Bayer had seven patents in big data during Q4 2023. Bayer AG’s patents in Q4 2023 focus on methods for identifying progenies for plant breeding, determining soil properties using soil spectrum data, and predicting the performance of pathogen clearance processes. These methods involve utilizing historical data, hyperspectral sensors, and computer algorithms to optimize breeding pipelines, generate crop prescriptions, and improve pathogen clearance efficiency. GlobalData’s report on Bayer gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Smarter leaders trust GlobalData

Report-cover

Data Insights Bayer AG - Company Profile

Buy the Report

Data Insights

The gold standard of business intelligence.

Find out more

Bayer grant share with big data as a theme is 57% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Methods and systems for identifying progenies for use in plant breeding (Patent ID: US20230386609A1)

The patent filed by Bayer AG discloses methods for identifying progenies for plant breeding using a computer-implemented approach. The method involves accessing a data structure containing phenotypic data of progenies, determining prediction scores based on historical data, selecting progenies based on these scores, and identifying a set of progenies for further breeding phases. The system includes a data storage device, a computing device, and a breeding pipeline for commercialization, with the computing device generating prediction models and selecting progenies based on various factors like expected performance, risk of failure, genetic diversity, and traits.

The method further involves training prediction models based on historical phenotypic data, selecting progenies based on specific thresholds, and identifying progenies based on factors like genetic diversity, expected performance, and risk of failure. The system also allows for user input to identify the pool of progenies and considers factors like probability of success, deviation from desired profiles, and trait integration in the selection process. The non-transitory computer-readable storage media includes executable instructions for accessing data structures, determining prediction scores, selecting progenies, identifying sets of progenies based on various factors, and directing them to the next phase of the breeding pipeline. The instructions also cover training prediction models, selecting progenies based on thresholds, and identifying progenies based on specific algorithms and factors like deviation from profiles, risk, and trait integration.

To know more about GlobalData’s detailed insights on Bayer, buy the report here.

Data Insights

From

The gold standard of business intelligence.

Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.

GlobalData

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.