Limin Dai

Low organic carbon utilization efficiency is a core bottleneck restricting the application of biofloc technology (BFT) in intensive aquaculture, accompanied by limited total nitrogen removal, excessive biofloc accumulation, and underutilized chemical energy in organic wastes. To address this issue, this study develops a novel biofloc technology–microbial fuel cell (BFT-MFC) coupled system that exploits surplus carbon sources in BFT as electron donors for bioelectricity generation while synergistically enhancing water purification performance. Compared with a conventional standalone BFT system, the coupled system was systematically evaluated in terms of water quality regulation, biofloc control and electricity generation performance. Results showed that the BFT-MFC system maintained relatively stable dissolved oxygen, pH, and temperature throughout the operation period. The ammonia nitrogen concentration remained relatively low in the BFT-MFC system, although a transient increase to approximately 0.35 mg/L occurred around day 20 before subsequently declining, and total nitrogen fluctuated within 4.29–12.87 mg/L, with substantially less accumulation than that observed in the BFT system, in contrast to the control group, where TN continuously rose to a peak of 23.55 mg/L. Total organic carbon was stabilized within a narrower range of 150–245 mg/L, compared with the wide fluctuation of 129.6–360 mg/L in the single BFT system. Additionally, the coupled system exhibited lower net biofloc accumulation based on floc-volume measurements, while maintaining effective water-quality regulation, and the integrated MFC delivered a maximum output voltage of 295.9 mV and a peak power density of 1716.8 mW m⁻². Overall, the BFT-MFC coupled system integrates wastewater purification, biofloc regulation and energy recovery into a single unit, offering a promising sustainable strategy for industrial recirculating aquaculture.

This paper presents a comprehensive review on near-infrared (NIR) spectroscopy applied in food analysis, systematically elaborating its core principles, widespread industrial applications, advanced chemometric strategies, and cutting-edge technological progress. NIR spectroscopy (760–2500 nm), characterized by rapid, non-destructive detection and minimal sample preparation, has been widely implemented in quality evaluation and safety monitoring of grains, meat, fruits and vegetables, dairy, fermented products, tea, coffee, and other processed foods, realizing quantitative analysis of nutrients, freshness assessment, texture prediction, adulteration identification, origin tracing, and rapid preliminary screening of toxin/pesticide residues. A series of chemometric methods, including spectral preprocessing (SNV, MSC, S-G smoothing), feature extraction, and variable selection (CARS, PSO-CMW, ICPA), as well as linear/nonlinear modeling algorithms (PLS, SVM, BP-ANN, fuzzy clustering) significantly boost the accuracy and robustness of spectral analysis. Meanwhile, portable NIR devices and online monitoring systems promote on-site and real-time detection in food supply chains. Despite existing challenges such as calibration transfer, matrix interference, and model generalization, innovations like multimodal data fusion, deep learning integration, and intelligent algorithm optimization offer effective solutions. This review not only summarizes the latest research advances of NIR technology in the food field but also emphasizes its significant advantages as a rapid, non-destructive complementary tool to traditional destructive detection methods, providing theoretical support and technical reference for accelerating the industrial translation and standardized application of NIR spectroscopy, and ultimately safeguarding global food quality and safety.

Biofloc technology (BFT), traditionally centered on feed supplementation and water purification in aquaculture, harbors untapped multifunctional potential as a sustainable resource management platform. This review systematically explores beyond conventional applications. BFT leverages microbial consortia to drive resource recovery, yielding bioactive compounds with antibacterial/antioxidant properties, microbial proteins for efficient feed production, and algae biomass for nutrient recycling and bioenergy. In environmental remediation, its porous microbial aggregates remove microplastics and heavy metals through integrated physical, chemical, and biological mechanisms, addressing critical aquatic pollution challenges. Agri-aquatic integration systems create symbiotic loops where nutrient-rich aquaculture effluents fertilize plant cultures, while plants act as natural filters to stabilize water quality, reducing freshwater dependence and enhancing resource efficiency. Emerging applications, including pigment extraction for ornamental fish and the anaerobic fermentation of biofloc waste into organic amendments, further demonstrate its alignment with circular economy principles. While technical advancements highlight its capacity to balance productivity and ecological stewardship, challenges in large-scale optimization, long-term system stability, and economic viability necessitate interdisciplinary research. By shifting focus to its underexplored functionalities, this review positions BFT as a transformative technology capable of addressing interconnected global challenges in food security, pollution mitigation, and sustainable resource use, offering a scalable framework for the future of aquaculture and beyond.

