New research combines multiscale experiments and machine learning to predict storage life of Moso bamboo (IMAGE)
Caption
Hydrothermal Aging of Moso Bamboo: Degradation Mechanisms and Storage Life Prediction
The fluctuations of storage temperature and humidity detrimentally affect the bamboo quality and longevity, making it crucial to investigate. Herein, we explored the physical and mechanical properties of moso bamboo (Phyllostachys edulis) subjected to 100-day moist heat cycling aging (MHCA-1: transitioning from low-temperature/high-humidity to high-temperature/low-humidity; MHCA-2: transitioning from low-temperature/low-humidity to high-temperature/high-humidity; CHT: 25 °C-constant temperature and 60% relative humidity) alongside a control group. Employing a multiscale characterization and Random Forest (RF) modeling, we evaluated the impacts of temperature and humidity fluctuations on the bamboo quality, and the influence mechanism of storage conditions on its physical and mechanical properties were elucidated. Results indicated that elevated temperature and humidity led to remarkable fluctuation in bamboo moisture (from –20.36% to 32.99%), weight gain (from –32.69% to 6.19%), and dimensional expansion (from –5.37% to 2.38%). Conversely, high-temperature and low-humidity drying conditions resulted in moisture loss and dimensional shrinkage. Total color difference (TCD) of bamboo cortex followed the order: MHCA-2 (7.46) < CHT (12.24) < MHCA-1 (20.10) < control (22.63). The TCD of bamboo pith positively was related with storage temperature. Periodic moist heat aging induced the permanent deformation in bamboo, reducing its elastic modulus by 30.05%–43.79%. Under moist heat aging conditions, the characteristic hemicellulose functional groups, including hydroxyl (–OH), carbonyl (C=O), ether (C–O–C), and aromatic C=C moieties exhibited remarkable structural modifications, i.e., peak weakening, shifting, or morphological alterations in Fourier transform infrared (FT-IR) spectra. Additionally, these conditions elevated the thermal decomposition onset temperature of cellulose while decreasing its peak intensity. Overall, the RF modeling approach demonstrated a high accuracy in predicting bamboo behavior under varying moisture-heat conditions. It improved bamboo storage and recycling by supporting sorting and grading with reliable long-term data.
Credit
International Centre for Bamboo and Rattan, Key Laboratory of NFGA/Beijing for Bamboo & Rattan Science and Technology, Beijing 100102, China
Usage Restrictions
N/A
License
Original content