Citrus fruits, classified under the Rutaceae family and Citrus genus, are valued for their high nutritional content, attributed to their rich array of natural bioactive compounds. To ensure both quality and nutritional value, precise non-destructive testing methods are crucial. Among these, computer vision and spectroscopy technologies have emerged as key tools. This review examines the principles and applications of computer vision technologies—including traditional computer vision, hyperspectral, and multispectral imaging—as well as various spectroscopy techniques, such as infrared, Raman, fluorescence, terahertz, and nuclear magnetic resonance spectroscopy. Additionally, data fusion methods that integrate these technologies are discussed. The review explores innovative uses of these approaches in Citrus quality inspection and grading, damage detection, adulteration identification, and traceability assessment. Each technology offers distinct characteristics and advantages tailored to the specific testing requirements in Citrus production. Through data fusion, these technologies can be synergistically combined, enhancing the accuracy and depth of Citrus quality assessments. Future advancements in this field will likely focus on optimizing data fusion algorithms, selecting effective preprocessing and feature extraction techniques, and developing portable, on-site detection devices. These innovations will drive the Citrus industry toward increased intelligence and precision in quality control.

Nondestructive diagnostics of soluble sugar, total nitrogen and their ratio of tomato leaves in greenhouse by polarized spectra–hyperspectral data fusion

Biofloc technology (BFT) as an efficient aquaculture alternative is attracting attention for boosting biosecurity with minimal water exchange and reduced feed intake. BFT relies on applying organic carbon to maintain a high C/N ratio above 10, which allows heterotrophs to assimilate toxic nitrogen. A high percentage of carbon loss is thus generated from BFT. For this review, a thorough search of the relevant literature was conducted to gather valuable information on the optimization of carbon utilization. The keywords searched included ‘BFT’, ‘carbon use efficiency’, ‘carbon conversion’, ‘carbon retention’, ‘carbon emission’, ‘carbon loss’, and ‘carbon release’. The current review discusses the possible effects of various C/N ratios, carbon types, addition strategies, and technology integration with respect to the optimized carbon utilization in BFT. Given the extreme lack of accessible research, it was concluded that the carbon utilization in BFT is still in its initial research stage. Anyhow, this review sheds light on plausible approaches for boosted carbon utilization by adopting slow-release carbon, reducing carbon input, integrating with other technologies, and enhancing interactions between functional microbes within BFT, thereby contributing to sustainable aquaculture.

Non-destructive testing (NDT) methods are increasingly applied in modern agriculture to enable the rapid, efficient, and non-invasive evaluation of crops and agricultural products. Among these, polarization spectroscopy analysis (PSA) combines polarization information with spectral data to provide detailed insights into plant and soil properties. This review summarizes the principles and key parameters of polarimetry and highlights PSA applications, including crop health monitoring, pest and disease detection, chlorophyll and nutrient estimation, seed quality assessment, and soil moisture and pollution evaluation. PSA demonstrates advantages over conventional spectroscopy by revealing structural information and maintaining robustness in complex environments. Its ability to support precision agriculture through the real-time monitoring and early detection of stress factors underscores its potential for smart agricultural systems. Future efforts should focus on data fusion, model optimization, equipment miniaturization, and enhanced adaptability to fully realize PSA’s role in intelligent agriculture.

Non-destructive testing (NDT) methods are playing a crucial role in modern agriculture by providing efficient, rapid, and non-invasive means of evaluating agricultural materials. This shift from traditional, often destructive, testing methods is driven by the need for better quality control, improved food safety, and the demands of intelligent and precise agriculture Polarization spectroscopy analysis (PSA) has emerged as an advanced, non-destructive testing method of growing importance in agricultural engineering. By integrating polarization characteristics with spectral data, PSA enables the detailed analysis of various agricultural products and processes.This review provides a systematic overview of the principles and key parameters of polarimetry. Furthermore, it highlights a wide range of PSA applications in agricultural materials, such as crop health assessment, pest detection, chlorophyll estimation, and the evaluation of water, nitrogen, phosphorus, and potassium content. In addition, it sheds light on further applications, including non-destructive testing of seed health and agricultural product quality, soil moisture and pollution monitoring, underwater and nighttime environmental imaging, and integration with hyperspectral and multispectral technologies.Polarization spectroscopy is an analytical technology capable of revealing physical structural information unresolved by traditional spectroscopy, especially in complex environments where it demonstrates greater resistance to interference. With its ability to monitor plant nutrition, predict seed germination, assess fruit and vegetable quality, and detect early pests and diseases, this technology holds great promise for precision agriculture. Future efforts should optimize data fusion, build efficient models, miniaturize intelligent equipment, and enhance the real-time performance and adaptability of non-destructive testing to support smart agriculture..

Although chitosan (CS)- and essential oil (EO)-based packaging systems have been widely reviewed, a focused synthesis connecting nano-delivery design with interfacial regulation, film-network evolution, release behavior, and preservation performance in real food systems remains lacking. This review addresses that gap by examining CS-based nano-delivery systems for EOs in active food packaging, with an emphasis on how carrier design and multiscale organization govern functional performance. Major delivery strategies, including nanoemulsions, nanoparticles, nanogels, Pickering emulsions, nanofibrous systems, and nanocomposites, are discussed in relation to EO stabilization, dispersion uniformity, and controlled release. Their effects on film microstructure, mechanical and barrier properties, thermal stability, optical behavior, and antimicrobial and antioxidant activities are further evaluated alongside preservation outcomes in fruits, vegetables, dairy products, meat, and aquatic products. Particular attention is given to structure-function relationships across the carrier, interface, and film-network levels, and to the distinction between established active-packaging functions and emerging smart-packaging applications. Current challenges include EO compositional variability, limited cross-study comparability, sensory constraints, migration and regulatory concerns, and insufficiently scalable fabrication routes. Future work should prioritize mechanism-informed interfacial design, standardized evaluation frameworks, food-specific release-preservation correlations, and scalable green manufacturing.