Although biofloc technology (BFT) currently offers advantages such as improving aquaculture water quality, providing natural bait for cultured animals, and reducing pests and diseases, single BFT systems face technical bottlenecks, including the complex regulation of the carbon–nitrogen ratio, accumulation of suspended substances, and acidification of the bottom sludge. Therefore, constructing a composite system with complementary functions through technology integration, such as with aquaponics, biofilm technology, integrated multi-trophic aquaculture systems (IMTAs), and recirculating aquaculture systems (RASs), has become the key path to breaking through industrialization barriers. This paper systematically reviews the action mechanisms, synergistic effects, and challenges of the four mainstream integration models incorporating BFT, providing theoretical support for the environmental–economic balance of intensive aquaculture.

Globally, the proportion of the consumption of fruits in the human diet shows an increasing trend. However, fruits may incur significant losses during the post-harvest storage and transportation process due to metabolic activities and mechanical damage. Post-harvest coating technology has been proven to be an effective means of reducing quality loss, and it offers the advantages of being environmentally friendly, energy-efficient, and free of chemical residues. This article begins with an introduction to the three main mechanisms of coating preservation, including physical barrier effects, physiological metabolism regulation, and antibacterial and antioxidant effects. Secondly, this paper comprehensively reviews the latest progress of coating application technology in the field of fruit preservation, and summarizes the development of coating application technology in recent years, which is divided into two categories: traditional technology and fiber coating formation technology. Among these, the spraying method in traditional technology and microfluidic spinning technology in fiber coating formation technology are emphasized. This information will help to further develop coating application techniques to improve post-harvest fruit preservation.

In order to improve the utilization efficiency of corn seeds and meet the demand of single-seed seeding technology in agriculture, this study was conducted to explore the effect of freezing damage detection on the endosperm and embryo sides of single corn seeds, based on hyperspectral imaging combined with a feature fusion algorithm and a machine learning method. First, hyperspectral image data of the endosperm and embryo sides of three freezing damage categories of corn seeds were collected, and the average spectra of the endosperm part and embryo part were obtained by threshold segmentation. Then, the spectral data were preprocessed (none, SNV, and 5-3 smoothing), and the feature wavelengths were extracted using the feature wavelength extraction algorithm (SPA and 2DCOS). The modeling accuracy results based on the hyperspectral data of the endosperm and embryo sides at the full waveband and feature wavelength (including feature wavelength fusion) were compared and analyzed. In the endosperm side’s freezing damage identification, the SNV+SVM model obtained the highest accuracies of 92.9% and 90.0% with the training set and testing set, based on the full-waveband data. The SNV+SPA-2DCOS+SVM model, based on the feature wavelengths, obtained the highest accuracies of 92.9% and 91.2% with the training set and testing set, respectively. In terms of the embryo side’s freezing damage identification, the results on the embryo side were better than those on the endosperm side. The 5-3 smoothing+LDA model, based on the full-waveband data, achieved the highest accuracy results of 97.7% and 95.9% with the training and testing sets. In the meantime, the none+SPA-2DCOS+LDA model, based on the feature wavelengths, achieved the same highest accuracy results with the training and testing sets. When the fusion algorithm consisting of SPA and 2D-COS was used, the model’s performance on the endosperm side was better than that of the full-waveband analysis with only 19 feature wavelengths, while the recognition effect on embryo side could be achieved with only 15 feature wavelengths. These results provide a theoretical basis for constructing a multi-spectral detection system for the rapid and nondestructive identification of frozen corn seeds.

Postharvest preservation of fruits is one of the key issues in the current agriculture and food processing industry. Surface coating treatment, a promising technology for postharvest fruit preservation, has gathered significant attention due to its ability to reduce water loss, regulate gas exchange, and inhibit respiration, thereby achieving postharvest fruit preservation. Among them, chitosan-based coating has a wide application prospect due to its superior film-forming capability, high biosecurity, wide range of sources, etc. This review summarizes the structural features, physicochemical properties, modification strategies, and preservation mechanisms of chitosan-based coatings, focusing on their applications in postharvest fruit storage. Unlike prior works, it highlights advanced modifications (e.g., nanocomposite, multifunctional grafting) that enhance antimicrobial activity, mechanical strength, and environmental adaptability. Challenges in fruit preservation—such as microbial resistance and stability—are analyzed, with solutions proposed via material innovation. The discussion on industrial scalability emphasizes chitosan’s biodegradability, cost-effectiveness, and alignment with sustainable agriculture, while addressing technical bottlenecks. This work bridges fundamental research and practical use, advancing chitosan-based coatings toward greener, safer, and scalable postharvest solutions.

