中国农业大学学报2024，Vol.29Issue(8)：179-189,11.DOI:10.11841/j.issn.1007-4333.2024.08.15
基于NIRS的农业废弃物堆肥检测研究进展
Research progress on NIRS-based detection of agricultural waste composting
摘要
Abstract
In order to gain an in-depth and systematic understanding of the research advances and current applications of near-infrared spectroscopy(NIRS)in the study of agricultural waste composting,a literature search was conducted based on the Web of Science core database and the CNKI database.'Near-infrared spectroscopy','agricultural waste','composting'and'aerobic fermentation'were used as keywords.A total of 58 relevant literature articles were screened through this search.Subsequently,a synthesis and summary of existing research work were undertaken,which focused on three aspects of composting fundamental characteristic detection,process monitoring and quality assessment.The results are as follows:1)To improve the accuracy of models in detecting basic composting features,it's important to increase the number of samples,identify relevant spectral bands,and adapt different algorithms;2)Effective real-time monitoring of the composting process using NIRS requires refining universal models and improving hardware to ensure greater sensitivity and reliability;3)Further improvements in the NIRS evaluation system for composting can be achieved through methods like transfer learning,predicting multiple characteristics simultaneously,and grading quality.These contribute to better accuracy and reliability in assessments.Looking ahead,the integration of NIRS with emerging technologies such as machine learning,deep learning,computer vision and hyperspectral imaging is expected to create new opportunities for data-intensive scientific exploration in agriculture and provide practical guidance for on-site monitoring and quality control in agricultural waste composting.关键词
近红外光谱技术/农业废弃物/堆肥/过程监测/质量评估Key words
near-infrared spectroscopy/agricultural waste/compost/process monitoring/quality assessment分类
农业科技引用本文复制引用
骆立,孙绘骐,史苏安,张红美,杨增玲,韩鲁佳..基于NIRS的农业废弃物堆肥检测研究进展[J].中国农业大学学报,2024,29(8):179-189,11.基金项目
国家重点研发计划(2022YFD2002103) （2022YFD2002103）
国家现代农业产业技术体系资助(CARS36) （CARS36）
教育部"创新团队发展技术"项目(IRT1293) （IRT1293）
