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Using VIS-NIR spectroscopy and multi-omics analysis to compare mango anthracnose under natural and inoculated
Ye Sun1, Diandian Liang1, Dandan Zhou2
1College of Food Science and Light Industry, Nanjing Technology University, Nanjing 211816, China.
Abstract:
Current studies on the detection and analysis of anthracnose in mangoes using optical technology mostly rely on inoculation methods. However, to what extent the inoculation (InI) can represent the biological and metabolic differences of the naturally infected (NaI) diseases remains unknown. Therefore, this study systematically compared microbial community composition, metabolite profiles, and visible near-infrared (VIS-NIR) spectral characteristics to evaluate whether InI can serve as a reliable substitute for NaI in laboratory research. The results revealed distinct microbial and metabolic differences between the two infection modes. In the InI group, Colletotrichum-xanthorrhoeae dominated (99.6 %), whereas the NaI group exhibited a more diverse microbial composition, with Colletotrichum-xanthorrhoeae (66.7 %) coexisting with Botryosphaeria agaves (32.9 %). Metabolomic analysis identified 255 differential metabolites, with only three shared among the top 20 most significant ones, indicating substantial biochemical variations between infection types. Spectral analysis in the 400-1000 nm range demonstrated that the effective wavelength regions differed between InI and NaI in the early stages, with In-I-early at 786-798 nm and Na-I-early at 631-637 nm. Spectral reflectance differences between the two infection modes may stem from variations in metabolite composition and pigment accumulation, affecting optical absorption and scattering, especially in the unique spectral features with phenolic compounds, flavonoids, and organic acids of NaI. In addition, the Partial Least Squares Discriminate Analysis (PLS-DA) model was used to discriminate two types of diseased mangoes. The detection accuracy rate for the early-stage of InI is as high as 100.00 %, while the early stage of NaI is 89.92 %. In conclusion, the findings indicate that inoculation may not fully replicate the physiological and biochemical complexity of natural infection, emphasizing the need to consider natural disease models when developing non-destructive optical detection techniques for anthracnose in mangoes.
Insights
Mango anthracnose detection using optical technology differs between inoculated and natural infections. Natural infections show greater microbial diversity and unique spectral signatures, suggesting inoculation is not a perfect substitute for lab research.
Area of Science:
- Agricultural science
- Plant pathology
- Spectroscopy
Background:
- Optical technology is widely used for detecting mango anthracnose, often relying on artificial inoculation methods.
- The representativeness of inoculated infections (InI) versus naturally infected diseases (NaI) in mangoes remains unclear.
- Understanding these differences is crucial for developing accurate, non-destructive detection techniques.
Purpose of the Study:
- To systematically compare microbial communities, metabolite profiles, and VIS-NIR spectral characteristics of InI and NaI mango anthracnose.
- To evaluate the reliability of InI as a substitute for NaI in laboratory research for optical detection.
- To identify key spectral differences and assess the accuracy of optical detection models for both infection types.
Main Methods:
- Comparative analysis of microbial community composition using sequencing.
- Metabolomic profiling to identify differential metabolites.
- Visible Near-Infrared (VIS-NIR) spectroscopy (400-1000 nm) for spectral characteristic analysis.
- Partial Least Squares Discriminant Analysis (PLS-DA) for classification accuracy.
Main Results:
- Distinct microbial compositions were observed: InI was dominated by Colletotrichum-xanthorrhoeae (99.6%), while NaI showed higher diversity with C. xanthorrhoeae (66.7%) and Botryosphaeria agaves (32.9%).
- Metabolomic analysis revealed 255 differential metabolites, with only three shared among the top 20, indicating significant biochemical variations.
- Early-stage spectral analysis showed unique effective wavelength regions: InI at 786-798 nm and NaI at 631-637 nm, linked to metabolite and pigment differences.
- PLS-DA models achieved 100% accuracy for early InI detection but 89.92% for early NaI detection.
Conclusions:
- Inoculation methods do not fully replicate the complex physiological and biochemical characteristics of natural mango anthracnose infections.
- Significant differences in microbial communities, metabolite profiles, and spectral signatures exist between InI and NaI.
- Natural disease models are essential for developing robust and accurate non-destructive optical detection techniques for mango anthracnose.