In this paper, the feasibility of identifying freezing damage on the endosperm side and embryo side of single corn seeds was studied by combining hyperspectral imaging technology and the deep convolutional neural network (DCNN) method. Firstly, hyperspectral image data of the endosperm and embryo side of three freezing-damage categories of corn seeds were collected, and the average spectra of the endosperm part and embryo part were obtained with the range of 450–979 nm. After the spectral data were pre-processed by non-pretreatment or standard normal variation (SNV) pretreatment, a support vector machine (SVM) and a DCNN model were established for freezing-damage identification. Finally, multiple evaluation indexes (including accuracy, sensitivity, specificity, and precision) were used to comprehensively evaluate the performance of the SVM and DCNN models in the whole waveband. The results showed that the DCNN model obtained better performance in accuracy, sensitivity, specificity, and accuracy. The values of each category, especially for the category-2 and category-3 testing sets of the SVM model, were lower than those of the DCNN model. The classification results of the embryo-side corn seeds were better than those of the endosperm side. The accuracy value of the testing set of the DCNN model on the embryo side was higher than 96.7%, while the accuracy value of the DCNN model on the endosperm side was lower than 93.8%. The specificity values of the SVM and DCNN models were both higher than 94%. In addition, the sensitivity and precision values of the category-2 testing set of the embryo-side DCNN model increased by at least 2.8% and 4.8%. The sensitivity value of the category-3 testing set of the DCNN model was improved by at least 8.2% and 4.4%. These results of the embryo side of the corn seed showed significant improvement in the training and testing set. This study proved that the DCNN model can accurately and quickly identify single freezing-damage corn seeds, which provided a theoretical basis for constructing an end-to-end recognition and classification model of frozen corn seeds.

The quality assurance of corn seeds is of utmost significance in all stages of production, storage, circulation, and breeding. However, the traditional detection method has some disadvantages, such as high labor intensity, strong subjectivity, low efficiency, cumbersome operation, etc. In view of this, it is of great significance to study more advanced detection methods. In this paper, the application of near-infrared spectroscopy and its imaging technology in the quality detection of corn seeds was reviewed. Firstly, the principles of these two technologies were introduced, and their components, data acquisition, and processing methods, as well as portability, were compared and discussed. Then, the application of these methods to the main quality of corn seeds (including variety and purity, vigor, internal components, mycotoxins, and other qualities such as frost damage, hardness, and maturity, etc.) was reviewed. Breakthroughs and innovations have been made in detection methods, spectral preprocessing methods and recognition algorithms. The significance of corn quality characteristics and the function of the applied algorithm were emphasized. Finally, the challenges and future research direction of spectral and its imaging technology was proposed, aiming to further enhance the accuracy, reliability, and practicability of the detection technology. With the rapid development of spectral and its imaging technology, the detection methods of corn quality are also advancing with the times. This is not just for corn, but more and more crops can be accurately detected by these technologies. It will become an important means of agricultural production inspection in the future.

The application of heat pump systems in agriculture, especially within livestock farms, has attracted considerable attention due to their potential for energy efficiency and improved environmental sustainability. Many studies have explored using heat pumps to optimize the indoor environments of barns. This review offers a comprehensive overview and analysis of the current applications of heat pump systems in livestock barn environmental control. Initially, it outlines the fundamental principle of heat pumps and the various types of heat pumps. Then, the technical advantages of the heat pump systems in regulating indoor temperature and humidity of livestock facilities, improving energy efficiency, and reducing environmental impacts are evaluated. Heat pump systems outperform conventional heating and cooling methods in terms of energy utilization and cost-effectiveness, and they positively contribute to reducing environmental pollution. However, some barriers obstruct the widespread adoption of heat pump systems, including policy and regulatory, economic and financial, and technological and infrastructure, as well as public perception and awareness. Future research is recommended to address these barriers. Thus, more heat pump systems in livestock farms could be extensively applied.