Kar Debashish, Dhal Sambandh Bhusan
Texas A&M AgriLife Research, College Station, TX, 77843, USA.
Department of Analytical Chemistry, Directorate of Energy, Environment, Science and Technology (EES&T), US Department of Energy, Idaho National Laboratory, Idaho Falls, ID, 83415, USA.
Environ Monit Assess. 2025 Feb 13;197(3):283. doi: 10.1007/s10661-025-13650-1.
Ensuring global food security in the face of growing population, climate change, and resource limitations is a critical challenge. Hyperspectral imaging (HSI), particularly when combined with drone technology, offers innovative solutions to enhance agricultural productivity and food quality by providing detailed, real-time data on crop health, disease detection, water and nutrient management, and post-harvest quality control. This review highlights the applications of drone-based HSI in precision agriculture, where it enables early detection of crop stress, accurate yield prediction, and soil health assessment. In post-harvest management, HSI is utilized to monitor food freshness and ripeness and detect potential contaminants, improving food safety and reducing waste. While the benefits of HSI are significant, challenges such as managing large volumes of data, translating spectral information into actionable insights, and ensuring cost-effective access for smallholder farmers remain barriers to its widespread adoption. Looking forward, future directions include advancements in miniaturized sensors, integration with Internet of Things (IoT) devices and satellite data for comprehensive agricultural monitoring, and expanding HSI applications to precision animal sciences. Collaboration among researchers, policymakers, and industry will be crucial to scaling the impact of HSI on global food systems, ensuring sustainable and equitable access to technology.
面对人口增长、气候变化和资源限制，确保全球粮食安全是一项严峻挑战。高光谱成像（HSI），尤其是与无人机技术相结合时，通过提供有关作物健康、病害检测、水分和养分管理以及收获后质量控制的详细实时数据，为提高农业生产力和粮食质量提供了创新解决方案。本综述重点介绍了基于无人机的高光谱成像在精准农业中的应用，它能够早期检测作物胁迫、准确预测产量以及评估土壤健康状况。在收获后管理中，高光谱成像用于监测食品的新鲜度和成熟度，并检测潜在污染物，从而提高食品安全并减少浪费。虽然高光谱成像的益处显著，但诸如管理大量数据、将光谱信息转化为可操作的见解以及确保小农户能够以成本效益方式获取等挑战，仍然是其广泛应用的障碍。展望未来，未来的发展方向包括小型化传感器的进步、与物联网（IoT）设备和卫星数据集成以进行全面农业监测，以及将高光谱成像应用扩展到精准动物科学领域。研究人员、政策制定者和行业之间的合作对于扩大高光谱成像对全球粮食系统的影响、确保可持续且公平地获取技术至关重要。
