Company Filing History:
Years Active: 2021-2025
Title: Barry Loyd Knight: Innovator in Agricultural Technology
Introduction
Barry Loyd Knight is a prominent inventor based in Cordova, TN (US), known for his significant contributions to agricultural technology. With a total of eight patents to his name, Knight has focused on leveraging machine learning to enhance agricultural practices. His innovative solutions aim to optimize crop production and improve the efficiency of agricultural operations.
Latest Patents
Knight's latest patents include a groundbreaking crop prediction system that utilizes machine learning to predict crop production and identify optimal farming operations. This system is designed to access geographic and agronomic information, allowing growers to make informed decisions based on weather conditions and soil composition. Another notable patent involves an online agricultural system that manages interactions between entities to facilitate transactions and transportation of crop products. This system analyzes historical and environmental data to determine market prices and optimize transactions for users.
Career Highlights
Throughout his career, Barry Loyd Knight has made significant strides in the field of agricultural technology. His work at Indigo Ag, Inc. has positioned him as a leader in the integration of machine learning within agriculture. Knight's innovative approaches have not only advanced agricultural practices but have also contributed to the sustainability of farming operations.
Collaborations
Knight has collaborated with notable colleagues, including David Patrick Perry and Geoffrey Von Maltzahn. These partnerships have fostered a collaborative environment that encourages innovation and the development of cutting-edge agricultural solutions.
Conclusion
Barry Loyd Knight's contributions to agricultural technology through his patents and collaborative efforts have made a lasting impact on the industry. His work continues to inspire advancements in farming practices and the application of machine learning in agriculture.