Improving Plant Research Information Management: A Success Story

The following article was written by a breeder and published in Top Seeds’ internal magazine, sharing a story about the successful implementation of PhenomeOne software in Top Seeds company and how it supports the research and development of their varieties.

Top Seeds International is a global vegetable seed company specializing in the research, production, and marketing of innovative, high-quality hybrid varieties.

Phenome Networks is a software company specializing in state-of-the-art solutions for plant breeding and variety testing. Leading seed companies use the company’s software as a core system for all research data. It is designed to support all the breeding and variety testing processes and improve cardinal decisions and product life cycle.

“PhenomeOne breeding software plays a central role in top seed R&D and PD processes, but for most employees, there is no direct interaction with this tool. The following article I will explain what Phenome is, our history with it, and how it is serving us these days.

Breeding software – why do we need it?

Imagine you are a Breeder or a Product Developer. The information you manage includes genotypic data (markers, pedigree), phenotypic data (field observations: shape, color, weight, and more), and multiple fields are managed simultaneously. Now, you need to combine all this information to efficiently develop a product. So, how can you do it?

Going back 10-15 years, most small-medium seed companies used spreadsheets for plant breeding management; this limited the ability to facilitate data management, which became much more detailed with the progress of genomic and digital tools available today. Spreadsheets also limit key breeding features such as keeping pedigree records and tracking inheriting patterns; they also enable only data without photos. Breeding software supports germplasm development and pedigree tracking, breeding fields design and planning, manage selections, crosses, observations, and more. Users can handle their data in a user-friendly and coherent way, grant and restrict other users from accessing it based on the business needs, analyze it, and more.

Who is Phenome?

Founded in 2008 by Prof. Dani Zamir (Hebrew University) and Dr. Yaniv Semel (CEO), the company specializes in plant breeding and variety testing software solutions. The software developed by Phenome is now being used by more than a hundred companies worldwide across the seed industry, food and beverage industry, chemical and crop protection, and oil and paper industry. Phenome Networks developed a software solution, an enterprise platform, well-designed to support high-scale operations done by global seed companies across many sites by multiple users and numerous crops.

A Little history

Back in 2014, when top seeds work volume was snowballing, and with it, the amount of data collected and managed, we realized that we maxed out the manageable capacity of spreadsheets.  We came to the understanding that to stay competitive, we must embrace the use of available technology in the form of breeding software. In March 2016, after one year of examining and testing the available products in the market, top seeds decided to implement Phenome’s software as its primary breeding management platform, and in so doing, it became Phenome’s 18^th customer. Over the years, we kept broadening our use of Phenome’s software, including during the product development process. The start was a bit bumpy, but Top Seeds and Phenome teams continuously collaborated (and still do) to overcome any obstacle together.

Recent development

A few years back, when we started implementing Phenome’s platform, we had a limited vision of how we should operate it between R&D and PD, leading these departments to work separately inside the same system while losing the advantages of data sharing and processing. We solved it during the past year by merging both departments’ activities into one virtual space where data collection is managed. We first mapped both departments’ needs and limitations and identified critical failure points. We then continued by modifying the technical language to be clear for all users, explaining work protocols, and delivering them to all our users, followed by technical support as required. As a result, all our users now work in the same virtual space, making our data flow faster, more accurately, with better transparency, improving our efficiency, our internal communication, and helpings us to achieve better results.”