The landscape of plant breeding has been fundamentally reshaped with the advent and subsequent advancements in software technology. Traditional plant breeding methodologies, while effective, were labor-intensive, error-prone, and time-consuming. The novel incorporation of software into the process has revolutionized breeding practices by automating complex processes, improving accuracy, and offering significant time savings.

Plant breeding, at its core, is the art and science of changing the traits of plants in order to produce desired characteristics. It has been practiced for over ten thousand years, ever since the transition of societies from hunter-gatherers to agriculturists. Breeding involves the manipulation of plant species with the intent to create hybrids that carry desirable characteristics of the parent plants, which may include disease resistance, yield, and drought tolerance, among others.

In the past, this process was heavily reliant on human expertise and meticulous record-keeping. With the advent of plant breeding software, these traditional methods have been significantly supplemented, if not outright replaced, with sophisticated algorithms and data management systems. Modern plant breeding software provide breeders with the tools to create, manage, and analyse all the data associated with their breeding programs. This may include pedigree information, phenotypic data, genotypic data, and genomic data, among others.

When we gaze into the future of plant breeding software, a few key trends and predictions begin to emerge.

• Firstly, the rise of predictive breeding powered by artificial intelligence (AI) and machine learning (ML) technologies is a trend that cannot be ignored. Predictive breeding uses statistical algorithms and machine-learning techniques to predict the potential outcome of different breeding combinations. This significantly reduces the need for trial-and-error approaches, thus saving time, labor, and resources. The field of AI and ML is rapidly advancing, and we can foresee an era where these technologies will be able to analyze vast amounts of data and predict outcomes with unprecedented accuracy.
• Secondly, the integration of genomics and bioinformatics into plant breeding software is a trend that is already underway and predicted to continue. Genomic selection, which uses molecular markers spread across the entire genome to predict breeding values, is an area of particular interest. This approach allows breeders to select parents based on their genomic breeding values rather than phenotypic traits alone, leading to improved accuracy and efficiency. The increasing affordability and availability of whole-genome sequencing will further drive the adoption of genomic selection in plant breeding.
• Thirdly, the incorporation of simulation modeling into plant breeding software is another emerging trend. Simulation modeling can predict how plants will respond to different environmental conditions and management practices, thus assisting breeders in making informed decisions.
• Lastly, the trend towards collaboration and open-source development is expected to accelerate. The sharing of data and software tools between researchers across the globe can foster innovation and accelerate the development of new varieties. This trend towards open-source development is already evident in the rise of platforms like GitHub, which allows developers to collaborate on software projects.

These trends indicate a promising future for plant breeding software. However, it is important to note that these advancements are not without their trade-offs. The increasing complexity of plant breeding software demands higher levels of technical expertise from breeders. Additionally, concerns regarding data security and privacy can arise with the increased sharing and digital storage of data.

Despite these challenges, the future of plant breeding software looks bright. The integration of advanced technologies like AI, ML, genomics, and simulation modeling, along with the trend towards open-source development, are poised to revolutionize the field of plant breeding. This is an exciting time to be involved in this field, as these advancements stand to fundamentally change the way we breed plants, leading to improved varieties and ultimately contributing to global food security.