research Center peach trees in bloom.
Clemson field data will be collected from peach germplasm at the Musser Fruit Research Center.
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Specialty crops may never rival row crops in the number of acres planted, but there’s no reason they can’t use the same technological advances – such as big data.

In the United States, the specialty crop industry is valued at $36 billion. The competitiveness and sustainability of this industry is currently threatened by declining land availability, labor shortages, pests, diseases, increasing costs, supply shortages and climate change. To help the industry overcome these challenges and ensure an adequate food supply, two Clemson University agriculture researchers have joined colleagues on a research initiative focused on expanding existing resources by providing easier access to “big data.”

Ksenija Gasic
Ksenija Gasic

Ksenija Gasic, horticulture professor and peach breeder and geneticist in the Clemson Plant and Environmental Sciences 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 application 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 these tools to collect data, as well as train breeders and allied scientists how to use the tools and databases.

“Specialty crop data are being generated at exponential rates and 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.”

The project aims to meet the demand for accessible big data resources by expanding 25 databases for Rosaceae, citrus, vaccinium and pulse crops. The Rosacea family includes pome fruit trees such as apple, pear and quince, stone fruit trees such as peach, apricot, almond, plum, sweet and tart cherry, as well as some berries such as strawberry and 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, such as disease resistance or cold tolerance. Development of these tools will be enhanced with input from project scientists as they receive 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. BIMS is a database system used by breeders to store, manage and analyze data. Clemson field data will be collected from peach germplasm at the Musser Fruit Research Center. Using standardized tools to capture and store research data ensures that it can easily processed, analyzed and retrieved for future projects.

Trevor Rife
Trevor Rife

“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, Washington State University, is 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 United States Department of Agriculture 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 United States Department of Agriculture’s National Institute of Food and Agriculture (NIFA).

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 change the way knowledge is processed, communicated, accessed and used. The use of these technologies generates large amounts of data, or big data, that can be used to improve plant breeding research outcomes.

Gasic said benefits provided by this project will support the acceleration and more efficient production of new cultivars for 25 specialty tree fruit, nut, berry and pulse crops. It also will enable breeders to manage and analyze their data for making enhanced decisions. In addition, it will allow for more efficient development of new cultivars that require less labor and are more resistant to pests and diseases, as well as cultivars that are more resilient to climate change.


The researchers say this project serves as a model of cyber-collaboration, efficient resource utilization and database sustainability. Other benefits include optimizing a return in investment of federally-funded research data by making them available for re-use 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, as well as providing support for conversion of valuable legacy specialty crop databases or efficient creation of new databases for orphan specialty crops with emerging database needs.

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