Xing Yingying, Wang Xiukang
Key Laboratory of Applied Ecology of Loess Plateau, College of Life Science, Yan'an University, Yan'an, Shaanxi, China.
Front Plant Sci. 2024 Dec 6;15:1444560. doi: 10.3389/fpls.2024.1444560. eCollection 2024.
Precision water and fertilizer application technologies have emerged as crucial innovations in sustainable agriculture, addressing the pressing need to enhance crop yield and quality while optimizing resource use and minimizing environmental impacts. This review systematically explores the latest advancements in precision water and fertilizer application technologies. It examines the integration of advanced sensors, remote sensing, and machine learning algorithms in precision agriculture, assessing their roles in optimizing irrigation and nutrient management. The study evaluates various precision techniques, including micro-irrigation systems, variable rate technology (VRT), and predictive modeling, along with their implementation in diverse agricultural settings. Furthermore, the review addresses the challenges posed by soil environmental heterogeneity and emphasizes the necessity for a scientific index system to guide precise applications. Advanced irrigation methods, such as subsurface drip irrigation and micro-sprinkling, improve water-use efficiency and reduce salinity levels, while precision fertilization techniques optimize nutrient uptake and minimize leaching. The integration of machine learning and remote sensing facilitates real-time monitoring and adaptive management, resulting in increased resource use efficiency and reduced environmental pollution. However, the effectiveness of these technologies is contingent upon addressing soil heterogeneity and developing standardized application indices. This review highlights the novel combination of advanced sensing technologies and data analytics in precision agriculture, enabling targeted interventions tailored to specific field conditions. It underscores the importance of integrating soil microbial community dynamics and biochemical indicators with precision management practices to enhance soil fertility and crop performance. Furthermore, the development of predictive models and time series analysis tools represents a significant advancement in anticipating and responding to changing environmental conditions. Precision water and fertilizer application technologies offer substantial benefits for sustainable agricultural practices by improving crop yields, enhancing resource efficiency, and mitigating environmental impacts. The strategic integration of these technologies with tailored agricultural practices and robust monitoring systems is essential for optimizing nutrient cycling and maintaining soil health. Addressing existing challenges through interdisciplinary research and collaborative efforts will further advance the implementation of precision agriculture, contributing to long-term soil sustainability and global food security.
精准水肥一体化技术已成为可持续农业中的关键创新,满足了在优化资源利用和减少环境影响的同时提高作物产量和品质的迫切需求。本综述系统地探讨了精准水肥一体化技术的最新进展。它研究了先进传感器、遥感和机器学习算法在精准农业中的整合,评估了它们在优化灌溉和养分管理中的作用。该研究评估了各种精准技术,包括微灌系统、变量施肥技术(VRT)和预测模型,以及它们在不同农业环境中的应用。此外,综述还讨论了土壤环境异质性带来的挑战,并强调了建立科学指标体系以指导精准应用的必要性。先进的灌溉方法,如地下滴灌和微喷灌,提高了水分利用效率并降低了盐分水平,而精准施肥技术则优化了养分吸收并减少了淋溶。机器学习和遥感的整合促进了实时监测和自适应管理,提高了资源利用效率并减少了环境污染。然而,这些技术的有效性取决于解决土壤异质性问题和制定标准化的应用指标。本综述强调了精准农业中先进传感技术和数据分析的新颖结合,能够根据特定田间条件进行有针对性的干预。它强调了将土壤微生物群落动态和生化指标与精准管理实践相结合以提高土壤肥力和作物性能的重要性。此外,预测模型和时间序列分析工具的开发是在预测和应对不断变化的环境条件方面的重大进步。精准水肥一体化技术通过提高作物产量、增强资源效率和减轻环境影响,为可持续农业实践带来了巨大益处。将这些技术与量身定制的农业实践和强大的监测系统进行战略整合,对于优化养分循环和维持土壤健康至关重要。通过跨学科研究和合作努力应对现有挑战,将进一步推动精准农业的实施,为长期土壤可持续性和全球粮食安全做出贡献。