Core Viewpoint - The Guangdong Seed Industry Expo showcased over a hundred agricultural technology innovations, highlighting the province's commitment to driving industrial upgrades through technological advancements in agriculture [2][3][4]. Group 1: Agricultural Technology Innovations - The "Guangdong Agricultural Technology Innovation Achievements Exhibition" featured more than a hundred significant results, including advanced equipment and innovative technologies that demonstrate the deep integration of technological innovation and industrial development [3][4][5]. - Key innovations included a lychee-picking robot developed by South China Agricultural University, which can operate in all weather conditions, significantly reducing labor intensity and improving operational efficiency during the high-temperature harvesting season [10][11]. - The Guangdong Academy of Agricultural Sciences introduced a low-temperature dormancy preservation technology for lychees, achieving over 80% nutrient retention after one year of freezing [14][15]. Group 2: Focus Areas and Breakthroughs - Guangdong is focusing on nine key areas to tackle critical agricultural technology bottlenecks, including seed industry revitalization, disease prevention, smart equipment, value-added processing, land protection, and green low-carbon initiatives [19][20]. - Significant breakthroughs have been made in breeding new varieties of shrimp, rice, and peanuts, as well as establishing technical systems for preserving Lingnan fruits and preventing citrus greening disease [21][22]. Group 3: Smart Agriculture Trends - The trend towards smart and precise agriculture is evident, with the introduction of intelligent sensing and environmental control technologies for pig farming, optimizing feeding and environmental conditions through AI [30][31]. - In crop cultivation, mechanization and smart technologies are addressing traditional challenges, with the development of a series of agricultural machines covering the entire process from management to harvesting, applied over 111.2 million mu in the past three years [34][35]. Group 4: Industry Collaboration and Future Prospects - The exhibition showcased the collaborative efforts of 28 modern agricultural technology innovation teams and 20 award-winning agricultural technology promotion projects, reflecting Guangdong's vibrant practice of driving high-quality agricultural development through technology [27][28]. - Leading companies and research institutions, including Huawei and DJI, presented their advancements in smart agriculture, indicating a shift towards data-driven and intelligent agricultural practices that enhance productivity and sustainability [57][60].

Core Insights - The upgraded agricultural scientific discovery model has achieved significant enhancements in capabilities, transitioning agricultural biological breeding from "experience trial and error" to a new paradigm of "intelligent creation" [1][2] Group 1: Model Enhancements - The model's knowledge base has expanded from over 1 million to over 2 million full-text documents, providing a higher quality and more comprehensive foundation for agricultural scientific research [1] - The data coverage has increased from over 30 species to over 50 core species, with a total data volume exceeding 10 billion entries, establishing a solid data foundation for deep exploration of superior gene resources [1] - The platform integrates over 100 specialized analytical tools and predictive models, optimizing the autonomous invocation and orchestration processes of multi-agent systems [1] Group 2: Breeding and Management Capabilities - The performance of the full-process digital breeding module has been enhanced, supporting multi-dimensional gene function prediction and precise site design for targeted trait improvement [1] - The intelligent breeding capabilities have been extended to the planting management phase, adding functionalities for variety screening, growth assessment, and pest identification based on actual field production needs [1] - The upgraded model incorporates natural language interaction capabilities, enabling "zero-code" natural language analysis for gene mining, trait prediction, and program design [2] Group 3: Efficiency Improvements - Initial estimates suggest that the efficiency of researchers in key R&D processes can be improved by approximately 10 times [2] - The model supports panoramic R&D program intelligent planning, allowing for the completion of over 1,000 steps of calculations and design simulations in about 24 hours, with efficiency improvements in related processes reaching over 90% [2]