Prodiplosis longifila is a pest of significant economic relevance, severely impacting crops like tomatoes and asparagus. Its effect on crops of ornamental foliage remains poorly documented, despite its growing importance in the agricultural sector. This study addresses our knowledge gap by implementing and validating digital tools of epidemiology (DE) and citizen science (CS) to enable a dynamic and participatory approach to pest monitoring. A trend analysis of scientific publications was conducted using web searches and social media interactions to identify topics concerning Prodiplosis over time, our knowledge gaps, and emerging areas of public interest. We assessed the impact of Prodiplosis on foliage crops, focusing on indirect effects and farmer-led management strategies shared through digital communication. Results show that digital tools such as trend monitoring on social media, web data analysis, WhatsApp group discussions, and farmer-managed digital platforms were effective for identifying the pest’s distribution, significance, and control practices. DE and CS approaches revealed critical knowledge gaps concerning the biology, ecology, and management of Prodiplosis, particularly in ornamental crops. Field data confirmed the pest’s negative impact on foliage yield and quality, with a strong dependence on chemical control methods, often applied without technical guidance. This study introduces an innovative methodology for assessing pest impacts through digital data analysis, offering practical insights for agricultural and policy decision-making. Moreover, the study highlights the potential of natural language processing as a powerful tool for synthesizing and detecting patterns in textual data and enhances the efficiency of pest surveillance and management systems.
Valbuena-Gaona et al. (Wed,) studied this question.
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