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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #391512

Research Project: Smart Optical Sensing of Food Hazards and Elimination of Non-Nitrofurazone Semicarbazide in Poultry

Location: Quality and Safety Assessment Research Unit

Title: Macro-micro exploration on dynamic interaction between aflatoxigenic Aspergillus flavus and maize kernels using Vis/NIR hyperspectral imaging and SEM technology

item LU, YAO - China Agricultural University
item JIA, BEIBEI - Chinese Academy Of Inspection And Quarantine
item Yoon, Seung-Chul
item Ni, Xinzhi
item Zhuang, Hong
item Guo, Baozhu
item Gold, Scott
item FOUNTAIN, JAKE - Mississippi State University
item Glenn, Anthony - Tony
item Lawrence, Kurt
item ZHANG, FENG - Chinese Academy Of Inspection And Quarantine
item WANG, WEI - China Agricultural University
item LU, JIAN - Google
item WEI, CHAOJIE - China Agricultural University
item JIANG, HONGZHE - Nanjing Forestry University
item LUO, JIAJUN - China Agricultural University

Submitted to: International Journal of Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/3/2024
Publication Date: 3/6/2024
Citation: Lu, Y., Jia, B., Yoon, S.C., Ni, X., Zhuang, H., Guo, B., Gold, S.E., Fountain, J.C., Glenn, A.E., Lawrence, K.C., Zhang, F., Wang, W., Lu, J., Wei, C., Jiang, H., Luo, J. 2024. Macro-micro exploration on dynamic interaction between aflatoxigenic Aspergillus flavus and maize kernels using Vis/NIR hyperspectral imaging and SEM technology. International Journal of Food Microbiology. 416.

Interpretive Summary: Aspergillus flavus is a toxin-producing fungus and causes disease on agricultural crops by producing a significant amount of toxic compounds (aflatoxins). However, it is still unclear how Aspergillus flavus grows and aflatoxins are accumulated in maize kernels and the kernels are damaged. In this study, visible-near infrared hyperspectral imaging (HSI) and scanning electron microscope (SEM) were used to investigate the interaction of the fungal growth, toxin accumulation, and kernel damage. Hyperspectral image analysis was used to study the dynamic process of fungal infection and visualize the subtle changes in maize matrix. SEM images were analyzed to study the dynamic growth process of the fungus on a microscopic level and the interaction process between the fugus and nutrient loss from maize kernel tissues. The study findings suggested that both macro-level (HSI) and micro-level (SEM) analyses could reveal the dynamic interactions of A. flavus and maize kernel complex and could be used for quantitative prediction of aflatoxin production.

Technical Abstract: 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 CCRC = 100 %, CCRV = 97 %, CCRIV = 93 %, and the prediction models of AFB1 based on PLSR with satisfactory performance (R2C = 0.96, R2V = 0.95, R2IV = 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.