The nondestructive testing of agricultural products has always been a key technology for the modernization of agriculture and food. By applying a sinusoidal voltage (current) excitation signal of variable frequency, the relationship between the amplitude, frequency and phase of the response signal is obtained, and the measured response function in a certain frequency range is obtained, constructing the correlation between impedance spectroscopy and matter properties. Electrical impedance spectroscopy (EIS) is a widely used method for the nondestructive characterization of agricultural products, and its applications in the agricultural field has attracted increasing attention. This paper summarizes the research of electrical impedance spectroscopy (EIS) in the detection of grain quality, fruit and vegetable quality, meat quality and food quality from 2005 to 2022. The potential and development direction of electrical impedance spectroscopy in the nondestructive testing of agricultural product quality are prospected, which provides a reference for scientific researchers who applied electrical impedance spectroscopy in agricultural product quality detection.

Grain drying technology is a core process for ensuring food quality, extending storage life, and improving processing adaptability. With the continuous growth of global food demand and the increasing requirements for food quality and energy efficiency, traditional drying technologies face multiple challenges. This paper reviews six major grain drying technologies, comprising hot air drying, microwave drying, infrared drying, freeze drying, vacuum drying, and solar drying. It provides an in-depth discussion of the working principles, advantages, and limitations of each technology, and analyzes their performance in practical applications. In response to challenges such as high energy consumption, uneven drying, and quality loss during the drying process, the paper also explores the research progress of several hybrid drying systems, such as microwave–hot air drying combined systems and solar–infrared drying systems. Although these emerging technologies show significant potential in improving drying efficiency, energy saving, and maintaining food quality, their high costs, scalability, and process stability still limit large-scale applications. Therefore, future research should focus on reducing energy consumption, improving drying precision, and optimizing drying system integration, particularly by introducing intelligent control systems. This would maximize the preservation of food quality while improving the system’s economic efficiency and sustainability, promoting innovation in food production and processing technologies, and further advancing global food security and sustainable agricultural development.

Pesticides directly pollute the environment and food, eventually being absorbed into the human body. Their residues are highly toxic and pose serious health risks. Chromatography and gas liquid chromatography tandem mass spectrometry are widely employed for pesticide residue detection. However, these methods are often labor-intensive due to complex pretreatment processes, time-consuming procedures, and high energy consumption. Surface-enhanced Raman spectroscopy is regarded as a new detection method for agricultural residues due to its advantages of high sensitivity, excellent specificity, comprehensive fingerprint information and nondestructive to samples. This technique enables efficient detection of trace pesticide residues in both liquid and solid samples via simple extraction. In this review, the classification of SERS substrates, peak attribution of Raman reporter molecules, label-free detection of single and mixed pesticide residues, and the application of labeled detection have been comprehensively reviewed. The study aims to provide a valuable reference for pesticide residue detection, particularly for the simultaneous detection of multiple pesticide residues. Additionally, the review explores the challenges and future prospects of SERS technology in pesticide residue detection, including the difficulties of achieving synchronous detection, advancements in intelligent algorithm development, and the construction of portable on-site detection platforms. These innovations are designed to simplify the detection process and offer insights into selecting optimal sensing methods for on-site detection of multiple pesticide residues.

Food contaminants, including harmful microbes, pesticide residues, heavy metals and illegal additives, pose significant public health risks. While traditional detection methods are effective, they are often slow and require complex equipment, which limits their application in real-time monitoring and rapid response. Surface-enhanced Raman scattering (SERS) technology has gained widespread use in related research due to its hypersensitivity, non-destructibility and molecular fingerprinting capabilities. In recent years, Au-Ag bimetallic nanoparticles (Au-Ag BNPs) have emerged as novel SERS substrates, accelerating advancements in SERS detection technology. Au-Ag BNPs can be classified into Au-Ag alloys, Au-Ag core–shells and Au-Ag aggregates, among which the Au-Ag core–shell structure is more widely applied. This review discusses the types, synthesis methods and practical applications of Au-Ag BNPs in food contaminants. The study aims to provide valuable insights into the development of new Au-Ag BNPs and their effective use in detecting common food contaminants. Additionally, this paper explores the challenges and future prospects of SERS technology based on Au-Ag BNPs for pollutant detection, including the development of functional integrated substrates, advancements in intelligent algorithms and the creation of portable on-site detection platforms. These innovations are designed to streamline the detection process and offer guidance in selecting optimal sensing methods for the on-site detection of specific pollutants.

The inherent complexity of cellulose, hemicellulose, and lignin contributes to the recalcitrance of lignocellulosic biomass, resulting in a low conversion efficiency and high cost of bioethanol conversion. Pretreatment methods that disrupt the plant cell structure of lignocellulose, such as straw, can significantly enhance the conversion efficiency. In this study, we utilized an acid-assisted mechanocatalytic depolymerization technique to pretreat rice straw, and the results demonstrated a significant disruption of the cellulose structure of the straw. Compared to the untreated straw, the particle size of pretreated straw reduced from 279 μm to 11.8 μm, the crystallinity of cellulose decreased from 43.05% to 22.71%, the specific surface area increased by 177%, and the surface oxygen-to-carbon ratio (O/C) ratio was enhanced by 75%. The changes in microstructure enabled the pretreated straw to achieve a total sugar yield of over 95% within 12 h of enzymatic hydrolysis, significantly superior to the 36.24% yield from untreated straw, the 45.20% yield from acid impregnated straw, and the 73.25% yield from ball milled straw. Consequently, acid-assisted mechanocatalytic depolymerization emerges as a highly effective pretreatment strategy to enhance both the enzymatic hydrolysis and the overall conversion efficiency of rice straw.

The terahertz waves are electromagnetic waves with frequencies ranging from 0.1 to 10 THz, exhibiting characteristics of both microwave and infrared, including fingerprint characteristics, coherence, and safety. Due to the weak interactions among most organic macromolecules in substances, the vibrational modes of molecular frameworks, as well as dipole rotation and vibration transitions, often correspond to the terahertz spectral region. Consequently, there has been growing interest in applying terahertz technology within the food industry. This review summarizes the fundamental principles of terahertz spectroscopy for substance detection and highlights recent advances and applications in food analysis. Key applications include harmful contaminant detection, component analysis, quality assessment, and adulteration identification. Additionally, this review discusses current challenges in applying terahertz spectroscopy to food analysis, such as strong water absorption, matrix interference, and the lack of comprehensive spectral databases. Finally, the paper outlines future prospects, including the development of lightweight and cost-effective terahertz sources and detectors for on-site analysis, as well as the integration of terahertz spectroscopy with other modern detection technologies to enhance analytical performance. This work aims to serve as a reference for further research and development of terahertz spectroscopy in the food sector.