Vision-spectroscopy cooperative sensing and cold atmospheric plasma inactivation for early warning and management of agricultural product diseases
Year: 2026
Type: article
Abstract: Pathogen-induced disease causes heavy post-harvest losses and threatens food safety, yet routine inspection rarely identifies an infection before it becomes visible. This study evaluates multimodal sensing, threshold-based early warning and plasma-based decontamination for post-harvest disease management in strawberry (Fragaria × ananassa cv. ‘Hongyan’). A dual-branch network, pairing a ResNet-34 visual encoder with a one-dimensional convolutional spectral encoder through bidirectional cross-modal attention, fuses RGB imagery with near-infrared hyperspectral reflectance. Across five severity grades the fused model reached 93.5 ± 0.7% accuracy over fifteen cross-validation runs and 94.2% on a fruit-level held-out test set of 260 samples (95% CI 91.4 to 97.1), with a weighted F1 score of 0.938 and a Cohen’s Kappa of 0.927. Its 2.7-point margin over an unweighted late-fusion baseline did not reach significance after correction for eleven held-out comparisons (continuity-corrected McNemar $$\:{\chi\:}^{2}$$ = 4.00, Holm-adjusted $$\:p$$ = 0.140). Alarms preceded the expert-confirmed transition to a visible lesion by 52.0 ± 9.6 h in the 80-fruit monitoring cohort. Cold atmospheric plasma parameters were screened systematically: 1.5 W/cm 2 in Ar/O 2 for 180 s delivered more than a 3.5-log reduction for Botrytis cinerea , Colletotrichum gloeosporioides and Aspergillus niger ; the measured quality attributes did not differ significantly from untreated controls under the tested conditions. Leakage assays and a sigmoidal dose-response model support membrane damage associated with oxidative stress. The proposed progression from membrane peroxidation through enzyme disruption to DNA damage remains a mechanistic hypothesis. Sensing and treatment were evaluated separately; the present evidence is limited to one commodity, laboratory conditions and no integrated pilot-scale trial.
Source: Scientific Reports
Authors: BaoJing Sun, Wei Zhang, XiaoLong Hu
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7221764201
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