College of Mechanical and Electrical Engineering, Shandong Intelligent Engineering Laboratory of Agricultural Equipment, Shandong Agricultural University, Tai'an 271018, China.
Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China.
Int J Food Microbiol. 2024 May 2;416:110661. doi: 10.1016/j.ijfoodmicro.2024.110661. Epub 2024 Mar 6.
Aspergillus flavus and its toxic metabolites-aflatoxins infect and contaminate maize kernels, posing a threat to grain safety and human health. Due to the complexity of microbial growth and metabolic processes, dynamic mechanisms among fungal growth, nutrient depletion of maize kernels and aflatoxin production is still unclear. In this study, visible/near infrared (Vis/NIR) hyperspectral imaging (HSI) combined with the scanning electron microscope (SEM) was used to elucidate the critical organismal interaction at kernel (macro-) and microscopic levels. As kernel damage is the main entrance for fungal invasion, maize kernels with gradually aggravated damages from intact to pierced to halved kernels with A. flavus were cultured for 0-120 h. The spectral fingerprints of the A. flavus-maize kernel complex over time were analyzed with principal components analysis (PCA) of hyperspectral images, where the pseudo-color score maps and the loading plots of the first three PCs were used to investigate the dynamic process of fungal infection and to capture the subtle changes in the complex with different hardness of the maize matrix. The dynamic growth process of A. flavus and the interactions of fungus-maize complexes were explained on a microscopic level using SEM. Specifically, fungus morphology, e.g., hyphae, conidia, and conidiophore (stipe) was accurately captured on the microscopic level, and the interaction process between A. flavus and nutrient loss from the maize kernel tissues (i.e., embryo, and endosperm) was described. Furthermore, the growth stage discrimination models based on PLSDA with the results of CCR = 100 %, CCR = 97 %, CCR = 93 %, and the prediction models of AFB based on PLSR with satisfactory performance (R = 0.96, R = 0.95, R = 0.93 and RPD = 3.58) were both achieved. In conclusion, the results from both macro-level (Vis/NIR-HSI) and micro-level (SEM) assessments revealed the dynamic organismal interactions in A. flavus-maize kernel complex, and the detailed data could be used for modeling, and quantitative prediction of aflatoxin, which would establish a theoretical foundation for the early detection of fungal or toxin contaminated grains to ensure food security.
黄曲霉及其有毒代谢物——黄曲霉毒素感染并污染玉米籽粒，对粮食安全和人类健康构成威胁。由于微生物生长和代谢过程的复杂性，真菌生长、玉米籽粒营养物质耗竭和黄曲霉毒素产生之间的动态机制尚不清楚。在这项研究中，利用可见/近红外（Vis/NIR）高光谱成像（HSI）结合扫描电子显微镜（SEM）来阐明在玉米籽粒（宏观）和微观水平上关键的生物体相互作用。由于籽粒损伤是真菌入侵的主要入口，因此将从完整到刺穿再到半粒玉米籽粒逐渐受损的玉米籽粒与黄曲霉一起培养 0-120 小时。随着时间的推移，通过高光谱图像的主成分分析（PCA）对黄曲霉-玉米籽粒复合物的光谱指纹进行分析，其中使用伪彩色评分图和前三主成分的加载图来研究真菌感染的动态过程，并捕获不同硬度的玉米基质中复合物的细微变化。利用 SEM 从微观水平上解释黄曲霉的动态生长过程以及真菌-玉米复合物的相互作用。具体来说，在微观水平上准确地捕捉到真菌形态，例如菌丝、分生孢子和分生孢子梗（茎），并描述了黄曲霉与玉米籽粒组织（即胚和胚乳）营养物质损失之间的相互作用过程。此外，还基于 PLSDA 建立了基于 CCR=100%、CCR=97%和 CCR=93%的生长阶段判别模型，以及基于 PLSR 的 AFB 预测模型，均取得了令人满意的性能（R=0.96、R=0.95、R=0.93 和 RPD=3.58）。总之，来自宏观水平（Vis/NIR-HSI）和微观水平（SEM）评估的结果揭示了黄曲霉-玉米籽粒复合物中的动态生物体相互作用，详细的数据可用于建模和黄曲霉毒素的定量预测，为早期检测真菌或毒素污染的谷物提供理论基础，以确保食品安全。
