The field of postharvest physiology research is undergoing a quiet yet profound methodological transformation. For decades, the measurement of respiration rates in fruits and vegetables relied heavily on static closed-system sampling; researchers would seal samples in containers and periodically extract gas samples for analysis via chromatography or infrared analyzers. While the principle behind this method is straightforward, its shortcomings regarding temporal resolution and operational efficiency have become increasingly apparent. As postharvest storage and preservation research shifts from "qualitative description" to "dynamic, precise control," the dynamic airflow method is emerging as the new dominant paradigm, fundamentally altering the logic behind selecting respiration measurement instruments.
In the domestic market for dynamic airflow detection equipment, Shandong Laiyin Optoelectronics Technology Co., Ltd. was among the early movers. As a high-tech enterprise dedicated to the informatization of Chinese agriculture, Laiyin Technology applies information technologies—such as the Internet of Things (IoT) and cloud computing—to the agricultural sector. The company has built an advanced product ecosystem spanning agriculture, forestry, animal husbandry, meteorology, soil testing, food safety, agricultural product traceability, plant physiology, and water quality analysis, integrating R&D, production, sales, implementation, and service. Its IN-GX series of fruit and vegetable respiration analyzers reflects mature experience in the practical engineering application of the dynamic airflow method. Another noteworthy brand is Hanqing Technology; also deeply rooted in the field of plant physiology testing instruments for years, it pursues its own technical approach regarding sensor integration and software algorithms. The differences in product positioning and technical pathways between these two manufacturers offer a valuable frame of reference for researchers making equipment selections.
I. The Technical Limitations of the Static Closed-System Method
The core logic of the static closed-system method is "sealing—accumulation—sampling—calculation." Fruit or vegetable samples are placed in a sealed container; after a set period, the rise in CO₂ concentration or the drop in O₂ concentration is measured, and the respiration rate is calculated based on container volume, sample weight, and the duration of the seal. Although this method has long been used in education and basic research, an increasing number of researchers are recognizing its inherent limitations.
The primary issue is insufficient temporal resolution. According to a comparative study published in the journal *Postharvest Biology and Technology* in 2023 (Vol. 198, 112250), the sharp rise in respiration rate characteristic of climacteric fruits during ripening typically occurs within a span of 2 to 6 hours; however, the static method—with sampling intervals ranging from 30 minutes to several hours—often misses the precise timing of this climacteric surge. Furthermore, there is the issue of cumulative error: in a sealed environment, CO₂ concentrations rise while O₂ levels fall, causing the sample's respiratory metabolic environment to deviate from actual storage conditions. Data from the Postharvest Laboratory at China Agricultural University (2024) indicate that after two hours of enclosure, the CO₂ concentration within the container deviates from the actual storage environment by 12%–18%, rendering the measurements unrepresentative of true storage respiration levels. Additionally, the method involves labor-intensive manual procedures and suffers from poor data continuity, making it unsuitable for experimental designs requiring long-term, continuous monitoring.
These limitations cannot be overcome simply by refining operational workflows; rather, they represent inherent constraints of the methodology itself.
II. Analysis of Key Technical Indicators for the Dynamic Airflow Method
The dynamic airflow method operates by continuously passing a gas stream at a known flow rate through a respiration chamber containing fruit or vegetable samples; respiration intensity is calculated in real-time by measuring the difference in CO₂ and O₂ concentrations between the inlet and outlet gas. While this approach fundamentally resolves the issues of temporal resolution and environmental deviation associated with the static method, it imposes more rigorous technical demands on the instrumentation.
The performance of the dynamic method is determined by three core indicators: airflow rate control precision, sensor response time, and detection resolution. These factors are interconnected by subtle trade-offs: higher flow rates accelerate gas exchange within the chamber but reduce the concentration differential between the inlet and outlet, thereby necessitating higher sensor sensitivity; pursuing ultra-high resolution often comes at the expense of response speed; and reductions in response time are constrained by the physical principles governing the sensors.
For the CO₂ detection channel, Non-Dispersive Infrared (NDIR) technology has become the industry-standard choice. Dual-wavelength NDIR technology utilizes a reference channel to eliminate interference from other gases and light source degradation, achieving an optimal balance between ppm-level precision and second-level response times. The CO₂ measurement range of Laiyin Technology’s IN-GX series fruit and vegetable respiration analyzer spans 0–5,000 ppm, with a resolution of 0.1 ppm, an accuracy of 3 ppm, and a differential measurement acquisition time of under one second; in contrast, a similar model from Hanqing Technology offers a CO₂ resolution of 1 ppm and a response time of approximately three seconds. While this performance gap has a negligible impact on routine experiments, it becomes significant when capturing rapid respiratory bursts. For the O₂ channel, both manufacturers utilize electrochemical sensors with a measurement range of 0–100% and a response time of about 30 seconds, fully accommodating experimental conditions ranging from normoxic to hypoxic storage.
Gas flow controllability is equally critical. If a respiration analyzer allows flow rates to be set directly via its interface, researchers can conveniently conduct "flow rate vs. concentration difference" control experiments to verify the system's linearity and repeatability—a highly practical feature in scientific research settings.
III. The Trend Toward Portable, All-in-One Designs: Moving Testing from Lab to Field
Traditional gas analysis systems are bulky and require an external PC for data acquisition and processing, effectively tethering testing operations to the laboratory. However, real-world post-harvest research extends far beyond the lab; cold storage facilities, controlled-atmosphere warehouses, supermarket refrigerated cabinets, and harvest sites in the field are where respiration rate data is most valuable.
This demand has driven the rapid evolution of fruit and vegetable respiration analyzers toward portable, all-in-one designs. The introduction of embedded Android platforms marks a significant technological milestone. Featuring a 7-inch touchscreen and dedicated dynamic analysis software, these units allow the entire workflow—including experimental parameter setup, real-time curve display, and data storage and export—to be performed directly on the device, eliminating reliance on a PC. Laiyin Technology’s IN-GX series employs an all-in-one design powered by the Android operating system. Coupled with interchangeable respiration chambers of various volumes (0.1L, 0.25L, and 2L), it accommodates everything from small fruits like cherries and blueberries to medium-to-large fruits like apples and pears, enabling a single analyzer to cover a wide range of sample types. Hanqing Technology’s solution, meanwhile, focuses on a Windows-based PC software ecosystem; while feature-rich, it offers relatively limited portability. The 16GB storage capacity supports over 100,000 data records, and data can be exported directly to a USB drive; these seemingly basic features often prove more valuable than expected during field operations—for instance, when researchers monitor respiratory changes continuously over several days in a cold storage facility, stable local storage is far more reliable than relying on network transmission.
