Smart agriculture stations provide continuous agroclimatic data that can support pest risk assessment and early-warning decision-making in crop protection. This short communication evaluates model-derived aphid risk patterns using smart agriculture station data collected from a nectarine orchard in Nurdağı/Gedikli, Gaziantep Province, Türkiye. The analysis covered the continuous observation period from 13 September 2023 to 3 January 2024, comprising 2,680 consecutive hourly records. Model-derived aphid risk values were classified into low, moderate, high, and very high categories for descriptive assessment. Mean risk was 51.85%, with very high-risk conditions accounting for 47.46% and low-risk conditions for 43.58% of records. The longest continuous very-high-risk period occurred from 25 September to 17 November 2023, and October represented the peak risk period. Aphid risk showed a positive relationship with air temperature and negative relationships with relative humidity and leaf wetness. These results indicate that station-based model outputs may help identify periods requiring intensified field monitoring and support site-specific pest management. However, the study did not include direct aphid population observations, species identification, or crop damage assessment. Therefore, the results represent a preliminary assessment of model-derived environmental risk rather than direct evidence of aphid abundance or infestation. Multi-season and multi-site field validation is required to assess reliability and practical applicability.
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Ekrem ASLAN (2026) studied this question.
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